Fungal diversity of marine biofilms on artificial reefs in the north-central Gulf of Mexico

Amy L. Salamone; Brent M. Robicheau; Allison K. Walker

doi:10.1515/bot-2016-0032

Article Publicly Available

Fungal diversity of marine biofilms on artificial reefs in the north-central Gulf of Mexico

Amy L. Salamone
Amy L. Salamone obtained her MS in Coastal Sciences from the University of Southern Mississippi’s Gulf Coast Research Laboratory in Ocean Springs, Mississippi, USA. She is currently a research technician at Weyerhaeuser Forest Pathology Lab in Centralia, Washington, USA.
, Brent M. Robicheau
Brent M. Robicheau has an MSc and a BScH in Biology from Acadia University. His fields of interest include the molecular characterization of fungi and mitochondrial genomes, the doubly uniparental inheritance of mitochondria in marine bivalves, and the evolution of ribosomal RNA genes in eukaryotes. He presently works as a laboratory manager and research assistant in the Department of Biology at Acadia University in Wolfville, Nova Scotia, Canada.
and Allison K. Walker
Allison K. Walker is an assistant professor in the Department of Biology at Acadia University in Nova Scotia, Canada, specializing in the ecology and taxonomy of intertidal fungi. She and her students employ traditional morphological as well as molecular phylogenetic and genomic approaches in the study of marine and coastal fungi. Ongoing collaborations include work in the Gulf of Mexico and northern temperate coastal ecosystems. In 2015, she was the recipient of the Martin-Baker Early Career Researcher Award from the Mycological Society of America.

Published/Copyright: September 17, 2016

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From the journal Botanica Marina Volume 59 Issue 5

Abstract

We present the first characterization of fungal community diversity of natural mixed-species biofilms on artificial marine reefs. Four artificial reefs in the Mississippi (MS) Sound, USA, representing low-profile (underwater) and high-profile (periodically air-exposed) conditions were sampled every 3 months over a 23-month period to investigate changes in fungal diversity within reef biofilms. Fungal presence was assessed via PCR amplification of the internal transcribed spacer (ITS) region of fungal ribosomal DNA, and by terminal restriction fragment length polymorphism (T-RFLP) analysis of fungal ITS regions – the latter being used to track variation in fungal community structure with respect to season, location, and reef profile type. Fungal communities were also characterized taxonomically through both morphological identification and phylogenetic comparisons of ITS gene sequences, with 36 fungal genera cultured from reef biofilms. Using a multivariate statistical approach, significant temporal and spatial differences in fungal biofilm communities were detected. High-profile reefs differed significantly in biofilm fungal community composition across the 10 sampling periods. This assessment of marine fungal biofilm communities over time provides novel insights into the fungal diversity present on artificial reefs in an understudied region, the north-central Gulf of Mexico.

Keywords: artificial reef; fungal biodiversity; Gulf of Mexico; marine biofilm; marine fungi

Introduction

The majority of the world’s population currently lives within 100 km of a coastline. Increased use of coastal habitats by human populations puts a growing pressure on marine ecosystems through destructive economic development, pollution, and over-exploitation of marine natural resources (Burt et al. 2009). As a remediation effort, “human-made” artificial reefs are increasingly promoted to alleviate the deleterious impacts of human activities on coastal ecosystems. Artificial reefs in coastal areas can increase fishing yields, amplify oyster habitats, contribute to shoreline stabilization, mitigate organic pollution, and enhance water quality (Pickering et al. 1999, Davis et al. 2002, Miller 2002). Artificial shoreline structures including reefs, seawalls, embankments, jetties, and piers have become widespread landscape elements in developed coastal regions around the world; however, their resulting ecological impacts remain under-studied (for examples of very recent discourse on the subject, see Ajemian et al. 2015, Mazzei and Biber 2015, Scott et al. 2015; also refer to Chapman and Bulleri 2003 for earlier work).

The present method for determining the success of an artificial reef as a functioning, sustainable ecosystem is to evaluate the fish assemblage inhabiting the reef by direct observation. Consequently, artificial reefs are often only evaluated once they have matured, despite microbial communities (fungi, bacteria, archaea, algae, and diatoms) forming complex biofilms on immersed surfaces in seawater almost immediately (Miao and Qian 2005). Proper management practices for maintaining artificial reefs require knowledge of the colonization of these habitats by marine microbes and their subsequent successional patterns. Properties of this initial biofilm formation can determine trophic relationships and the colonization and recruitment of other marine organisms (Callow and Callow 2006). Biofilm establishment on introduced substrate leads to settlement induction for many sessile invertebrates [e.g. barnacles, mussels (see Rahim et al. 2004, Burt et al. 2009, Granneman and Steele 2015)] which, over time, influence the diversity of a mature artificial reef’s fauna. Hladyz et al. (2011) reported that substrate composition is a crucial factor in marine biofilm development and later growth of the artificial reef; substrate differences revealed by stable isotope analysis have an effect on energy flow to primary consumers in aquatic food webs. Biofilm microbial communities are important in the production and decomposition of organic matter and in the cycling of limiting nutrients (Mouton et al. 2012).

Aquatic fungal communities in biofilms can be excellent candidates as bioindicators of ecosystem disturbance. Notably, the opportunistic strategy of fungal nutrition enables swift responses to changing conditions (Gutiérrez et al. 2011). Measures of species diversity and fungal biomass can be useful ecosystem indicators for reflecting the ecological health of a given habitat (Solé et al. 2008, González and Hanlin 2010).

Fungi are ubiquitous in the marine environment and certain species can thrive in even the harshest habitats (Solé et al. 2008). Fungi, including those found in association with artificial reefs, are an often overlooked component of marine ecosystems despite their potential to shed light on basal food web dynamics. Fungi may function as secondary producers, fuelling many of the primary consumers that support artificial reef habitats. Significant extracellular enzymatic hydrolysis has been reported in the marine environment at times when high levels of fungal carbon is present, suggesting that the current marine microbial loop model needs to reflect the role of fungi in organic matter processing (Gutiérrez et al. 2011). Despite evidence that fungi can colonize even extreme marine environments, such as deep-sea hydrothermal vents and hypersaline waters, their distribution, diversity, and ecological role in the sea remain poorly documented.

The objective of this study was to characterize fungal communities within marine biofilms on both periodically air-exposed and submerged artificial reefs in the Mississippi (MS) Sound (north-central Gulf of Mexico, USA), over a 23-month period. We studied artificial reefs created from multiple substrates and colonized by fastidious fauna. Fungal diversity in artificial reef biofilms was compared between two high- and two low-profile reefs, between longitudinal positions in the MS Sound, and among the four reefs sampled using multivariate statistics. For culturable fungi, only those species actively sporulating can be identified morphologically. Thus, we also included a molecular approach to characterize nucleic acids present in all stages of the fungal lifecycle, facilitating detection and identification of species that are difficult to culture or identify morphologically. This study presents the first report of natural mixed-species fungal biofilm communities from in situ artificial reef substrates in the marine environment.

Materials and methods

Substrate collection

Sampling of artificial reef biofilms began prior to the Deepwater Horizon oil spill, which occurred on April 20, 2010. Two high-profile and two low-profile artificial reefs were sampled in both the East and West MS Sound (Figure 1). Artificial reef substrate was collected, beginning in September 2009, at both high-profile artificial reefs (Katrina Key, Square Handkerchief Key). Sampling at the low-profile artificial reef, USM Reef, began in November 2010, while Legacy Towers Reef sampling began in March 2011. Subsequent sampling dates for Katrina Key Reef and Square Handkerchief Key were October and November 2009, January, March, April, September, and November 2010, and March and July 2011. Sampling dates for the low-profile artificial reef, USM Reef, were November 2010, and March and July 2011. Sampling dates for Legacy Towers Reef were March and July 2011. For each sampling date, substrate samples were taken at the same three subsites on each artificial reef. Subsites were chosen to include the newest rock comprising the reef. Substrate was collected using 4.23-m oyster tongs, placed in sterile zippered plastic bags for storage on ice, and transported back to the laboratory. The number of sample substrates collected at each sampling event ranged from four to eight, depending on size and visual estimates of biofilm.

Figure 1:

Location of artificial reef sites along the Mississippi Gulf Coast, USA: (K) Katrina Key Reef, high-profile, limestone rock, established August 17, 2009; (L) Legacy Towers Reef, low-profile, limestone rock, replenished in 2007; (U) USM Reef, low-profile, mixed oyster shells and limestone rubble, replenished in 2009; (H) Square Handkerchief Key Reef, high-profile, crushed concrete, established July 9, 2009.

Biofilm collection

Biofilm collection techniques were based on the methods of Lyautey et al. (2005). Upon returning to the laboratory, the rocks were placed in labelled sterile plastic containers according to sample site with 100 ml sterile distilled water. Biofilm was removed by brushing the rocks in sterile plastic containers with a sterile toothbrush to loosen any firmly attached material. Once the water was saturated with biofilm, it was filtered to remove sand, invertebrates, and other flotsam that was also attached to the rocks by pouring through a 500-μm mesh sieve over a funnel and into two 50-ml conical tubes. The biofilm was then allowed to settle overnight in a 4°C incubator. Excess water was then poured off and the biofilm was pipetted into two 2-ml collection tubes. The 2-ml tubes were then centrifuged at 16,708×g and liquid was decanted. One tube of biofilm was stored at 4°C for culturing and morphological identification of fungi. The second biofilm pellet was stored at −20°C until bulk community DNA extraction was conducted.

Morphological identification of fungal isolates

Fungi from biofilm were isolated using traditional culture techniques from all samples of all reef sites. Biofilm was initially streaked onto antibiotic saltwater agar (ASWA) containing penicillin G and streptomycin (both Sigma-Aldrich, St. Louis, MO, USA) to inhibit bacterial growth and incubated at ambient temperature until mycelia were observed. Each morphologically distinct colony was subcultured onto potato dextrose agar (PDA) until axenic cultures were obtained. Axenic cultures were incubated at ambient temperature until reproductive structures were observed. Fungal structures were removed using a flame-sterilized needle and slide-mounted in lactophenol cotton blue. Identifications were made by observation of definitive reproductive structures using a Nikon Eclipse 80 microscope with Nomarski interference contrast optics (Nikon Instruments Inc., Melville, NY, USA). Dichotomous and pictorial keys (Malloch 1981, St-Germain and Summerbell 1996, Barnett and Hunter 1998) were used to make taxonomic identifications based on micromorphology.

Molecular identification of fungal isolates

Thirteen fungal isolates which were sterile after 4 weeks of incubation were subjected to ITS sequencing. Mycelia from each isolate were stored at −20°C in a 2-ml collection tube prior to DNA extraction with an Ultraclean Microbial DNA isolation kit (MoBio Laboratories, Inc., Carlsbad, CA, USA). The suggested protocol was followed with the exception of an initial digestion at 30°C for 4 h in a dry bath incubator with 200 U lyticase (Sigma-Aldrich, St. Louis, MO, USA), 300 μl Microbead solution (MoBio Laboratories, Inc., Carlsbad, CA, USA), and 35 μl solution MD1 (MoBio Laboratories, Inc., Carlsbad, CA, USA) followed by tissue homogenization with a micropestle (Thermo Fisher Scientific, Pittsburgh, PA, USA).

Ascomycete isolates were PCR-amplified with the primers ITS 1-F (5′ CTT GGT CAT TTA GAG GAA GTA A 3′; Gardes and Bruns 1993) and ITS 4-A (5′ CGC CGT TAC TGG GGC AAT CCC TG 3′; Larena et al. 1999). PCR conditions were as follows: initial denaturation at 95°C for 3 min, 35 cycles of denaturation at 95°C for 1 min, annealing at 52°C for 30 s, extension at 72°C for 1 min, followed by a final extension at 72°C for 10 min (Walker and Campbell 2010) in a Thermo Electron Px2 thermocycler (Thermo Electron Corp., Waltham, MA, USA) and a Peltier Thermal Cycler PTC-100 (Bio-Rad Laboratories, Hercules, CA, USA). Non-ascomycete isolates were amplified with the primer pair ITS 1-F and ITS 4 (5′ TCC TCC GCT TAT TGA TAT GC 3′; White et al. 1990) and the following PCR parameters: initial denaturation at 94°C for 2 min, 34 cycles of denaturation at 94°C for 1 min, annealing at 51°C for 1 min, extension at 72°C for 2 min, followed by a final extension at 72°C for 8 min (Robinson et al. 2009). In both instances, the universal forward-sequencing tail M13 (−40) (5′ GTT TTC CCA GTC ACG AC 3′) was attached to primer ITS 1-F. Sequences were obtained from the University of Illinois Core Sequencing Facility (Urbana-Champaign, IL, USA) or Beckman Coulter Genomics (Danvers, MA, USA), using Applied Biosystems 3730xl DNA analyzers (Applied Biosystems, Foster City, CA, USA).

Molecular identification of ITS sequences of the fungal isolates was calculated using a >98% pairwise identity (PI) threshold; as a preliminary test, ITS sequences were first aligned (using BLAST; Altschul et al. 1997) to NCBI’s reference genomic sequences database refseq_genomic. In cases where there was no alignment meeting the >98% PI threshold, the alignment search was broadened to the NCBI nucleotide collection database (nr/nt). Candidate sequences that produced alignments with the highest pairwise identities and E-values to our unknown isolates were hypothesized to be members of the same species. If a >98% PI value could not be obtained, sequences with the next highest PI values were used. To further test that our preliminary identifications (based on pairwise identities and E-values alone) were correct, a dendrogram with 500 bootstrap replicates was constructed using MEGA6 (Tamura et al. 2007) upon building an alignment of the highest NCBI matches using CLUSTAL Omega (McWilliam et al. 2013). Additionally, because we were not concerned with resolving evolutionary relationships beyond species-specific clades – but rather wanted to test the statistical validity of the pairwise identities – our substitution model parameters chosen were p-distance (number of nucleotide differences divided by total number of nucleotides compared) and the Jukes-Cantor model (equal substitution rate for all nucleotides), as these should reflect the PI calculation in BLAST (Tamura et al. 2007). We also assumed uniform rates among sites and used pairwise deletion to account for large interspecific ITS sequence differences. Thus, our species identifications based on ITS (the accepted species-level barcode region for fungi; see Schoch et al. 2012) rDNA data took into account PI and phylogenetic tree data.

Optimization of DNA extraction from biofilms in preparation for T-RFLP analyses

Biofilms are mainly composed of extracellular polymeric substances (EPS), which contain polysaccharides, proteins, salts, and humic substances (Callow and Callow 2006). Consequently, microbes within a biofilm are often difficult to lyse and the nucleic acids, once purified, may still contain inhibitory substances. Furthermore, the fungal cell wall structure is highly complex, consisting of thick layers of chitin, β-glucans, lipids, and peptides. A series of comparisons was required to determine the optimal extraction technique for fungal biofilm community DNA. Based on methods described by Karakousis et al. (2006), four factors were compared: (i) lyticase (Sigma-Aldrich, St. Louis, MO, USA) concentration: 200 U (Campbell et al. 2009) and 400 U (Karakousis et al. 2006); (ii) digestion buffer type: sorbitol buffer (Griffiths et al. 2006) and MoBio-supplied extraction kit buffer; (iii) initial digestion time: 4 h (Campbell et al. 2009) and overnight (Karakousis et al. 2006); and (iv) extraction kit: UltraClean Microbial DNA Extraction kit and PowerBiofilm DNA Extraction kit (MoBio Laboratories, Inc., Carlsbad, CA, USA). For this study, these comparisons revealed that digestion with 200 U lyticase in MoBio PowerBiofilm buffers BF1 and BF2 for 4 h at 30°C in a dry bath incubator, then physical disruption with a tissue homogenizer and micropestle, followed by extraction with MoBio PowerBiofilm DNA Extraction kit produced the greatest yield of DNA for downstream reactions. To standardize the biofilm samples, 0.25 ml of the biofilm pellet was used for each DNA extraction from each sample site.

Isolation, PCR amplification, and HaeIII digestion of total fungal community DNA

Fungal biofilm community structure was analyzed using terminal-restriction fragment length polymorphism of the fungal ITS region (ITS T-RFLP). ITS rDNA was PCR-amplified in triplicate reactions for each sample using the fungal primers ITS 1-F (Gardes and Bruns 1993) and ITS 4-A (Larena et al. 1999) – as most fungi reported from marine environments belong to the phylum Ascomycota (Shearer et al. 2007) – with ITS 1-F labelled on the 5′ end with the fluorescent dye FAM (6-carboxyfluorescein) and PCR conditions as previously stated. All PCR products were combined and purified using a QIAquick PCR purification kit (Qiagen, Valencia, CA, USA). DNA purity and concentration were assessed using a NanoDrop ND-1000 spectrophotometer (Nanodrop Products, Wilmington, DE, USA). Each sample was then subjected to a restriction digest in a 1.5-ml microcentrifuge tube using the enzyme HaeIII (Roche Applied Science, Indianapolis, IN, USA). The digest reaction contained 100 ng purified PCR product, 1 μl (10 U μl⁻¹) HaeIII enzyme, 1 μl SuRE/Cut Buffer M (10 X) (Roche, available from Sigma-Aldrich), and ddH₂O to equal a 10 μl total volume. Restriction digest reactions were incubated at 37°C for 3 h in a dry bath incubator. Fragment samples were stored at −20°C before being sent to the University of Illinois Core Sequencing Facility (Urbana-Champaign, IL, USA) for analysis using an Applied Biosystems 3730xl DNA analyzer (Applied Biosystems, Foster City, CA, USA).

Data analysis

The cleavage site for HaeIII is located between the second and third bases of the 5′…GG↓CC...3′ nucleotide sequence. The use of the T-RFLP technique yields only one fluorescently labelled T-RF per species, and T-RF size is quantified by capillary gel electrophoresis. Phylotype richness (a conservative proxy for species richness) for each sampling site can then be quantified by the number of T-RFs in a fungal community profile (Walker and Campbell 2010).

T-RFLP chromatograms were retrieved from GeneMapper Version 3.7 software (Applied Biosystems, Foster City, CA, USA) and exported as Microsoft Excel comma separated values files (.csv) for each sample site. The .csv files were converted to text documents (.txt) and analyzed using R statistical computational software (R Core Team 2010) and the R-script T-RFLP analysis algorithm (Abdo et al. 2006). These routines removed artifact peaks by normalizing the peak values, calculating the standard deviation while assuming that the true mean was equal to 0, and identifying peaks that had values larger than 3 standard deviations. These steps were repeated until no peaks exceeded 3 standard deviations, and then a data matrix was created including only the identified T-RF peaks (Abdo et al. 2006). The software program Paleontological Statistics (PAST) was used to convert the R-generated data matrix into a Microsoft Excel-compatible file (Hammer et al. 2001). We used peak height in T-RFLP profiles as a proxy for the relative abundance of fungal taxa represented by each restriction fragment (Walker and Campbell 2010). In Microsoft Excel, a matrix was generated for every sampling period that accounted for each T-RF and their original.csv file peak height values, or “abundance proxy”. These matrices were then combined to form a complete data set detailing the relative abundances for each T-RF per site. Peaks were assumed to be uninformative and were removed from subsequent analysis if they occurred in <3 profiles (Stepanauskas et al. 2003).

Plymouth Routines in Multivariate Ecological Research software (PRIMER 6, PRIMER-E Ltd, Plymouth, UK) was used to perform community analyses. Bray-Curtis similarity matrices were generated for aggregated reef site T-RF data and for reef profile comparison T-RF data. Prior to calculation, T-RF data were log (x+1) transformed to normalize the concentration data. Nonmetric multidimensional scaling (NMDS) was used to explore the relationships between samples for each time period. Ordination patterns were clarified with overlaid groupings determined through hierarchical cluster analysis of the same similarity data. Analysis of similarity (ANOSIM) tests were performed to elucidate statistically significant fungal T-RF community differences between groups with respect to factors such as sampling time, reef profile, and reef location in the MS Sound. If the ANOSIM test statistic R is centred on 0, it indicates no differences among the groups. As R approaches 1 or −1, the null hypothesis is rejected, indicating a significant difference among groups (Clarke and Gorley 2006). The similarity percentages (SIMPER) routine was applied to decipher percentage contributions from each T-RF to the similarity and dissimilarity of each reef in relation to the others. The trend correlation procedure BEST in PRIMER 6 was used to find any matches between the among-sample patterns of the T-RF communities and any patterns from the abiotic variables associated with those samples. Diversity indices were calculated using the DIVERSE module of PRIMER 6.

The Linear mixed model procedure in SPSS (v. 18.0) (SPSS, Inc., Chicago, IL, USA) was used to examine differences between high-profile reef fungal T-RF communities over time and fungal diversity changes over time, as conveyed by scores for the first two NMDS axes, as well as by fungal diversity as conveyed by the Shannon-Wiener diversity index of T-RF data. The linear mixed model included time as a repeated measure, and also included terms for reef (Handkerchief vs. Katrina) and the interaction between reef and time. Both compound symmetry (CS) and first-order autoregressive (AR1) covariance structures were considered, and the simpler CS covariance structure was used for interpretations. The selection of covariance structure was based on the lower Akaike’s information criterion.

Results

Morphological and molecular identification of fungal isolates

A total of 295 fungal isolates, representing 36 fungal genera, were cultured from the artificial reef biofilm samples over the 23-month sampling period and were identified using morphological techniques (for all sporulating isolates as possible) and ITS gene sequencing (of 13 sterile isolates) (Table 1). The most common culturable fungal genera isolated from the marine biofilms during this study included Aspergillus (Figure 2A), Aureobasidium (Figure 2D), Cladosporium (Figure 2B), Penicillium (Figure 2C), and Trichoderma (Figure 2E). Thirteen of the fungal isolates obtained did not sporulate under laboratory conditions; ITS gene sequencing and phylogenetic analysis aided in species-level identifications of these isolates (Figure 3; Table 2). ITS sequences generated during this study were deposited in NCBI GenBank under the accession numbers KJ170301– KJ170313. Known ecology for the fungi identified through ITS rDNA sequencing is also given in Table 2.

Table 1:

Fungal genera isolated from artificial reef marine biofilms, where n is the total number of isolates obtained from each reef.

Genus	Artificial reef (% occurrence)
	High-profile		Low-profile
	Katrina Reef (n=70)	Handkerchief Reef (n=89)	Legacy Towers Reef (n=23)	USM Reef (n=45)
Ascomycota
Acremonium	8.1%	1.1%	8.7%	2.2%
Alternaria	1.4%	–	–	–
Arthrinium	1.4%	–	–	–
Aspergillus	1.4%	6.4%	4.3%	8.9%
Aureobasidium	13.5%	7.7%	–	2.2%
Bipolaris	–	–	4.3%	2.2%
Cladosporium	13.5%	15.4%	4.4%	33.3%
Curvularia	–	–	13.0%	2.2%
Exophiala	–	1.1%	–	–
Fusarium	–	–	4.3%	2.2%
Nigrospora	–	1.1%	–	–
Ochroconis	1.4%	–	–	–
Paecilomyces	–	1.1%	–	–
Penicillium	30.4%	34.1%	30.5%	26.8%
Pestalotia	1.4%	–	–	–
Pestalotiopsis	1.4%	–	–	–
Phaeoacremonium	–	1.1%	–	–
Phoma	–	1.1%	–	–
Pithomyces	1.4%	1.1%	–	2.2%
Pseudozyma	1.4%	–	–	–
Scopulariopsis	1.4%	–	–	–
Sepedonium	–	2.2%	–	–
Stachylidium	–	1.1%	–	–
Talaromyces	–	1.1%	–	–
Trichoderma	12.2%	15.5%	17.5%	6.7%
Trichophyton	–	1.1%	–	–
Williopsis	–	1.1%	–	–
Basidiomycota
Tilletiopsis	1.4%	–	–	–
Trichosporon	1.4%	–	–	–
Zygomycota
Mortierella	2.7%	3.3%	–	4.5%
Mucor	2.8%	1.1%	4.4%	2.2%
Phycomyces	–	–	–	2.2%
Rhopalomyces	1.4%	–	4.3%	2.2%
Spiromyces	–	2.2%	4.3%	–

Figure 2:

Representatives of the most common culturable fungal genera isolated from marine biofilms on the artificial reefs during this study: (A) Aspergillus (400X) (B) Cladosporium (400X) (C) Penicillium (400X) (D) Aureobasidium (400X) (E) Trichoderma (160X).

Figure 3:

Phylogenetic analyses of ITS rDNA sequences of cultured isolates from marine biofilms. Maximum parsimony trees are shown; maximum likelihood and neighbor-joining phylogenetic reconstruction methods resolved the same species-specific clades. Isolates collected in this study are indicated in blue. NCBI GenBank sequences with the highest E value and pairwise identity (PI) match to sequenced isolates are indicated in black. Black numbers next to nodes represent bootstrap values for 500 replicates, while red numbers to the right of the sample names are the PI reported during NCBI BLAST alignments. (A) Ascomycota (B) Basidiomycota (C) Zygomycota.

Table 2:

ITS rDNA sequence identifications of selected sterile marine biofilm fungal isolates and literature references. Reef site codes: K=Katrina; H=Handkerchief.

Isolate no.[Site]	Identification [GenBank accession]	Literature reference
1 [K]	Letendraea helminthicola [KJ170301]	Known parasite of some large species of Helminthosporium (e.g. Helminthosporium dematiaceous)¹
2 [K]	Malassezia restricta [KJ170302]	Nematodes Malenchus sp. and Tylolaimophorus typicus known as hosts³; found on human cutaneous surfaces²
3 [H]	Barnettozyma californica [KJ170303]	Found on apple, pear, and plum blossoms⁴; assumed to be transported by Drosophila and also present in soil^5,6
4 [K]	Rhodotorula mucilaginosa [KJ170304]	Red yeast previously isolated from lakes and ponds of Patagonia; many strains produce carotenoids⁷
5 [K]	Rhodotorula aurantiaca [KJ170305]	Psychrophilic yeast; known from Antarctic ice⁸
6 [H]	Exophiala heteromorpha [KJ170306]	Black yeast known from high-altitude oak and concrete railway ties in Turkey, also a rare opportunist in humans⁹
7 [K]	Humicola phialophoroides [KJ170307]	Known from soil of southern Taiwan¹⁰, Humicola spp. are often obtained from plant litter¹¹
8 [K]	Pseudozyma aphidis [KJ170308]	A soil fungus¹² first isolated from aphid secretions¹³
9 [H]	Purpureocillium lilacinum [KJ170309]	Common saprobe known from soils, insects, nematodes, and humans¹⁴
10 [H]	Trichoderma harzianum [KJ170310]	Soil fungus, known antagonist of the plant pathogens Sclerotium rolfsii and Rhizoctonia solani¹⁵
11 [H]	Aureobasidium pullulans [KJ170311]	Widespread saprophyte¹⁶, often found on crops¹⁷; can occur as endophyte (e.g. in sweet cherries¹⁸)
12 [H]	Acremonium alternatum [KJ170312]	Known to reduce Podosphaera xanthii infections in cucumber¹⁹; also recovered as an endophyte of mangrove Rhizophora mucronata occurring at high-tide levels along the west coast of India²⁰
13 [K]	Mucor moelleri [KJ170313]	N₂O-producing soil fungus²¹, known as root endophyte of flooded oak trees (Quercus robur) in Poland²²

¹Berkeley and Broome, 1859; ²Sugita et al., 2004; ³Renker et al., 2003; ⁴Vadkertiová et al., 2012; ⁵Morais et al., 2006; ⁶Kurtzman, 2011; ⁷Libkind et al., 2004; ⁸Sabri et al., 2001; ⁹Döğen et al., 2013; ¹⁰Ko et al., 2011; ¹¹Estrada-Medina et al., 2016; ¹²Rau et al., 2005; ¹³Rau et al., 2004; ¹⁴Luangsa-ard et al., 2011; ¹⁵Elad et al., 1980; ¹⁶Schena et al., 2003; ¹⁷Deshpande et al., 1992; ¹⁸Schena et al. 2000; ¹⁹Kasselaki et al., 2006; ²⁰Ananda and Sridhar, 2002; ²¹Jirout, 2015; ²²Kwaśna et al., 2016.

T-RFLP analysis

T-RFLP analysis revealed 203 species-level fungal phylotypes present in artificial reef biofilms, while traditional morphological methods detected 77 species-level phylotypes. Seventy-two ITS T-RFLP chromatograms were generated during this study, one for each of the three subsites sampled per reef per sampling period. An ANOSIM performed on the Bray-Curtis similarity matrix of all T-RF data from all the reef subsites at all the sampling time periods revealed a between-reef R=0.573 with p<0.001 and a between-time R=0.959 with p<0.001. A two-way crossed ANOSIM performed on the same Bray-Curtis similarity matrix revealed a between-longitudinal R=0.483 with p<0.001 and a between-time R=0.939 with p<0.001. Cluster analyses and NMDS were used to help elucidate 2-D NMDS (stress 0.19) T-RF patterns from all reef subsites at all sampling time periods (Figure 4). NMDS plots depicted fungal T-RF community similarity patterns that occurred with sampling time periods and patterns shown by individual reefs and longitudinal positions in the MS Sound. Relationships between abiotic variables and fungal T-RF composition revealed a correlation statistic Rho=0.292 for the temporal variable with p<0.007, indicating that time was the only abiotic variable contributing to observed community differences.

Figure 4:

NMDS cluster visualization of the Bray-Curtis similarity index of all the reefs for all the sampling time periods. Similarity groups show differences in artificial reef fungal biofilm community T-RF patterns with time; fungal biofilm communities do vary among reef sites [Handkerchief (H), Katrina (K), Legacy (L), USM (U)] at each sampling period (01–10).

To compare fungal biofilm communities between low-profile and high-profile reefs, T-RFLP data from every reef subsite was examined for three sampling periods between November 2010 and July 2011. T-RF abundances were log (x+1) transformed prior to calculation of the Bray-Curtis similarity matrix. A cluster analysis overlay on the NMDS plot (stress=0.09) revealed T-RF distributional patterns between high and low profiles (Figure 5). A two-way crossed ANOSIM on this Bray-Curtis analysis matrix showed significant between-time (R=0.889, p<0.001), between-reef (R=0.517, p<0.001), and between-profile differences (R=0.167, p<0.019).

Figure 5:

NMDS cluster overlay of Bray-Curtis similarity matrix of all reefs [Handkerchief (H), Katrina (K), Legacy (L), USM (U)] labelled by reef profile and sampling date [Nov. 2010 (08), March 2011 (09), July 2011 (10)].

More sampling events for the high-profile reefs (Katrina and Handkerchief) than for the low-profile reefs (USM and Legacy) allowed more intensive temporal comparisons of the two high-profile reefs. For Katrina and Handkerchief reefs only, linear mixed model type III tests of fixed effects with the dependent variable NMDS1 (Bray-Curtis index) yielded a significant time difference (p<0.001) as well as a significant reef effect (p<0.005). A similar analysis with the dependent variable NMDS2 (Bray-Curtis index) showed a significant between-reef difference (p<0.006), a significant time difference (p<0.001), and a significant reef-with-time interaction (p<0.001) (Figure 5). Application of the SIMPER routine was, therefore, valid, as statistical differences in fungal communities did exist between the two reefs. The SIMPER routine revealed individual T-RFs contributing the most to the dissimilarity between Katrina and Handkerchief reefs (Table 3).

Table 3:

Ten ITS T-RF lengths contributing most to fungal community dissimilarity between Katrina and Handkerchief Reefs based on SIMPER analysis.

T-RF length (bp)	Average abundance		Average dissimilarity (%)	% Contribution
T-RF length (bp)	Katrina	Handkerchief	Average dissimilarity (%)	% Contribution
298	5.66	1.62	2.01	3.99
474	2.34	3.42	1.75	3.46
84	3.01	4.07	1.47	2.91
56	7.22	5.6	1.39	2.74
135	2.34	2.14	1.32	2.61
390	0	2.52	1.29	2.56
57	2.93	4.32	1.26	2.49
120	0.22	2.85	1.08	2.14
108	2.65	4.71	0.94	1.86
186	0.61	2.15	0.92	1.83

Phylotype richness and Shannon diversity were calculated for T-RF data using the DIVERSE module of PRIMER 6 for Katrina and Handkerchief reefs over all the time periods and for all four reefs for the three sampling events between November 2010 and July 2011. Shannon diversity varied greatly among all four reefs, and even among the reef subsites. However, in July 2011, all four reefs had an average diversity index between 2 and 2.2. In SPSS, linear mixed model type III ANOVA of fixed effects for the dependent variable, diversity, and using the CS covariance structure showed significant shifting diversity among sample times (p<0.001). The same analysis with phylotype richness as the dependent variable revealed significant variation among sampling times (p<0.001) and a divergence between reefs with time (p<0.001). The phylotype richness contrast between Katrina and Handkerchief reefs showed an increasing trend until the last sampling period, with Handkerchief almost always exhibiting higher richness than Katrina, and both reefs gradually increased in fungal diversity with time (Figure 6).

Figure 6:

Shannon diversity index values for low-profile and high-profile reefs (A) and for Handkerchief and Katrina reefs (B). Phylotype richness values for Handkerchief and Katrina reefs are given in (C).

In summary, significant temporal differences were found among fungal biofilm communities when comparing all four artificial reefs across all the ten sampling events. Longitudinal differences in fungal communities were observed between reefs in the West MS Sound (Handkerchief and USM) and those in the East MS Sound (Katrina and Legacy). No statistically significant difference in fungal communities was detected between high- and low-profile reef types (i.e. different reef substrate types). The two high-profile reefs, Handkerchief and Katrina, differed significantly in fungal biofilm community composition between reefs across the 10 sampling periods.

Discussion

All of the culturable fungi we isolated from the MS artificial reef biofilms belong to genera classified as facultative marine genera, as defined by Kohlmeyer (1974): “those from freshwater or terrestrial milieus able to grow (and possibly also to sporulate) in the marine environment”. Five genera of zygomycetes, five genera of basidiomycetes, and 26 genera of ascomycetes were cultured from the artificial reef marine biofilms during this study.

Temporal variation represented the predominant detectable effect on fungal biofilm communities during this 23-month study. Temporal variation can significantly influence the total number of species and biomass present in an artificial reef habitat (Bohnsack et al. 1994). In the MS Sound, stratification can change dramatically within a day in some areas (Vinogradov et al. 2004). Within well-mixed waters, elevated vertical salinity gradients can develop within a few hours and can also vanish within a short time due to tidal currents passing between the barrier islands (Vinogradov et al. 2004). Marine fungi can differ widely in their optimal growth conditions relative to temperature and salinity, but they are also considered to be highly adaptable to changing conditions (Ritchie 1959). This may explain why a statistical difference was found in overall temporal variation of the fungal biofilm community, but no significant effect of temperature or salinity alone was detected.

Phylotype richness and diversity of the fungal biofilm community changed with time during this study. The average Shannon diversity at Handkerchief Reef was higher than at the other reefs for all the sampling times except September 2010. Shannon diversity showed a slight increasing trend for both high-profile reefs over time. During the November 2010 and March 2011 sampling events, Shannon diversity varied among all four reefs, and even among the reef subsites, but in July 2011, all four reefs had an average diversity index between 2 and 2.2. Phylotype richness increased at all four artificial reefs sampled, with the exception of the last sampling period (July 2011). As the fungal biofilm community matures, an interactive successional stage can occur, allowing new species to recruit while competition and changes in physical habitat may cause less well-adapted species to be lost from the community (Jackson 2003, Thompson et al. 2004).

Variations in substrate composition can have a substantial influence on the biofilm community and subsequent benthic assemblages (Rahim et al. 2004, Hladyz et al. 2011). Katrina Reef was composed of limestone, Handkerchief Reef was composed of crushed concrete bridge materials, Legacy Reef was made of limestone rubble, and USM Reef was composed of limestone rock and oyster shells. Considerable differences exist among each reef’s shellfish assemblages. Handkerchief Reef’s substrate had a noticeably thick layer of biofilm cover on the first sampling dates (September and October 2009, visual observation). Oyster growth was first observed beginning in November 2009 and persisted through subsequent sampling events, with the substrate completely covered with oysters by the March and July 2011 sampling events. In contrast, the Katrina, USM, and Legacy reef substrates did not exhibit oyster growth. Unique fungal phylotypes were identified at each site, and substrate type may be a contributing factor to the community differences observed, indicating that substrate may determine which species can grow at a particular site.

Significant differences were found in the fungal biofilm communities among all four artificial reefs with time throughout this study. Fungal community dissimilarity was explored between Handkerchief and Katrina reefs, which showed numerous variant T-RFs each contributing only a small percentage to the overall dissimilarity, suggesting that no one fungal phylotype was dominant. The actual determinants of fungal biofilm community structure are likely to include complex interactions among fungal and other microbial species, substrate availability, and nutrient concentration fluctuations (Hax and Golladay 1993, Gulis et al. 2006, Wargo and Hogan 2006).

Fungal communities in biofilm on artificial reefs were characterized using morphology and molecular tools to provide insight into baseline fungal species diversity present in the north-central Gulf of Mexico. Our multivariate statistical approach to assessing marine ascomycete diversity may inform the future development of artificial reefs and their management, fungal-bacterial interaction studies, and temporal, environmental, and anthropogenic coastal impact assessments. Our characterization of artificial reef fungal biofilm communities represents the first step towards understanding the fungal component of microbial diversity of hard substrata within the MS Sound, an economically productive estuary for fisheries including shellfish. Considering the increasing number of reports on the occurrence of marine fungi and their involvement in detrital processing, it can be concluded that the current microbial loop model neglects the role of fungi in the processing of organic matter in marine environments (Hyde et al. 1998, Singh et al. 2010, Gutiérrez et al. 2011, Mouton et al. 2012). Further research is needed to determine fungal roles in marine ecological processes in hopes of providing a more complete model of organic material degradation in coastal ecosystems, foundational to food webs and nutrient cycling (Gutiérrez et al. 2011, Mouton et al. 2012). Our approach has afforded the collection of baseline data to help improve the understanding of underlying fungal diversity present in artificial reef biofilms. This, in turn, will prove valuable for monitoring artificial reef biological communities in the early stages of colonization.

About the authors

Amy L. Salamone

Amy L. Salamone obtained her MS in Coastal Sciences from the University of Southern Mississippi’s Gulf Coast Research Laboratory in Ocean Springs, Mississippi, USA. She is currently a research technician at Weyerhaeuser Forest Pathology Lab in Centralia, Washington, USA.

Brent M. Robicheau

Brent M. Robicheau has an MSc and a BScH in Biology from Acadia University. His fields of interest include the molecular characterization of fungi and mitochondrial genomes, the doubly uniparental inheritance of mitochondria in marine bivalves, and the evolution of ribosomal RNA genes in eukaryotes. He presently works as a laboratory manager and research assistant in the Department of Biology at Acadia University in Wolfville, Nova Scotia, Canada.

Allison K. Walker

Allison K. Walker is an assistant professor in the Department of Biology at Acadia University in Nova Scotia, Canada, specializing in the ecology and taxonomy of intertidal fungi. She and her students employ traditional morphological as well as molecular phylogenetic and genomic approaches in the study of marine and coastal fungi. Ongoing collaborations include work in the Gulf of Mexico and northern temperate coastal ecosystems. In 2015, she was the recipient of the Martin-Baker Early Career Researcher Award from the Mycological Society of America.

Acknowledgments

The authors gratefully acknowledge J. Campbell, M.C. Aime, D.J. Grimes, C. Rakocinski, and K. Dillon for their assistance with this project. K. Lucas of the Mississippi Department of Marine Resources is thanked for assistance with maps. The Mississippi Department of Marine Resources provided field sampling and boat assistance. The authors are grateful to K. A. Seifert and anonymous reviewers for manuscript improvements. This research was supported by the Coastal Impact Assistance Program Grant # 16LFD37000402001GRO4084. A.K. Walker gratefully acknowledges a Myron P. Backus Graduate Fellowship from the Mycological Society of America.

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Received: 2016-4-19

Accepted: 2016-8-12

Published Online: 2016-9-17

Published in Print: 2016-10-1

Articles in the same Issue

https://doi.org/10.1515/bot-2016-0032

Keywords for this article

artificial reef; fungal biodiversity; Gulf of Mexico; marine biofilm; marine fungi