Genetic and genomic architecture of the evolution of resistance to antifungal drug combinations

Single-cell detection of copy number changes reveals dynamic mechanisms of adaptation to antifungals in Candida albicans

Genomic copy number changes are associated with antifungal drug resistance and virulence across diverse fungal pathogens, but the rate and dynamics of these genomic changes in the presence of antifungal drugs are unknown. Here we optimized a dual-fluorescent reporter system in the diploid pathogen Candida albicans to quantify haplotype-specific copy number variation (CNV) and loss of heterozygosity (LOH) at the single-cell level with flow cytometry. We followed the frequency and dynamics of CNV and LOH at two distinct genomic locations in the presence and absence of antifungal drugs in vitro and in a murine model of candidiasis. Copy number changes were rapid and dynamic during adaptation to fluconazole and frequently involved competing subpopulations with distinct genotypes. This study provides quantitative evidence for the rapid speed at which diverse genotypes arise and undergo dynamic population-level fluctuations during adaptation to antifungal drugs in vitro and in vivo.

Public health implications of antibiotic resistance in sewage water: an epidemiological perspective

The emergence and rapid spread of antibiotic resistance pose a major threat to global health, attributing to misuse and overuse of antibiotics resulting in antibiotics-resistant bacteria through natural mutation or transfer of resistance genes. A cross-sectional study was carried out, in which a total of 36 samples were systematically collected; of these, 26 were derived from the wastewater efflux and 10 from the receiving waters at several critical junctures along the Sutlej River. Herein, this study elucidated elevated levels of antibiotic resistance among bacterial isolates sourced from urban wastewater. Escherichia coli (E. coli) was the highest at 90% among the isolates, followed by Klebsiella pneumoniae (K. pneumoniae) at 58%, Pseudomonas aeruginosa (P. aeruginosa) at 55%, and Salmonella spp. at 53%. Many antibiotics were found to be more resistant including Ciproflaxacin, Co-Trimaxazole, Ampicillin and Tetracycline. Several antibiotic-resistance genes were found in isolated bacterial spp., such as Aminoglycosides (aadA), Sulfonamides (Sul1, Sul3), Tetracyclines (Tet (A/B/D)) and Cephalosporins (Bla_CTM X) at 41%, 35%, 29% and 12% respectively. Furthermore, the development of innovative wastewater treatment models and surveillance programs are crucial to counteract the dissemination of antibiotic resistance. To investigate the genetic determinants of antibiotic resistance, molecular analysis was performed, including DNA isolation, PCR amplification, and sequence analysis. The study helps investigate a diverse range of ARBs and ARGs in wastewater, which highlights the need of better laws for antibiotic usage and wastewater treatment processes. This investigation also stresses on regular monitoring of ARBs and ARGs in sewage wastewater. Through proactive interventions and sustained scientific inquiry, we can strive toward preserving environmental integrity and public health for successive generations.

Uniqueness of Candida auris cell wall in morphogenesis, virulence, resistance, and immune evasion

Candida auris has drawn global attention due to its alarming multidrug resistance and the emergence of pan resistant strains. C. auris poses a significant risk in nosocomial candidemia especially among immunocompromised patients. C. auris showed unique virulence characteristics associated with cell wall including cell polymorphism, adaptation, endurance on inanimate surfaces, tolerance to external conditions, and immune evasion. Notably, it possesses a distinctive cell wall composition, with an outer mannan layer shielding the inner 1,3-β glucan from immune recognition, thereby enabling immune evasion and drug resistance. This review aimed to comprehend the association between unique characteristics of C. auris's cell wall and virulence, resistance mechanisms, and immune evasion. This is particularly relevant since the fungal cell wall has no human homology, providing a potential therapeutic target. Understanding the complex interactions between the cell wall and the host immune system is essential for devising effective treatment strategies, such as the use of repurposed medications, novel therapeutic agents, and immunotherapy like monoclonal antibodies. This therapeutic targeting strategy of C. auris holds promise for effective eradication of this resilient pathogen.

DDSBC: A Stacking Ensemble Classifier-Based Approach for Breast Cancer Drug-Pair Cell Synergy Prediction

Breast cancer (BC) ranks as a leading cause of mortality among women worldwide, with incidence rates continuing to rise. The quest for effective treatments has led to the adoption of drug combination therapy, aiming to enhance drug efficacy. However, identifying synergistic drug combinations remains a daunting challenge due to the myriad of potential drug pairs. Current research leverages machine learning (ML) and deep learning (DL) models for drug-pair synergy prediction and classification. Nevertheless, these models often underperform on specific cancer types, including BC, as they are trained on data spanning various cancers without any specialization. Here, we introduce a stacking ensemble classifier, the drug-drug synergy for breast cancer (DDSBC), tailored explicitly for BC drug-pair cell synergy classification. Unlike existing models that generalize across cancer types, DDSBC is exclusively developed for BC, offering a more focused approach. Our comparative analysis against classical ML methods as well as DL models developed for drug synergy prediction highlights DDSBC's superior performance across test and independent datasets on BC data. Despite certain metrics where other methods narrowly surpass DDSBC by 1-2%, DDSBC consistently emerges as the top-ranked model, showcasing significant differences in scoring metrics and robust performance in ablation studies. DDSBC's performance and practicality position it as a preferred choice or an adjunctive validation tool for identifying synergistic or antagonistic drug pairs in BC, providing valuable insights for treatment strategies.

MMFSyn: A Multimodal Deep Learning Model for Predicting Anticancer Synergistic Drug Combination Effect

Combination therapy aims to synergistically enhance efficacy or reduce toxic side effects and has widely been used in clinical practice. However, with the rapid increase in the types of drug combinations, identifying the synergistic relationships between drugs remains a highly challenging task. This paper proposes a novel deep learning model MMFSyn based on multimodal drug data combined with cell line features. Firstly, to ensure the full expression of drug molecular features, multiple modalities of drugs, including Morgan fingerprints, atom sequences, molecular diagrams, and atomic point cloud data, are extracted using SMILES. Secondly, for different modal data, a Bi-LSTM, gMLP, multi-head attention mechanism, and multi-scale GCNs are comprehensively applied to extract the drug feature. Then, it selects appropriate omics features from gene expression and mutation omics data of cancer cell lines to construct cancer cell line features. Finally, these features are combined to predict the synergistic anti-cancer drug combination effect. The experimental results verify that MMFSyn has significant advantages in performance compared to other popular methods, with a root mean square error of 13.33 and a Pearson correlation coefficient of 0.81, which indicates that MMFSyn can better capture the complex relationship between multimodal drug combinations and omics data, thereby improving the synergistic drug combination prediction.

Allosteric inhibition of tRNA synthetase Gln4 by N-pyrimidinyl-β-thiophenylacrylamides exerts highly selective antifungal activity

Candida species are among the most prevalent causes of systemic fungal infections, which account for ∼1.5 million annual fatalities. Here, we build on a compound screen that identified the molecule N-pyrimidinyl-β-thiophenylacrylamide (NP-BTA), which strongly inhibits Candida albicans growth. NP-BTA was hypothesized to target C. albicans glutaminyl-tRNA synthetase, Gln4. Here, we confirmed through in vitro amino-acylation assays NP-BTA is a potent inhibitor of Gln4, and we defined how NP-BTA arrests Gln4's transferase activity using co-crystallography. This analysis also uncovered Met496 as a critical residue for the compound's species-selective target engagement and potency. Structure-activity relationship (SAR) studies demonstrated the NP-BTA scaffold is subject to oxidative and non-oxidative metabolism, making it unsuitable for systemic administration. In a mouse dermatomycosis model, however, topical application of the compound provided significant therapeutic benefit. This work expands the repertoire of antifungal protein synthesis target mechanisms and provides a path to develop Gln4 inhibitors.

MPFFPSDC: A multi-pooling feature fusion model for predicting synergistic drug combinations

Drug combination therapies are common practice in the treatment of cancer, but not all combinations result in synergy. As traditional screening approaches are restricted in their ability to uncover synergistic drug combinations, computer-aided medicine is becoming a increasingly prevalent in this field. In this work, a predictive model of potential interactions between drugs named MPFFPSDC is presented, which can maintain the symmetry of drug inputs and eliminate inconsistencies in predictive results caused by different drug inputting sequences or positions. The experimental results show that MPFFPSDC outperforms comparative models in major performance indicators and exhibits better generalization for independent data. Furthermore, the case study demonstrates that our model can capture molecular substructures that contribute to the synergistic effect of two drugs. These results indicate that MPFFPSDC not only offers strong predictive performance, but also has good model interpretability that may provide new insights for the study of drug interaction mechanisms and the development of new drugs.

Current Progress in Sporothrix brasiliensis Basic Aspects

Sporotrichosis is known as a subacute or chronic infection, which is caused by thermodimorphic fungi of the genus Sporothrix. It is a cosmopolitan infection, which is more prevalent in tropical and subtropical regions and can affect both humans and other mammals. The main etiological agents causing this disease are Sporothrix schenckii, Sporothrix brasiliensis, and Sporothrix globosa, which have been recognized as members of the Sporothrix pathogenic clade. Within this clade, S. brasiliensis is considered the most virulent species and represents an important pathogen due to its distribution and prevalence in different regions of South America, such as Brazil, Argentina, Chile, and Paraguay, and Central American countries, such as Panama. In Brazil, S. brasiliensis has been of great concern due to the number of zoonotic cases that have been reported over the years. In this paper, a detailed review of the current literature on this pathogen and its different aspects will be carried out, including its genome, pathogen-host interaction, resistance mechanisms to antifungal drugs, and the caused zoonosis. Furthermore, we provide the prediction of some putative virulence factors encoded by the genome of this fungal species.

yEvo: experimental evolution in high school classrooms selects for novel mutations that impact clotrimazole resistance in Saccharomyces cerevisiae

Antifungal resistance in pathogenic fungi is a growing global health concern. Nonpathogenic laboratory strains of Saccharomyces cerevisiae are an important model for studying mechanisms of antifungal resistance that are relevant to understanding the same processes in pathogenic fungi. We have developed a series of laboratory modules in which high school students used experimental evolution to study antifungal resistance by isolating azole-resistant S. cerevisiae mutants and examining the genetic basis of resistance. We have sequenced 99 clones from these experiments and found that all possessed mutations previously shown to impact azole resistance, validating our approach. We additionally found recurrent mutations in an mRNA degradation pathway and an uncharacterized mitochondrial protein (Csf1) that have possible mechanistic connections to azole resistance. The scale of replication in this initiative allowed us to identify candidate epistatic interactions, as evidenced by pairs of mutations that occur in the same clone more frequently than expected by chance (positive epistasis) or less frequently (negative epistasis). We validated one of these pairs, a negative epistatic interaction between gain-of-function mutations in the multidrug resistance transcription factors Pdr1 and Pdr3. This high school-university collaboration can serve as a model for involving members of the broader public in the scientific process to make meaningful discoveries in biomedical research.

Targeting fungal membrane homeostasis with imidazopyrazoindoles impairs azole resistance and biofilm formation

Fungal infections cause more than 1.5 million deaths annually. With an increase in immune-deficient susceptible populations and the emergence of antifungal drug resistance, there is an urgent need for novel strategies to combat these life-threatening infections. Here, we use a combinatorial screening approach to identify an imidazopyrazoindole, NPD827, that synergizes with fluconazole against azole-sensitive and -resistant isolates of Candida albicans. NPD827 interacts with sterols, resulting in profound effects on fungal membrane homeostasis and induction of membrane-associated stress responses. The compound impairs virulence in a Caenorhabditis elegans model of candidiasis, blocks C. albicans filamentation in vitro, and prevents biofilm formation in a rat model of catheter infection by C. albicans. Collectively, this work identifies an imidazopyrazoindole scaffold with a non-protein-targeted mode of action that re-sensitizes the leading human fungal pathogen, C. albicans, to azole antifungals.

From cell lines to cancer patients: personalized drug synergy prediction

MOTIVATION

Combination drug therapies are effective treatments for cancer. However, the genetic heterogeneity of the patients and exponentially large space of drug pairings pose significant challenges for finding the right combination for a specific patient. Current in silico prediction methods can be instrumental in reducing the vast number of candidate drug combinations. However, existing powerful methods are trained with cancer cell line gene expression data, which limits their applicability in clinical settings. While synergy measurements on cell line models are available at large scale, patient-derived samples are too few to train a complex model. On the other hand, patient-specific single-drug response data are relatively more available.

RESULTS

In this work, we propose a deep learning framework, Personalized Deep Synergy Predictor (PDSP), that enables us to use the patient-specific single drug response data for customizing patient drug synergy predictions. PDSP is first trained to learn synergy scores of drug pairs and their single drug responses for a given cell line using drug structures and large scale cell line gene expression data. Then, the model is fine-tuned for patients with their patient gene expression data and associated single drug response measured on the patient ex vivo samples. In this study, we evaluate PDSP on data from three leukemia patients and observe that it improves the prediction accuracy by 27% compared to models trained on cancer cell line data.

AVAILABILITY AND IMPLEMENTATION

PDSP is available at https://github.com/hikuru/PDSP.

Biology and molecular interactions of Parastagonospora nodorum blotch of wheat

Parastagonospora nodorum is one of the important necrotrophic pathogens of wheat which causes severe economical loss to crop yield. So far, a number of effectors of Parastagonospora nodorum origin and their target interacting genes on the host plant have been characterized. Since targeting effector-sensitive gene carefully can be helpful in breeding for resistance. Therefore, constant efforts are required to further characterize the effectors, their interacting genes, and underlying biochemical pathways. Furthermore, to develop effective counter-strategies against emerging diseases, continuous efforts are required to determine the qualitative resistance that demands to screen of diverse genotypes for host resistance. Stagonospora nodorum blotch also refers to as Stagonospora glume blotch and leaf is caused by Parastagonospora nodorum. The pathogen deploys necrotrophic effectors for the establishment and development on wheat plants. The necrotrophic effectors and their interaction with host receptors lead to the establishment of infection on leaves and extensive lesions formation which either results in host cell death or suppression/activation of host defence mechanisms. The wheat Stagonospora nodorum interaction involves a set of nine host gene-necrotrophic effector interactions. Out of these, Snn1-SnTox1, Tsn1-SnToxA and Snn-SnTox3 are one of the most studied interaction, due to its role in the suppression of reactive oxygen species production, regulating the cytokinin content through ethylene-dependent wayduring initial infection stage. Further, although the molecular basis is not fully unveiled, these effectors regulate the redox state and influence the ethylene biosynthesis in infected wheat plants. Here, we have discussed the biology of the wheat pathogen Parastagonospora nodorum, role of its necrotrophic effectors and their interacting sensitivity genes on the redox state, how they hijack the resistance mechanisms, hormonal regulated immunity and other signalling pathways in susceptible wheat plants. The information generated from effectors and their corresponding sensitivity genes and other biological processes could be utilized effectively for disease management strategies.

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

MOTIVATION

Drug combination therapy has become an increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experiments. Therefore, computational screening has become an important way to prioritize drug combinations. Graph neural network has recently shown remarkable performance in the prediction of compound-protein interactions, but it has not been applied to the screening of drug combinations.

RESULTS

In this paper, we proposed a deep learning model based on graph neural network and attention mechanism to identify drug combinations that can effectively inhibit the viability of specific cancer cells. The feature embeddings of drug molecule structure and gene expression profiles were taken as input to multilayer feedforward neural network to identify the synergistic drug combinations. We compared DeepDDS (Deep Learning for Drug-Drug Synergy prediction) with classical machine learning methods and other deep learning-based methods on benchmark data set, and the leave-one-out experimental results showed that DeepDDS achieved better performance than competitive methods. Also, on an independent test set released by well-known pharmaceutical enterprise AstraZeneca, DeepDDS was superior to competitive methods by more than 16% predictive precision. Furthermore, we explored the interpretability of the graph attention network and found the correlation matrix of atomic features revealed important chemical substructures of drugs. We believed that DeepDDS is an effective tool that prioritized synergistic drug combinations for further wet-lab experiment validation.

AVAILABILITY AND IMPLEMENTATION

Source code and data are available at https://github.com/Sinwang404/DeepDDS/tree/master.

Systematic Prediction of Antifungal Drug Synergy by Chemogenomic Screening in Saccharomyces cerevisiae

Since the earliest days of using natural remedies, combining therapies for disease treatment has been standard practice. Combination treatments exhibit synergistic effects, broadly defined as a greater-than-additive effect of two or more therapeutic agents. Clinicians often use their experience and expertise to tailor such combinations to maximize the therapeutic effect. Although understanding and predicting biophysical underpinnings of synergy have benefitted from high-throughput screening and computational studies, one challenge is how to best design and analyze the results of synergy studies, especially because the number of possible combinations to test quickly becomes unmanageable. Nevertheless, the benefits of such studies are clear-by combining multiple drugs in the treatment of infectious disease and cancer, for instance, one can lessen host toxicity and simultaneously reduce the likelihood of resistance to treatment. This study introduces a new approach to characterize drug synergy, in which we extend the widely validated chemogenomic HIP-HOP assay to drug combinations; this assay involves parallel screening of comprehensive collections of barcoded deletion mutants. We identify a class of "combination-specific sensitive strains" that introduces mechanisms for the synergies we observe and further suggest focused follow-up studies.

Cellular Calcium Levels Influenced by NCA-2 Impact Circadian Period Determination in Neurospora

Intracellular calcium signaling has been implicated in the control of a variety of circadian processes in animals and plants, but its role in microbial clocks has remained largely cryptic. To examine the role of intracellular Ca²⁺ in the Neurospora clock, we screened mutants with knockouts of calcium transporter genes and identified a gene encoding a calcium exporter, nca-2, uniquely as having significant period effects. The loss of NCA-2 results in an increase in the cytosolic calcium level, and this leads to hyper-phosphorylation of core clock components, FRQ and WC-1, and a short period, as measured by both the core oscillator and the overt clock. Genetic analyses showed that mutations in certain frq phospho-sites and in Ca²⁺-calmodulin-dependent kinase 2 (camk-2) are epistatic to nca-2 in controlling the pace of the oscillator. These data are consistent with a model in which elevated intracellular Ca²⁺ leads to the increased activity of CAMK-2, leading to enhanced FRQ phosphorylation, accelerated closure of the circadian feedback loop, and a shortened circadian period length. At a mechanistic level, some CAMKs undergo more auto-phosphorylations in the Δnca-2 mutant, consistent with high calcium levels in the Δnca-2 mutant influencing the enzymatic activities of CAMKs. NCA-2 interacts with multiple proteins, including CSP-6, a protein known to be required for circadian output. Most importantly, the expression of nca-2 is circadian clock-controlled at both the transcriptional and translational levels, and this in combination with the period effects seen in strains lacking NCA-2 firmly places calcium signaling within the larger circadian system, where it acts as both an input to and an output from the core clock.

Antifungal Drug Resistance: Molecular Mechanisms in Candida albicans and Beyond

Fungal infections are a major contributor to infectious disease-related deaths across the globe. Candida species are among the most common causes of invasive mycotic disease, with Candida albicans reigning as the leading cause of invasive candidiasis. Given that fungi are eukaryotes like their human host, the number of unique molecular targets that can be exploited for antifungal development remains limited. Currently, there are only three major classes of drugs approved for the treatment of invasive mycoses, and the efficacy of these agents is compromised by the development of drug resistance in pathogen populations. Notably, the emergence of additional drug-resistant species, such as Candida auris and Candida glabrata, further threatens the limited armamentarium of antifungals available to treat these serious infections. Here, we describe our current arsenal of antifungals and elaborate on the resistance mechanisms Candida species possess that render them recalcitrant to therapeutic intervention. Finally, we highlight some of the most promising therapeutic strategies that may help combat antifungal resistance, including combination therapy, targeting fungal-virulence traits, and modulating host immunity. Overall, a thorough understanding of the mechanistic principles governing antifungal drug resistance is fundamental for the development of novel therapeutics to combat current and emerging fungal threats.

Differential Roles of a Family of Flavodoxin-Like Proteins That Promote Resistance to Quinone-Mediated Oxidative Stress in Candida albicans

Survival of the fungal pathogen Candida albicans within a mammalian host relies on its ability to resist oxidative stress. The four flavodoxin-like proteins (Pst1, Pst2, Pst3, and Ycp4) that reside on the inner surface of the C. albicans plasma membrane represent a recently discovered antioxidant mechanism that is essential for virulence. Flavodoxin-like proteins combat oxidative stress by promoting a two-electron reduction of quinone molecules, which prevents the formation of toxic semiquinone radicals. Previous studies indicated that Pst3 played a major role in promoting resistance to the small quinone molecules p-benzoquinone and menadione. Analysis of additional quinones confirmed this role for Pst3. To better define their function, antibodies were raised against each of the four flavodoxin-like proteins and used to quantify protein levels. Interestingly, the basal level of flavodoxin-like proteins differed, with Pst3 and Ycp4 being the most abundant. However, after induction with p-benzoquinone, Pst1 and Pst3 were the most highly induced, resulting in Pst3 becoming the most abundant. Constitutive expression of the flavodoxin-like protein genes from a TDH3 promoter resulted in similar protein levels and showed that Pst1 and Pst3 were better at protecting C. albicans against p-benzoquinone than Pst2 or Ycp4. In contrast, Pst1 and Ycp4 provided better protection against oxidative damage induced by tert-butyl hydroperoxide. Thus, both the functional properties and the relative abundance contribute to the distinct roles of the flavodoxin-like proteins in resisting oxidative stress. These results further define how C. albicans combats the host immune response and survives in an environment rich in oxidative stress.

Antifungal resistance on Sporothrix species: an overview

INTRODUCTION

The treatment of human and animal sporotrichosis is often performed with antifungal agents; however, the emergence of antifungal-resistant strains of Sporothrix species has been reported. We aimed to discuss the ability of Sporothrix species in developing resistance to the conventional antifungals and mechanisms for this.

METHODOLOGY

Published data on databases (PubMed, Science Direct, Google Scholar) were investigated using a combination of keywords from 2008 to 2019 by the StArt tool.

RESULTS

The minimal inhibitory concentrations values based on the Clinical and Laboratory Standards Institute (CLSI) from eight references were classified according to the epidemiological cutoff values in wild-type or non-wild-type strains. In this way, non-wild-type S. schenckii and, mainly, S. brasiliensis isolates were recognized on itraconazole, amphotericin B, terbinafine, and voriconazole, which are strains that deserve more attention toward antifungal control, with a probable risk of mutation to antifungal resistance. Among the few reviewed studied on antifungal resistance, the melanin production capacity (DHN-melanin, L-DOPA melanin, and pyomelanin), the low genetic diversity due to the abnormal number of chromosomes, and the mutation in cytochrome P450 are some of the factors for developing resistance mechanism.

CONCLUSIONS

The emergence of Sporothrix species with in vitro antifungal resistance was evidenced and the possible mechanisms for resistance development may be due to the melanin production capacity, genetic diversity and mutations in cytochrome P450. Further studies should be carried out targeting gene expression for the development of antifungal resistance on Sporothrix species in order to prospect new therapeutic targets for human and veterinary use.

Experimental Evolution of Candida by Serial Passaging in Host Cells

Experimental evolution is an experiment class of its own; instead of requiring an a priori hypothesis, the genetic adaptation of microbes to defined environments tells us about the underlying pathways and mechanisms. Such experiments are often deceptively simple in their design, based on a single abiotic stressor and what is in essence a long-term continuous culture. However, they generally provide a starting point to thorough follow-up analyses (which are specific for the organism at hand and not part of this method chapter). In this chapter, we describe a method to use a biotic stressor which is frequently encountered by pathogenic fungi-macrophage-like cells-in a serial passaging regime. Experimental evolution under such conditions can reveal new virulence attributes and mechanisms by selecting for adaptive mutations against the host cell-induced stress.It is important to note that every evolution experiment is different, and these techniques should be taken as a general guideline to be adapted to different organisms and questions. Then, it is a powerful tool with many potential applications in pathobiology research.

The Genetic Architecture of Emerging Fungicide Resistance in Populations of a Global Wheat Pathogen

Containing fungal diseases often depends on the application of fungicidal compounds. Fungicides can rapidly lose effectiveness due to the rise of resistant individuals in populations. However, the lack of knowledge about resistance mutations beyond known target genes challenges investigations into pathways to resistance. We used whole-genome sequencing data and association mapping to reveal the multilocus genetic architecture of fungicide resistance in a global panel of 159 isolates of Parastagonospora nodorum, an important fungal pathogen of wheat. We found significant differences in azole resistance among global field populations. The populations evolved distinctive combinations of resistance alleles which can interact when co-occurring in the same genetic background. We identified 34 significantly associated single nucleotide polymorphisms located in close proximity to genes associated with fungicide resistance in other fungi, including a major facilitator superfamily transporter. Using fungal colony growth rates and melanin production at different temperatures as fitness proxies, we found no evidence that resistance was constrained by genetic trade-offs. Our study demonstrates how genome-wide association studies of a global collection of pathogen strains can recapitulate the emergence of fungicide resistance. The distinct complement of resistance mutations found among populations illustrates how the evolutionary trajectory of fungicide adaptation can be complex and challenging to predict.

Antifungal resistance-modifying multiplexing action of Momordica charantia protein and phosphorylated derivatives on the basis of growth-dependent gene coregulation in Candida albicans

Fungal growth-dependent gene coregulation is strongly implicated in alteration of gene-encoding target proteases ruling with an antifungal resistance niche and biology of resistant mutants. On the basis of multi-alterative processes in this platform, the resistance-modifying strategy is designed in ketoconazole resistant Candida albicans and evaluated with less selective Momordica charantia protein and allosterically phosphorylated derivatives at the Thr102, Thr24 and Thr255 sites, respectively. We demonstrate absolutely chemo-sensitizing efficacy regarding stepwise-modifying resistance in sensitivity, by a load of only 26.23-40.00 μg/l agents in Sabouraud's dextrose broth. Five successive modifying-steps realize the decreasing of ketoconazole E-test MIC50 from 11.10 to a lower level than 0.10 mg/l. With the ketoconazole resistance-modifying, colony undergoes a high-frequency morphological switch between high ploidy (opaque) and small budding haploid (white). A cellular event in the first modifying-step associates with relatively slow exponential growth (ie, a 4-h delay)-dependent action, mediated by agents adsorption. Moreover, multiple molecular roles are coupled with intracellularly and extracellularly binding to ATP-dependent RNA helicase dbp6; the 0.08-2.45 fold upregulation of TATA-box-binding protein, rRNA-processing protein and translation initiation factor 5A; and the 7.52-55.33% decrease of cytochrome P450 lanosterol 14α-demethylase, glucan 1, 3-β glucosidase, candidapepsin-1 and 1-acylglycerol-3-phosphate O-acyltransferase. Spatial and temporal gene coregulation, in the transcription and translation initiation stages with rRNA-processing, is a new coprocessing platform enabling target protease attenuations for resistance-impairing. An updated resistance-modifying measure of these agents in the low-dose antifungal strategic design may provide opportunities to a virtually safe therapy that is in high dose-dependency.

LAY SUMMARY

A new platform to modify resistance is fungal growth-dependent gene coregulation. MAP30 and phosphorylated derivatives are candidate resistance-modifying agents. Low-dose stepwise treatment absolutely modifies azole resistance in model fungus.

FtsZ-Independent Mechanism of Division Inhibition by the Small Molecule PC190723 in Escherichia coli

While cell division is a critical process in cellular proliferation, very few antibiotics have been identified that target the bacterial cell-division machinery. Recent studies have shown that the small molecule PC190723 inhibits cell division in several Gram-positive bacteria, with a hypothesized mechanism of action involving direct targeting of the tubulin homolog FtsZ, which is essential for division in virtually all bacterial species. Here, it is shown that PC190723 also inhibits cell division in the Gram-negative bacterium Escherichia coli if the outer membrane permeability barrier is compromised genetically or chemically. The results show that the equivalent FtsZ mutations conferring PC190723 resistance in Staphylococcus aureus do not protect E. coli against PC190723, and that suppressors of PC190723 sensitivity in E. coli, which do not generically decrease outer membrane permeability, do not map to FtsZ or other division proteins. These suppressors display a wide range of morphological and growth phenotypes, and one exhibits a death phenotype in the stationary phase similar to that of a mutant with disrupted lipid homeostasis. Finally, a complementing FtsZ-msfGFP fusion is used to show that PC190723 does not affect the Z-ring structure. Taken together, the findings suggest that PC190723 inhibits growth and division in E. coli without targeting FtsZ. This study highlights the importance of utilizing a combination of genetic, chemical, and single-cell approaches to dissect the mechanisms of action of new antibiotics, which are not necessarily conserved across bacterial species.

Candida albicans Genetic Background Influences Mean and Heterogeneity of Drug Responses and Genome Stability during Evolution in Fluconazole

Antimicrobial resistance is an evolutionary phenomenon with clinical implications. We tested how replicates from diverse strains of Candida albicans, a prevalent human fungal pathogen, evolve in the commonly prescribed antifungal drug fluconazole. Replicates on average increased in fitness in the level of drug they were evolved to, with the least fit parental strains improving the most. Very few replicates increased resistance above the drug level they were evolved in. Notably, many replicates increased in genome size and changed in drug tolerance (a drug response where a subpopulation of cells grow slowly in high levels of drug), and variability among replicates in fitness, tolerance, and genome size was higher in strains that initially were more sensitive to the drug. Genetic background influenced the average degree of adaptation and the evolved variability of many phenotypes, highlighting that different strains from the same species may respond and adapt very differently during adaptation.

The importance of within-species diversity in determining the evolutionary potential of a population to evolve drug resistance or tolerance is not well understood, including in eukaryotic pathogens. To examine the influence of genetic background, we evolved replicates of 20 different clinical isolates of Candida albicans, a human fungal pathogen, in fluconazole, the commonly used antifungal drug. The isolates hailed from the major C. albicans clades and had different initial levels of drug resistance and tolerance to the drug. The majority of replicates rapidly increased in fitness in the evolutionary environment, with the degree of improvement inversely correlated with parental strain fitness in the drug. Improvement was largely restricted to up to the evolutionary level of drug: only 4% of the evolved replicates increased resistance (MIC) above the evolutionary level of drug. Prevalent changes were altered levels of drug tolerance (slow growth of a subpopulation of cells at drug concentrations above the MIC) and increased diversity of genome size. The prevalence and predominant direction of these changes differed in a strain-specific manner, but neither correlated directly with parental fitness or improvement in fitness. Rather, low parental strain fitness was correlated with high levels of heterogeneity in fitness, tolerance, and genome size among evolved replicates. Thus, parental strain background is an important determinant in mean improvement to the evolutionary environment as well as the diversity of evolved phenotypes, and the range of possible responses of a pathogen to an antimicrobial drug cannot be captured by in-depth study of a single strain background.

IMPORTANCE Antimicrobial resistance is an evolutionary phenomenon with clinical implications. We tested how replicates from diverse strains of Candida albicans, a prevalent human fungal pathogen, evolve in the commonly prescribed antifungal drug fluconazole. Replicates on average increased in fitness in the level of drug they were evolved to, with the least fit parental strains improving the most. Very few replicates increased resistance above the drug level they were evolved in. Notably, many replicates increased in genome size and changed in drug tolerance (a drug response where a subpopulation of cells grow slowly in high levels of drug), and variability among replicates in fitness, tolerance, and genome size was higher in strains that initially were more sensitive to the drug. Genetic background influenced the average degree of adaptation and the evolved variability of many phenotypes, highlighting that different strains from the same species may respond and adapt very differently during adaptation.

Resistance Mechanisms of Saccharomyces cerevisiae to Commercial Formulations of Glyphosate Involve DNA Damage Repair, the Cell Cycle, and the Cell Wall Structure

The use of glyphosate-based herbicides is widespread and despite their extensive use, their effects are yet to be deciphered completely. The additives in commercial formulations of glyphosate, though labeled inert when used individually, have adverse effects when used in combination with other additives along with the active ingredient. As a species, Saccharomyces cerevisiae has a wide range of resistance to glyphosate-based herbicides. To investigate the underlying genetic differences between sensitive and resistant strains, global changes in gene expression were measured, when yeast were exposed to a glyphosate-based herbicide (GBH). Expression of genes involved in numerous pathways crucial to the cell's functioning, such as DNA replication, MAPK signaling, meiosis, and cell wall synthesis changed. Because so many diverse pathways were affected, these strains were then subjected to in-lab-evolutions (ILE) to select mutations that confer increased resistance. Common fragile sites were found to play a role in adaptation to resistance to long-term exposure of GBHs. Copy number increased in approximately 100 genes associated with cell wall proteins, mitochondria, and sterol transport. Taking ILE and transcriptomic data into account it is evident that GBHs affect multiple biological processes in the cell. One such component is the cell wall structure which acts as a protective barrier in alleviating the stress caused by exposure to inert additives in GBHs. Sed1, a GPI-cell wall protein, plays an important role in tolerance of a GBH. Hence, a detailed study of the changes occurring at the genome and transcriptome levels is essential to better understand the effects of an environmental stressor such as a GBH, on the cell as a whole.

Molecular Hydrogen Metabolism: a Widespread Trait of Pathogenic Bacteria and Protists

Pathogenic microorganisms use various mechanisms to conserve energy in host tissues and environmental reservoirs. One widespread but often overlooked means of energy conservation is through the consumption or production of molecular hydrogen (H2). Here, we comprehensively review the distribution, biochemistry, and physiology of H2 metabolism in pathogens. Over 200 pathogens and pathobionts carry genes for hydrogenases, the enzymes responsible for H2 oxidation and/or production. Furthermore, at least 46 of these species have been experimentally shown to consume or produce H2 Several major human pathogens use the large amounts of H2 produced by colonic microbiota as an energy source for aerobic or anaerobic respiration. This process has been shown to be critical for growth and virulence of the gastrointestinal bacteria Salmonella enterica serovar Typhimurium, Campylobacter jejuni, Campylobacter concisus, and Helicobacter pylori (including carcinogenic strains). H2 oxidation is generally a facultative trait controlled by central regulators in response to energy and oxidant availability. Other bacterial and protist pathogens produce H2 as a diffusible end product of fermentation processes. These include facultative anaerobes such as Escherichia coli, S Typhimurium, and Giardia intestinalis, which persist by fermentation when limited for respiratory electron acceptors, as well as obligate anaerobes, such as Clostridium perfringens, Clostridioides difficile, and Trichomonas vaginalis, that produce large amounts of H2 during growth. Overall, there is a rich literature on hydrogenases in growth, survival, and virulence in some pathogens. However, we lack a detailed understanding of H2 metabolism in most pathogens, especially obligately anaerobic bacteria, as well as a holistic understanding of gastrointestinal H2 transactions overall. Based on these findings, we also evaluate H2 metabolism as a possible target for drug development or other therapies.

Five-Feature Model for Developing the Classifier for Synergistic vs. Antagonistic Drug Combinations Built by XGBoost

Combinatorial drug therapy can improve the therapeutic effect and reduce the corresponding adverse events. In silico strategies to classify synergistic vs. antagonistic drug pairs is more efficient than experimental strategies. However, most of the developed methods have been applied only to cancer therapies. In this study, we introduce a novel method, XGBoost, based on five features of drugs and biomolecular networks of their targets, to classify synergistic vs. antagonistic drug combinations from different drug categories. We found that XGBoost outperformed other classifiers in both stratified fivefold cross-validation (CV) and independent validation. For example, XGBoost achieved higher predictive accuracy than other models (0.86, 0.78, 0.78, and 0.83 for XGBoost, logistic regression, naïve Bayesian, and random forest, respectively) for an independent validation set. We also found that the five-feature XGBoost model is much more effective at predicting combinatorial therapies that have synergistic effects than those with antagonistic effects. The five-feature XGBoost model was also validated on TCGA data with accuracy of 0.79 among the 61 tested drug pairs, which is comparable to that of DeepSynergy. Among the 14 main anatomical/pharmacological groups classified according to WHO Anatomic Therapeutic Class, for drugs belonging to five groups, their prediction accuracy was significantly increased (odds ratio < 1) or reduced (odds ratio > 1) (Fisher's exact test, p < 0.05). This study concludes that our five-feature XGBoost model has significant benefits for classifying synergistic vs. antagonistic drug combinations.

Eucalyptal D Enhances the Antifungal Effect of Fluconazole on Fluconazole-Resistant Candida albicans by Competitively Inhibiting Efflux Pump

The frequent emergence of azole-resistant strains has increasingly led azoles to fail in treating candidiasis. Combination with other drugs is a good option to effectively reduce or retard its incidence of resistance. Natural products are a promising synergist source to assist azoles in treating resistant candidiasis. Eucalyptal D (ED), a formyl-phloroglucinol meroterpenoid, is one of the natural synergists, which could significantly enhance the anticandidal activity of fluconazole (FLC) in treating FLC resistant C. albicans. The checkerboard microdilution assay showed their synergistic effect. The agar disk diffusion test illustrated the key role of ED in synergy. The rhodamine 6G (R6G) efflux assay reflected ED could reduce drug efflux, but quantitative reverse transcription PCR analysis revealed the upregulation of CDR1 and CDR2 genes in ED treating group. Efflux pump-deficient strains were hyper-susceptible to ED, thus ED was speculated to be the substrate of efflux pump Cdr1p and Cdr2p to competitively inhibit the excretion of FLC or R6G, which mainly contributed to its synergistic effect.

Selection of Candida albicans trisomy during oropharyngeal infection results in a commensal-like phenotype

When the fungus Candida albicans proliferates in the oropharyngeal cavity during experimental oropharyngeal candidiasis (OPC), it undergoes large-scale genome changes at a much higher frequency than when it grows in vitro. Previously, we identified a specific whole chromosome amplification, trisomy of Chr6 (Chr6x3), that was highly overrepresented among strains recovered from the tongues of mice with OPC. To determine the functional significance of this trisomy, we assessed the virulence of two Chr6 trisomic strains and a Chr5 trisomic strain in the mouse model of OPC. We also analyzed the expression of virulence-associated traits in vitro. All three trisomic strains exhibited characteristics of a commensal during OPC in mice. They achieved the same oral fungal burden as the diploid progenitor strain but caused significantly less weight loss and elicited a significantly lower inflammatory host response. In vitro, all three trisomic strains had reduced capacity to adhere to and invade oral epithelial cells and increased susceptibility to neutrophil killing. Whole genome sequencing of pre- and post-infection isolates found that the trisomies were usually maintained. Most post-infection isolates also contained de novo point mutations, but these were not conserved. While in vitro growth assays did not reveal phenotypes specific to de novo point mutations, they did reveal novel phenotypes specific to each lineage. These data reveal that during OPC, clones that are trisomic for Chr5 or Chr6 are selected and they facilitate a commensal-like phenotype.

Opportunistic fungal pathogens commonly acquire extra copies of chromosomes that can provide a fitness benefit under acute stress such as exposure to antifungal agents but how these extra copies affect fungal life-style and interactions with their hosts is poorly understood. Here we show that in C. albicans the acquisition of specific whole chromosome trisomies during oropharyngeal infection in mice results in a commensal-like phenotype. Our data indicate that trisomies of chromosomes 5 and 6 alter several related virulence-associated traits that affect how the host recognizes and responds to C. albicans during oropharyngeal infection, thereby inducing this commensal-like phenotype. Whole genome sequencing revealed that trisomies were mostly maintained in subsequent oral infections and that de novo mutations that arose were not shared among strains. We hypothesize that both in vivo and in vitro phenotypes are likely the result of allelic imbalance of specific genes on the trisomic chromosomes, rather than due to whole chromosome trisomy.

Difficult but Not Impossible: in Search of an Anti-Candida Vaccine

Purpose of Review

Pervasive fungal infection among the immunocompromised population, in conjunction with a lack of effective treatment options, has demanded further scrutiny. Millions of people are still dying annually from fungal infections. While existing treatment for these fungal infections exists, it is difficult to administer without adverse effects in the immunocompromised and is slowly becoming obsolete due to varying mutation rates and rising resistance in multiple species. Thus, vaccines may be a viable target for preventing and treating fungal infections and addressing the critical challenge of such infections.

Recent Findings

Candida albicans, along with other non-albicans Candida species, is among the more virulent class of fungal specimens considered for vaccine development. C. albicans is responsible for a large percentage of invasive fungal infections among immunocompromised and immunocompetent populations and carries a relatively high mortality rate. In the last decade, a recent increase in infective capacity among Candida species has shed light on the lack of adequate fungal vaccine choices. While roadblocks still exist in the development of antifungal vaccines, several novel targets have been examined and proposed as candidates.

Summary

Success in vaccine development has universal appeal; an anti-Candida vaccine formulation could be modified to work against other fungal infections and thus bolster the antifungal pipeline.

A CRISPR Interference Platform for Efficient Genetic Repression in Candida albicans

Fungal pathogens are emerging as an important cause of human disease, and Candida albicans is among the most common causative agents of fungal infections. Studying this fungal pathogen is of the utmost importance and necessitates the development of molecular technologies to perform comprehensive genetic and functional genomic analysis. Here, we designed and developed a novel clustered regularly interspaced short palindromic repeat interference (CRISPRi) system for targeted genetic repression in C. albicans We engineered a nuclease-dead Cas9 (dCas9) construct that, paired with a guide RNA targeted to the promoter of an endogenous gene, is capable of targeting that gene for transcriptional repression. We further optimized a favorable promoter locus to achieve repression and demonstrated that fusion of dCas9 to an Mxi1 repressor domain was able to further enhance transcriptional repression. Finally, we demonstrated the application of this CRISPRi system through genetic repression of the essential molecular chaperone HSP90 This is the first demonstration of a functional CRISPRi repression system in C. albicans, and this valuable technology will enable many future applications in this critical fungal pathogen.IMPORTANCE Fungal pathogens are an increasingly important cause of human disease and mortality, and Candida albicans is among the most common causes of fungal disease. Studying this important fungal pathogen requires a comprehensive genetic toolkit to establish how different genetic factors play roles in the biology and virulence of this pathogen. Here, we developed a CRISPR-based genetic regulation platform to achieve targeted repression of C. albicans genes. This CRISPR interference (CRISPRi) technology exploits a nuclease-dead Cas9 protein (dCas9) fused to transcriptional repressors. The dCas9 fusion proteins pair with a guide RNA to target genetic promoter regions and to repress expression from these genes. We demonstrated the functionality of this system for repression in C. albicans and show that we can apply this technology to repress essential genes. Taking the results together, this work presents a new technology for efficient genetic repression in C. albicans, with important applications for genetic analysis in this fungal pathogen.

Penetrating cations induce pleiotropic drug resistance in yeast

Substrates of pleiotropic drug resistance (PDR) transporters can induce the expression of corresponding transporter genes by binding to their transcription factors. Penetrating cations are substrates of PDR transporters and theoretically may also activate the expression of transporter genes. However, the accumulation of penetrating cations inside mitochondria may prevent the sensing of these molecules. Thus, whether penetrating cations induce PDR is unclear. Using Saccharomyces cerevisiae as a model, we studied the effects of penetrating cations on the activation of PDR. We found that the lipophilic cation dodecyltriphenylphosphonium (C₁₂TPP) induced the expression of the plasma membrane PDR transporter genes PDR5, SNQ2 and YOR1. Moreover, a 1-hour incubation with C₁₂TPP increased the concentration of Pdr5p and Snq2p and prevented the accumulation of the PDR transporter substrate Nile red. The transcription factor PDR1 was required to mediate these effects, while PDR3 was dispensable. The deletion of the YAP1 or RTG2 genes encoding components of the mitochondria-to-nucleus signalling pathway did not prevent the C₁₂TPP-induced increase in Pdr5-GFP. Taken together, our data suggest (i) that the sequestration of lipophilic cations inside mitochondria does not significantly inhibit sensing by PDR activators and (ii) that the activation mechanisms do not require mitochondria as a signalling module.

Molecular Evolution of Antifungal Drug Resistance

The fungal pathogens Candida albicans, Cryptococcus neoformans, and Aspergillus fumigatus have transitioned from a rare curiosity to a leading cause of human mortality. The management of infections caused by these organisms is intimately dependent on the efficacy of antifungal agents; however, fungi that are resistant to these treatments are regularly isolated in the clinic, impeding our ability to control infections. Given the significant impact fungal pathogens have on human health, it is imperative to understand the molecular mechanisms that govern antifungal drug resistance. This review describes our current knowledge of the mechanisms by which antifungal drug resistance evolves in experimental populations and clinical settings. We explore current antifungal treatment options and discuss promising strategies to impede the evolution of drug resistance. By tackling antifungal drug resistance as an evolutionary problem, there is potential to improve the utility of current treatments and accelerate the development of novel therapeutic strategies.

Emerging mechanisms of antimicrobial resistance in bacteria and fungi: advances in the era of genomics

Bacteria and fungi continue to develop new ways to adapt and survive the lethal or biostatic effects of antimicrobials through myriad mechanisms. Novel antibiotic resistance genes such as lsa(C), erm(44), VCC-1, mcr-1, mcr-2, mcr-3, mcr-4, bla _KLUC-3 and bla _KLUC-4 were discovered through comparative genomics and further functional studies. As well, mutations in genes that hitherto were unknown to confer resistance to antimicrobials, such as trm, PP2C, rpsJ, HSC82, FKS2 and Rv2887, were shown by genomics and transcomplementation assays to mediate antimicrobial resistance in Acinetobacter baumannii, Staphylococcus aureus, Enterococcus faecium, Saccharomyces cerevisae, Candida glabrata and Mycobacterium tuberculosis, respectively. Thus, genomics, transcriptomics and metagenomics, coupled with functional studies are the future of antimicrobial resistance research and novel drug discovery or design.

A chromosome 4 trisomy contributes to increased fluconazole resistance in a clinical isolate of Candida albicans

Candida albicans is an important opportunistic fungal pathogen capable of causing both mucosal and disseminated disease. Infections are often treated with fluconazole, a front-line antifungal drug that targets the biosynthesis of ergosterol, a major component of the fungal cell membrane. Resistance to fluconazole can arise through a variety of mechanisms, including gain-of-function mutations, loss of heterozygosity events and aneuploidy. The clinical isolate P60002 was found to be highly resistant to azole-class drugs, yet lacked mutations or chromosomal rearrangements known to be associated with azole resistance. Transcription profiling suggested that increased expression of two putative drug efflux pumps, CDR11 and QDR1, might confer azole resistance. However, ectopic expression of the P60002 alleles of these genes in a drug-susceptible strain did not increase fluconazole resistance. We next examined whether the presence of three copies of chromosome 4 (Chr4) or chromosome 6 (Chr6) contributed to azole resistance in P60002. We established that Chr4 trisomy contributes significantly to fluconazole resistance, whereas Chr6 trisomy has no discernible effect on resistance. In contrast, a Chr4 trisomy did not increase fluconazole resistance when present in the standard SC5314 strain background. These results establish a link between Chr4 trisomy and elevated fluconazole resistance, and demonstrate the impact of genetic background on drug resistance phenotypes in C. albicans.

The novel nematicide wact-86 interacts with aldicarb to kill nematodes

Parasitic nematodes negatively impact human and animal health worldwide. The market withdrawal of nematicidal agents due to unfavourable toxicities has limited the available treatment options. In principle, co-administering nematicides at lower doses along with molecules that potentiate their activity could mitigate adverse toxicities without compromising efficacy. Here, we screened for new small molecules that interact with aldicarb, which is a highly effective treatment for plant-parasitic nematodes whose toxicity hampers its utility. From our collection of 638 worm-bioactive compounds, we identified 20 molecules that interact positively with aldicarb to either kill or arrest the growth of the model nematode Caenorhabditis elegans. We investigated the mechanism of interaction between aldicarb and one of these novel nematicides called wact-86. We found that the carboxylesterase enzyme GES-1 hydrolyzes wact-86, and that the interaction is manifested by aldicarb’s inhibition of wact-86’s metabolism by GES-1. This work demonstrates the utility of C. elegans as a platform to search for new molecules that can positively interact with industrial nematicides, and provides proof-of-concept for prospective discovery efforts.

Many nematicides that have been used to kill plant and animal parasitic nematodes are being phased out over concerns of toxicity to humans. One potential solution to reduce toxicity is to use the nematicide at a lower concentration in combination with a second compound that together will produce a synergistic killing effect. That is, the use of either molecule alone at low concentrations is non-lethal, but when used together at these same concentrations, the cocktail is lethal. This strategy has two benefits. First, the killing effect is concentrated at the site of use and as the two molecules diffuse from the targeted site, toxicity is negated. Second, less of the toxic molecule is needed and therefore less is dispersed into the environment. Here, we describe our use of a model nematode called C. elegans to search for molecules that interact with aldicarb, which is one of the nematicides being phased out by environmental agencies. We identified 20 compounds that interact with aldicarb and describe how one of these, called wact-86, functions with aldicarb to kill worms. Our work provides proof-of-principle that C. elegans is a useful model for identifying compounds that positively interact with industrial nematicides and for understanding the nature of such interactions.

Bioactivity in Rhododendron: A Systemic Analysis of Antimicrobial and Cytotoxic Activities and Their Phylogenetic and Phytochemical Origins

The exceptional diversity of the genus Rhododendron has a strong potential for identification, characterization, and production of bioactive lead compounds for health purposes. A particularly relevant field of application is the search for new antibiotics. Here, we present a comparative analysis of nearly 90 Rhododendron species targeted toward the search for such candidate substances. Through a combination of phytochemical profiles with antimicrobial susceptibility and cytotoxicity, complemented by phylogenetic analyses, we identify seven potentially antimicrobial active but non-cytotoxic compounds in terms of mass-to-charge ratios and retention times. Exemplary bioactivity-guided fractionation for a promising Rhododendron species experimentally supports in fact one of these candidate lead compounds. By combining categorical correlation analysis with Boolean operations, we have been able to investigate the origin of bioactive effects in further detail. Intriguingly, we discovered clear indications of systems effects (synergistic interactions and functional redundancies of compounds) in the manifestation of antimicrobial activities in this plant genus.

Future therapies targeted towards eliminating Candida biofilms and associated infections

INTRODUCTION

Candida species are common human commensals and cause either superficial or invasive opportunistic infections. The biofilm form of candida as opposed to its suspended, planktonic form, is predominantly associated with these infections. Alternative or adjunctive therapies are urgently needed to manage Candida infections as the currently available short arsenal of antifungal drugs has been compromised due to their systemic toxicity, cross-reactivity with other drugs, and above all, by the emergence of drug-resistant Candida species due to irrational drug use. Areas covered: Combination anti-Candida therapies, antifungal lock therapy, denture cleansers, and mouth rinses have all been proposed as alternatives for disrupting candidal biofilms on different substrates. Other suggested approaches for the management of candidiasis include the use of natural compounds, such as probiotics, plants extracts and oils, antifungal quorum sensing molecules, anti-Candida antibodies and vaccines, cytokine therapy, transfer of primed immune cells, photodynamic therapy, and nanoparticles. Expert commentary: The sparsity of currently available antifungals and the plethora of proposed anti-candidal therapies is a distinct indication of the urgent necessity to develop efficacious therapies for candidal infections. Alternative drug delivery approaches, such as probiotics, reviewed here is likely to be a reality in clinical settings in the not too distant future.

Beauvericin Potentiates Azole Activity via Inhibition of Multidrug Efflux, Blocks Candida albicans Morphogenesis, and Is Effluxed via Yor1 and Circuitry Controlled by Zcf29

Invasive fungal infections are a leading cause of human mortality. Effective treatment is hindered by the rapid emergence of resistance to the limited number of antifungal drugs, demanding new strategies to treat life-threatening fungal infections. Here, we explore a powerful strategy to enhance antifungal efficacy against leading human fungal pathogens by using the natural product beauvericin. We found that beauvericin potentiates the activity of azole antifungals against azole-resistant Candida isolates via inhibition of multidrug efflux and that beauvericin itself is effluxed via Yor1. As observed in Saccharomyces cerevisiae, we determined that beauvericin inhibits TOR signaling in Candida albicans To further characterize beauvericin activity in C. albicans, we leveraged genome sequencing of beauvericin-resistant mutants. Resistance was conferred by mutations in transcription factor genes TAC1, a key regulator of multidrug efflux, and ZCF29, which was uncharacterized. Transcriptional profiling and chromatin immunoprecipitation coupled to microarray analyses revealed that Zcf29 binds to and regulates the expression of multidrug transporter genes. Beyond drug resistance, we also discovered that beauvericin blocks the C. albicans morphogenetic transition from yeast to filamentous growth in response to diverse cues. We found that beauvericin represses the expression of many filament-specific genes, including the transcription factor BRG1 Thus, we illuminate novel circuitry regulating multidrug efflux and establish that simultaneously targeting drug resistance and morphogenesis provides a promising strategy to combat life-threatening fungal infections.

Analysis of Repair Mechanisms following an Induced Double-Strand Break Uncovers Recessive Deleterious Alleles in the Candida albicans Diploid Genome

The diploid genome of the yeast Candida albicans is highly plastic, exhibiting frequent loss-of-heterozygosity (LOH) events. To provide a deeper understanding of the mechanisms leading to LOH, we investigated the repair of a unique DNA double-strand break (DSB) in the laboratory C. albicans SC5314 strain using the I-SceI meganuclease. Upon I-SceI induction, we detected a strong increase in the frequency of LOH events at an I-SceI target locus positioned on chromosome 4 (Chr4), including events spreading from this locus to the proximal telomere. Characterization of the repair events by single nucleotide polymorphism (SNP) typing and whole-genome sequencing revealed a predominance of gene conversions, but we also observed mitotic crossover or break-induced replication events, as well as combinations of independent events. Importantly, progeny that had undergone homozygosis of part or all of Chr4 haplotype B (Chr4B) were inviable. Mining of genome sequencing data for 155 C. albicans isolates allowed the identification of a recessive lethal allele in the GPI16 gene on Chr4B unique to C. albicans strain SC5314 which is responsible for this inviability. Additional recessive lethal or deleterious alleles were identified in the genomes of strain SC5314 and two clinical isolates. Our results demonstrate that recessive lethal alleles in the genomes of C. albicans isolates prevent the occurrence of specific extended LOH events. While these and other recessive lethal and deleterious alleles are likely to accumulate in C. albicans due to clonal reproduction, their occurrence may in turn promote the maintenance of corresponding nondeleterious alleles and, consequently, heterozygosity in the C. albicans species.

IMPORTANCE

Recessive lethal alleles impose significant constraints on the biology of diploid organisms. Using a combination of an I-SceI meganuclease-mediated DNA DSB, a fluorescence-activated cell sorter (FACS)-optimized reporter of LOH, and a compendium of 155 genome sequences, we were able to unmask and identify recessive lethal and deleterious alleles in isolates of Candida albicans, a diploid yeast and the major fungal pathogen of humans. Accumulation of recessive deleterious mutations upon clonal reproduction of C. albicans could contribute to the maintenance of heterozygosity despite the high frequency of LOH events in this species.

Trends and Challenges in Pesticide Resistance Detection

Pesticide resistance is a crucial factor to be considered when developing strategies for the minimal use of pesticides while maintaining pesticide efficacy. This goal requires monitoring the emergence and development of resistance to pesticides in crop pests. To this end, various methods for resistance diagnosis have been developed for different groups of pests. This review provides an overview of biological, biochemical, and molecular methods that are currently used to detect and quantify pesticide resistance. The agronomic, technical, and economic advantages and drawbacks of each method are considered. Emerging technologies are also described, with their associated challenges and their potential for the detection of resistance mechanisms likely to be selected by current and future plant protection methods.

Using combination therapy to thwart drug resistance

Drug combination therapy is a promising strategy to extend the lifespan of our antimicrobials. Drug combinations used in treatment must be carefully selected to minimize the evolution of resistance, either by carefully determining drug pairs that hinder the acquisition of resistance mechanisms, or by screening for combinations that inhibit growth and show reduced vulnerability to resistance. Modeling of interactions between drugs has provided intriguing insights into strategies for combination therapy deployment. Ultimately, more rigorous clinical trials need to be performed to evaluate the laboratory and modeling results and advance treatment options.

Dual action antifungal small molecule modulates multidrug efflux and TOR signaling

There is an urgent need for new strategies to treat invasive fungal infections, which are a leading cause of human mortality. Here, we establish two activities of the natural product beauvericin, which potentiates the activity of the most widely deployed class of antifungal against the leading human fungal pathogens, blocks the emergence of drug resistance, and renders antifungal-resistant pathogens responsive to treatment in mammalian infection models. Harnessing genome sequencing of beauvericin-resistant mutants, affinity purification of a biotinylated beauvericin analog, and biochemical and genetic assays reveals that beauvericin blocks multidrug efflux and inhibits the global regulator TORC1 kinase, thereby activating the protein kinase CK2 and inhibiting the molecular chaperone Hsp90. Substitutions in the multidrug transporter Pdr5 that enable beauvericin efflux impair antifungal efflux, thereby impeding resistance to the drug combination. Thus, dual targeting of multidrug efflux and TOR signaling provides a powerful, broadly effective therapeutic strategy for treating fungal infectious disease that evades resistance.

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations.

Drug combinations represent a promising strategy for overcoming fungal drug resistance and treating complex diseases. There is an urgent need to establish powerful computational methods for systematic prediction of synergistic drug combination on a large scale. Based on the assumption that principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa, NLLSS was developed to predict potential synergistic drug combinations by integrating known synergistic drug combinations, unlabeled drug combinations, drug-target interactions, and drug chemical structures. NLLSS has obtained the reliable performance in the cross validation and experimental validations, which indicated that NLLSS has an excellent performance of identifying potential synergistic drug combinations. Out of 13 predicted antifungal synergistic drug combinations, 7 candidates were experimentally confirmed. It is anticipated that NLLSS would be an important and useful resource by providing a new strategy to identify potential synergistic antifungal combinations, explore new indications of existing drugs, and provide useful insights into the underlying molecular mechanisms of synergistic drug combinations.

Mapping the Hsp90 Genetic Network Reveals Ergosterol Biosynthesis and Phosphatidylinositol-4-Kinase Signaling as Core Circuitry Governing Cellular Stress

Candida albicans is a leading human fungal pathogen that causes life-threatening systemic infections. A key regulator of C. albicans stress response, drug resistance, morphogenesis, and virulence is the molecular chaperone Hsp90. Targeting Hsp90 provides a powerful strategy to treat fungal infections, however, the therapeutic utility of current inhibitors is compromised by toxicity due to inhibition of host Hsp90. To identify components of the Hsp90-dependent circuitry governing virulence and drug resistance that are sufficiently divergent for selective targeting in the pathogen, we pioneered chemical genomic profiling of the Hsp90 genetic network in C. albicans. Here, we screen mutant collections covering ~10% of the genome for hypersensitivity to Hsp90 inhibition in multiple environmental conditions. We identify 158 HSP90 chemical genetic interactors, most of which are important for growth only in specific environments. We discovered that the sterol C-22 desaturase gene ERG5 and the phosphatidylinositol-4-kinase (PI4K) gene STT4 are HSP90 genetic interactors under multiple conditions, suggesting a function upstream of Hsp90. By systematic analysis of the ergosterol biosynthetic cascade, we demonstrate that defects in ergosterol biosynthesis induce cellular stress that overwhelms Hsp90's functional capacity. By analysis of the phosphatidylinositol pathway, we demonstrate that there is a genetic interaction between the PI4K Stt4 and Hsp90. We also establish that Stt4 is required for normal actin polarization through regulation of Wal1, and suggest a model in which defects in actin remodeling induces stress that creates a cellular demand for Hsp90 that exceeds its functional capacity. Consistent with this model, actin inhibitors are synergistic with Hsp90 inhibitors. We highlight new connections between Hsp90 and virulence traits, demonstrating that Erg5 and Stt4 enable activation of macrophage pyroptosis. This work uncovers novel circuitry regulating Hsp90 functional capacity and new effectors governing drug resistance, morphogenesis and virulence, revealing new targets for antifungal drug development.