Evolutionary divergence in the fungal response to fluconazole revealed by soft clustering

Natural trait variation across Saccharomycotina species

Among molecular biologists, the group of fungi called Saccharomycotina is famous for its yeasts. These yeasts in turn are famous for what they have in common-genetic, biochemical, and cell-biological characteristics that serve as models for plants and animals. But behind the apparent homogeneity of Saccharomycotina species lie a wealth of differences. In this review, we discuss traits that vary across the Saccharomycotina subphylum. We describe cases of bright pigmentation; a zoo of cell shapes; metabolic specialties; and species with unique rules of gene regulation. We discuss the genetics of this diversity and why it matters, including insights into basic evolutionary principles with relevance across Eukarya.

Candidiasis: From cutaneous to systemic, new perspectives of potential targets and therapeutic strategies

Candidiasis is an infection caused by fungi from a Candida species, most commonly Candida albicans. C. albicans is an opportunistic fungal pathogen typically residing on human skin and mucous membranes of the mouth, intestines or vagina. It can cause a wide variety of mucocutaneous barrier and systemic infections; and becomes a severe health problem in HIV/AIDS patients and in individuals who are immunocompromised following chemotherapy, treatment with immunosuppressive agents or after antibiotic-induced dysbiosis. However, the immune mechanism of host resistance to C. albicans infection is not fully understood, there are a limited number of therapeutic antifungal drugs for candidiasis, and these have disadvantages that limit their clinical application. Therefore, it is urgent to uncover the immune mechanisms of the host protecting against candidiasis and to develop new antifungal strategies. This review synthesizes current knowledge of host immune defense mechanisms from cutaneous candidiasis to invasive C. albicans infection and documents promising insights for treating candidiasis through inhibitors of potential antifungal target proteins.

Coordinated Regulation of Membrane Homeostasis and Drug Accumulation by Novel Kinase STK-17 in Response to Antifungal Azole Treatment

The emergence of antifungal resistance, especially to the most widely used azole class of ergosterol biosynthesis inhibitors, makes fungal infections difficult to treat in clinics and agriculture. When exposed to azoles, fungi can make adaptive responses to alleviate azole toxicity and produce azole tolerance. However, except for azole efflux pumps and ergosterol biosynthesis genes, the role of most azole responsive genes in azole resistance is unknown. In this study, STK-17, whose transcription is upregulated by azoles, was characterized as a novel kinase that is required for azole resistance. Deletion or dysfunction of STK-17 led to azole hypersensitivity in Neurospora crassa and to other ergosterol biosynthesis inhibitors such as amorolfine, terbinafine, and amphotericin B, but not fatty acid and ceramide biosynthesis inhibitors. STK-17 was also required for oxidative stress resistance, but this was not connected to azole resistance. RNA-seq results showed that stk-17 deletion affected the basal expression and the response to ketoconazole of some membrane protein genes, indicating functional association of STK-17 with the membrane. Notably, deletion of stk-17 affected the normal response to azoles of erg genes, including the azole target-encoding gene erg11, and erg2, erg6, and erg24, and led to abnormal accumulation of sterols in the presence of azoles. HPLC-MS/MS analysis revealed increased intracellular azole accumulation in the stk-17 mutant, possibly due to enhanced azole influx and reduced azole efflux that was independent of the major efflux pump CDR4. Importantly, STK-17 was widely distributed and functionally conserved among fungi, thus providing a potential antifungal target.

IMPORTANCE Antifungal resistance is increasing worldwide, especially to the most widely used azole class of ergosterol biosynthesis inhibitors, making control of fungal infections more challenging. A lot of effort has been expended in elucidating the mechanism of azole resistance and revealing potential antifungal targets. In this study, by analyzing azole-responsive genes in Neurospora crassa, we discovered STK-17, a novel kinase, that is required for azole resistance in several types of fungi. It has a role in regulating membrane homeostasis, responses to azole by ergosterol biosynthesis genes and azole accumulation, thus, deepening our understanding on the mechanism of azole stress response. Additionally, STK-17 is conserved among fungi and plays important roles in fungal development and stress resistance. Kinase inhibitors are broadly used for treating diseases, and our study pinpoints a potential drug target for antifungal development.

What 'Omics Can Tell Us About Antifungal Adaptation

Invasive candidiasis, the most frequent healthcare-associated invasive fungal infection, is commonly caused by Candida albicans. However, in recent years other antifungal-resistant Candida species—namely Candida glabrata and Candidaauris—have emerged as a serious matter of concern. Much of our understanding of the mechanisms regulating antifungal resistance and tolerance relies on studies utilizing C. albicans, C. glabrataand the model yeast Saccharomyces cerevisiae. ‘Omics studies have been used to describe alterations in metabolic, genomic and transcriptomic expression profiles upon antifungal treatment of fungal cells. The physiological changes identified by these approaches could significantly affect fungal fitness in the host and survival during antifungal challenge, as well as provide further understanding of clinical resistance. Thus, this review aims to comparatively address ‘omics data for C. albicans, C. glabrata andS. cerevisiae published from 2000 to 2021 to identify what these technologies can tell us regarding cellular responses to antifungal therapy. We will also highlight possible effects on pathogen survival and identify future avenues for antifungal research.

Sterol uptake analysis in Saccharomyces and non-Saccharomyces wine yeast species

Sterols are essential components of the yeast membrane and their synthesis requires oxygen. Yet, Saccharomyces cerevisiae has developed the ability to take up sterols from the medium under anaerobiosis. Here we investigated sterol uptake efficiency and the expression of genes related to sterol import in Saccharomyces and non-Saccharomyces wine yeast species fermenting under anaerobic conditions. The sterol uptake efficiency of 39 strains was evaluated by flow cytometry (with 25-NBD Cholesterol, a fluorescent cholesterol probe introduced in the medium) and we found an important discrepancy between Saccharomyces and non-Saccharomyces wine yeast species that we correlated to a lower final cell population and a lower fermentation rate. A high uptake of sterol was observed in the various Saccharomyces strains. Spot tests performed on 13 of these strains confirmed the differences between Saccharomyces and non-Saccharomyces strains, suggesting that the presence of the sterol uptake transporters AUS1 and PDR11 could cause these discrepancies. Indeed, we could not find any homologue to these genes in the genome of Hanseniaspora uvarum, H. guillermondii, Lachancea thermotolerans, Torulaspora delbreueckii, Metschnikowia pulcherrima, or Starmarella bacillaris species. The specialization of sterol import function for post genome-duplication species may have favored growth under anaerobiosis.

Potentiated inhibition of Trichoderma virens and other environmental fungi by new biocide combinations

Abstract

Fungi cause diverse, serious socio-economic problems, including biodeterioration of valuable products and materials that spawns a biocides industry worth ~$11 billion globally. To help combat environmental fungi that commonly colonise material products, this study tested the hypothesis that combination of an approved fungicide with diverse agents approved by the FDA (Food and Drug Administration) could reveal potent combinatorial activities with promise for fungicidal applications. The strategy to use approved compounds lowers potential development risks for any effective combinations. A high-throughput assay of 1280 FDA-approved compounds was conducted to find those that potentiate the effect of iodopropynyl-butyl-carbamate (IPBC) on the growth of Trichoderma virens; IPBC is one of the two most widely used Biocidal Products Regulations–approved fungicides. From this library, 34 compounds in combination with IPBC strongly inhibited fungal growth. Low-cost compounds that gave the most effective growth inhibition were tested against other environmental fungi that are standard biomarkers for resistance of synthetic materials to fungal colonisation. Trifluoperazine (TFZ) in combination with IPBC enhanced growth inhibition of three of the five test fungi. The antifungal hexetidine (HEX) potentiated IPBC action against two of the test organisms. Testable hypotheses on the mechanisms of these combinatorial actions are discussed. Neither IPBC + TFZ nor IPBC + HEX exhibited a combinatorial effect against mammalian cells. These combinations retained strong fungal growth inhibition properties after incorporation to a polymer matrix (alginate) with potential for fungicide delivery. The study reveals the potential of such approved compounds for novel combinatorial applications in the control of fungal environmental opportunists.

Key points

• Search with an approved fungicide to find new fungicidal synergies in drug libraries.

• New combinations inhibit growth of key environmental fungi on different matrices.

• The approach enables a more rapid response to demand for new biocides.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-021-11211-3.

Candidiasis and Mechanisms of Antifungal Resistance

Candidiasis can be present as a cutaneous, mucosal or deep-seated organ infection, which is caused by more than 20 types of Candida sp., with C. albicans being the most common. These are pathogenic yeast and are usually present in the normal microbiome. High-risk individuals are patients of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), organ transplant, and diabetes. During infection, pathogens can adhere to complement receptors and various extracellular matrix proteins in the oral and vaginal cavity. Oral and vaginal Candidiasis results from the overgrowth of Candida sp. in the hosts, causing penetration of the oral and vaginal tissues. Symptoms include white patches in the mouth, tongue, throat, and itchiness or burning of genitalia. Diagnosis involves visual examination, microscopic analysis, or culturing. These infections are treated with a variety of antifungals that target different biosynthetic pathways of the pathogen. For example, echinochandins target cell wall biosynthesis, while allylamines, azoles, and morpholines target ergosterol biosynthesis, and 5-Flucytosine (5FC) targets nucleic acid biosynthesis. Azoles are commonly used in therapeutics, however, because of its fungistatic nature, Candida sp. evolve azole resistance. Besides azoles, Candida sp. also acquire resistance to polyenes, echinochandins, and 5FC. This review discusses, in detail, the drug resistance mechanisms adapted by Candida sp.

Amn1 governs post-mitotic cell separation in Saccharomyces cerevisiae

Post-mitotic cell separation is one of the most prominent events in the life cycle of eukaryotic cells, but the molecular underpinning of this fundamental biological process is far from being concluded and fully characterized. We use budding yeast Saccharomyces cerevisiae as a model and demonstrate AMN1 as a major gene underlying post-mitotic cell separation in a natural yeast strain, YL1C. Specifically, we define a novel 11-residue domain by which Amn1 binds to Ace2. Moreover, we demonstrate that Amn1 induces proteolysis of Ace2 through the ubiquitin proteasome system and in turn, down-regulates Ace2’s downstream target genes involved in hydrolysis of the primary septum, thus leading to inhibition of cell separation and clumping of haploid yeast cells. Using ChIP assays and site-specific mutation experiments, we show that Ste12 and the a1-α12 heterodimer are two direct regulators of AMN1. Specifically, a1-α2, a diploid-specific heterodimer, prevents Ste12 from inactivating AMN1 through binding to its promoter. This demonstrates how the Amn1-governed cell separation is highly cell type dependent. Finally, we show that AMN1^368D from YL1C is a dominant allele in most strains of S. cerevisiae and evolutionarily conserved in both genic structure and phenotypic effect in two closely related yeast species, K. lactis and C. glabrata.

Separation of mother and daughter cells after mitosis in eukaryotes enacts various functional and/or developmental needs and has significant medical and industrial implications. How this cellular behaviour is regulated is far from being concluded. We report here a novel Amn1 mediated post-mitotic cell separation in a budding yeast strain, YL1C and demonstrate that the post-mitotic cell separation can be regulated through a ubiquitin-conjugated protein degradation of Ace2 by Amn1. The Amn1-governed switch of cell separation is evolutionarily conserved and highly cell type dependent. These findings provide insights into the molecular mechanism of how post-mitotic cell separation is regulated in budding yeast, and data for translating into medical and industrial applications.

Comparative Transcriptomics Highlights New Features of the Iron Starvation Response in the Human Pathogen Candida glabrata

In this work, we used comparative transcriptomics to identify regulatory outliers (ROs) in the human pathogen Candida glabrata. ROs are genes that have very different expression patterns compared to their orthologs in other species. From comparative transcriptome analyses of the response of eight yeast species to toxic doses of selenite, a pleiotropic stress inducer, we identified 38 ROs in C. glabrata. Using transcriptome analyses of C. glabrata response to five different stresses, we pointed out five ROs which were more particularly responsive to iron starvation, a process which is very important for C. glabrata virulence. Global chromatin Immunoprecipitation and gene profiling analyses showed that four of these genes are actually new targets of the iron starvation responsive Aft2 transcription factor in C. glabrata. Two of them (HBS1 and DOM34b) are required for C. glabrata optimal growth in iron limited conditions. In S. cerevisiae, the orthologs of these two genes are involved in ribosome rescue by the NO GO decay (NGD) pathway. Hence, our results suggest a specific contribution of NGD co-factors to the C. glabrata adaptation to iron starvation.

Describing Genomic and Epigenomic Traits Underpinning Emerging Fungal Pathogens

An unprecedented number of pathogenic fungi are emerging and causing disease in animals and plants, putting the resilience of wild and managed ecosystems in jeopardy. While the past decades have seen an increase in the number of pathogenic fungi, they have also seen the birth of new big data technologies and analytical approaches to tackle these emerging pathogens. We review how the linked fields of genomics and epigenomics are transforming our ability to address the challenge of emerging fungal pathogens. We explore the methodologies and bioinformatic toolkits that currently exist to rapidly analyze the genomes of unknown fungi, then discuss how these data can be used to address key questions that shed light on their epidemiology. We show how genomic approaches are leading a revolution into our understanding of emerging fungal diseases and speculate on future approaches that will transform our ability to tackle this increasingly important class of emerging pathogens.

A Network of Paralogous Stress Response Transcription Factors in the Human Pathogen Candida glabrata

The yeast Candida glabrata has become the second cause of systemic candidemia in humans. However, relatively few genome-wide studies have been conducted in this organism and our knowledge of its transcriptional regulatory network is quite limited. In the present work, we combined genome-wide chromatin immunoprecipitation (ChIP-seq), transcriptome analyses, and DNA binding motif predictions to describe the regulatory interactions of the seven Yap (Yeast AP1) transcription factors of C. glabrata. We described a transcriptional network containing 255 regulatory interactions and 309 potential target genes. We predicted with high confidence the preferred DNA binding sites for 5 of the 7 CgYaps and showed a strong conservation of the Yap DNA binding properties between S. cerevisiae and C. glabrata. We provided reliable functional annotation for 3 of the 7 Yaps and identified for Yap1 and Yap5 a core regulon which is conserved in S. cerevisiae, C. glabrata, and C. albicans. We uncovered new roles for CgYap7 in the regulation of iron-sulfur cluster biogenesis, for CgYap1 in the regulation of heme biosynthesis and for CgYap5 in the repression of GRX4 in response to iron starvation. These transcription factors define an interconnected transcriptional network at the cross-roads between redox homeostasis, oxygen consumption, and iron metabolism.

Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum

Comparative functional genomics aims to measure and compare genome-wide functional data such as transcriptomes, proteomes, and epigenomes across multiple species to study the conservation and divergence patterns of such quantitative measurements. However, computational methods to systematically compare these quantitative genomic profiles across multiple species are in their infancy. We developed Arboretum, a novel algorithm to identify modules of co-expressed genes and trace their evolutionary history across multiple species from a complex phylogeny. To interpret the results from Arboretum we developed several measures to examine the extent of conservation and divergence in modules and their relationship to species lifestyle, cis-regulatory elements, and gene duplication. We applied Arboretum to study the evolution of modular transcriptional regulatory programs controlling transcriptional response to different environmental stresses in the yeast Ascomycota phylogeny. We found that modules of similar patterns of expression captured the transcriptional responses to different stresses across species; however, the genes exhibiting these patterns were not the same. Divergence in module membership was associated with changes in lifestyle and specific clades and that gene duplication was a major factor contributing to the divergence of module membership.

An Antifungal Combination Matrix Identifies a Rich Pool of Adjuvant Molecules that Enhance Drug Activity against Diverse Fungal Pathogens

There is an urgent need to identify new treatments for fungal infections. By combining sub-lethal concentrations of the known antifungals fluconazole, caspofungin, amphotericin B, terbinafine, benomyl, and cyprodinil with ∼3,600 compounds in diverse fungal species, we generated a deep reservoir of chemical-chemical interactions termed the Antifungal Combinations Matrix (ACM). Follow-up susceptibility testing against a fluconazole-resistant isolate of C. albicans unveiled ACM combinations capable of potentiating fluconazole in this clinical strain. We used chemical genetics to elucidate the mode of action of the antimycobacterial drug clofazimine, a compound with unreported antifungal activity that synergized with several antifungals. Clofazimine induces a cell membrane stress for which the Pkc1 signaling pathway is required for tolerance. Additional tests against additional fungal pathogens, including Aspergillus fumigatus, highlighted that clofazimine exhibits efficacy as a combination agent against multiple fungi. Thus, the ACM is a rich reservoir of chemical combinations with therapeutic potential against diverse fungal pathogens.

Evolution of regulatory networks in Candida glabrata: learning to live with the human host

The opportunistic human fungal pathogen Candida glabrata is second only to C. albicans as the cause of Candida infections and yet is more closely related to Saccharomyces cerevisiae. Recent advances in functional genomics technologies and computational approaches to decipher regulatory networks, and the comparison of these networks among these and other Ascomycete species, have revealed both unique and shared strategies in adaptation to a human commensal/opportunistic pathogen lifestyle and antifungal drug resistance in C. glabrata. Recently, several C. glabrata sister species in the Nakeseomyces clade representing both human associated (commensal) and environmental isolates have had their genomes sequenced and analyzed. This has paved the way for comparative functional genomics studies to characterize the regulatory networks in these species to identify informative patterns of conservation and divergence linked to phenotypic evolution in the Nakaseomyces lineage.

Comparative analysis of gene regulatory networks: from network reconstruction to evolution

Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.

Unraveling the biology of a fungal meningitis pathogen using chemical genetics

The fungal meningitis pathogen Cryptococcus neoformans is a central driver of mortality in HIV/AIDS. We report a genome-scale chemical genetic data map for this pathogen that quantifies the impact of 439 small-molecule challenges on 1,448 gene knockouts. We identified chemical phenotypes for 83% of mutants screened and at least one genetic response for each compound. C. neoformans chemical-genetic responses are largely distinct from orthologous published profiles of Saccharomyces cerevisiae, demonstrating the importance of pathogen-centered studies. We used the chemical-genetic matrix to predict novel pathogenicity genes, infer compound mode of action, and to develop an algorithm, O2M, that predicts antifungal synergies. These predictions were experimentally validated, thereby identifying virulence genes, a molecule that triggers G2/M arrest and inhibits the Cdc25 phosphatase, and many compounds that synergize with the antifungal drug fluconazole. Our work establishes a chemical-genetic foundation for approaching an infection responsible for greater than one-third of AIDS-related deaths.

ModuleBlast: identifying activated sub-networks within and across species

Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFκB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.

Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules

Comparative functional genomics studies the evolution of biological processes by analyzing functional data, such as gene expression profiles, across species. A major challenge is to compare profiles collected in a complex phylogeny. Here, we present Arboretum, a novel scalable computational algorithm that integrates expression data from multiple species with species and gene phylogenies to infer modules of coexpressed genes in extant species and their evolutionary histories. We also develop new, generally applicable measures of conservation and divergence in gene regulatory modules to assess the impact of changes in gene content and expression on module evolution. We used Arboretum to study the evolution of the transcriptional response to heat shock in eight species of Ascomycota fungi and to reconstruct modules of the ancestral environmental stress response (ESR). We found substantial conservation in the stress response across species and in the reconstructed components of the ancestral ESR modules. The greatest divergence was in the most induced stress, primarily through module expansion. The divergence of the heat stress response exceeds that observed in the response to glucose depletion in the same species. Arboretum and its associated analyses provide a comprehensive framework to systematically study regulatory evolution of condition-specific responses.

The Candida glabrata sterol scavenging mechanism, mediated by the ATP-binding cassette transporter Aus1p, is regulated by iron limitation

During disseminated infection by the opportunistic pathogen Candida glabrata, uptake of sterols such as serum cholesterol may play a significant role during pathogenesis. The ATP-binding cassette transporter Aus1p is thought to function as a sterol importer and in this study, we show that uptake of exogenous sterols occurred under anaerobic conditions in wild-type cells of C. glabrata but not in AUS1-deleted mutant (aus1Δ) cells. In aerobic cultures, growth inhibition by fluconazole was prevented in the presence of serum, and AUS1 expression was upregulated. Uptake of sterol by azole treated cells required the presence of serum, and sterol alone did not reverse FLC inhibition of growth. However, if iron availability in the growth medium was limited by addition of the iron chelators ferrozine or apo-transferrin, growth of wild-type cells, but not aus1Δ cells, was rescued. In a mouse model of disseminated infection, the C. glabrata aus1Δ strain caused a significantly decreased kidney fungal burden than the wild-type strain or a strain in which AUS1 was restored. We conclude that sterol uptake in C. glabrata can occur in iron poor environment of host tissues and thus may contribute to C. glabrata pathogenesis.

Matching experiments across species using expression values and textual information

Motivation: With the vast increase in the number of gene expression datasets deposited in public databases, novel techniques are required to analyze and mine this wealth of data. Similar to the way BLAST enables cross-species comparison of sequence data, tools that enable cross-species expression comparison will allow us to better utilize these datasets: cross-species expression comparison enables us to address questions in evolution and development, and further allows the identification of disease-related genes and pathways that play similar roles in humans and model organisms. Unlike sequence, which is static, expression data changes over time and under different conditions. Thus, a prerequisite for performing cross-species analysis is the ability to match experiments across species.

Results: To enable better cross-species comparisons, we developed methods for automatically identifying pairs of similar expression datasets across species. Our method uses a co-training algorithm to combine a model of expression similarity with a model of the text which accompanies the expression experiments. The co-training method outperforms previous methods based on expression similarity alone. Using expert analysis, we show that the new matches identified by our method indeed capture biological similarities across species. We then use the matched expression pairs between human and mouse to recover known and novel cycling genes as well as to identify genes with possible involvement in diabetes. By providing the ability to identify novel candidate genes in model organisms, our method opens the door to new models for studying diseases.

Availability: Source code and supplementary information is available at: www.andrew.cmu.edu/user/aaronwis/cotrain12.

Contact:zivbj@cs.cmu.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Milbemycins: more than efflux inhibitors for fungal pathogens

Existing antifungal agents are still confronted to activities limited to specific fungal species and to the development of resistance. Several improvements are possible either by tackling and overcoming resistance or exacerbating the activity of existing antifungal agents. In Candida glabrata, azole resistance is almost exclusively mediated by ABC transporters (including C. glabrata CDR1 [CgCDR1] and CgCDR2) via gain-of-function mutations in the transcriptional activator CgPDR1 or by mitochondrial dysfunctions. We also observed that azole resistance was correlating with increasing virulence and fitness of C. glabrata in animal models of infection. This observation motivated the re-exploitation of ABC transporter inhibitors as a possible therapeutic intervention to decrease not only the development of azole resistance but also to interfere with the virulence of C. glabrata. Milbemycins are known ABC transporter inhibitors, and here we used commercially available milbemycin A3/A4 oxim derivatives to verify this effect. As expected, the derivatives were inhibiting C. glabrata efflux with the highest activity for A3 oxim below 1 μg/ml. More surprising was that oxim derivatives had intrinsic fungicidal activity above 3.2 μg/ml, thus highlighting effects additional to the efflux inhibition. Similar values were obtained with C. albicans. Our data show that the fungicidal activity could be related to reactive oxygen species formation in these species. Transcriptional analysis performed both in C. glabrata and C. albicans exposed to A3 oxim highlighted a core of commonly regulated genes involved in stress responses, including genes involved in oxidoreductive processes, protein ubiquitination, and vesicle trafficking, as well as mitogen-activated protein kinases. However, the transcript profiles contained also species-specific signatures. Following these observations, experimental treatments of invasive infections were performed in mice treated with the commercial A3/A4 oxim preparation alone or in combination with fluconazole. Tissue burden analysis revealed that oxims on their own were able to decrease fungal burdens in both Candida species. In azole-resistant isolates, oxims acted synergistically in vivo with fluconazole to reduce fungal burden to levels of azole-susceptible isolates. In conclusion, we show here the potential of milbemycins not only as drug efflux inhibitors but also as effective fungal growth inhibitors in C. glabrata and C. albicans.

DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data

Background

Modeling dynamic regulatory networks is a major challenge since much of the protein-DNA interaction data available is static. The Dynamic Regulatory Events Miner (DREM) uses a Hidden Markov Model-based approach to integrate this static interaction data with time series gene expression leading to models that can determine when transcription factors (TFs) activate genes and what genes they regulate. DREM has been used successfully in diverse areas of biological research. However, several issues were not addressed by the original version.

Results

DREM 2.0 is a comprehensive software for reconstructing dynamic regulatory networks that supports interactive graphical or batch mode. With version 2.0 a set of new features that are unique in comparison with other softwares are introduced. First, we provide static interaction data for additional species. Second, DREM 2.0 now accepts continuous binding values and we added a new method to utilize TF expression levels when searching for dynamic models. Third, we added support for discriminative motif discovery, which is particularly powerful for species with limited experimental interaction data. Finally, we improved the visualization to support the new features. Combined, these changes improve the ability of DREM 2.0 to accurately recover dynamic regulatory networks and make it much easier to use it for analyzing such networks in several species with varying degrees of interaction information.

Conclusions

DREM 2.0 provides a unique framework for constructing and visualizing dynamic regulatory networks. DREM 2.0 can be downloaded from: www.sb.cs.cmu.edu/drem.

DNA replication stress differentially regulates G1/S genes via Rad53-dependent inactivation of Nrm1

MBF and SBF transcription factors regulate a large family of coordinately expressed G1/S genes required for early cell-cycle functions including DNA replication and repair. SBF is inactivated upon S-phase entry by Clb/CDK whereas MBF targets are repressed by the co-repressor, Nrm1. Using genome-wide expression analysis of cells treated with methyl methane sulfonate (MMS), hydroxyurea (HU) or camptothecin (CPT), we show that genotoxic stress during S phase specifically induces MBF-regulated genes. This occurs via direct phosphorylation of Nrm1 by Rad53, the effector checkpoint kinase, which prevents its binding to MBF target promoters. We conclude that MBF-regulated genes are distinguished from SBF-regulated genes by their sensitivity to activation by the S-phase checkpoint, thereby, providing an effective mechanism for enhancing DNA replication and repair and promoting genome stability.

Biological interaction networks are conserved at the module level

Background

Orthologous genes are highly conserved between closely related species and biological systems often utilize the same genes across different organisms. However, while sequence similarity often implies functional similarity, interaction data is not well conserved even for proteins with high sequence similarity. Several recent studies comparing high throughput data including expression, protein-protein, protein-DNA, and genetic interactions between close species show conservation at a much lower rate than expected.

Results

In this work we collected comprehensive high-throughput interaction datasets for four model organisms (S. cerevisiae, S. pombe, C. elegans, and D. melanogaster) and carried out systematic analyses in order to explain the apparent lower conservation of interaction data when compared to the conservation of sequence data. We first showed that several previously proposed hypotheses only provide a limited explanation for such lower conservation rates. We combined all interaction evidences into an integrated network for each species and identified functional modules from these integrated networks. We then demonstrate that interactions that are part of functional modules are conserved at much higher rates than previous reports in the literature, while interactions that connect between distinct functional modules are conserved at lower rates.

Conclusions

We show that conservation is maintained between species, but mainly at the module level. Our results indicate that interactions within modules are much more likely to be conserved than interactions between proteins in different modules. This provides a network based explanation to the observed conservation rates that can also help explain why so many biological processes are well conserved despite the lower levels of conservation for the interactions of proteins participating in these processes.

Accompanying website: http://www.sb.cs.cmu.edu/CrossSP

The evolution of gene expression regulatory networks in yeasts

Gene regulation is a major source of phenotypic diversity between and within species. This aspect of evolution has long been addressed from the sole point of view of the genome sequence. The incredible development of transcriptomics approaches now allows one to actually study the topology and the properties of regulatory networks on an evolutionary perspective. This new discipline is called comparative functional genomics or comparative transcriptomics. This article reviews some of the main advances made in this field, using yeast species, and especially the species sequenced in the frame of the Genolevures program, as a model.

Large scale comparison of innate responses to viral and bacterial pathogens in mouse and macaque

Viral and bacterial infections of the lower respiratory tract are major causes of morbidity and mortality worldwide. Alveolar macrophages line the alveolar spaces and are the first cells of the immune system to respond to invading pathogens. To determine the similarities and differences between the responses of mice and macaques to invading pathogens we profiled alveolar macrophages from these species following infection with two viral (PR8 and Fuj/02 influenza A) and two bacterial (Mycobacterium tuberculosis and Francisella tularensis Schu S4) pathogens. Cells were collected at 6 time points following each infection and expression profiles were compared across and between species. Our analyses identified a core set of genes, activated in both species and across all pathogens that were predominantly part of the interferon response pathway. In addition, we identified similarities across species in the way innate immune cells respond to lethal versus non-lethal pathogens. On the other hand we also found several species and pathogen specific response patterns. These results provide new insights into mechanisms by which the innate immune system responds to, and interacts with, invading pathogens.

Cross-species discovery of syncretic drug combinations that potentiate the antifungal fluconazole

The authors screen for compounds that show synergistic antifungal activity when combined with the widely-used fungistatic drug fluconazole. Chemogenomic profiling explains the mode of action of synergistic drugs and allows the prediction of additional drug synergies.

The authors screen for compounds that show synergistic antifungal activity when combined with the widely-used fungistatic drug fluconazole. Chemogenomic profiling explains the mode of action of synergistic drugs and allows the prediction of additional drug synergies.

Chemical screens with a library enriched for known drugs identified a diverse set of 148 compounds that potentiated the action of the antifungal drug fluconazole against the fungal pathogens Cryptococcus neoformans, Cryptococcus gattii and Candida albicans, and the model yeast Saccharomyces cerevisiae, often in a species-specific manner.

Chemogenomic profiles of six confirmed hits in S. cerevisiae revealed different modes of action and enabled the prediction of additional synergistic combinations; three-way synergistic interactions exhibited even stronger synergies at low doses of fluconazole.

The synergistic combination of fluconazole and the antidepressant sertraline was active against fluconazole-resistant clinical fungal isolates and in an in vivo model of Cryptococcal infection.

Rising fungal infection rates, especially among immune-suppressed individuals, represent a serious clinical challenge (Gullo, 2009). Cancer, organ transplant and HIV patients, for example, often succumb to opportunistic fungal pathogens. The limited repertoire of approved antifungal agents and emerging drug resistance in the clinic further complicate the effective treatment of systemic fungal infections. At the molecular level, the paucity of fungal-specific essential targets arises from the conserved nature of cellular functions from yeast to humans, as well as from the fact that many essential yeast genes can confer viability at a fraction of wild-type dosage (Yan et al, 2009). Although only ∼1100 of the ∼6000 genes in yeast are essential, almost all genes become essential in specific genetic backgrounds in which another non-essential gene has been deleted or otherwise attenuated, an effect termed synthetic lethality (Tong et al, 2001). Genome-scale surveys suggest that over 200 000 binary synthetic lethal gene combinations dominate the yeast genetic landscape (Costanzo et al, 2010). The genetic buffering phenomenon is also manifest as a plethora of differential chemical–genetic interactions in the presence of sublethal doses of bioactive compounds (Hillenmeyer et al, 2008). These observations frame the difficulty of interdicting network functions in eukaryotic pathogens with single agent therapeutics. At the same time, however, this genetic network organization suggests that judicious combinations of small molecule inhibitors of both essential and non-essential targets may elicit additive or synergistic effects on cell growth (Sharom et al, 2004; Lehar et al, 2008). Unbiased screens for drugs that synergistically enhance a specific bioactive effect, but which are not themselves individually active—termed a syncretic combination—are one means to substantially elaborate chemical space (Keith et al, 2005). Indeed, compounds that enhance the activity of known agents in model yeast and cancer cell line systems have been identified both by focused small molecule library screens and by computational methods (Borisy et al, 2003; Lehar et al, 2007; Nelander et al, 2008; Jansen et al, 2009; Zinner et al, 2009).

To extend the stratagem of chemical synthetic lethality to clinically relevant fungal pathogens, we screened a bioactive library of known drugs for synergistic enhancers of the widely used fungistatic drug fluconazole against the clinically relevant pathogens C. albicans, C. neoformans and C. gattii, as well as the genetically tractable budding yeast S. cerevisiae. Fluconazole is an azole drug that inhibits lanosterol 14α-demethylase, the gene product of ERG11, an essential cytochrome P450 enzyme in the ergosterol biosynthetic pathway (Groll et al, 1998). We identified 148 drugs that potentiate the antifungal action of fluconazole against the four species. These syncretic compounds had not been previously recognized in the clinic as antifungal agents, and many acted in a species-specific manner, often in a potent fungicidal manner.

To understand the mechanisms of synergism, we interrogated six syncretic drugs—trifluoperazine, tamoxifen, clomiphene, sertraline, suloctidil and L-cycloserine—in genome-wide chemogenomic profiles of the S. cerevisiae deletion strain collection (Giaever et al, 1999). These profiles revealed that membrane, vesicle trafficking and lipid biosynthesis pathways are targeted by five of the synergizers, whereas the sphingolipid biosynthesis pathway is targeted by L-cycloserine. Cell biological assays confirmed the predicted membrane disruption effects of the former group of compounds, which may perturb ergosterol metabolism, impair fluconazole export by drug efflux pumps and/or affect active import of fluconazole (Kuo et al, 2010; Mansfield et al, 2010). Based on the integration of chemical–genetic and genetic interaction space, a signature set of deletion strains that are sensitive to the membrane active synergizers correctly predicted additional drug synergies with fluconazole. Similarly, the L-cycloserine chemogenomic profile correctly predicted a synergistic interaction between fluconazole and myriocin, another inhibitor of sphingolipid biosynthesis. The structure of genetic networks suggests that it should be possible to devise higher order drug combinations with even greater selectivity and potency (Sharom et al, 2004). In an initial test of this concept, we found that the combination of a non-synergistic pair drawn from the membrane active and sphingolipid target classes exhibited potent three-way synergism with a low dose of fluconazole. Finally, the combination of sertraline and fluconazole was active in a G. mellonella model of Cryptococcal infection, and was also efficacious against fluconazole-resistant clinical isolates of C. albicans and C. glabrata.

Collectively, these results demonstrate that the combinatorial redeployment of known drugs defines a powerful antifungal strategy and establish a number of potential lead combinations for future clinical assessment.

Resistance to widely used fungistatic drugs, particularly to the ergosterol biosynthesis inhibitor fluconazole, threatens millions of immunocompromised patients susceptible to invasive fungal infections. The dense network structure of synthetic lethal genetic interactions in yeast suggests that combinatorial network inhibition may afford increased drug efficacy and specificity. We carried out systematic screens with a bioactive library enriched for off-patent drugs to identify compounds that potentiate fluconazole action in pathogenic Candida and Cryptococcus strains and the model yeast Saccharomyces. Many compounds exhibited species- or genus-specific synergism, and often improved fluconazole from fungistatic to fungicidal activity. Mode of action studies revealed two classes of synergistic compound, which either perturbed membrane permeability or inhibited sphingolipid biosynthesis. Synergistic drug interactions were rationalized by global genetic interaction networks and, notably, higher order drug combinations further potentiated the activity of fluconazole. Synergistic combinations were active against fluconazole-resistant clinical isolates and an in vivo model of Cryptococcus infection. The systematic repurposing of approved drugs against a spectrum of pathogens thus identifies network vulnerabilities that may be exploited to increase the activity and repertoire of antifungal agents.

Coevolution within a transcriptional network by compensatory trans and cis mutations

Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of "coevolution" between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.