Transcriptome and network analyses in Saccharomyces cerevisiae reveal that amphotericin B and lactoferrin synergy disrupt metal homeostasis and stress response

Resistance mechanisms of Saccharomyces cerevisiae against silver nanoparticles with different sizes and coatings

To investigate the underlying resistance mechanisms of Saccharomyces cerevisiae against Ag-NPs with different particle sizes and coatings, transcriptome sequencing (RNA-seq) technology was used to characterize the transcriptomes from S. cerevisiae exposed to 20-PVP-Ag, 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag, respectively. The steroid biosynthesis was found as a general pathway for Ag-NPs stress responding, in which ERG6 and ERG3 were inhibited and ERG11, ERG25 and ERG5 were significantly up-regulated to resist the stress by supporting the later mutation and resistance and modulate drug efflux indirectly. The resistance mechanism of S. cerevisiae to 20-PVP-Ag seems different from that of 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag. Under the 20-PVP-Ag, transmembrane transporter activity, transition metal ion homeostasis and oxidative phosphorylation pathway were main resistance pathways to enhance cell transport processes. While 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag mainly impacted RNA binding, structural constituent of ribosome and ribosome pathway which can provide more energy to maintain the number and function of protein in cells. This study reveals the differences in resistance mechanisms of S. cerevisiae to Ag-NPs with different particle sizes and coatings, and explains several main regulatory mechanisms used to respond to silver stress. It will provide theoretical basis for the study of chemical risk assessment.

Pivotal Role of GSTO2 in Ferroptotic Neuronal Injury After Intracerebral Hemorrhage

Previous research has found that an adaptive response to ferroptosis involving glutathione peroxidase 4 (GPX4) is triggered after intracerebral hemorrhage. However, little is known about the mechanisms underlying adaptive responses to ferroptosis. To explore the mechanisms underlying adaptive responses to ferroptosis after intracerebral hemorrhage, we used hemin-treated HT22 cells to mimic brain injury after hemorrhagic stroke in vitro to evaluate the antioxidant enzymes and performed bioinformatics analysis based on the mRNA sequencing data. Further, we determined the expression of GSTO2 in hemin-treated hippocampal neurons and in a mouse model of hippocampus-intracerebral hemorrhage (h-ICH) by using Western blot. After hemin treatment, the antioxidant enzymes GPX4, Nrf2, and glutathione (GSH) were upregulated, suggesting that an adaptive response to ferroptosis was triggered. Furthermore, we performed mRNA sequencing to explore the underlying mechanism, and the results showed that 2234 genes were differentially expressed. Among these, ten genes related to ferroptosis (Acsl1, Ftl1, Gclc, Gclm, Hmox1, Map1lc3b, Slc7a11, Slc40a1, Tfrc, and Slc39a14) were altered after hemin treatment. In addition, analysis of the data retrieved from the GO database for the ten targeted genes showed that 20 items on biological processes, 17 items on cellular components, and 19 items on molecular functions were significantly enriched. Based on the GO data, we performed GSEA and found that the glutathione metabolic process was significantly enriched in the hemin phenotype. Notably, the expression of glutathione S-transferase omega (GSTO2), which is involved in glutathione metabolism, was decreased after hemin treatment, and overexpression of Gsto2 decreased lipid reactive oxygen species level in hemin-exposed HT22 cells. In addition, the expression of GSTO2 was also decreased in a mouse model of hippocampus-intracerebral hemorrhage (h-ICH). The decreased expression of GSTO2 in the glutathione metabolic process may be involved in ferroptotic neuronal injury following hemorrhagic stroke.

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.

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html).

Extracting novel hypotheses and findings from RNA-seq data

Over the past decade, improvements in technology and methods have enabled rapid and relatively inexpensive generation of high-quality RNA-seq datasets. These datasets have been used to characterize gene expression for several yeast species and have provided systems-level insights for basic biology, biotechnology and medicine. Herein, we discuss new techniques that have emerged and existing techniques that enable analysts to extract information from multifactorial yeast RNA-seq datasets. Ultimately, this minireview seeks to inspire readers to query datasets, whether previously published or freshly obtained, with creative and diverse methods to discover and support novel hypotheses.

Resistance to Antifungal Drugs

Pathogenic fungi have several mechanisms of resistance to antifungal drugs, driven by the genetic plasticity and versatility of their homeostatic responses to stressful environmental cues. We critically review the molecular mechanisms of resistance and cellular adaptations of pathogenic fungi in response to antifungals and discuss the factors contributing to such resistance. We offer suggestions for the translational and clinical research agenda of this rapidly evolving and medically important field. A better understanding of antifungal resistance should assist in developing better detection tools and inform optimal strategies for preventing and treating refractory mycoses in the future.

Inhibition of Dermatophyte Fungi by Australian Jarrah Honey

Superficial dermatophyte infections, commonly known as tineas, are the most prevalent fungal ailment and are increasing in incidence, leading to an interest in alternative treatments. Many floral honeys possess antimicrobial activity due to high sugar, low pH, and the production of hydrogen peroxide (H2O2) from the activity of the bee-derived enzyme glucose oxidase. Australian jarrah (Eucalyptus marginata) honey produces particularly high levels of H2O2 and has been found to be potently antifungal. This study characterized the activity of jarrah honey on fungal dermatophyte species. Jarrah honey inhibited dermatophytes with minimum inhibitory concentrations (MICs) of 1.5-3.5% (w/v), which increased to ≥25% (w/v) when catalase was added. Microscopic analysis found jarrah honey inhibited the germination of Trichophyton rubrum conidia and scanning electron microscopy of mature T. rubrum hyphae after honey treatment revealed bulging and collapsed regions. When treated hyphae were stained using REDOX fluorophores these did not detect any internal oxidative stress, suggesting jarrah honey acts largely on the hyphal surface. Although H2O2 appears critical for the antifungal activity of jarrah honey and its action on fungal cells, these effects persisted when H2O2 was eliminated and could not be replicated using synthetic honey spiked with H2O2, indicating jarrah honey contains agents that augment antifungal activity.

Lactoferrin Is Broadly Active against Yeasts and Highly Synergistic with Amphotericin B

Lactoferrin (LF) is a multifunctional milk protein with antimicrobial activity against a range of pathogens. While numerous studies report that LF is active against fungi, there are considerable differences in the level of antifungal activity and the capacity of LF to interact with other drugs. Here we undertook a comprehensive evaluation of the antifungal spectrum of activity of three defined sources of LF across 22 yeast and 24 mold species and assessed its interactions with six widely used antifungal drugs. LF was broadly and consistently active against all yeast species tested (MICs, 8 to 64 μg/ml), with the extent of activity being strongly affected by iron saturation. LF was synergistic with amphotericin B (AMB) against 19 out of 22 yeast species tested, and synergy was unaffected by iron saturation but was affected by the extent of LF digestion. LF-AMB combination therapy significantly prolonged the survival of Galleria mellonella wax moth larvae infected with Candida albicans or Cryptococcus neoformans and decreased the fungal burden 12- to 25-fold. Evidence that LF directly interacts with the fungal cell surface was seen via scanning electron microscopy, which showed pore formation, hyphal thinning, and major cell collapse in response to LF-AMB synergy. Important virulence mechanisms were disrupted by LF-AMB treatment, which significantly prevented biofilms in C. albicans and C. glabrata, inhibited hyphal development in C. albicans, and reduced cell and capsule size and phenotypic diversity in Cryptococcus Our results demonstrate the potential of LF-AMB as an antifungal treatment that is broadly synergistic against important yeast pathogens, with the synergy being attributed to the presence of one or more LF peptides.

Different Pathways Mediate Amphotericin-Lactoferrin Drug Synergy in Cryptococcus and Saccharomyces

Fungal infections are an increasing cause of morbidity and mortality. Current antifungal drugs are limited in spectrum, few new drugs are in development, and resistance is an increasing issue. Drug synergy can enhance available drugs and extend their lifetime, however, few synergistic combinations are in clinical use and mechanistic data on how combinations work is lacking. The multifunctional glycoprotein lactoferrin (LF) acts synergistically with amphotericin B (AMB) in a range of fungal species. Whole LF binds and sequesters iron, and LF can also be digested enzymatically to produce cationic peptides with distinct antimicrobial functions. To understand how LF synergizes AMB, we previously undertook a transcriptomic analysis in Saccharomyces and found a paradoxical down-regulation of iron and stress response, suggesting stress pathway interference was dysregulating an appropriate response, resulting in cell death. To extend this to a fungal pathogen, we here perform the same analysis in Cryptococcus neoformans. While both fungi responded to AMB in a similar way, the addition of LF produced remarkably contrasting results, with the Cryptococcus transcriptome enriched for processes relating to cellular stress, up-regulation of endoplasmic-reticulum-associated protein degradation (ERAD), stress granule disassembly and protein folding, endoplasmic reticulum-Golgi-vacuole trafficking and autophagy, suggesting an overall disruption of protein and lipid biosynthesis. These studies demonstrate that the mechanism of LF-mediated synergy is species-specific, possibly due to differences in the way LF peptides are generated, bind to and enter cells and act on intracellular targets, illustrating how very different cellular processes can underlie what appears to be a similar phenotypic response.

Development of Fangjiomics for Systems Elucidation of Synergistic Mechanism Underlying Combination Therapy

The rapid development of omics technology provides an opportunity for fulfilling the understanding of the synergistic mechanism of combination therapy. However, a systems theory to analyze synergy remains an ongoing challenge. Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism which has been utilized to systematically elucidate the synergistic mechanisms underlying combination therapy using multi-target-, pathway- or network-based quantitative methods. Besides, our ability to understand the polyhierarchical structure in synergy is driven based on multi-level omics data fusion in Fangjiomics. According to the basic principle of “Jun-Chen-Zuo-Shi”, further global integration across various omics platforms and phenotype-driven quantitative multi-scale modeling would accelerate development in Fangjiomics-based dissection of synergy in multi-drug combination therapies.

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Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism.

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We developed the pathway-based analysis of synergistic mechanisms in Fangjiomics.

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The theory of network-based synergistic targets is proposed in Fangjiomics.

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The hierarchical relationship of synergy in multilevel omics is dissected in Fangjiomics.

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The principle of “Jun-Chen-Zuo-Shi” is proposed to accelerate the development in Fangjiomics-based dissection of synergy.

Doxorubicin induces an extensive transcriptional and metabolic rewiring in yeast cells

Doxorubicin is one of the most effective chemotherapy drugs used against solid tumors in the treatment of several cancer types. Two different mechanisms, (i) intercalation of doxorubicin into DNA and inhibition of topoisomerase II leading to changes in chromatin structure, (ii) generation of free radicals and oxidative damage to biomolecules, have been proposed to explain the mode of action of this drug in cancer cells. A genome-wide integrative systems biology approach used in the present study to investigate the long-term effect of doxorubicin in Saccharomyces cerevisiae cells indicated the up-regulation of genes involved in response to oxidative stress as well as in Rad53 checkpoint sensing and signaling pathway. Modular analysis of the active sub-network has also revealed the induction of the genes significantly associated with nucleosome assembly/disassembly and DNA repair in response to doxorubicin. Furthermore, an extensive re-wiring of the metabolism was observed. In addition to glycolysis, and sulfate assimilation, several pathways related to ribosome biogenesis/translation, amino acid biosynthesis, nucleotide biosynthesis, de novo IMP biosynthesis and one-carbon metabolism were significantly repressed. Pentose phosphate pathway, MAPK signaling pathway biological processes associated with meiosis and sporulation were found to be induced in response to long-term exposure to doxorubicin in yeast cells.

RNA-Seq analysis of global transcriptomic changes suggests a roles for the MAPK pathway and carbon metabolism in cell wall maintenance in a Saccharomyces cerevisiae FKS1 mutant

FKS1 encodes a β-1,3-glucan synthase, which is a key player in cell wall assembly in Saccharomyces cerevisiae. Here we analyzed the global transcriptomic changes in the FKS1 mutant to establish a correlation between the changes in the cell wall of the FKS1 mutant and the molecular mechanism of cell wall maintenance. These transcriptomic profiles showed that there are 1151 differentially expressed genes (DEGs) in the FKS1 mutant. Through KEGG pathway analysis of the DEGs, the MAPK pathway and seven pathways involved in carbon metabolism were significantly enriched. We found that the MAPK pathway is activated for FKS1 mutant survival and the synthesis of cell wall components are reinforced in the FKS1 mutant. Our results confirm that the FKS1 mutant has a β-1,3-glucan defect that affects the cell wall and partly elucidate the molecular mechanism responsible for cell wall synthesis. Our greater understanding of these mechanisms helps to explain how the FKS1 mutant survives, has useful implications for the study of similar pathways in other fungi, and increases the theoretical foundation for the regulation of the cell wall in S. cerevisiae.