*Article* **Skin Culturable Microbiota in Farmed European Seabass (***Dicentrarchus labrax***) in Two Aquacultures with and without Antibiotic Use**

**Ana Ramljak 1, Irena Vardi´c Smrzli´c 1, Damir Kapetanovi´c 1,\*, Fran Barac 1, Anamarija Kolda 1, Lorena Peri´c 1, Ivana Balenovi´c 2, Tin Klanjšˇcek 1 and Ana Gavrilovi´c 3**

**Abstract:** This study examined culturable skin microbiota that was associated with farmed European seabass (*Dicentrarchus labrax*). Healthy European seabass were sampled during summer commercial harvest from one conventional fish farm where antibiotics are used, and from another practicing a certified antibiotic-free fish aquaculture. Physicochemical and microbiological analysis of seawater and sediment were performed, as well as determination of culturable bacteria, including *Vibrio*, from skin swabs of European seabass and seawater and sediment at both farms. Samples were processed for isolation of bacteria and their characterization by molecular and antibiotic susceptibility tests. In both fish farms, most of the bacteria that were identified in the skin belonged to the genera *Pseudomonas* and *Vibrio*. Some of the microbiota that were identified are known to be pathogenic to fish: *V. alginolyticus*, *V. anguillarum*, and *V. harveyi*. *Vibrio* strains showed higher resistance to certain antibiotics compared to previous studies. This study provides, for the first time, information on the culturable skin bacteria that is associated with healthy European seabass under culture conditions with and without the use of antibiotics. This information will be useful in assessing how changes in culturable microbiota may affect the health of farmed European seabass, indicating a potential problem for fish health management during disease outbreaks.

**Keywords:** bacteria; European seabass aquaculture; Adriatic Sea; antibiotic resistance; *Pseudomonas*; *Vibrio*

#### **1. Introduction**

Common fish diseases and environmental pollution can lead to economic losses and poor and unprofitable production in aquaculture [1]. European seabass (*Dicentrarchus labrax*) is one of the most farmed fish species in Croatia and tops the list of most farmed fish species in the European Union [2]. Its cultivation is threatened by several common bacterial pathogens and the infections that are caused by them. For example, *Photobacterium damselae* causes photobacteriosis in European seabass with a mortality rate between 60% and 80% [1]. *Vibrio* species are ubiquitous in aquatic ecosystems, while many *Vibrio* species are serious opportunistic pathogens causing the most common bacterial diseases [3–5]. Control of bacterial pathogens in aquaculture production is routinely achieved by the administration of antibiotics. However, excessive antibiotic use has led to the emergence of antibiotic-resistant bacteria [1].

As the skin, along with the gills, is an organ that is involved in the primary defense of the organism from pathogens, it is important to investigate its microflora and how microflora disorders lead to disease development. Microflora refers to the microorganisms

**Citation:** Ramljak, A.;

Vardi´c Smrzli´c, I.; Kapetanovi´c, D.; Barac, F.; Kolda, A.; Peri´c, L.; Balenovi´c, I.; Klanjšˇcek, T.; Gavrilovi´c, A. Skin Culturable Microbiota in Farmed European Seabass (*Dicentrarchus labrax*) in Two Aquacultures with and without Antibiotic Use. *J. Mar. Sci. Eng.* **2022**, *10*, 303. https://doi.org/10.3390/ jmse10030303

Academic Editor: Snježana Zrnˇci´c

Received: 29 December 2021 Accepted: 11 February 2022 Published: 22 February 2022

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**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/).

that are present on the mucous membranes and skin of fish [6]. Although microorganisms that are pathogenic to fish are part of the normal fish microflora, they do not cause disease unless the balance of the microflora is disturbed Disturbances in the balance (dysbiosis) are often caused by the specificities of aquaculture such as high stocking density and low oxygen concentration [7], but also by changes of physical and chemical conditions in water, temperature fluctuations, seasonality, climate variability, and the use of antibiotics [8]. The skin microbiota of the fish that are exposed to such stress is usually composed of microorganisms that are pathogenic to fish [7]. The viscoelasticity of the skin mucus blocks various bacteria, and upon contact with the bacterial pathogen, the fish excrete more mucus and alter the composition of the skin microflora [9].

Most of the research on European seabass microflora has focused on the gut microbiota that is exposed to conventional [10] and alternative diets [11], as well as on the effects of probiotics on the balance of the gut microbiota [12]. Several researchers focus on the seasonal survey of the marine aquaculture microbiome in a European seabass farm [13], the assessment of seawater microbial quality, and the health status of farmed European seabass [14], with more specific characterization of isolated *Vibrio* species [5]. The evaluation of the tissue-specific diversity of microbiomes within and between sea bass and sea bream [7], as well as the recent study of the effects of aging on the skin and gill microbiota of farmed European sea bass and sea bream, were done by Rosado et al. [7,15].

Although studies of the European seabass skin microbiota are not numerous [3,6,7], one study examined the basic diversity of skin microbiomes and gills of farmed seabass and gilthead sea bream [7], but the link to the history of antibiotic therapy remained unclear. Some recent reports have studied the health problems of European seabass in aquaculture [3,6], but only one correlates the abundance of bacteria with problems that are associated with subsequent antibiotic treatment with oxytetracycline [6]. The abundance of taxa belonging to the non-pathogenic marine group NS3a, and *Polaribacter* 4 decreased in the skin microbiome of diseased fish with oxytetracycline therapy [6], while the pathogens *Pseudomonas* and *Stenotrophomonas* increased significantly. However, there is a lack of available information on the microbiota in the skin of European seabass that are grown in farming practices without a history of antibiotic therapy. Due to the increasing importance of aquaculture, more research is needed in disease prevention and alternative treatments to prevent bacterial resistance to antibiotics [1].

In the present study, we characterized the culturable bacteria of the skin of healthy adult European seabass during summer commercial harvest in two cage fish farms. This included one conventional farm where antibiotics are used to treat disease, and the other practicing a certified antibiotic-free production. The main objectives of the research are: to compare the culturable bacteria of farmed European seabass between these two fish farms and to identify the potential opportunistic bacterial pathogens and determine their susceptibility to antibiotics.

#### **2. Materials and Methods**

#### *2.1. Sampling*

This study was conducted on two floating cage fish farms, NAS farm in the northern, and MAS farm in the middle Adriatic (Figure 1). Both farms are in the semi open sea, with the NAS farm at depth of approximately 49 m, and MAS farm depth of approximately 22 m. The cages that are 10 m deep contain European seabass (*Dicentrarchus labrax*) and sea bream (*Sparus aurata*). Samples of fish, seawater, and sediments were collected during the summer at both farms. During the sampling year, the NAS farm was subjected to regular periodical control to determine antibiotic residues by an independent certification control service. Antibiotic-free production has been practiced since the beginning of aquaculture production on the NAS farm. The MAS farm differed from the NAS farm with respect to the usage of antibiotics. The antibiotics were administered at therapeutic dosage by a professional veterinarian at the farm based on a positive diagnosis. Usually, antibiotic treatment is conducted for the full period that is required for therapy and as little as necessary. The

available information concerning antibiotic administration at the NAS farm have been undisclosed, however it is known that most used antibiotics in the Mediterranean countries are flumequine and oxytetracycline [16]. No clinical signs of fish disease were observed during sampling on both farms, and no antibiotic was used on the MAS farm at the time of sampling. The fish samples were obtained from cages of European seabass that were harvested for commercial purposes at the NAS and MAS farm. A total of 10 individual fish were obtained during commercial catch at each farm. One skin swab per fish was taken from 1 cm2 areas below the dorsal fin using sterile rods with a 1 cm cotton tip (Deltalab, Barcelona, Spain) for isolation and later bacterial identification. We specifically chose this area for swab collection because this area was not affected by fish handling during sampling which could have caused unwanted contamination. The samples were then serially diluted in 10 mL of sterile phosphate buffer saline (PBS, Sigma, St. Louis, MO, USA) [17]. During sampling, the health status of the fish was assessed and biometric data, namely, the total length and total weight, were recorded.

**Figure 1.** Sampling locations: NAS—marine fish farm in the north Adriatic and MAS—marine fish farm in the middle Adriatic.

Sediment and seawater samples were collected from the NAS and MAS farm below the cages containing the European sea bass. Sediment samples (10 g of the top sediment layer) were collected from each farm using Ekman grab. Seawater samples were collected at four different depths (0.5 m below the surface, 6 m deep, 12 m deep, and 0.5 m above the bottom) using a Niskin water sampler and poured in sterile 0.5 L bottles. All the samples were serially diluted in 10 mL of sterile PBS solution (Sigma) and counts were determined by inoculating the undiluted and serially diluted samples on appropriate media for enumeration and isolation for microbial and molecular analysis (see below).

#### *2.2. Physicochemical and Microbiological Analysis of Seawater and Sediment*

The measurements of physicochemical parameters of seawater were carried out at both farms. The pH was measured electrometrically with portable digital SevenGo pro/Ion multiparameter probes (Mettler Toledo, Schwerzenbach, Switzerland) with an accuracy of 0.001 mg/L. The concentration of dissolved oxygen (mg/L), oxygen saturation of water (%), and the temperature (◦C) were measured with a SevenGo pro/SG9 OptiOx probe (Mettler Toledo) with a precision of 0.01 mg/L. Conductivity and total dissolved solids (TDS) were measured with a SevenGo pro/conductivity probe (Mettler Toledo) with a precision of 0.1 mg/L.

The total coliforms and *Escherichia coli* were determined using Colilert-18™ and Quanti-Tray/2000 substrate technology (IDEXX, Westbrook, ME, USA). After incubation for 24 h

at 35 ◦C, the appearance of a yellow color of the chamber allowed the evaluation of total coliforms, and fluorescence under UV light indicates the presence of *E*. *coli*. Enterococci were determined using Enterolert-E™ and Quanti-Tray/2000 (IDEXX). After incubation for 24 h at 41 ◦C, the appearance of fluorescence indicates the presence of enterococci [18]. Quanti-Tray/2000 indicates the most probable number of bacteria (MPN) in a 100 mL sample using the manufacturer's reagents.

#### *2.3. Number of Heterotrophic Bacteria and Vibrio Count*

The number of heterotrophic bacteria (Heterotrophic Plate Count (HPC)) of the skin, seawater, and sediment, was determined by the spread plate method on Difco™ Marine Agar 2216 medium (BD, Sparks, MD, USA) that was incubated at 22 ◦C for 3–5 days. The spread plate method on a selective Thiosulfate-Citrate-Bile-Sucrose (TCBS) medium (BD), was used for the isolation of the bacteria of the genus *Vibrio* from fish skin swabs, sediment, and seawater samples. The plates were incubated at 22 ◦C for 24 h. The results are reported as the mean number of colony forming units (CFU) in 1 mL of sediment and seawater or per 1 cm2 of skin ± the standard deviation of two technical replicates by sample type [18]. Subsequently, two bacterial colonies representing different morphologies per plate on Marine Agar and TCBS agar were selected from each sample and transferred to Difco™ Tryptic Soy Agar (TSA) (BD) with the addition of 1% NaCl (Kemika, Zagreb, Croatia) (MTSA) plates to obtain a pure culture. After purification and plating on the MTSA plates, a total of 146 bacterial isolates were obtained.

#### *2.4. DNA Isolation and PCR Amplification of Partial 16S rRNA Gene*

A small amount of every purified bacterial colony was taken by a sterile loop and subjected to DNA isolation using GenEluteTM Mammalian Genomic DNA 132 Miniprep Kit (Sigma) according to the manufacturer's instructions. Partial 16S rRNA gene sequence was amplified in PCR reaction mixtures containing 1× EmeraldAmp® GT PCR Master Mix (Takara, Shiga, Japan), 0.4 pmol/μL of primers 27F and 1492R (Wilson et al., 1990), 2 μL of DNA template, and nuclease-free water to the final volume of 50 μL. The reaction conditions were described previously [18]. Electrophoresis in 1.5% agarose gel was performed to check the presence of products of approximately 1450 bp length.

#### *2.5. Sequencing and Phylogenetic Analysis of Vibrio sp.*

The amplified PCR products were further sequenced commercially by Macrogen (Amsterdam, The Netherlands). The obtained sequences were edited manually and/or in BioEdit version 7.2.5. [19] and deposited in the GenBank under accession numbers: OL979296—OL979441. The sequences were analyzed by comparison with previously characterized 16S rRNA gene of the closest bacteria from the GenBank database using the NCBI BLAST program (Bethesda, MD, USA) and the percentage of similarity is highlighted.

To differentiate *Vibrio* species phylogenetic analysis that was based on the 16S rRNA gene sequence was conducted using MEGA11 [20]. The evolutionary history was inferred by using the maximum likelihood method and Kimura 2-parameter model. A discrete Gamma distribution was used to model the evolutionary rate differences among sites (5 categories (+G, parameter = 0.3935). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 69 nucleotide sequences, 15 of which were references from GenBank (accession numbers shown in the Table S1 in Supplementary File). There was a total of 1724 positions per sequence in the final dataset.

#### *2.6. Antimicrobial Susceptibility*

The Kirby–Bauer disk diffusion method on BBL™ Mueller Hinton II agar (BD) was used to determine the antimicrobial susceptibility of the isolated bacterial strains. The most used antibiotics in aquaculture were selected. The following antimicrobial disks were used for the test (the amounts are given in micrograms in parentheses): ampicillin (10), streptomycin (10), gentamicin (10), chloramphenicol (30), ciprofloxacin (5), erythromycin (15), imipenem (10), oxytetracycline (30), sulfamethoxazole/trimethoprim (23.75/1.25), vancomycin (30) that is manufactured by BBL™ Sensi-Disk™, and enrofloxacin (5), florfenicol (30), and flumequine (30) that is manufactured by Thermo Scientific™ Oxoid (Hampshire, UK). The inoculum was prepared in 5 mL of sterile 0.85% suspension medium (BioMérieux). On the Vitek Systems ATB 1550 instrument (BioMérieux, Marcy l'Etoile, France), the turbidity for each inoculum was adjusted to 0.5 according to the McFarland value scale [14]. After 24 h incubation at 22 ◦C, the diameter of the zone of inhibition was measured with a ruler and the values were interpreted as sensitive, moderately sensitive, or resistant according to the manufacturer's instructions.

#### *2.7. Statistical Analysis*

Statistical analysis was applied to detect the differences of heterotrophic bacteria and *Vibrio* content between the skin swabs, the seawater, and the sediment samples from both farms. Statistical significance of differences in the number of antibiotic-resistant bacterial isolates between the farms in each type of sample (skin, seawater, sediment) was also analyzed. The non-parametric Mann–Whitney U-test was applied for statistical analyses using SigmaPlot version 14.0 (Systat Software Inc., San Jose, CA, USA). The observed differences were statistically significant at *p* < 0.05. Venn diagrams were drawn to visualize the NAS and MAS culturable bacteria using a freely available web tool (http: //bioinformatics.psb.ugent.be/webtools/Venn/, accessed on 15 December 2021).

#### **3. Results**

#### *3.1. Results of Sea Bass Health Examination*

An examination of the health status of the European seabass from both cage farms revealed no clinical signs of disease. In the NAS farm, the total length of the fish ranged from 28.5 cm to 34.8 cm and the total weight ranged from 281.5 g to 487.7 g. In the MAS farm, the total length of the sampled European seabass ranged from 30.9 cm to 43.2 cm, and the total weight ranged from 254.2 g to 686.5 g. The total body length was statistically significantly higher for the fish from farm MAS (*p* < 0.05) (Figure 2).

**Figure 2.** (**A**) The total body length (cm) and (**B**) the total body weight (g) of sea bass (N = 10) from sites NAS (-) and MAS (-). Square boxes indicate the lower and upper quartiles and the whiskers represent the minimum and maximum data values (1.5 interquartile range). The medians are depicted by a solid line. \* Significant difference (*p* < 0.05) between the sites.

#### *3.2. Physicochemical and Microbiological Analysis of Seawater*

Table 1 shows the physicochemical parameters of the seawater from both fish farms.

**Table 1.** Physicochemical analysis of seawater from the NAS and MAS fish farms.

NAS—North Adriatic Sea antibiotic-free farm; MAS—Middle Adriatic Sea conventional farm; Secchi—Secchi depth; Sal.—Salinity; Cond.—Conductivity; TDS—Total dissolved solids; Temp.—Temperature; DO (mg/L)— Dissolved oxygen values; DO%—Dissolved oxygen saturation.

The results of the microbiological analysis of the seawater and sediment from the two farms are presented in Table 2. Although the levels of total coliform bacteria in the seawater column were notably higher at the NAS farm, the difference between two farms was not statistically significant. The levels of *E*. *coli* were higher at the MAS farm, but also with no statistically significant difference (*p* > 0.05).

**Table 2.** Microbiological analysis of seawater and sediment from the NAS and MAS farms.

NAS—North Adriatic Sea antibiotics-free farm; MAS—Middle Adriatic Sea conventional farm; TC—Total coliforms; EC—*E. coli*; EN—Enterococci.

The studied parameters in the sediment samples had higher values in the samples from the MAS farm, except for the number of *E*. *coli*, which had the same value in the sediment samples from both farms.

#### *3.3. Number of Heterotrophic Bacteria and Vibrio Count*

The results of the microbiological analysis of skin swabs of European seabass from the NAS and the MAS farm are presented in Table 3. The total number of heterotrophic bacteria (HPC) from the skin swabs of European seabass between the farms was statistically significantly higher in the NAS antibiotics-free farm, as well as the number of bacteria of the genus *Vibrio* (*p* < 0.05).

**Table 3.** Microbiological analysis of heterotrophic bacteria (HPC) and *Vibrio* count from skin swabs of European seabass, seawater, and sediment from NAS and MAS farm.

The differences in the total number of heterotrophic bacteria in seawater between the farms were not statistically significant (*p* > 0.05). The number of bacteria of the genus *Vibrio* was higher in the seawater samples from the MAS farm, and the differences were statistically significantly higher than in the NAS farm (*p* < 0.05).

#### *3.4. Culturable Microbiota*

The 16S rRNA gene sequences were generated for 81 and 64 bacterial isolates from NAS and MAS farm, respectively. The results from the datasets of each fish farm were composed of three compartments: the skin swabs of European seabass, seawater, and sediments. Of the total number of bacterial isolates from the NAS farm, 28 were from skin swabs, 32 were from seawater, and 21 were from sediments. Based on the sequence comparison, 33 bacterial species were identified among the isolates from the NAS farm, which are listed in Table 4. Of them, two, namely *V*. *alginolyticus* and *V*. *harveyi*, were identified in both the skin and seawater. Only *Bacillus hwajinpoensis* was found in the skin and sediment (Figure 3).

**Figure 3.** Venn diagram of the bacterial species that were identified in culturable microbiota of fish skin, seawater, and sediment associated with the NAS marine fish farm.

At the MAS farm, 20 isolates out of 64 in total were isolated from the European seabass swabs, while 22 accounted for seawater and sediment isolates. A total of 22 bacterial species were identified among the isolates from all the sample types in the MAS farm (Table 5). Despite the difference of species number (Table 5) among the bacterial communities of the fish skin (11 species), seawater (3 species), and sediment (4 species), species *Marinobacter litoralis*, and two species from the genus *Pseudoalteromonas* (*Pseudoalteromonas tetraodonis*, *Pseudoalteromonas undina*) were detected in the seawater and sediment, whereas *V*. *toranozoniae* was identified in the skin and sediment (Figure 4).

**Table 5.** Results of molecular identification of the bacterial isolates from the MAS conventional farm.

**Figure 4.** Venn diagram of the bacterial species that were identified in culturable microbiota of fish skin, seawater, and sediment associated with marine fish farm MAS.

A total of seven bacterial genera were identified by molecular analysis of bacterial isolates (N = 28) from skin swabs of European seabass from the NAS antibiotic-free farm. Figure 5A shows the occurrence of bacterial genera of skin swabs. The most common bacteria were bacteria of the genus *Vibrio* (53%), followed by the genera *Pseudoalteromonas* (14%) and *Pseudochrobactrum* (14%). *V. alginolyticus* (17.9%), and *Pseudochrobactrum sacchaloryticum* (14.3%), where *V. cyclitrophicus* (14.3%) and *V. harveyi* (14.3%) accounted for the largest number of the 11 bacterial species that were isolated (Table 4).

At the NAS antibiotics-free farm, the greatest diversity of bacterial genera (seven genera) was found in samples of skin swabs of European seabass. A total of five bacterial genera were detected in the sediment samples, while four bacterial genera were detected in the seawater samples. The most dominant bacterial genus that was identified in the seawater samples was *Vibrio* (65%), followed by *Pseudoalteromonas* (25%) (Figure 5C). Among the bacterial species, *V. chagasii* (18.8%), *Pseudoalteromonas shioyasakiensis* (9.4%), *Pseudoalteromonas tetraodonis* (9.4%), *V. kanaloae* (9.4%), and *V. tubiashii* (9.4%) were the most frequently identified.

In the sediment samples from the NAS farm, 21 bacterial isolates were obtained from five bacterial genera, among which the genus *Bacillus* (62%) dominated (Figure 5E). *B*. *aquimaris* (33.3%), *Photobacterium aphoticum* (19.0%), and *B*. *hwajinpoensis* (14.3%) corresponded to the most frequently identified bacterial species (Table 4).

*V*. *alginolyticus* and *V*. *harveyi* were isolated from European seabass skin swabs and seawater at the NAS antibiotic-free farm. *B*. *hwajinpoensis* was isolated from the skin swabs and sediment at the same farm. The seawater samples displayed the highest diversity of bacterial species (N = 16). A total of 11 bacterial species were identified from the skin swabs from the European seabass samples, while nine species were identified in the sediment samples (Table 4).

At the MAS conventional farm, among 20 bacterial isolates from skin swabs of European seabass, eight bacterial genera were identified, as shown in Figure 5B. The dominant bacterial genera were *Vibrio* (35%) and *Pseudomonas* (20%). Of the 12 bacterial species from the skin swabs of European seabass, *V*. *anguillarum* (20%), *Shewanella arctica* (15%), and *V*. *toranzoniae* (15%) were the most abundant (Table 5).

A total of four bacterial genera were identified in seawater samples from the MAS farm (22 bacterial isolates), of which the genus *Marinobacter* (59%) and the genus *Pseudoalteromonas* (27%) were the most abundant. The results of the presence of bacterial genera in the seawater samples are shown in Figure 5D. *M*. *litoralis* was most frequently identified bacterial species (59.1% of the total seawater isolates) (Table 5).

The identified bacterial genera from the sediment of the MAS farm and their representation are shown in Figure 5F. Among the six bacterial genera, *Vibrio* (36%), *Pseudoalteromonas* (23%), and *Photobacterium* (18%) were the most abundant. The most dominant bacterial

species were *V. toranzoniae* (27.3%), *Photobacterium lutimaris* (18.2%), and *Pseudoalteromonas tetraodonis* (18.2%) (Table 5).

**Figure 5.** Representation of the bacterial genera (percentage) in: (**A**)—European seabass skin swab samples from the NAS and (**B**)—the MAS farm; (**C**)—in seawater samples from the NAS farm and (**D**)—the MAS farm; (**E**)—in sediment samples from the NAS farm and (**F**)—the MAS farm.

*V. toranzoniae* was identified in European seabass swab samples and in sediment samples from the MAS farm with antibiotic use. *M. litoralis* was identified in the seawater and in the sediment samples at this farm, as well as *Pseudoalteromonas tetraodonis* and *Pseudoalteromonas undina*. Other bacterial species were detected only in one sample type. Only the genus *Pseudomonas* and the genus *Vibrio* were identified from the swab samples at both farms.

To confirm the identity of *Vibrio* species and check their grouping within different clades, phylogenetic analysis based on 16S rRNA including reference sequences from GenBank was performed. As expected, phylogenetic analysis confirmed grouping into five clades: *V*. *splendidus*, *V*. *anguillarum*, *V*. *orientalis*, *V*. *fortis*, and *V*. *harveyi* as well as branching with the same species (Figure 6). In the Tables 4 and 5 the percent of identity with the known *Vibrio* species from GenBank are shown.

**Figure 6.** Phylogenetic analysis of studied *Vibrio* species that was inferred from partial 16S rRNA gene sequences using MEGA11 software—the clades are indicated by brackets.

#### *3.5. Antimicrobial Resistance of Bacterial Isolates*

The disc diffusion test for susceptibility to 13 antibiotics was performed using the total of 145 bacterial isolates from the two fish farms. The number of isolates that were resistant to individual antibiotics and the percentage of resistant isolates are shown in Table 6.

**Table 6.** Differences in antibiotic resistance of the bacterial isolates from the NAS antibiotic-free European seabass farm versus farm MAS conventional farm.

N—number of analyzed bacterial isolates, No. of isolates—number of resistant bacterial isolates, %—percentage of resistant bacterial isolates.

Most of the bacterial isolates from the skin swabs of European seabass from the NAS farm without antibiotic use showed resistance to vancomycin (85.7%), ampicillin (57.1%), enrofloxacin (39.3%), erythromycin (39.3%), and streptomycin (39.3%). All the isolates of *V. alginolyticus* were resistant to vancomycin and ampicillin (Table 7). The resistance of isolates to other antibiotics was inconsistent.

**Table 7.** Antibiotic resistance of bacteria from the genus *Vibrio*.

N—number of analyzed bacterial isolates, No. of isolates—number of resistant bacte-rial isolates, %—percentage of resistant bacterial isolates.

Most of the bacterial isolates from the skin swabs of European seabass from the MAS conventional farm with antibiotic use were resistant to ampicillin (100.0%), vancomycin (100.0%), erythromycin (75.0%), florfenicol (65.0%), and imipenem (65.0%). The predominant bacterial species in the samples was *V. anguillarum* and the isolates were resistant to enrofloxacin, ampicillin, erythromycin, vancomycin, and streptomycin (Table 7). No statistically significant differences in the number of antibiotic-resistant bacterial isolates were found between the two farms (*p* > 0.05).

Similar to the isolates from the skin swabs, most bacterial isolates from seawater from the NAS antibiotics-free farm showed resistance to vancomycin (84.4%), ampicillin (50.0%), enrofloxacin (31.3%), erythromycin (37.5%), and streptomycin (40.6%). The predominant bacterial species in the seawater samples was *V. chagasii* and all *V*. *chagasii* isolates showed resistance to vancomycin (Table 7).

Among the bacterial isolates from the farm seawater samples at the MAS farm, vancomycin resistance was the most common (90.9%). In seawater samples, the most common bacterial species was *M. litoralis* and all *M. litoralis* isolates were resistant to vancomycin, while resistance was not consistent among the other antibiotics. The differences in the number of resistant bacterial isolates between the two farms were not statistically significant (*p* > 0.05).

Most of the bacterial isolates from the sediment samples from the NAS antibiotics-free farm showed resistance to enrofloxacin (61.9%) and flumequine (52.9%). *B. aquimaris* was the most common isolate and most of the bacterial isolates (six out of seven) were resistant to enrofloxacin. For other antibiotics, the resistance of the bacterial isolates was not uniform.

As high as 86.4% of total bacterial isolates from the MAS farm sediment samples were resistant to vancomycin. This is also characteristic for the most numerous sediment isolates that were identified as *V. toranzoniae* (Table 7). In contrast to the results of resistance from the skin swabs and seawater isolates, the number of antibiotic-resistant bacterial isolates between the two farms were statistically significantly higher at the NAS antibiotic-free farm than in the MAS conventional farm (*p* < 0.05).

#### **4. Discussion**

The quality of seawater has a great influence on the success of fish farming. Stress that is caused by disturbances in seawater quality negatively affects fish growth and development [21]. The seawater physicochemical parameters that were measured at the NAS and MAS farms were consistent with previous studies on Adriatic Sea bass farms [17,22,23].

Microbiological analysis of the seawater samples and skin swabs of European seabass revealed a higher HPC and *Vibrio* count in the seawater samples from the MAS farm, but conversely higher HPC and *Vibrio* count from skin swabs from the NAS farm. This HPC count from the skin swabs of European seabass from the NAS farm (69.1 ± 21.7 CFU/cm2) is lower than a previously reported range between 102 and 104 CFU/cm2, at other geographical locations [8]. The higher *Vibrio* count in the seawater samples from the MAS farm can be explained by the influence of the higher seawater temperature which stimulates bacterial growth [22,24]. Interestingly, a higher *Vibrio* count was detected in samples from the fish skin than in the seawater of the NAS farm. This phenomenon was described by Vatsos [25] who documented the quantitative and qualitative differences between the culturable microbiota of the fish skin and that in the water from the host environment. Although the identification of *Vibrio* species is challenging due to similarities, both in phenotypic properties and 16S rRNA sequences, phylogenetic analyses can differentiate clades and subgroups affiliation [26]. That is why we used this analysis for the *Vibrio* species differentiation.

In this study, a similar number of bacterial genera was observed in each type of sample (skin swabs, seawater, sediment) after analyzing the composition of the culturable microbiota from the two investigated farms (under culture conditions with and without the use of antibiotics). This could be because each bacterial species grows under specific culture conditions. A total of four genera were found in the seawater samples from both farms, but with different prevalence. The number of bacterial species differed between the seawater samples from the NAS antibiotics-free farm and the MAS conventional farm, where 16 and 6 bacterial species, respectively, were identified. The diversity of bacterial species is strongly influenced by the quality of seawater in the farm [27]. Considering that the physicochemical and microbiological parameters in both farms showed seawater quality that is suitable for farming [17,23], the use of antibiotics at the MAS farm may have affected diversity of the bacterial species. Rosado et al. [6] stated that the use of antibiotics can affect the change in the composition of bacterial species in the skin microbiota, reducing the diversity of bacteria and the resistance of farmed fish to bacterial infections. Nevertheless, in this work, 12 bacterial species were identified from skin swabs in the MAS farm where antibiotics are regularly administered. At the NAS farm, where antibiotics are not used, 11 bacterial species were identified from the skin swabs. However, two common genera, *Pseudomonas*

and *Vibrio*, were identified in the skin swab samples at both farms. Our observation agrees with those of Což Rakovac et al. [ ˇ 28], who previously reported *Pseudomonas* isolates from wild and farmed sea bass in the Northern Adriatic Sea. These results are similar with those of recent study of skin microbiota of farmed European seabass in South Adriatic (Croatia and Montenegro), where most of the isolated bacteria comprised of *Vibrio*, *Photobacterium*, and *Pseudomonas* genera [16]. The skin is one of the main entry points for pathogens and infections, while the mucus of the fish skin has an important role in the immune system and has an antibacterial effect [1]. Therefore, one of the objectives of this study was to identify bacterial species from skin swabs of European seabass with particular emphasis on pathogenic bacteria to fish. An analysis of the identified bacterial species reveals some potentially pathogenic bacteria to fish [4]. According to the study of De Bruijn et al. [8], the microbiota of fish skin contains pathogenic bacteria to fish that do not cause disease unless the microbiota balance is disturbed. It is well known that antibiotic use can promote the proliferation of opportunistic pathogens [29], e.g., *V. anguillarum* in skin swabs from MAS conventional farm.

*Pseudoalteromonas undina* was isolated from skin swabs of European seabass from the NAS farm. *P*. *undina* is widely distributed in seawater, especially in farms that are rich in organic matter, but has not been reported as a pathogenic bacterium, except in a study by Pujalte et al. [30], in which it caused mortalities of sea bass. The opportunistic pathogens *V*. *alginolyticus* and *V*. *harveyi* have also been isolated from NAS farms. *V*. *alginolyticus* is known to cause vibriosis [17,31], while *V*. *harveyi* is also a potential threat for European seabass farming [5,32].

The samples of European seabass skin swabs from the MAS farm also contained some potentially pathogenic bacteria to fish. *V*. *anguillarum* is one of the causative agents of vibriosis in the Adriatic Sea [14], while *V*. *toranzoniae* has only been identified as a pathogen in diseased sea eels (*Genypterus chilensis*) in Chile [33]. In addition, *Pseudomonas gessardii* has been isolated and identified as a larval shrimp opportunistic pathogen in a recent study, while *V*. *alginolyticus* has been identified as the primary pathogen [31].

Considering the potential pathogenicity of *V*. *alginolyticus*, *V*. *anguillarum*, and *V*. *harveyi*, it is important to highlight their resistance to antibiotics, although this varied from isolate to isolate. *V*. *alginolyticus* from the skin swabs of European seabass from a NAS farm showed resistance to streptomycin and ampicillin. In previous studies, *V*. *alginolyticus* that was isolated from skin swabs of sea bass from three farms in the Adriatic Sea (Lim Bay, Lamjana and Mali Ston Bay) showed higher resistance to five (ampicillin, penicillin, piperacillin, sulfamethoxazole/trimethoprim, and trimethoprim) of the 13 antibiotics that were tested (ampicillin, streptomycin, gentamicin, imipenem, chloramphenicol, florfenicol, ciprofloxacin, enrofloxacin, erythromycin, oxytetracycline, sulfamethoxazole/trimethoprim, vancomycin, and flumequine) [17]. In addition, all the isolates of *V*. *alginolyticus* in this study were sensitive or moderately sensitive to sulfamethoxazole/trimethoprim, which is commonly used to treat vibriosis; this is consistent with the studies of Zorrilla et al. [34] who tested seven antimicrobial agents (ampicillin, amoxicillin, tetracycline, oxytetracycline, trimethoprim-sulphamethoxazole, oxolinic acid, and flumequine). Isolates of *V*. *harveyi* from the NAS farm were found to be resistant to ampicillin, erythromycin, and vancomycin. In a similar study, Vei´c [5] tested nine antibiotics (ampicilin, trimethoprim/sulfadiazine, chloramphenicol, oxytetracycline, enrofloxacin, flumequine, nalidixic acid, gentamicin, and neomycin) and described resistance to gentamicin and neomycin, as well as to ampicillin and erythromycin in all the strains, and intermediate sensitivity to nalidixic acid and oxytetracycline in the same *V*. *harveyi* strains that were isolated from diseased European seabass in the Adriatic Sea. Kang et al. [35] tested 16 antibiotics (ampicillin, cefotaxime, cefotetan, cephalothin, chloramphenicol, ciprofloxacin, cefepime, erythromycin, gentamicin, kanamycin, nalidixic acid, rifampicin, streptomycin, tetracycline, trimethoprim/sulfamethoxazole, and vancomycin) and reported that *V*. *harveyi* that was isolated from seawater in South Korea was resistant to ampicillin and vancomycin, and sensitive to erythromycin.

*V*. *anguillarum* that was isolated from the MAS conventional farm was resistant to ampicillin, enrofloxacin, erythromycin, streptomycin, and vancomycin. Resistance of *V*. *anguillarum* that was isolated from farmed rainbow trout (*Oncorhynchus mykiss*) was determined for cloxacillin, ampicillin, sulfamethoxazole/trimethoprim, and erythromycin [36]. Variations in results are commonly attributed to the difference between the tested organism as well as the sampling location. In a recent study that was carried out by Kapetanovi´c et al. [14], *V*. *anguillarum* that was isolated from the skin and gills of European seabass (Mali Ston Bay) showed resistance to gentamicin, erythromycin, and streptomycin, which is not entirely consistent with the results of this study. Similarly, Vei´c [5] determined the resistance of isolated *V*. *anguillarum* strains from diseased European seabass in the Adriatic Sea to ampicillin and erythromycin. Thus, in our study, *V*. *anguillarum* was found to be more resistant, indicating the possible development of bacterial resistance to certain antibiotics to which resistance was not found in previous studies.

The results of antimicrobial resistance in sediment seem to be somewhat controversial, as resistance is higher in the sediment from the NAS farm where antibiotics are not used. Increased antibacterial resistance of bacteria in sediment is often the most sensitive environmental indicator of past antibiotic use [37]. *Vibrionaceae* were widely distributed in sediment samples on fish farms in the western Mediterranean and their resistance is known due to the antibiotics administered [38]. Interestingly, in our study, antibiotic resistance was detected in the microbiota of the NAS farm where antibiotics were not administered since the aquaculture production was established. Antibiotic resistance depends on the species and the location where the bacteria was isolated. It is well known that antibiotic resistance is higher along the coasts and in sheltered bays than in open waters but could also occur in more remote waters due to the influence of non-aquatic organisms or pollutants [39].

The resistant strains at the antibiotic-free farm could be of terrestrial/agricultural origin. In fact, the nearby island of Cres is known for its traditional and extensive farming of autochthonous sheep, which has previously been diagnosed clinical mastitis, enterotoxaemia, actinobacillosis, contagious ecthyma, foot rot, and *Brucella ovis* infection [40]. The use of various antibiotics for treatment of bacterial diseases in sheep, including those based on enrofloxacin and flumequine [40,41], might promote the development of antibiotic resistance that can potentially be carried towards surface waters and sediments by rainfall runoffs [42]. This should be considered as a potential risk for the release of bacterial pathogens into the water column and the spread of antibiotic resistance across different marine compartments and should be investigated in future studies. There is also the possibility that resistant bacteria were introduced on the NAS farm by fingerlings, which also should be investigated.

These results confirm the presence of some potentially pathogenic bacteria for fish. Bacterial fish diseases are usually treated with antibiotics. The most commonly used antibiotics include tetracyclines and fluoroquinolones. However, there is a risk of antibiotic resistance development, as multidrug-resistant bacteria can be easily spread in the marine environment. In addition, the inadequate treatment of fish diseases with antibiotics can lead to selection of bacteria that respond less to antibiotic treatments and increase the likelihood of disease outbreaks in fish farms. The need to reduce financial losses in European seabass aquaculture, overcome the risk of spreading antibiotic-resistant bacteria, and concerns about environmental impacts and consumer safety require alternative and sustainable control measures for frequent antibiotic therapy in aquaculture.

To our knowledge, this is the first study comparing the culturable microbiota at fish farms with and without the use of antibiotics. Our results should be extended in further studies with a larger number of samplings as well as antibiotic residues analyses in the water and sediment, all of which may affect the results. Before each stocking in the cages, the microbiota of the skin of fish fingerlings should be analyzed and included in further studies. Based on the preliminary results of the present study, further research is needed to confirm these findings and to investigate whether and how the microbiota differs seasonally in these farms with and without antibiotic use.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jmse10030303/s1, Table S1: List of bacterial isolates/strains and their accession numbers from GenBank used for the phylogenetic tree construction (Figure 6, Results).

**Author Contributions:** Conceptualization, D.K., A.R. and A.G.; methodology, A.R., I.V.S., A.K., D.K. and A.G.; validation, I.B. and A.G.; field work, T.K., D.K., A.G. and I.B.; formal analysis, A.R., D.K., I.V.S. and F.B.; investigation, D.K., I.B., F.B. and A.G.; resources, D.K. and I.B.; writing—original draft preparation, A.R., D.K., I.V.S. and L.P.; writing—review and editing, A.K. and A.G.; visualization, A.R., D.K. and I.V.S.; supervision, I.V.S., L.P. and A.G.; project administration, T.K., D.K.; principal investigator, T.K.; funding acquisition, T.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work has been fully supported by the Croatian Science Foundation's funding of the under the project AqADAPT—Grant No IP-2018-01-3150, Croatian Academy of Sciences and Arts, and Croatian Ministry of Science and Education under the bilateral project with Germany (DAAD) EXAQUA.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available because it's an ongoing scientific project AqADAPT—Grant No IP-2018-01-31504.

**Acknowledgments:** This work has been fully supported by the Croatian Science Foundation's funding of the under the project AqADAPT—Grant No IP-2018-01-3150. We also thank the Croatian Academy of Sciences and Arts for funding the project: The presence of resistant bacterial strains as part of the natural microflora of European seabass (*Dicentrarchus labrax*) cultured under conditions with and without the use of antibiotics: truths and prejudices. We thank our colleagues at the Helmholtz Centre for Environmental Research GmbH-UFZ, Leipzig, Germany, who collaborated on the Croatian-German bilateral project: Exploring the potential of phage and microbiomes to control pathogens in aquaculture (EXAQUA). The publication of this article was funded by the Croatian Ministry of Science and Education within the framework of the bilateral project with Germany (DAAD) EXAQUA. We thank the anonymous reviewers for their useful comments and suggestions for our article.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**

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**12. Necrotizing fasciitis**

Necrotizing fasciitis represents clinically severe pyogenic infection (cellulitis) of the skin and underlying soft tissue [113–117]. Deep, painful, and intractable ulceration subacutely progresses predominantly on the extremities (**Figure 40**). Minor trauma may provide the entry for pathogens. The condition uncommonly follows

#### **Figure 39.**

*Lethal Fournier's gangrene of the rectum (gross, H&E and immunostain). Transmural necrotic and gangrenous inflammation is seen in the lower part of the rectum in a female patient aged 60's suffering from myelodysplastic syndrome. Gram-negative rods are immunoreactive for* E. coli*-related lipopolysaccharide.*

#### **Figure 40.**

As illustrated in **Figure 39**, fulminant necrotizing inflammation involved the lower part of the rectum in a female patient suffering from myelodysplastic syndrome. Emergency surgery disclosed transmural gangrenous necrosis of the rectal wall with massive mixed bacterial infection, including *E. coli*. Occasionally, Fournier's gangrene has been complicated with rectal cancer [111, 112].

*Fournier's gangrene (gross, H&E, Gram and immunostain). Debridement specimen discloses massive transmural necrosis of the scrotal tissue. Gas bubbles are scattered in the heavily infected necrotic tissue. Grampositive cocci are immunoreactive for streptococcal antigens. This case represents fulminant streptococcal*

*Fournier's gangrene (gross findings of two male cases). Massive hemorrhagic necrosis started from the scrotum and extended to the left hip and leg (left). Marked black swelling of the scrotum is serious, and necrotizing change extends toward the perianal region (right). The rapidly progressive gangrene caused death in both*

*patients. The penis is spared in the left case, but massively involved in the right case.*

Necrotizing fasciitis represents clinically severe pyogenic infection (cellulitis) of the skin and underlying soft tissue [113–117]. Deep, painful, and intractable ulceration subacutely progresses predominantly on the extremities (**Figure 40**). Minor trauma may provide the entry for pathogens. The condition uncommonly follows

**12. Necrotizing fasciitis**

*infection with gas formation (non-clostridial gas gangrene).*

**Figure 37.**

*Pathogenic Bacteria*

**Figure 38.**

**120**

*Necrotizing fasciitis (gross and H&E). Deep and painful ulceration is caused by local and invasive bacterial infection. This aged male diabetic case had a history of arterial replacement therapy for atherosclerosis obliterans. In order to relieve pain and to avoid septicemic spread of infection, amputation surgery was performed. Necrotizing inflammation extends to the striated muscle layer.*

surgical procedures. Diabetes mellitus, immunosuppression, alcoholism, drug abuse, atherosclerosis-related ischemia, and malnutrition may be prodromal to this troublesome condition. It may be seen in healthy persons [118]. Necrotizing fasciitis is categorized into two types: type I (polymicrobial infection) and type II (monobacterial infection).

In **Figure 41**, necrotizing fasciitis seen in a poorly controlled diabetic male patient is presented. In the wintertime, a fan heater gave the patient a severe burn on his sole, because he did not feel pain sensation due to diabetic peripheral neuropathy. The doctor-shy patient did not visit a hospital for 1 week, and this allowed the lesion far progressed. Severe atherosclerosis had provoked dry gangrene in his

#### **Figure 41.**

*Localized severe burn on the sole of a diabetic male caused by a fan heater, resulting in necrotizing fasciitis (gross appearance). Because of diabetic neuropathy, deep ulcers occurred on the senseless foot. Dry gangrene on the first and second toes (arrowheads) indicates the association of diabetes-related atherosclerosis obliterans. The importance of foot care in diabetic patients should be emphasized.*

toes. Diabetes-related neutrophilic dysfunction provided him with the vulnerability to infection. Polymicrobial (type I) necrotizing fasciitis resulted in septicemia. Emergency amputation saved his life. The importance of foot care for patients with diabetes mellitus should be emphasized.

**13.1 Fulminant streptococcal infection without gangrene of the extremities**

Pseudomonas*-related necrotizing fasciitis in a young lady suffering from anorexia nervosa (gross, H&E and immunostain). Her leg with massive necrotic/gangrenous lesions was amputated (left, after sampling of histological specimens). Massive bacterial growth provoked little inflammatory reaction. The bacteria are immunoreactive for* Pseudomonas aeruginosa *antigen detected by a monoclonal antibody (the courtesy by Dr. Takashi Tsuchida, a pathologist in Hamamatsu Medical University Hospital, Hamamatsu, Japan).*

internal organs may cause the fatal disease.

**Figure 42.**

*Pathology of Gangrene*

*DOI: http://dx.doi.org/10.5772/intechopen.93505*

**123**

carbohydrate antigen specific for group A *Streptococcus* [127].

Fulminant infection of group A β-hemolytic *Streptococcus* (*Streptococcus pyogenes*) is typically featured by progressive gangrene in the soft tissue of the extremities, as described above in the Section 10.1. Streptococcal toxic shock syndrome provokes an aggressive lethal condition without predisposing diseases [123, 124]. It should be of note that fulminant group A streptococcal infection is also encountered in cases without gangrenous lesions of the extremities [125]. Streptococcal infection in the

We experienced five cases of fulminant streptococcal infection without gangrene of the extremities (**Table 1**). Four of five cases were young and immunocompetent, and encountered at forensic autopsy. Infectious foci were seen in internal organs such as the tonsil, bronchus, puerperal endometrium, and urinary bladder. The clinical course was very short ranging from 2 to 4 days. Infective and hemorrhagic cystitis with systemic streptococcal dissemination was encountered in an aged female patient with a history of cerebral infarction and femoral neck fracture (**Figure 43**). Necrotizing endometritis in a puerperal lady was the cause of streptococcal toxic shock-like syndrome, as illustrated in **Figure 44**. It can be categorized in so-called puerperal fever. Pregnancy-associated lethal infection should be of particular notice [126]. Group A *Streptococcus* infection was proven by microbial culture in two cases, and immunoreactivities of streptococcal antigens and Strep A were shown on the Gram-positive cocci in all five cases. Strep A is a

There are two different pathological mechanisms in fulminant streptococcal infection without gangrene of the extremities [125]. One form with overwhelming bacterial growth is characterized by secondary systemic bacterial dissemination accompanying bacterial emboli with poor neutrophilic reaction. Bacterial embolism in the adrenal gland provokes bilateral adrenal hemorrhage (acute adrenocortical insufficiency), being categorized in Waterhouse-Friderichsen syndrome [128] (**Figure 45**). Another form without bacterial embolism was featured by bacterial

Infrequently, necrotizing fasciitis is caused by *Pseudomonas aeruginosa* [119, 120]. Reportedly, the mortality rate of this type II lesion is 30%, and the infection often happens in the immunocompromised patients. Clinicians should consider empiric pseudomonal antibiotic coverage for preventing the progression of necrotizing limb infection.

An 18-year-old female patient had suffered from anorexia nervosa for 6 years. She happened to develop phlegmonous inflammation on her left lower leg, rapidly progressing to multifocal ulceration and gangrene. In 3 days, she underwent surgical amputation. *Pseudomonas aeruginosa* was cultured from blood and the leg lesion of necrotizing fasciitis. Immunohistochemical identification of the pseudomonal microbe was achieved by using a commercial monoclonal antibody. Representative features are illustrated in **Figure 42**.

Classic pathogens of cellulitis represent group A β-hemolytic *Streptococcus* and less frequently *Staphylococcus aureus*, but a diverse range of microorganisms, including *Pseudomonas aeruginosa* (as described above), cause cellulitis. Erythematous nodular lesions formed on the leg of neutropenic or leukemic patients were caused by *Stenotrophomonas maltophilia* [121]. Facial cellulitis may result from *Haemophilus influenzae* infection [122].


**1. Introduction**

Advancement in electrotechnical devices has indeed revolutionize our daily lives. It will be hard to imagine going through our daily lives without cell phones, computers, and internets, to name a few. Consequently, our reliance on electrotechnical devices has been increasing significantly, and thus the dependability of these devices is becoming crucial.

Dependability of a device is determined by its reliability and its constituting components therein. Reliability is defined as the probability that a product, system, or service will perform its intended function adequately for a specified period of time or will operate in a defined environment without failure. The component of reliability is as depicted in Figure 1 to the following: The components of reliability include probability, durability, dependability, availability and quality over time [1].

**Citation:** Tan, C.-M. Editorial for Special Issue on Reliability Analysis of Electrotechnical Devices. *Appl. Sci.* **2022**, *12*, 4086. https://doi.org/ 10.3390/app12084086

Received: 7 April 2022 Accepted: 13 April 2022 Published: 18 April 2022

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**Copyright:** © 2022 by the author. 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/).

**Figure 1.** Different between Reliability and Current Quality Practice.

Although reliability is part of quality as can be learnt from the definition of quality according to ISO8402, which stated that quality is the totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs [2]. These stated or implied needs of course include the operation of products at prolonged period or its mission lifetime. However, due to the impossibility to check the reliability of every single product, as reliability tests usually involve time-consuming and destructive measurements, quality assurance can only assure the quality practice of the incoming materials, manufacturing processes through SPC, Cpk and yield, and product outcoming quality check against specifications. This renders a risk in the reliability of the products as depicted in Figure 1.

Figure 1 shows the strength distributions of two product batches, A and B. As the strength of the products in batch A is well above the specification, its quality at time zero is consider excellent whilst products in batch B suffers some yield loss. In both cases, their strengths are above the expected load to be applied to them, and hence they can operate without failure. During continuous operations, the strengths of products will degrade as expected. Thus, their mean strengths will be reduced, but the spread of the strength distribution increases since not all the products in a batch will degrade equally. If the degradation rate of products in batch A is much higher than that of batch B, some products in batch A will go below the load at time t', and some failure will occur. Such failures are considered as reliability failure. On the other hand, there is no failure for products in batch B, although its yield is not 100%. This figure explains the limitations of the current quality assurance methodology as degradation rate can only be found through reliability or accelerated life test. Even if reliability test is performed but with no failure, degradation rate will not be able to determine either.

However, the determination of the degradation rate can be time consuming and cost intensive as the number of failures in a selected accelerated life test must be sufficient to provide a good estimation of the degradation rate of a batch. Furthermore, the choice of accelerated life test must correspond to the dominant failure mechanisms of the products in normal field operating conditions, and this requires detail failure analysis of field failure if the product is already in the market or a good understanding of the possible various failure mechanisms before the products are launched.

To address the above-mentioned, and in view of the short time to market available for products, a new research area has recently emerged where the physics of failures and material sciences are employed to explore the various possible degradation mechanisms with the aid of powerful simulation tools. Statistical concept is also incorporated in the simulation to show the possible variation in the time to failure and reliability statistics is employed for the extrapolation of time to failure from accelerated test conditions to different field operating conditions. Such research area is called reliability sciences where experimentation, multi-scale simulation, atomistic finite element modelling and statistics are used concurrently, so that reliability of components can be predicted before the assembly of the final product. In this way, the reliability of a product will be determined beforehand, allowing for faster and cheaper modifications, before 'final' products are developed. This is a paradigm shift in product reliability assurance, and current reliability evaluation, when performed on the final product, would then act as secondary measurements, confirming the initially predicted reliability [3].

This special issue focusses on the exploration of the underlying degradation sciences. We focus on technical important devices, including antenna for IoT, 3D stack-chips for today high-performance integrated circuit assembly, Lithium-Ion battery (LiB) for electric vehicle and energy storage, devices in radiation environment such as space applications as the demand for satellites increases for IoT applications and medical applications, and printed circuit board assembly for wireless communication in public transport. As accelerated life tests for some highly reliable products can be too long, degradation analysis is employed. Improving the accuracy of the degradation test data analysis with respect to the measurement errors is also included in this special issue.

#### **2. Electromagnetic Interference for Stack-Chips and Antenna**

3D stack-chips are becoming common due to the increasing complexity of circuits and the requirement of small outline for an integrated circuit. Various factors can affect their reliability such as the stress induced from TSV [4], thermal dissipation effectiveness in the dense and 3D structure of the chips [5]. One of the advantages of using 3D stack-chip is the low latency of the interconnections for high-speed operation [6]. However, such high-speed operation can also induce electromagnetic field that can couple to the dices above and below, due to their proximity, resulting in serious electromagnetic interference (EMI) between the dices. Dipesh et al. first examined such issue using electromagnetic computation method apply to integrated circuit.

They found that near field electromagnetic measurement is ineffective to identify the hot spots of electromagnetic emission within the stacked dies, and they thus developed a computational method to identify the electromagnetic emission hot spots in integrated circuits with experimental verification. They found that if the stack distance between dices is too small, the coupled magnetic field strength can be as high as 16 times as compared with an unstacked IC. Thus, a minimum distance between the stack must be maintained. The method they developed can be carried out at the IC design stage before fabrication, enabling optimization of the stack distance as well as circuit design for reducing the EMI, and eliminating the significant cost of fabrication owing to improper design.

Using the method developed, they also identified the key dimensional parameters of a miniaturized single element of T-shaped MIMO antenna which is commonly used today for data communication. They found an optimized antenna with 1 GHz improvement in the bandwidth due to the improved return loss that provides new opportunities for the antenna's utilization in different applications. This optimized antenna has lower current distribution that gives lower power dissipation, and its 1 m sphere EMI was also reduced.

These are examples of using computational power to ensure good performances and lower power dissipation, which in turn can lead to better durability.

#### **3. Electronic Devices under Radiation Environment**

Radiation on electronics is no longer limit to space application only. Advances in semiconductor technology have enhanced the functionality of integrated circuits (ICs) with reduced feature sizes down to nm. Proton and neutron radiation are always present around us but have not been detrimental to electronics at sea level. With the decreasing feature size of transistors and the increasing density of transistors in ICs, the effect of radiation on the reliability of semiconductor devices, sensors, and their electronic circuits (collectively called electronic systems) is no longer negligible, even at sea level. ISO26262 International safety standard states the requirements for automotive electronics to be radiation immune to a certain level. Thus, radiation reliability of electronics is an emerging area that cannot be neglected [7].

Although the dominant radiation source at sea level for electronics is neutron, neutron radiation test is rarely available due to the control difficult for neutron beam. Chiang et al. investigated the possibility of having proton to replace neutron for electronics using Monte Carlo simulation, and they found that 200 MeV protons closely resemble the effect from neutron radiation, and this concur with the suggestion from NASA, USA. They also used the Monte Carlo simulation to demonstrate the invalidity of the conventional concept of using linear energy transfer (LET) of radiation particles to estimate the single event effect (SEE) in electronic devices. Instead, lineal calculation of energy lost per step for each specific track should be used for the prediction of microelectronic devices failure due to SEEs. With such Monte Carlo simulation, they managed to predict the radiation reliability of microelectronics devices.

The increasing application of radiation therapy in medical treatment and diagnosis has also subjected the medical electronics to radiation. X-ray is a familiar example which subjects electronics to photon radiation, and the emerging proton therapy is another example which subjects electronics to stray proton radiation. Silicon devices are vulnerable to radiation, and to improve the reliability of the radiation system with good electronic control, Gallium Nitride (GaN) devices are suggested. Vimal et al. developed a GaNbased readout system in proton therapy treatment system. In particular, they designed an operation amplifier (OPA) which is a basic circuit module for the electronic in the readout system using GaN and simulation results indicated good performances. The proposed OPA was also configured for different applications such as transimpedance amplifier, integrator, and the adder which are needed in the prompt gamma readout system. Simulation results show successful operation for these applications. When these different applications are

put together, a complete GaN-based prompt gamma readout circuit is implemented, and the result shows successful processing of the prompt gamma signal where its energy and position of the proton beam in a human body can be accurately provided for subsequent digital conversion and information extraction.

The increasing demand of IoT also prompt the significant increase in the need of satellites for communication. Radiation effects should be carefully monitored for the reliability of the electronics of satellites in the outer space, but radiation hardened electronics are too costly for IoT applications. In addition to the electronics components used, the solder joints of components onto printed circuit board also need to be reliable. It is found that the reliabilities of the commonly used Sn/Pb and SnAgCu solder joints are not good under the thermal shock conditions in the outer space. Guo et al. proposed an environmentally friendly interconnection material, namely pressureless sintered micron silver which is economical. Before predicting the reliability of this material in the proposed applications, the degradation mechanism of this material under the deep space environment was studied. They employed finite element analysis (FEA) to study the degradation physics, and their results were verified with their experiments. Their studies showed an elasticity degradation during the thermal shock, which induces lattice shift and dislocation slip in the microstructure. The dislocation piling up causes the effective elastic modulus of sintered joints to decline due to broken atomic bonds. With the understanding of the degradation physics, degradation model can be developed to extrapolate the lifetime of such material from accelerated test condition to predict its reliability and suitability in deep space usage.

The increasing important of electronics operating under radiation environment can be seen from the above description, and from the above few works, one can see that there are still a lot more work needed in this area.

#### **4. Remaining Useful Life (RUL) of Lithium-Ion Battery (LiB)**

While product lifetime can be predicted through reliability tests in most cases, field reliability is likely different. A typical rule of thumb is to expect the unreliability in the field to be twice what was observed in the lab. This is because product will usually receive harsher treatment in the field than in the lab. Units being tested in the labs are often carefully set up and adjusted by engineers prior to the beginning of the test. The tests are performed by trained technicians who are adept at operating the product being tested. Most end-use customers do not have the training and experience in its operation, thus leading to many more operator-induced failures than would be experienced during in-house testing [8].

In some cases, accelerated life test cannot be performed such as LiB and other highly reliable products. This is because accelerated test condition for LiB can affect the chemistry in LiB and the degradation mechanisms will be completely different from that operate at normal condition. For highly reliable products, the test time is simply too high and accelerated degradation tests usually employed.

Regardless of the situations, ability to estimate the remaining useful life of a product, as it might have been through various operating conditions, will be useful. Tan et al. developed a methodology to estimate the RUL for LiB. Their method combines the electrochemistry-based electrical model and semi-empirical capacity fading model on a discharge curve of a LiB for the estimation of its maximum stored charge capacity, and thus its state of health (SoH). The method developed produces a close form that relates SoH with the number of charge-discharge cycles as well as operating temperatures and currents, and its inverse application allows us to estimate the remaining useful life of LiB for a given SoH threshold level. The estimation time is less than 5 s as the combined model is a closed-form model, and hence it is suitable for real time and on-line applications.

#### **5. Degradation Analysis**

With the increasing product reliability, prediction of lifetime through accelerated life test can be too long, and degradation analysis is usually employed. However, in most degradation tests, the measuring processes may cause variation in the observed measures. As the measuring process is inherent to the degradation testing, it is important to establish schemes that define a certain level of permissible measurement error such that a robust reliability estimation can be obtained. Rodriguez-Picon et al. proposed an approach to deal with this measurement error based on a deconvolution operation. An illustrative example based on a fatigue-crack growth dataset is presented to illustrate the applicability of the proposed scheme.

#### **6. Failure Analysis**

Failure analysis is common in electronic industry; however, the depth of analysis needs to be further to uncover the underlying science of the failure mode. Physics of failure is needed to ensure product reliability as only then root cause can be identified. Tan et al. demonstrated a step-by-step failure analysis methodology for multilayer printed circuit boards that led an observed failure mode to the root cause with verification of the root cause and the effectiveness of the corresponding corrective action. This printed circuit board (PCB) is used in public transport systems. With the identified root cause, a modified processing method was developed and the observed failure mode was no longer observed with this modified method, which verified the root cause. The PCBs with the modified processing method also underwent appropriate reliability tests and the corrective action of this modified processing method is confirmed.

Li et al. performed detail failure analysis on failure obtained from low temperature and shock test that mimic deep space exploration. They found that the failure was in the Pb-free (Sn-3.0Ag-0.5Cu) solder joint, and the low temperature changes the fracture characteristic of Sn-3.0Ag-0.5Cu (SAC305) from ductileness to brittleness. The crack occurred at solder joints from the stress loaded by shock test. When the crack reached a specific length, the failure occurred. A verification test was conducted to verify the failure mechanism. The transition temperature range of SAC305 was also confirmed as −70–−80 ◦C.

#### **7. Future Outlook**

Reliability of products is an implicit expectation from users, but the current quality assurance method is limited to provide sufficient information to assure product reliability. Reliability tests on products are also facing challenges as mentioned earlier, and a paradigm shift is on the reliability science. This is an important and emerging area in reliability, and it requires professional from different disciplines to come together and share their works so that we can gel the different aspects of reliability science together. With the increasing variety of electrotechnical devices in increasing application areas, many research works are expected. We look forward to seeing the explosion in this area.

**Funding:** This research received no external funding.

**Acknowledgments:** This issue would not be possible without the contributions of various authors, hardworking and professional reviewers, and dedicated editorial team of applied Sciences. Congratulations to all authors. I would like to take this opportunity to show my sincere gratefulness to all reviewers. Finally, I like to express my gratitude to the editorial team of Applied Sciences that make this work possible.

**Conflicts of Interest:** The author declares no conflict of interest.

#### **References**


**2. Mathematical Formulation**

Consider the magnetohydrodynamic flow of an electrically conducting viscous fluid through the gap between two coaxial tubes. It is assumed that a uniform magnetic field *B*0 is applied transversely to the flow. Further, considering that the magnetic Reynolds number is small, the induced magnetic field is negligible. A schematic diagram of the geometry of the problem under consideration is shown in Figure 1.

**Figure 1.** Effects of an endoscope on peristaltic motion.

The geometry of the wall surface is described as

$$
\overline{R}\_1 = a\_1 \tag{1}
$$

$$
\overline{R}\_2 = a\_2 + b \cos \frac{2\pi}{\lambda} (\overline{Z} - c\overline{t}) \tag{2}
$$

where *a*1, and *a*2 are the radii of the inner and the outer tubes, respectively; *b* is the amplitude of the wave; λ is the wavelength; *c* is the propagation velocity; and *t* is the time.

In the laboratory frame (*R*, *Z*), the flow is unsteady, but, by introducing a wave frame (*r* , *z*) moving with velocity *c* away from the fixed frame, the flow can be treated as steady [10]. The coordinate frames are related by the transformations.

$$
\overline{z} = \overline{Z} - c\overline{t}, \; \overline{r} = \overline{R}, \; \overline{w} = \overline{\mathcal{W}} - c, \; \overline{u} = \overline{\mathcal{U}} \tag{3}
$$

where (*u*, *w*) and -*U*, *W* are the velocity components in radial and axial directions in moving and fixed coordinates, respectively. Using the transformations (3), the equations that govern the flow are

$$
\frac{\partial \overline{u}}{\partial \overline{r}} + \frac{\partial \overline{w}}{\partial \overline{z}} + \frac{\overline{u}}{\overline{r}} = 0 \tag{4}
$$

$$\begin{split} \rho \left[ \overline{u} \frac{\partial \overline{u}}{\partial r} + \overline{w} \frac{\partial \overline{u}}{\partial \overline{z}} \right] &= \quad -\frac{\partial \overline{p}}{\partial \overline{r}} + \frac{\partial}{\partial \overline{r}} \Big( 2\mu (\overline{r}) \left. \frac{\partial \overline{u}}{\partial \overline{r}} \right) \\ &+ \frac{2\mu (\overline{r})}{\overline{r}} \Big[ \frac{\partial \overline{u}}{\partial \overline{r}} - \frac{\overline{u}}{\overline{r}} \Big] \\ &+ \frac{\partial}{\partial \overline{z}} \Big( \mu (\overline{r}) \left( \frac{\partial \overline{u}}{\partial \overline{z}} + \frac{\partial \overline{w}}{\partial \overline{r}} \right) \Big) \end{split} \tag{5}$$

$$\begin{split} \partial \left[ \overline{u} \frac{\partial \overline{u}}{\partial \overline{\tau}} + \overline{w} \frac{\partial \overline{w}}{\partial \overline{z}} \right] &= \begin{split} -\frac{\partial \overline{p}}{\partial \overline{z}} + \frac{\partial}{\partial \overline{z}} \Big( 2\mu (\overline{r}) \frac{\partial \overline{w}}{\partial \overline{z}} \Big) \\ + \frac{1}{\overline{r}} \frac{\partial}{\partial \overline{r}} \Big( \overline{r} \mu (\overline{r}) \left( \frac{\partial \overline{u}}{\partial \overline{z}} + \frac{\partial \overline{w}}{\partial \overline{r}} \right) \Big) \\ - \sigma B\_0^2 (\overline{w} + c) \end{split} \tag{6}$$

where *u* and *w* are the velocity components in the *r* and *z* directions, respectively; ρ is the density; σ is the electrically conductivity of the fluid; and μ is the variable viscosity. The governing equations can be dimensionalized by the following non-dimensional parameters.

$$\begin{aligned} r &= \frac{\overline{r}}{a\_2}, z = \frac{\overline{z}}{\overline{\lambda}}, w = \frac{\overline{w}}{c}, u = \frac{\lambda \overline{u}}{a\_2 c}, p = \frac{a\_2^2 \overline{p}}{\lambda c \mu}, r\_1 = \frac{\overline{r}\_1}{a\_2}, \ \delta = \frac{a\_2}{\lambda} \\\ r\_2 &= \frac{\overline{r}\_2}{a\_2} = 1 + \varphi \cos(2\pi z), \ Re = \frac{\rho c a\_2}{\mu}, M = \sqrt{\frac{\underline{a}}{\mu}} B\_0 a\_2 \end{aligned} \tag{7}$$

where φ is the amplitude ratio, Re is the Reynolds number, δ is the dimensionless wave number, and *M* is the magnetic parameter.

Using the above non-dimensional parameters in Equations (4)–(6), the following system of equations is obtained.

$$\frac{1}{r}\frac{\partial (ru)}{\partial r} + \frac{\partial w}{\partial z} = 0 \tag{8}$$

$$\begin{split} \text{Re}\delta^3 \Big[ u \frac{\partial \boldsymbol{u}}{\partial t} + \boldsymbol{w} \frac{\partial \boldsymbol{u}}{\partial z} \Big] &= \quad -\frac{\partial p}{\partial r} + \boldsymbol{\delta^2} \frac{\partial}{\partial r} \Big( 2\mu(r) \left. \frac{\partial \boldsymbol{u}}{\partial r} \right|\_{} + \boldsymbol{\delta^2} \Big( \frac{2\mu(r)}{r} \left( \frac{\partial \boldsymbol{u}}{\partial r} - \frac{\boldsymbol{u}}{r} \right) \Big) \\ &\quad + \boldsymbol{\delta^2} \Big( \frac{\partial}{\partial z} \Big( \mu(r) \left( \frac{\partial \boldsymbol{u}}{\partial z} \boldsymbol{\delta^2} + \frac{\partial \boldsymbol{w}}{\partial r} \right) \Big) \Big) \end{split} \tag{9}$$

$$\begin{split} \delta \text{Re} \Big[ \mu \frac{\partial w}{\partial r} + w \frac{\partial w}{\partial z} \Big] &= -\frac{\partial p}{\partial z} + \delta^2 \frac{\partial}{\partial z} \Big( 2\mu(r) \left. \frac{\partial w}{\partial z} \right| \\ &+ \frac{1}{r} \frac{\partial}{\partial r} \Big( r\mu(r) \left( \frac{\partial \mu}{\partial z} \delta^2 + \frac{\partial w}{\partial r} \right) \Big) - M^2 w \end{split} \tag{10}$$

Using the long wavelength approximation and dropping terms of order δ and higher, the above equations reduce to

$$\frac{\partial p}{\partial r} = 0\tag{11}$$

$$\frac{1}{r}\frac{\partial}{\partial r}\Big(r\mu(r)\Big.\frac{\partial w}{\partial r}\Big)=\frac{\partial p}{\partial z}+M^2w\tag{12}$$

The relevant boundary conditions in new parameters are

$$\begin{cases} w = -1 & at \quad r = r\_1 \\ w = -1 & at \quad r = r\_2 \end{cases} \tag{13}$$


**11. Marine sponges-derived antifouling and antibiofilm compounds**

Bacterial biofilms are surface-attached microorganism's communities that are protected by an extracellular matrix of biomolecules. Continuous use of chemical antifoulants resulted in increased tributyltin concentration and created extensive pollution problems in marine organisms. Natural antifouling molecules from marine have been recently reviewed and researches hope that will provide more specific and less toxic antifouling activity in future. Antifouling compounds derived from sponges were found to be very effective, environmentally friendly biocides and less toxic [205]. In the last few years several studies were directed to find the most promising alternative technologies to antifouling in marine organisms, especially from sponges. In a recent study structurally different compounds containing 3-alkylpyridine moiety were evaluated for antifouling potential. The compounds, namely haminols, saraine and 3-alkylpyridinium salts extracted from *Reniera sarai, Haliclona* sp. and the mollusk *Haminoea fusar* is obtained by synthesis, showed very good antifouling potential larvae of the barnacle *Amphibalanus amphitrite*. Bromopyrrole or diterpene alkaloids derivatives isolated from *Agelas linnaei* and *Ageles nakamurai* Indonesian marine sponges exhibited cytotoxic activity. Moreover, agelasine derivatives inhibited settling of larvae of *Balanus improvisus* in an antifouling bioassay as well as the growth of planktonic forms of biofilm forming bacteria *S. epidermidis* [206].

### **12. Conclusion**

Marine invertebrates (Porifera, Cnidaria, Mollusca, Arthropoda, Echinodermata, etc.) are considered as one of the major groups of biological organisms which gave huge number of natural products and secondary metabolites with interesting pharmacological properties and led in the formation of novel drugs. Among marine invertebrates, marine sponges (phylum: Porifera) is the most dominant responsible group for discovering significant number of natural components, which has been used as template to develop therapeutic drugs. These natural products possesses vast range of therapeutic application, including antimicrobial, antihypertensive, antioxidant, anticancer, anticoagulant, anti-inflammatory, immune modulator, and wound healing and other medicinal effects. Therefore, marine sponges are considered a rich source of chemical diversity and health benefits for developing drug candidates, nutritional supplements, cosmetics, and molecular probes that can be supported to increase the healthy life span of humans. In this chapter we included the most important and biologically active marine sponge-derived compounds and presented selected studies of most important bioactive and promising natural products and secondary metabolites from marine sponges.