*2.5. Silver*

Silver (Ag) is a transition metal that shares similar properties to other transition metals in groups three through twelve, and closely resembles the properties of Cu and gold (Au) [291,292]. In fungi, silver is implicated in the eradication of pathogens. As part of agricultural research, silver nanoparticles (Ag NPs) and Ag ions (Ag<sup>+</sup> ) have demonstrated their ability to control plant pathogens [293–295]. As a feed additive, silver has a positive effect on the intestinal microflora, aflatoxins, and mycotoxin absorption in farm animals and in the food industry is used in food packaging for its antimicrobial properties [291,296,297]. Thus, the development of silver as an antimicrobial agent should continue to be investigated, especially on the development of fungal resistance and the impacts on non-target organisms.

#### 2.5.1. Silver Transport and Homeostasis

Silver is a non-essential metal that has no designated cellular receptors or membrane channels for ion uptake. Much of the literature has focused on silver as an antimicrobial agent, but some studies have begun to clarify homeostatic mechanisms [81,114,116,298]. Silver has properties similar to copper, which has initiated the evaluation of copper homeostatic systems to investigate how they may contribute to silver uptake and transport [21,81,114,116,298].

In *S. cerevisiae*, Ctr1, high-affinity Cu<sup>+</sup> transporter, has been identified as a Ag<sup>+</sup> importer. This is based on observed reduced Ag<sup>+</sup> uptake in *ctr1*∆ mutants exposed to low silver concentrations, and transcriptional analysis that shows exposure to Ag NPs upregulates *CTR1* throughout the entire transcriptome [80,81]. The involvement of copper-related genes in Ag<sup>+</sup> homeostasis was also investigated by Hosiner et al. and Niazi et al.; both found

that short-term exposure to silver resulted in increased expression of copper MTs Cup1-1 and Cup1-2, suggesting these MTs sequester Ag<sup>+</sup> in response to silver stress [114,115]. The competitiveness of Cu<sup>+</sup> and Ag<sup>+</sup> for Cup1-1 and Cup1-2 should be further investigated to determine which ion the MTs have a higher affinity for. Other metal ion transporters (Pho84, Fet3, and Smf1) have been investigated for their involvement in Ag<sup>+</sup> uptake, but results indicate they are not [81].

Once inside the cell, there are not many known Ag<sup>+</sup> destinations. AgNO<sup>3</sup> exposure results in Ag<sup>+</sup> accumulation in the mitochondria, which, in return, reduces Cu<sup>+</sup> accumulation in the mitochondrial matrix [21]. The direct result of this action is reduced copper-dependent cytochrome *c* oxidase activity, suggesting that cytosolic Ag<sup>+</sup> is trafficked to the mitochondria via Cu<sup>+</sup> mitochondrial transporter Pic2, potentially with a higher affinity, which can be toxic to cells by reducing the rate of cellular respiration [21]. No other intracellular destinations have been identified in yeast, and silver homeostasis in filamentous fungi is still unknown.

#### 2.5.2. Silver Toxicity

Efflux systems are integral to cellular homeostasis, preventing the accumulation of toxic compounds within a cell. In *S. cerevisiae*, Ag<sup>+</sup> uptake can affect these systems, resulting in toxicity. Exposure to Ag<sup>+</sup> can increase the efflux rate of potassium ions (K<sup>+</sup> ) from *S. cerevisiae*, resulting in almost complete K<sup>+</sup> efflux from the cell. *S. cerevisiae* requires a minimum 30mM K<sup>+</sup> , suggesting those events can be toxic if the ion concentration is not restored [299,300]. Another mechanism of Ag<sup>+</sup> toxicity is its ability to alter cellular structure [100,103]. Ionic fluids can affect cell membrane integrity of yeast *Yarrowia lipolytica*, reducing the amount of ergosterol, which fluidizes the membrane, and increases internal lateral pressures [100]. Ag<sup>+</sup> exposure can also deform the cell wall, which is a likely a response to the down-regulation of genes involved in ergosterol synthesis (*ERG3*, *ERG5*, *ERG6*, *ERG11*, *ERG25*, and *ERG28*) in *S. cerevisiae* [80,99]. In the aquatic fungus *Articulospora tetracladia*, transcriptome analysis via RNAseq revealed toxicity of Ag<sup>+</sup> and Ag NPs may result from interrupted functioning of plasma/organelle membranes and downregulation of genes associated with cellular redox [301]. Silver toxicity has also been studied in other agriculturally relevant processes and it has been determined that AgNO<sup>3</sup> and Ag NPs can be useful in pathogen control of plant diseases [174,293,295]. It may be worthwhile to investigate silver homeostasis in addressing long-term effects of exposure.

#### 2.5.3. Silver Tolerance and Resistance

The worldwide increase of silver usage makes studies on mechanisms of silver resistance important; presently, few studies have reported on this. *CTR3* is implicated in Ag<sup>+</sup> resistance after an observed fold increase in its expression in a silver evolved strain of *S. cerevisiae* [116]. Insight into the expression of the Ctr3 transcription factor *MAC1* in the presence of Ag<sup>+</sup> may clarify its role in resistance. It is possible that MTs Cup1-1 and Cup1-2 are also involved in resistance. It was previously described that exposure to AgNO<sup>3</sup> and Ag NPs resulted in the increased expression of *CUP1-1* and *CUP1-2*, proposing that the encoded MTs may also bind Ag<sup>+</sup> and decrease sensitivity [81,114,115]. Similar results were observed in AgNO<sup>3</sup> exposure, where yeast had increased expression of *CUP1-1* and *CUP1-2* (4.79-fold and 4.71-fold, respectively) in an extended study that resulted in an evolved yeast strain, confirming the potential role of copper MTs in silver resistance [116]. Other Ag<sup>+</sup> transporters, Pho84, Fet3, and Smf1, were not implicated in Ag<sup>+</sup> uptake; however, significant down regulation (68.56-fold) of *PHO84* in silver evolved yeast has been observed, which may indicate that Pho84 plays a role in Ag<sup>+</sup> uptake, and may serve as a mechanism of Ag<sup>+</sup> resistance [81,116]. The effect of Ag<sup>+</sup> on genes involved in ergosterol biosynthesis was also investigated in a silver evolved yeast [116]. Results indicated downregulation of those genes, suggesting that one mechanism of action of resistance against Ag<sup>+</sup> toxicity could be the ability to inhibit their down regulation [116]. In the filamentous fungus *A. nidulans*, silver induced expression of copper exporter crpA, indicating that it

may play a role in silver export and resistance [90]. In *A. tetracladia*, resistance may be due to increased vacuolar function [301]. Overall, there has been some progress made in unveiling silver homeostasis in fungi, mostly by way of *S. cerevisiae*. Due to the increasing silver and Ag NP usage in many aspects of human life, silver–fungal interactions should be further investigated at the molecular level to decipher precise homeostatic and resistance mechanisms.

#### **3. Omics and Metal Homeostasis**

As the potential for commercial use of antifungal metals increases, so does the need to further investigate fungal homeostasis of essential and non-essential metals. Currently, research in this area is heavily reliant on assay based methods, which can be subjective and ambiguous. In this review, many of the discoveries of homeostatic mechanisms stemmed from the use of deletion libraries, microarrays, and PCR-based methods. This can restrict the scope of the research by only analyzing known genomic or transcriptiomic signatures.

The incorporation of an omics based approach is a resolution to this issue. The most popular omics utilizes bioinformatics to analyze fungal–metal interactions at a nucleotide and protein level, which can reveal novel genes and mutations. In genomics, the entirety of a genome is assessed and compared to others for similarities and differences that can contribute to an organism's characteristics [302,303]. Transcriptomics relies on RNA sequencing to survey gene expression through fold-changes in transcripts and proteomics assess foldchange in subsequent proteins. In fungi, omics is already incorporated into the identification of characteristics of multi-drug resistance, analysis of genomic divergence based on species origination, some analysis of metal tolerance due to short term exposure, and the analysis of the effects of exposure to non-metal selective pressures [210,301,304–306].

Bioinformatics analysis is used to translate omics results via computer programming methods. In nucleotide based omics, DNA or RNA is fragmented into segments or reads prior to sequencing. After sequencing, base calling assigns a nucleotide base to an intensity signal linked to a chromatogram peak and quality control measures are taken to trim reads of adapters used in the sequencing process and trim low quality bases [307]. Next, species that have a reference genome or transcriptome are mapped or aligned to that reference (resequencing). After genomic mapping, variant calling identifies distinctions between the re-sequenced organism and the reference [307]. After transcriptomic mapping, transcripts are quantified and analyzed for differential expression. Species that do not have a reference undergo de novo assembly, which constructs a genome or transcriptome from scratch. De novo assembly utilizes the fragmented reads by overlapping or matching them based on areas of similarity until the entire -ome is constructed [308]. Genome or transcriptome annotation can then be used for further interpretation of the sequencing data. In other omics, molecules produced by an organism are also analyzed and compared to chosen reference samples.

Steps within these bioinformatics pipelines require the use of computational tools written into the command line. Multiple tools with varying parameters exist to complete the same function; however, the user must decide which tools fit their scientific needs. This can result in variation between datasets and across scientific disciplines, based on accepted standards and norms. However, this limitation does not deduct from the vast amounts of data received.

With the increasing affordability of high-throughput omics, organisms can be analyzed at multiple omics levels. This is leading to a more comprehensive understanding of characteristics, especially in fungi where there is limited knowledge of their complexity. This type of research will also illuminate unique features of fungal metal homeostasis, toxicity, and resistance, especially of non-essential metals that are becoming conventional antimicrobial agents.
