**1. Introduction**

Recent estimates suggest that over 25% of drugs approved between 1981 and 2014 are natural products or directly derived from natural products [1]. The bacterial polyketide class of compounds constitutes a significant percentage of natural products used in clinical or agricultural settings. This class of compounds includes the antibiotic erythromycin B and the antifungal compound amphotericin B, among many others (Figure 1). Fungi are also prolific producers of valuable antibiotics such as the polyketides griseofulvin and strobilurin A. Industrial production of these compounds often relies on large-scale fermentation and semi-synthesis as the most efficient routes [2]. Thus, the development of new biosynthetic engineering platforms that can rationally manipulate and improve the production of these compounds is an important current goal.

Polyketides are produced in two phases: a polyketide synthase (PKS) first assembles a carbon skeleton that is later modified by tailoring enzymes that can introduce a high diversity of chemical functionalization. Type I PKS consist of large multifunctional proteins with individual functional domains that are covalently linked. Type I PKS are further sub-divided into iterative PKS (iPKS) and modular PKS (mPKS, Scheme 1). iPKS consists of a single module (Scheme 1A), where each catalytic domain typically accepts, extends,

**Citation:** Feng, J.; Hauser, M.; Cox, R.J.; Skellam, E. Engineering *Aspergillus oryzae* for the Heterologous Expression of a Bacterial Modular Polyketide Synthase. *J. Fungi* **2021**, *7*, 1085. https://doi.org/10.3390/jof7121085

Academic Editors: Tao Feng and Frank Surup

Received: 25 November 2021 Accepted: 14 December 2021 Published: 17 December 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

and processes different substrates during each cycle of chain extension. iPKS use the same set of functional domains repeatedly until chain extension is complete.

*J. Fungi* **2021**, *7*, x FOR PEER REVIEW 2 of 19

**Figure 1.** Examples of bioactive polyketide natural products from bacteria and fungi. **Figure 1.** Examples of bioactive polyketide natural products from bacteria and fungi.

**Scheme 1.** Type I PKS. (**A**) The iterative PKS involved in the biosynthesis of prestrobilurin A; (**B**) 6-module DEBS system that synthesizes 6-dEB; (**C**) engineered DEBS1-TE that synthesizes triketide lactones (TKL). Abbreviations: KS, ketosynthase; AT, acyl transferase; A, acyl carrier protein (ACP); DH, dehydratase; *C*-MeT, *C*-methyl transferase; ER, enoyl reductase; KR, keto-reductase; KR0 -inactive KR domain; TE, thiolesterase. Diagrams inspired by Keatinge-Clay [3]. **Scheme 1.** Type I PKS. (**A**) The iterative PKS involved in the biosynthesis of prestrobilurin A; (**B**) 6-module DEBS system that synthesizes 6-dEB; (**C**) engineered DEBS1-TE that synthesizes triketide lactones (TKL). Abbreviations: KS, ketosynthase; AT, acyl transferase; A, acyl carrier protein (ACP); DH, dehydratase; *C*-MeT, *C*-methyl transferase; ER, enoyl reductase; KR, keto-reductase; KR0 -inactive KR domain; TE, thiolesterase. Diagrams inspired by Keatinge-Clay [3].

quired, and titers can be low [8].

In contrast, mPKS consists of multiple modules. Each module typically accepts, extends, and processes a single substrate, and passes it to the next module for further pro-

Heterologous expression has emerged as a highly successful strategy for the production and engineering of microbial natural products in both bacteria and fungi [4]. Heterologous expression systems usually rely on host strains that are phylogenetically close to the producing organism to increase the likelihood that native transcriptional elements function properly, promoters remain functional, translation is efficient, the resulting proteins fold correctly, and codon usage is relatively conserved. In addition, post-translational modification processes, such as phosphopantetheinylation of acyl carrier proteins (ACP), must remain effective. Phylogenetically diverse organisms are also used as heterologous expression hosts for complex polyketides. Such organisms include *Escherichia coli* [5] and *Saccharomyces cerevisiae* [6,7], however, extensive host-engineering is often re-

*Aspergillus oryzae* is a filamentous fungus commonly used in the fermentation industry for the production of sake, miso, and soy sauce from rice [9]. It has a generally regarded as safe (GRAS) status and is easily cultured in the lab, amenable to genetic modification using a variety of techniques, and is known for its high protein production. Recently, *A. oryzae* has proven itself to be an extremely capable host for heterologous expression of

In contrast, mPKS consists of multiple modules. Each module typically accepts, extends, and processes a single substrate, and passes it to the next module for further processing. Type I iPKS are typical of fungi but are also known in bacteria, while type I mPKS are almost exclusively limited to bacteria.

Heterologous expression has emerged as a highly successful strategy for the production and engineering of microbial natural products in both bacteria and fungi [4]. Heterologous expression systems usually rely on host strains that are phylogenetically close to the producing organism to increase the likelihood that native transcriptional elements function properly, promoters remain functional, translation is efficient, the resulting proteins fold correctly, and codon usage is relatively conserved. In addition, post-translational modification processes, such as phosphopantetheinylation of acyl carrier proteins (ACP), must remain effective. Phylogenetically diverse organisms are also used as heterologous expression hosts for complex polyketides. Such organisms include *Escherichia coli* [5] and *Saccharomyces cerevisiae* [6,7], however, extensive host-engineering is often required, and titers can be low [8].

*Aspergillus oryzae* is a filamentous fungus commonly used in the fermentation industry for the production of sake, miso, and soy sauce from rice [9]. It has a generally regarded as safe (GRAS) status and is easily cultured in the lab, amenable to genetic modification using a variety of techniques, and is known for its high protein production.  *A. oryzae* does not produce significant amounts of its own secondary metabolites, meaning it is a clean host allowing facile detection and purification of heterologously produced compounds. Moreover, there are a number of examples where heterologous expression of a specific pathway in *A. oryzae* has exceeded the titer of the natural product reported in the native producer [18,19]. Advantages of fungi over other heterologous hosts are: the use of monocistronic operons, meaning separate genes can be individually controlled; numerous cellular compartments, where selective reactions may be contained to overcome toxicity; and tailoring enzymes that catalyze diverse and unique chemical modifications not accessible to other organisms [20]. However, *A. oryzae* has not yet been explored as a host for the production of bacterial polyketides. In particular, it is notable that reports of the presence of modular PKS in fungi are extremely rare [21]. However, successful expression of modular PKS in fungi could open up significant opportunities for the production of hybrid bacterial-fungal compounds unknown in nature, with potentially unique properties. In addition, fungi are capable of numerous oxidative tailoring modifications unknown in bacteria, offering further possibilities for the generation of novel compounds [22].

The biosynthesis of 6-deoxyerythronolide B (6-dEB) in *Saccharopolyspora erythraea* has long been used as a model mPKS system. Here, three large multimodular proteins (DEBS1, DEBS2, and DEBS3, Scheme 1B) work together to make the hexaketide macrolide 6-deoxyerythronolide B (6-dEB). DEBS1-TE is a well-studied simplified mPKS derived by fusing the C-terminal thiolesterase (TE) release domain of DEBS3 to the C-terminus of DEBS1 [23]. DEBS1-TE thus consists of a loading module and two extending modules that synthesize triketide lactone (TKL) from propionyl CoA and 2*S*-methylmalonyl CoA (Scheme 1C). The observed titers vary (0.5–20 mg·L −1 ) depending on the host used (Scheme 1) [24–27]. The acyltransferase (AT) domain within the DEBS1-TE loading module usually selects and activates propionyl-CoA, although other small acyl CoAs can be used if propionate is lacking.

A number of factors are likely to impede the use of fungal hosts for the successful expression of mPKS. For example, high concentrations of propionyl CoA are toxic to fungi through inhibition of crucial metabolic pathways [28,29] and 2*S*-methylmalonyl-CoA, required by mPKS extender modules, is not known to be synthesized by fungi. Additionally, actinobacterial genes are typically high GC% and it is unknown whether transcription and translation would be effective in *A. oryzae*. Furthermore, DEBS1-TE requires post-translational modification of the ACP domains by a phosphopantetheinyltransferase enzyme (PPTase), and it is unknown whether the native *A. oryzae* PPTase is capable of post-translationally modifying the ACP domains of mPKS.

In this study, we modified the metabolism of *A. oryzae* to enable the synthesis of TKL by the DEBS1-TE modular PKS. We established 2*S*-methylmalonyl-CoA biosynthesis *via* the introduction of a bacterial propionyl-CoA carboxylase complex (PCC); reassembled the 11.2 kb DEBS1-TE-coding region from synthetic codon-optimized gene fragments using rapid yeast recombination; introduced the bacterial phosphopantetheinyltransferase (PPTase) SePptII; investigated the propionyl-CoA synthesis and degradation pathways; and developed improved delivery of exogenous propionate. Overall, we demonstrated that *A. oryzae* can be used as an effective alternative host for the synthesis of bacterial polyketides that require toxic or non-native substrates, requiring minimal metabolic modification. *A. oryzae* may thus offer future advantages over other heterologous platforms for producing valuable and complex bacterial natural products.


*Fundamentals of Femtosecond Laser and Its Application in Ophthalmology DOI: http://dx.doi.org/10.5772/intechopen.106701*

procedure (Carl Zeiss Meditec AG), the intrastromal lenticule is sculpted for correction of myopic or astigmatic refractive error; during this procedure, FSL is used for the anterior and posterior dissection of both faces of the refractive lenticule in addition to the small incision in the mid-periphery of the cornea for safe extraction of the intrastromal lenticule. Other companies introduced their own laser systems later, such as SmartSight by Schwind and corneal lenticule extraction for advanced refractive correction by Ziemer Ophthalmic Systems AG. Research is continued to determine the superiority of FS-LASIK over RELEX and SMILE [ 4 , 5 , 14 , 15 ].

 When corneal incisions are used to treat astigmatism, Fs-technology allows for exceptional precision and control over all aspects of the keratotomy procedure. Fs-specific intrastromal keratotomies, on the other hand, reduce the risk of infection by avoiding open wounds.


*3.1.2 Bentonite after ion exchange experiments*

The results obtained after ion exchange experiments are presented as chemical composition of liquors before and after the procedure; **Table 3** shows the chemical composition of these liquors obtained by ICP, showing also the efficiency of ion exchange for each element. It can be noticed that for all elements present in original leaching liquor, the efficiency is over 90%.

After the ion exchange, the solution was filtered and the solid residue of the bentonite was dried and analyzed by XRD. The mineral species identified by X-ray diffraction (**Figure 3**), are majority mineral phases, such as quartz, anorthoclase, orthoclase, albite, berlinite, and silico-aluminates, typical of bentonite. Likewise, signs indicating the presence of rare earths and precious metals are noted, which corroborates that the exchange of these elements was made to the natural absorbent.

Finally, **Figure 4** shows the image of a bentonite particle after performing the ion exchange with the leaching liquors of a SEDEX-type mineral, where the semiquantitative composition and the distribution of the elements are shown by X-ray mapping, observing that, indeed, the aforementioned elements were absorbed in the bentonite ore.


*4.1. Performance*

Among the 720 segments, one of the ECG segments was significantly distorted by a motion noise; we excluded this segment and its label for further analysis. To evaluate the performance of a model, five-fold cross validation was used on both machine learning models and DeepER Net. This method commonly evaluates the predictability of a model [5]. In particular, the 719 segments were randomly shuffled and split into five folds. Furthermore, five-fold cross validation was applied for evaluation. The use of this cross validation scheme is independent of subjects, indicating that the segments extracted from a subject can be in both test set and training set. Because of the similarity between the test set and training set, this might lead to higher accuracy on the testing set.

We calculated the average performance of the machine learning models, as shown in Table 4, and then selected the best model for comparison purposes. Of these models, the random forest (RF) yielded the highest average accuracy (71.8 ± 2.3%), F1 score (0.67 ± 0.04), and AUC (0.80 ± 0.02). This was followed by the decision tree (DT), then SVM, the KNN, and finally the logistic regression (LR) showed the lowest performance. This highlights the fact that different models can give different performance, even when trained on the same handcrafted feature set, and that we need to find the most suitable model for each problem. In addition, the fact that the RF and LR demonstrated the highest and lowest performance, respectively, suggests that an ensemble model can be suitable for recognizing stress. However, the RF's AUC was less than 0.9, so it cannot be considered to be highly accurate [24].

Turning now to the performance of the proposed DeepER Net, we find that it showed the highest average accuracy (83.9 ± 2.3%), F1 score (0.81 ± 0.05), and AUC (0.92 ± 0.01). Compared with the RF, its average accuracy was 12.1% higher (*p*-value < 0.05 with paired *t*-test), its average F1 score was 0.14 higher (*p*-value < 0.05 with paired *t*-test), and its average AUC was 0.12 higher (*p*-value < 0.05 with paired *t*-test), clearly indicating that our deep learning approach was a substantial improvement. In addition, DeepER Net's AUC was greater than 0.9, so we can conclude that it is highly accurate for recognizing stress [24]. These results thus suggest that our deep learning approach is a promising option for accurately recognizing stress. Loss and accuracy information of the proposed DeepER Net during training is shown in Figure S1.

**Table 4.** Average metrics after five-fold cross validation. We used Equations (2) and (3) to calculate the average accuracy, F1 score, and AUC, as well as their standard deviations, and show these results as average ± standard deviation. Abbreviations : SVM, support vector machine; RF, random forest; KNN, k-nearest neighbors; LR, logistic regression; DT, decision tree; AUC, area under the ROC curve; ROC, receiver operating characteristic.


**1. Introduction**

Die-attach materials are crucial to power devices. It bonds the chip to the substrate and performs the functions of conducting current and heat. Traditional lead-free and Sn-Pb solders harm the environment and have lower operating temperatures, thus nano-Ag paste as a die-attach material is a feasible option with excellent electrical and thermal conductivity [1–3].

However, silver is prone to electrochemical migration (ECM) and forms dendritic crystals, which result in short-circuit failure [4,5]. Generally, moisture is believed to play a crucial role in the migration of silver, and as a result, silver migration is described as a moisture migration phenomenon. However, recent studies have found that ECM failure of silver occurs even in high temperature and dry environments. The role of O2 in dry environments is similar to that of H2O in the classical moisture migration process [6]. Firstly, silver oxidized at the anode and form the intermediate species Ag2O, which dissociated into silver cations and oxygen anions at a high temperature above 250 ◦C. Driven by the bias voltage, the silver cations move from anode to cathode through the insulating gap, while the oxygen anions move in the opposite direction to maintain charge neutrality. The continuous depletion of silver cations at the anode drives oxidation and dissociation until silver dendrites formed between the two electrodes. Subsequently, silver dendrites gradually appeared and result in short circuits [7,8].

It was concerned that the ECM of the sintered nano-Ag should be a failure risk for packaging wide band-gap (WBG) power semiconductors devices, which can theoretically be operated at extreme temperatures of 500 ◦C, not to mention the great increase of electrical bias [9]. Furthermore, the previous ECM of silver was only focused on thick film conductors

**Citation:** Ding, Z.; Wang, Z.; Zhang, B.; Lu, G.-Q.; Mei, Y.-H. A Reliable Way to Improve Electrochemical Migration (ECM) Resistance of Nanosilver Paste as a Bonding Material. *Appl. Sci.* **2022**, *12*, 4748. https://doi.org/10.3390/ app12094748

Academic Editor: David G. Calatayud

Received: 2 April 2022 Accepted: 6 May 2022 Published: 9 May 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

in conventional printed circuit boards (PCBs) [4,10]. Double-sided cooling (DSC) silicon carbide (SiC) power devices have attracted more and more attention in industries, especially in electric vehicle applications, because of their superior heat dissipation capability and power density [11]. However, the DSC SiC devices have a very small electrode spacing, e.g., 250 μm [12]. When the great sintered nano-Ag was used as die attachment in the DSC SiC devices, it is crucial to avoid the ECM failure of sintered nano-Ag to guarantee the reliability of electric vehicles. Unfortunately, there is a current lack of research on the ECM of silver suppression for the DSC SiC power devices.

Inhibition of the ECM of silver, such as alloying silver with indium or copper to form anti-ECM Ag-In and Ag-Cu alloys, had been studied [13,14]. Recently, we proposed the method of alloying silver with palladium aimed at inhibiting the formation of silver ions through oxidation and decomposition in the anode to delay the ECM of silver [15]. However, these alloying methods need very high processing temperatures in order to improve the resistance to the ECM of silver by alloying more at the higher temperature, not to mention the extremely high cost of indium, palladium, and so on.

In this paper, a nano-Ag composite paste was proposed with the 0.1wt% SiOx nanoparticles (NPs) as fillers. The conventional nano-Ag paste was compared as a reference. The lifetime for reaching the ECM failure was characterized in the first place. Then the thermomechanical reliability of the proposed nano-Ag-SiOx paste was verified in the aspects of die-shearing strength and thermal impedance by thermal shocking tests because it is critical to ensure promising thermo-mechanical reliability besides the improvement of the resistance to the ECM. Microstructures and porosity were analyzed to clarify the effects of SiOx doping on the ECM and the thermo-mechanical reliability. In the end, the proposed nano-Ag-SiOx paste was used as a die attachment for a DSC power device. The improvement of the lifetime of the ECM was validated in the high power density demonstration.


*3.5. Determination of Endogenous Formaldehyde Content in L. edodes*

Steam distillation was used to extract formaldehyde from *L. edodes* at each growth stage. Each sample was supernatant of 4 g *L. edodes* homogenized with 100 mL Tris-HCl (0.5 M, pH = 7.6) buffer and 10 mL 10% (*v*/*v*) phosphoric acid aqueous solution in a 250 mL distillation flask. Water vapor was collected into a 150 mL flask, and then immersed in an ice-bath. The distillation process was stopped when 6070 mL of the distillate was collected and made up to 100 mL by deionized water. Formaldehyde in the distillate was derived by adding 1 mL of the distillate, 3.5 mL acetate buffer (0.1 M, pH = 4.0) and 0.5 mL DNPH (3 mg/mL) into a centrifuge tube at 25 ◦C for 15 min. Then the derived sample was filtered through a 0.22 μm filter for HPLC analysis. The formaldehyde derivative (formaldehyde-DNPH) of each group was separated and determined by a reverse-phase HPLC system (Waters, Milford, MA, USA). The mobile phase was composed of 0.05% acetic acid in acetonitrile and 0.05% acetic acid in water. The injection volume was 20 μL. All samples were detected at 355 nm as previously reported [18].