In 2009 Candida auris was first isolated as fungal pathogen of human disease from ear canal of a patient in Japan. In less than a decade, this pathogen has rapidly spread around the world and has now become a major health challenge that is of particular concern because many strains are resistant to multiple class of antifungal drugs. The lack of available antifungals and rapid increase of this fungal pathogen provides an incentive for the development of new and more potent anticandidal drugs and drug combinatorial treatments. Here we have explored the growth inhibitory activity against C. auris of a synthetic dipeptide glutamine analogue, L-norvalyl-N3-(4-methoxyfumaroyl)-L-2,3- diaminopropanoic acid (Nva-FMDP), that acts as an inhibitor of glucosamine-6-phosphate (GlcN-6-P) synthase - a key enzyme in the synthesis of cell wall chitin. We observed that in contrast to FLC susceptible isolates of C. auris, FLC resistant isolates had elevated cell wall chitin and were susceptible to inhibition by Nva-FMDP. The growth kinetics of C. auris in RPMI-1640 medium revealed that the growth of FLC resistant isolates were 50–60% more inhibited by Nva-FMDP (8 μ g/ml) compared to a FLC susceptible isolate. Fluconazole resistant strains displayed increased transcription of CHS1, CHS2 and CHS3, and the chitin content of the fluconazole resistant strains was reduced following the Nva-FMDP treatment. Therefore, the higher chitin content in FLC resistant C. auris isolates may make the strain more susceptible to inhibition of the antifungal activity of the Nva-FMDP peptide conjugate.

Synthetic genetic interaction analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the interactions between genes, categorize into biological pathways, and characterize genes of unknown function. It has been extensively employed in model organisms for fundamental, systems-level assessment of the interactions between genes. However, more recently, genetic interaction mapping has been applied to fungal pathogens and has been instrumental for the study of clinically important infectious organisms. This protocol herein explains in the detail the methodology and analysis that can be employed to develop interaction maps in microbial pathogens. Such techniques can aid in bridging our understanding of complex genetic networks, with applications to diverse microbial pathogens to further our understanding of virulence, the use of antimicrobial therapies, and host-pathogen interactions.

Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .

Pathogenic fungi represent an increasing infectious disease threat to humans, especially with an increasing challenge of antifungal drug resistance. Over the decades, numerous tools have been developed to expedite the study of pathogenicity, initiation of disease, drug resistance and host-pathogen interactions. In this review, we highlight advances that have been made in the use of molecular tools using CRISPR technologies, RNA interference and transposon targeted mutagenesis. We also discuss the use of animal models in modelling disease of human fungal pathogens, focusing on zebrafish, the silkworm, Galleria mellonella and the murine model.

ABSTRACT
. Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host–pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host−pathogen interactions. 

Drug resistance is a rapidly emerging concern, thus prompting the development of novel therapeutics or combinatorial therapy. Currently, combinatorial therapy targets are based on knowledge of drug mode of action and/or resistance mechanisms, constraining the number of target proteins. Unbiased genome-wide screens could reveal novel genetic components within interaction networks as potential targets in combination therapies. Testing this, in the context of antimicrobial resistance, we implemented an unbiased genome-wide screen, performed in Saccharomyces cerevisiae expressing a Candida glabrata PDR1+ gain-of-function allele. Gain-of-function mutations in this gene are the principal mediators of fluconazole resistance in this human fungal pathogen. Eighteen synthetically lethal S. cerevisiae genetic mutants were identified in cells expressing C. glabrata PDR1+. One mutant, lacking the histone acetyltransferase Gcn5, was investigated further. Deletion or drug-mediated inhibition of Gcn5 caused a lethal phenotype in C. glabrata cells expressing PDR1+ alleles. Moreover, deletion or drug-mediated inactivation of Gcn5, inhibited the emergence of fluconazole-resistant C. glabrata isolates in evolution experiments. Thus, taken together, the data generated in this study provides proof of concept that synthetically lethal genetic screens can identify novel candidate proteins that when therapeutically targeted could allow effective treatment of drug-resistant infections.

Metal pollution has made a significant impact on the earth’s ecosystems and tolerance to metals in a wide variety of species has evolved. Metallothioneins, a group of cysteine-rich metal-ion binding proteins, are known to be a key physiological mechanism in regulating protection against metal toxicity. Many rivers across the southwest of England are detrimentally affected by metal pollution, but brown trout (Salmo trutta L.) populations are known to reside within them. In this body of work, two isoforms of metallothionein (MetA and MetB) isolated from trout occupying a polluted and a control river are examined. Using synthetic genetic array (SGA) analyses in the model yeast, Saccharomyces cerevisiae, functional genomics is used to explore the role of metallothionein isoforms in driving metal tolerance. By harnessing this experimental system, S. cerevisiae is used to (i) determine the genetic interaction maps of MetA and MetB isoforms; (ii) identify differences between the genetic interactions in both isoforms and (iii) demonstrate that pre-exposure to metals in metal-tolerant trout influences these interactions. By using a functional genomics approach leveraged from the model yeast Saccharomyces cerevisiae, we demonstrate how such approaches could be used in understanding the ecology and evolution of a non-model species.

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The impact of fungi on human and plant health is an ever-increasing issue. Recent studies have estimated that human fungal infections result in an excess of one million deaths per year and plant fungal infections resulting in the loss of crop yields worth approximately 200 million per annum. Sexual reproduction in these economically important fungi has evolved in response to the environmental stresses encountered by the pathogens as a method to target DNA damage. Meiosis is integral to this process, through increasing diversity through recombination. Mating and meiosis have been extensively studied in the model yeast Saccharomyces cerevisiae, highlighting that these mechanisms have diverged even between apparently closely related species. To further examine this, this review will inspect these mechanisms in emerging important fungal pathogens, such as Candida, Aspergillus, and Cryptococcus. It shows that both sexual and asexual reproduction in these fungi demonstrate a high degree of plasticity.

Many shark populations are in decline, primarily due to overexploitation. In response, conservation measures have been applied at differing scales, often severely restricting sales of declining species. Therefore, DNA barcoding was used to investigate sales of shark products in fishmongers and fish and chip takeaways in England. The majority of samples were identified as Spiny Dogfish (Squalus acanthias), which is critically endangered in the Northeast Atlantic and landings have been prohibited (although there is evidence of importation of this species). Significant differences in the species sold between retailer types were also identified, suggesting differing supply chains. The results underline issues surrounding the use of 'umbrella' sales terms where many species are labelled with the same designation. This denies consumer choice as purchasers cannot easily avoid declining species or those associated with high levels of toxicants. For the first time in Europe, minibarcodes are also used to identify species from dried shark fins. Despite a small sample size, analysis of UK wholesaler fins identified threatened sharks, including the endangered and CITES listed Scalloped Hammerhead (Sphyrna lewini). This highlights the global nature of the damaging trade in endangered shark species, in which Europe and the UK have a continuing role.

Gene overexpression is a widely used functional genomics approach in fungal biology. However, to date it has not been established in Zymoseptoria tritici which is an important pathogen of wheat (Triticum species). Here we report a suite of Gateway® recombination compatible ternary expression vectors for Agrobacterium tumefaciens mediated transformation of Z. tritici. The suite of 32 vectors is based on a combination of four resistance markers for positive selection against glufosinate ammonium, geneticin, hygromycin and sulfonylurea; three constitutive Z. tritici promoters (pZtATUB, pZtGAPDH and pZtTEF) and a nitrogen responsive promoter (pZtNIA1) for controlled expression of the open reading frames. Half of the vectors facilitate expression of proteins tagged with C-terminal EGFP. All 32 vectors allow high frequency targeting of the overexpression cassette into the Ku70 locus and complement the Ku70 gene when transformed into a Z. tritici ku70 null strain, thus circumventing additional phenotypes that can arise from random integration. This suite of ternary expression vectors will be a useful tool for functional analysis through gene overexpression in Z. tritici.

The lack of techniques for rapid assembly of gene deletion vectors, paucity of selectable marker genes available for genetic manipulation and low frequency of homologous recombination are major constraints in construction of gene deletion mutants in Zymoseptoria tritici. To address these issues, we have constructed ternary vectors for Agrobacterium tumefaciens mediated transformation of Z. tritici, which enable the single step assembly of multiple fragments via yeast recombinational cloning. The sulfonylurea resistance gene, which is a mutated allele of the Magnaporthe oryzae ILV2 gene, was established as a new dominant selectable marker for Z. tritici. To increase the frequency of homologous recombination, we have constructed Z. tritici strains deficient in the non-homologous end joining pathway of DNA double stranded break repair by inactivating the KU70 and KU80 genes. Targeted gene deletion frequency increased to more than 85% in both Z. tritici ku70 and ku80 null strains, compared to ⩽10% seen in the wild type parental strain IPO323. The in vitro growth and in planta pathogenicity of the Z. tritici ku70 and ku80 null strains were comparable to strain IPO323. Together these molecular tools add significantly to the platform available for genomic analysis through targeted gene deletion or promoter replacements and will facilitate large-scale functional characterization projects in Z. tritici.

The trend for large-scale genetic and phenotypic screens has revealed a wealth of information on biological systems. A major challenge is understanding how genes function and putative roles in networks. The majority of current gene knowledge is garnered from studies utilising the model yeast Saccharomyces cerevisiae. We demonstrate that synthetic dosage lethal genetic array methodologies can be used to study genetic networks in other yeasts, namely the fungal pathogen Candida glabrata, which has limited forward genetic tools, due to the lack of 'natural' mating. We performed two SDL screens in S. cerevisiae, overexpressing the transcriptional regulator UME6 as bait in the first screen and its C. glabrata ortholog CAGL0F05357g in the second. Analysis revealed that SDL maps share 204 common interactors, with 10 genetic interactions unique to C. glabrata indicating a level of genetic rewiring, indicative of linking genotype to phenotype in fungal pathogens. This was further validated by incorporating our results into the global genetic landscape map of the cell from Costanzo et al. to identify common and novel gene attributes. This data demonstrated the utility large data sets and more robust analysis made possible by interrogating exogenous genes in the context of the eukaryotic global genetic landscape.

Pathogenic microbes exist in dynamic niches and have evolved robust adaptive responses to promote survival in their hosts. The major fungal pathogens of humans, Candida albicans and Candida glabrata, are exposed to a range of environmental stresses in their hosts including osmotic, oxidative and nitrosative stresses. Significant efforts have been devoted to the characterization of the adaptive responses to each of these stresses. In the wild, cells are frequently exposed simultaneously to combinations of these stresses and yet the effects of such combinatorial stresses have not been explored. We have developed a common experimental platform to facilitate the comparison of combinatorial stress responses in C. glabrata and C. albicans. This platform is based on the growth of cells in buffered rich medium at 30°C, and was used to define relatively low, medium and high doses of osmotic (NaCl), oxidative (H(2)O(2)) and nitrosative stresses (e.g. dipropylenetriamine (DPTA)-NONOate). The effects of combinatorial stresses were compared with the corresponding individual stresses under these growth conditions. We show for the first time that certain combinations of combinatorial stress are especially potent in terms of their ability to kill C. albicans and C. glabrata and/or inhibit their growth. This was the case for combinations of osmotic plus oxidative stress and for oxidative plus nitrosative stress. We predict that combinatorial stresses may be highly significant in host defences against these pathogenic yeasts.