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Article

Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites

by
Hannah R. Flaherty
1,
Semra A. Aytur
2 and
John P. Bucci
2,3,*
1
Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
2
Department of Health Management and Policy, University of New Hampshire, Durham, NH 03824, USA
3
Marine Microverse Institute, Kittery, ME 03905, USA
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(11), 2076; https://doi.org/10.3390/jmse12112076
Submission received: 17 October 2024 / Revised: 9 November 2024 / Accepted: 12 November 2024 / Published: 17 November 2024
(This article belongs to the Special Issue Benthic Microbial Community in Marine and Coastal Environment)
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Abstract

:
Cancer remains a leading cause of death worldwide. Also threatening the public is the emergence of antibiotic resistance to existing medicines. Despite the challenge to produce viable natural products to market, there continues to be a need within public health to provide new chemotherapeutic drugs such as those exhibiting cytotoxicity and tumor cell growth-inhibitory properties. As marine genomic research advances, it is apparent that marine-derived sediment harbors uniquely potent bioactive compounds compared to their terrestrial counterparts. The Streptomyces genus in particular produces more than 30% of all secondary metabolites currently approved for human health, thus harboring unexplored reservoirs of chemotherapeutic and antibiotic agents to combat emerging disease. The present study identifies the presence of Streptomyces hygroscopicus and rapamycinicus in environmental sediment at locations within the U.S. Stellwagen Bank National Marine Sanctuary (SBNMS) from 2017 to 2022. Sequencing and bioinformatics methods catalogued biosynthetic gene clusters (BGCs) that drive cytotoxic and antibiotic biochemical processes in samples collected from sites permittable and protected to fishing activity. Poisson regression models confirmed that Sites 1 and 3 had significantly higher occurrences of rapamycinicus than other sites (p < 0.01). Poisson regression models confirmed that Sites 1, 2 and 3 had significantly higher occurrence for Streptomyces hygroscopicus across sites (p < 0.05). Interestingly, permitted fishing sites showed a greater prevalence of both species. Statistical analyses showed a significant difference in aligned hits with polyketide synthases (PKSs) and non-ribosomal peptide synthetases (NRPSs) by site and between species with hygroscopicus showing a greater quantity than rapamycinicus among Streptomyces spp. (p < 0.05; F = 4.7 > F crit).

1. Introduction

Cancer is a leading cause of death worldwide as more than eight million people die of different types each year [1]. This non-communicable disease is a significant societal, public health, and economic problem in the 21st century, responsible for almost one in four deaths worldwide [2]. Novel chemotherapeutics such as cytotoxic compounds that target DNA and RNA synthesis are needed for multiple types of cancer [3]. Equally concerning is the increasing public health threat to human health worldwide of antibiotic resistance [4]. The World Health Organization has called for a One Health, multidisciplinary approach to address this issue. Within marine microbiology disciplines, there remains a consistent need for the discovery of novel medicines associated with microorganisms that have demonstrated a new area of research dedicated to natural product discovery [5]. The aquatic environment’s unique biogeochemistry differs from terrestrial habitat and is home to a vast reservoir of undiscovered microbes harboring novel biosynthetic compounds. This study confirmed the presence of marine sediment-derived Streptomyces species, S. hygroscopicus, and rapamycin, in sediment samples collected multiple years from the Stellwagen Bank National Marine Sanctuary (SBNMS) located in the Gulf of Maine, Atlantic Ocean, USA. Preserving marine sanctuaries such as the SBNMS allows organisms in these environments to thrive and produce viable and diverse food webs. The present study provides a novel characterization of the relative abundance and quantification of biosynthetic gene clusters (BGCs), using bioinformatics algorithms to cross-reference the potential for cytotoxicity, including polyketide and NRP secondary metabolites that produce natural products, and those associated with the chemotherapeutic activity. This analysis builds on prior research by Heinrichs et al. (2020) [6], which used whole metagenome sequencing (WMS) to map the microbial communities of environmental sediment samples in similar locations from the SBNMS. Our work initiated the study on the secondary metabolite potential of relatively abundant Streptomyces within the sanctuary. This investigation underscores the importance of respecting these unique marine protected areas and promoting their preservation.
The Streptomyces genus has been considered a prolific producer of specialized natural products since the 1940s [7,8]. Within the family of Streptomycetes, more than 70% have shown efficacy as antibiotics (e.g., neomycin, streptomycin, erythromycin, and doxycycline) [9]. Streptomyces are ubiquitous, living in a wide range of environments with drastically different conditions, both terrestrial and marine. Natural products contain specialized primary and secondary metabolites, produced by Streptomyces spp. that yield a diversity of BGCs in the form of enzymatic activity and gene expression [10]. The Streptomyces linear genome consists of a high percentage of BGCs encoding the biosynthesis of antibiotics and secondary metabolites, such as polyketides, polyether, and NRPSs [11]. The current study focused on characterizing Streptomyces, recently discovered as an abundant genus in SBNMS samples according to prior research [6,12], a producer of anticancer drugs such as bleomycin, dactinomycin, mitomycin C, and doxorubicin.

Marine Derived Natural Products

A growing body of research demonstrates that marine-derived microbes in oceanic sediment have distinct genome structures compared to their terrestrial counterpart [13,14]. However, innovative techniques are needed to improve detectability of silent BGCs. Given the immensity of the marine environment, with oceans constituting more than 96% of the biosphere, numerous unexplored sediment surface regions have yet to be prospected. The unique marine environmental conditions compared to terrestrial systems have produced novel natural products not represented in terrestrial natural products [15]. Studies have shown micro-biosynthetic potential in sandy sediment using a combination of methods, including culturing, amplicon sequencing of keto synthase and adenylation domains within polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) genes [16]. Studies investigating prokaryotes continue to evaluate the potential for microbial production of bioactive compounds, including innovative culture-independent methods of environmental samples [17,18].
Marine-derived samples and pure culture strains containing Streptomyces spp. have shown cytotoxicity and antitumor activity due to NRPs/polyketide/polyether ionophore metabolite expression [19]. For example, cell cultures that produce medicinal compounds, such as salinispora A, a marine sediment bacterium, have been successfully isolated [15,20]. This strain yields a compound known as salinosporamide A; a potential anticancer agent to treat glioblastoma. Further investigation is needed to discover medicines for an array of cancer types produced within coastal shelves and deep-sea benthic environments [21]. Marine microbes from these habitats must withstand a harsh environment with an absence of light, low oxygen, and high-pressure conditions [22]. The adaptations developed by bacteria to withstand these conditions can prompt novel biochemical pathways (i.e., R-loops or RNA-DNA functions formed during transcription in the genome) that give rise to the production of distinct secondary metabolites unique to that environment compared to their terrestrial counterparts, adding value to human medicine [23,24].
The present study focused on categorizing sediment microbial communities and the degree to which they contain potential for natural products [12]. The purpose of this study was to confirm the presence of marine sediment-derived Streptomyces species including S. hygroscopicus and rapamycinicus collected from the Stellwagen Bank National Marine Sanctuary (SBNMS) in the Gulf of Maine, Atlantic Ocean, USA. Additional aims were to quantify metagenomic data using bioinformatics and to evaluate their antibiotic and chemotherapeutic potential as measured by the occurrence of polyketide and NRP secondary metabolites.

2. Materials and Methods

2.1. Sampling Sites and Sample Collection

The microbial source data analyzed in the present study were previously collected as sediment samples from the SBNMS, which is located approximately 15 km off the Cape Ann coastline within the Gulf of Maine, USA, under the permit #SBNMS-2017-005 [6]. The SBNMS benthic seafloor habitat supports a variety of fish and invertebrate species such as sand lance, Atlantic cod, haddock, cephalopods, crustaceans, and annelids [25].

2.2. Study Sites

Study sites were within regions of the SBNMS and designated as a part of the reauthorization of the National Marine Sanctuaries Act passed into law in 1992 and regulated by the National Oceanic and Atmospheric Administration (NOAA). It is a ‘working’ sanctuary, allowing commercial and recreational fishing. Sediment samples were collected seasonally during 2017–2019 from open and closed fishing sites (Table 1, Figure 1). Eleven sediment samples, one from each site, were analyzed. Samples were collected from the surficial layer (~20 cm) using a petite Van Veen grab (Ocean Instruments, Fall City, WA, USA) and 20 g was transferred to sterile 50 mL sterile Falcon® tubes (Thermo Scientific™ Inc., Waltham, MA, USA). The tubes were immediately placed on ice in a sealed container until being returned to the laboratory where they were stored frozen at −20 °C until molecular DNA analysis. Site selection was based on previous study mapping sediment type [26]. The sediment type was characterized as fine mud and silt (grain size 6–4 microns) to keep consistent substrates of microbial communities’ habitat. Confirmation was completed by particle sieve analysis and a collection similar procedure to Heinrichs et al. (2020) [6]. Analysis was completed at the time of collection. Sediment type classification was based on a Barnhardt scale (1_gravel, 2_sand_gravel, 3_sand_mud, 4_mud_sand) [27].

2.3. Cultured Isolates

Two marine media recipes were used to make solid agar and target growth of Streptomyces species from samples. During sediment collection, a 10-fold (10−1–10−7) serial dilution technique was used to inoculate 1.5 g of sediment sample to 10 mL of seawater and an additional series in deionized water for comparison. Immediately following inoculation, 50 uL of inoculant was spread onto the plates in quadrants for maximum growth. Prior to sediment collection, marine agar 2216 and International Streptomyces Project 4 (ISP4) media recipes were made to prepare solid agar plates for inoculation. For example, ISP4 was made with 37 g of this yeast malt recipe and 1 L of natural seawater. A separate series was made with deionized water then sterilized 121 °C for 15 min. Cultures were incubated to 10 to 14 days at room temperature (25 to 28 °C). Transfer and storage of cultures was completed following a modified isolate protocol [28]. This procedure was followed by inoculation and incubation of visually active colonies [29]. Colonies with densities of 2 to 8 were preserved in a suspension buffer at −20 °C until future sequencing.

2.4. DNA Extraction and Target Species Confirmation of Cultured Isolates

The present study focused on confirming the bioinformatics-predicted presence of Streptomyces species of colonies grown from culture isolates obtained from the sediment samples. According to the industry standards, DNA extraction and isolation procedures began with a lysate preparation for gram positive bacteria by transferring up to 1 mL of culture to a centrifuge tube and centrifuging at ~14,000 RPM for thirty seconds to pellet cells. The supernatant was poured off, avoiding the pellet, and 250 µL of resuspension solution was added to the pellet before the cells were resuspended by vortexing. The next step was to add 12 µL of lysozyme stock solution (400 ng/mL) and mix. Then, 250 µL of lysis buffer P and 12 µL of Proteinase K were added to the suspension and mixed well before being incubated at 37 °C for two hours. To bind to the column, 500 µL of solution buffer was added to the lysate and mixed well to obtain a homogenous mixture. Then, 500 µL of 96–100% ethanol was added shortly after. The spin column was assembled before applying 750 µL of the mixture and centrifuging at ~10k RPM for one minute. The entire lysate passed through the column, and the flow through was discarded. Once the spin column was reassembled, the mixture was applied to the column and centrifuged for one minute. The final step was the elution of the clean DNA. The spin column was assembled with a 1.7 mL elution tube before 200 µL of Elution Buffer B to the center of the column bed. The tube was then centrifuged at ~6000 RPM for one minute. A portion of the buffer passed through the column, allowing DNA hydration. The sample tube was centrifuged at 14,000 RPM for another two minutes to collect the total elution volume. The yield of DNA improved by 20–30% by pipetting the elution buffer back into the tube and repeating the process. Purified genomic DNA was stored 2–8 °C for up to 7 days and transferred to −20 °C for longer-term storage.
A Qubit® Fluorometer (Thermo Scientific™ Inc., USA) measured adequate sample DNA concentrations per isolated culture using the dsDNA Assay Kit. The standards ranged in concentration from 666.5 to 24.7 ng/mL. The sediment sample cultures were pooled to increase concentrations and ranged from 15 to 110 ng/mL. Sample thresholds were set to a concentration of 30 ng/mL. A species-specific, probe-based assay was modified from previous research [30], including a custom forward primer (F27): 5′-AGAGTTTGATCCTGGCTCAG-3′ and a reverse primer (RC_1492): 5′-TACGGCTACCTTGTTACGACTT-3′. Quantitative real-time (qPCR) was used to confirm Streptomyces species presence in cultured cell isolates from environmental sediment samples.

2.5. Bioinformatics Pipeline from Metagenomic Sequencing

The focus of the present study was on screening protein data produced from bioinformatics platforms to identify secondary metabolites and BGCs cross-referenced with chemotherapeutic properties (UniProt™, antiSMASH™) and based in part on previous analyses [31,32,33]. Researchers obtained metagenomic output files (FASTA) from whole genome, pair-end sequencings. Bioinformatics results from genome assembly and NCBI species identification were used to predict BGCs and characterize functional properties concerning chemotherapeutic molecular properties and secondary metabolites by the occurrence of Streptomyces hygroscopicus and rapamycinicus species [6,11]. These prior time-series assessments identified more than 5900 total species with 5% of Streptomyces species represented across 14 sampling sites. Researchers used the first replicate sample (forward and reverse paired reads) from all sites except Site 7 (2019). Using the program algorithms, the total number of metagenomic sequenced hits for all Streptomyces species was counted per site and collection year. Generalized linear models (SAS PROC GENMOD, SAS v9.4, Cary, NC, USA) were used to assess whether counts of Streptomyces hygroscopicus and rapamycinicus differed by sampling site. Models utilized a Poisson distribution with a log link function [34].

2.6. Screening Database I

The database I result provides functional metabolic information for each aligned sequence, using UniProt™ for gene function prediction concerning antibiotic and cancer therapeutics. This program offers functional clues to genes beyond a conventional NCBI BLAST search. We then can predict the function from gene sequence, the tertiary structure, interacting partners, or expression patterns of genes [35,36]. An additional primary screening procedure included cross-reference of the sample contiguous sequences with relevant search terms linked to the biosynthesis of PKS and NRPS secondary metabolites. Paladin® bioinformatics scripts were created from raw read assemblies using SPADES to produce UniProt™ program output for each sample hit. The relevant search terms were created to align with Streptomyces hygroscopicus and rapamycinicus strain-level isolates and their secondary metabolite classes of interest (type I, II, II, and NRPS) predicted by AntiSMASH™ and UniProt™ bioinformatics algorithms [28]. The unique NCBI accession ID generated from the genetic database, GenBank was used in each search [37]. Type I PKS biochemical modules contain complex multifunction proteins classified by domains. PKS or Polyketide (biologically active secondary metabolites) derived from natural sources such as bacteria function to produce biosynthesis genes that make antibiotics). NRPS are peptide secondary metabolites produced by microorganisms such as bacteria or fungi—metabolites not synthesized by ribosomes. Apoptotic is a form of programmed cell death occurring in multicellular organisms and tumors. Protein Tyrosine kinase is associated with apoptotic cell death activity. For example, Streptomyces rapamycin A is produced by Streptomyces rapamycinicus and its type I PKSs [38]. A search-term procedure used in the present study aimed to align high-confidence biochemical domains existing in each module cycles enzymes such as acyltransferase (AT), keto synthase (KS), and acyl carrier proteins (ACP) which collaborate to produce β-keto ester intermediate. For example, modules can produce long-chain polyketide transfer modules that produce chemotherapeutics associated with keto group modification processes. 1. Screening started with species extracted from assemblies for each sample. 2. UniProt™ output categories included relative abundance, associated organisms, proteins, and gene ontology (i.e., molecular and cellular processes). 3. From the UniProt™ data output, cross-referencing the occurrence of relevant BGC antibiotic and chemotherapeutic compounds aligned with bioactive enzyme activity. For example, glutamine amidotransferase (GATase) is a biosynthetic enzyme, which catalyzes the removal of the ammonia group, thus transforming the glutamine molecule and substrate, creating a new structure.

2.7. Screening Database II

The AntiSMASH™ 7.0 program was also used to cross-reference sample data based on sequenced data to predict high quality aligned sequence matches with biosynthetic gene clusters (BGCs) across genomes of interest using sample contiguous sequences (contig hits) [39]. The metrics used are similarity scores for given species of similar taxonomy, which determine the likelihood that coincide with the BGCs. The program’s algorithm starts by using each ascension number from our bioinformatics pipeline. Chemotherapeutic screening based on BGCs that harbor PKS and NRPS enzymes with high potential for cytotoxic activity. Criteria = Streptomyces and SM key word search >80% similarity. Bit Score > 80, SM = PKS T1, 2 and 3/NRPS.
Statistical analyses including generalized linear models using SAS PROC GENMOD (SAS v9.4, Cary, NC, USA) were used to assess whether counts of Streptomyces hygroscopicus and rapamycinicus differed by sampling site. Models utilized a Poisson distribution with a log link function [37].

3. Results

3.1. Streptomyces Abundance

Of the 11 total sediment samples collected, a total of 222 (S. hygroscopicus) and 114 (S. rapamycinicus) sequenced hits were screened using two bioinformatics methods (Table 2). Sequenced data were quantified across multiple years by Streptomyces species (including hygroscopicus and rapamycinicus) and categorized by site (open and closed to fishing activity). A single factor ANOVA comparing mean values of Streptomyces hits between sites significantly differed by year (F crit = 4.46; p < 0.01). The occurrence of Streptomyces spp. was significantly more prevalent at Sites 1 and 3 for all the years sampled (Figure 2).

3.2. Screening Database Analyses

The metagenomic sequenced data were analyzed according to taxonomic characterization. Aligned sequence analysis showed the occurrence of hits for Sites 1 (60, 31) and 3 (47, 52) was higher for hygroscopicus and rapamycinicus, respectively (Figure 3).
Database I revealed likely compounds and enzymes worthy of future study in marine sediment. The open-to-fishing sites showed a greater prevalence of both species overall (261 = 1, 2, 3 vs. 75 = 6, 7, 8, 9) (Table S1). In these results, the cross-referenced methods used to quantify all metagenomic sequenced hits showed a small % of sequenced hits (2/244) corresponding with the cancer therapeutic enzyme Glutamine amidotransferase. This molecule is critical in inhibiting the biochemical process that drives cancer cell growth and proliferation [39]. The results also report the number of aligned contiguous sequences and associated gene ontology categories of top enzymes involved in anticancer metabolism by species. For example, Phase I types of Dehydrogenases and Oxidases P450, and Phase II types Glucuronosyl transferase, N-Acetyltransferases and glutathione S-transferases (GSTs) are categorized [40].
The following compounds and enzymes produced by all Streptomyces spp. were evident across samples associated with rapamycin, geldamycin, doxerubin, nigericin, salinomycin and amidotransferase. Dehydrogenases were more prevalent (19/244) among the core BGCs evaluated. One example revealed that S. hygroscopicus from Site 3 was strongly associated with alcohol dehydrogenase GroES proteins that drive oxidoreductase activity, a known pathway to combat tumor cell growth.
Database II methods included cross-referenced contiguous hits with BGCs aligned according to NCBI BLAST accession IDs. Results showed the occurrence of core BGCs for Site 3 was 375 for hygroscopicus and 58 for rapamycinicus (Table S2). Further analyses showed that Site 3 has the highest total number (443) of predicted core BGCs for all Streptomyces species, followed by Site 1 (254) (Figure 4). Poisson regression models confirmed that Sites 1, 2, and 3 had significantly higher occurrence for Streptomyces hygroscopicus than the other sites (p < 0.05).
BGCs discovered for each site were also screened by secondary metabolite class and expressed in Database II (Table S2). The rationale for this objective was to visualize the proportions of strains that can produce chemotherapeutic and antibiotic compounds by gene cluster using the AntiSMASH™ algorithm. In successive secondary metabolite analysis, results showed that the proportion of chemotherapeutic and antibiotic enzymes was more prevalent at Site 3 than at other sites (Figure 5). Classification of molecular function by species showed that the number of sample hits corresponding to a large group of secondary metabolites, NRPS, PKS I, II, and II, was greater for hygroscopicus (Table S2). A relatively high abundance of BGCs identified are associated with compounds that facilitate tumor cell toxicity and polyketide synthases (PKSs) were observed within genomic regions. Statistical analyses showed a significant difference in the number of hits for NRPS and PKS metabolites by site and between species, with hygroscopicus showing a greater quantity than rapamycinicus and all other Streptomyces spp. (df 2; p < 0.05; F = 4.7 > F crit). The proportion of NRPS/PKS was 59.6% (137/230) for all species characterized. A small percentage (8/2285 or 0.39%) of corresponding hits for rapamycinicus and hygroscopicus were evident at Site 4.
Region 11 AntiSMASH™ results from a S. hygroscopicus sample contig hit encoded for a hybrid T1PKS/NRPS biosynthetic gene cluster (BGC), within the core BGC cluster. The core cluster illustrates how complex biosynthesis processes of both polyketides and non-ribosomal peptides can be with respect to harboring multiple metabolite classes with medicinal activity potential. This region encoded for antimycin A, a compound that has anticancer and anti-inflammatory and anti-fungal activities [41]. It favors reactive oxidative species (ROS) production and inhibits mitochondrial electron transport chain complex III, which can impair mitochondrial depolarization. This compound also suppresses tumorigenesis in lung cancer cells and is a potential therapeutic compound. Additionally, this compound has been shown to induce apoptosis and has been used to study sites of ROS production in mitochondria isolated from skeletal muscle of chronic obstructive pulmonary disease patients [42]. Figure 6 spatially illustrates the quantity of secondary metabolites by site.
Figure 7 shows the percentage of metabolite diversity that exists within the Streptomyces genome form BGC regions aligned with S. hygroscopicus strains identified by output. The most abundant proportion when the polyketides are combined was the NRPS metabolites at 23%. Results also showed that polyketides of all types (I, II, and III) had a combined proportion of 28% compared with the other metabolite classes, making them the second most abundant within the given sample. Terpenes (12%), siderophore and RiPP (8%) compounds were next higher in prevalence.
Figure 8 provides a graphic representation of predicted core BGCs showing > 98% similarity of multiple S. hygroscopicus strains according to results. The compound nigericin can exhibit cytotoxicity against tumor cells and has a high metabolite potential at low doses [27]. This core biosynthetic gene cluster also encodes for a type I polyketide synthase. This result demonstrates the extraordinary predictability for this cluster within the S. hygroscopicus genome.

4. Discussion

A combined bioinformatics approach was used to characterize various Streptomyces species and evaluate candidate strains with potential to produce compounds with medicinal value. Initial experiments were completed to cultivate Streptomyces from environmental samples on a marine and a species-specific agar (i.e., ISP4). Although, more experiments are needed to confirm Streptomyces species and delineate individual strains with respect to predicted secondary metabolites. Future studies include improved culture experiments, heterologous gene expression, followed by compound structure analyses.
These results support previous research that this region within the SBNMS may be unique regarding the prevalence of Streptomyces spp. [6]. Regarding relative abundance, Streptomyces hygroscopicus was among the top ten species identified at all sampling locations open and close to fishing. The results suggest that Streptomyces hygroscopicus and S. rapamycincus were prevalent within study sites such as 1 and 3, open fishing region. Sequenced hits that did not contain hygroscopicus were categorized in the top 10 highest according to bit score (S’), which represents the alignment quality between the query and target sequences (a higher bit score represents higher similarity).
Descriptive analysis of Streptomyces hygroscopicus and rapamycinicus biological processes and gene ontology proved effective for screening for biosynthetic metabolites, molecular processes, and medicinal compounds [43] (Tables S1 and S2). For example, the BGC results showed high protein hits coding for polyketide and NRPS metabolites observed in Sites 6 and 7. The results of this study report the presence of oxidoreductase in S. hygroscopicus and S. rapamycinicus in Sites 6 and 7, which are closed to fishing, but not in Sites 1 and 3 (open to fishing). This information is notable as there were more PKS protein hits in Site 7 than in Site 1, despite Site 3 having more overall hits. Based on the polyphenolic ring system and their biosynthetic pathways, the aromatic polyketides produced by type II PKSs are generally classified into several groups [44]. Specifically, the compound doxorubicin is an example of anthracyclines predicted in the present study; an aromatic polyketide produced by Streptomyces. These results suggest that sediment samples collected from undisturbed surficial sediment habitats may harbor a greater diversity of proteins and a more significant amount of secondary metabolite potential. Furthermore, Streptomyces hygroscopicus, S. hygroscopicus subsp. jinggangensis 5008, and S. hygroscopicus subsp. limoneus revealed genes encoding for modular polyketide synthases and non-ribosomal peptide synthase proteins, antibiotic biosynthesizing features, fatty acid and lipid biosynthetic processes, polyketide biosynthetic and acyltransferase activity. This study underscores the pressing need for more research within marine sediment environments, particularly in sites like the SBNMS, where Streptomyces spp. is more abundant. One notable secondary metabolite produced by S. hygroscopicus is geldanamycin, a benzoquinone-type polyketide ansamycins with antitumoral activity. Geldanamycins interact with the heat shock protein (HSP 90) chaperone, a vital protein in the tumorigenesis of human cells at nanomolar concentrations. Another new geldanamycin analog isolated from the fermentation of S. hygroscopicus A070101 that has cytotoxic activity against the human breast adenocarcinoma (MCF7) are melanoma (SK-MEL-2) and lung carcinoma (CR-L23) cell lines [45].
The present study demonstrated the high potential for bioactive molecules within sediment microbes such as macrolides, a group of antibiotics assembled by PKSs. For example, Elaiophylin is a bioactive macrolide produced by S. hygroscopicus [46]. It possesses various biological properties, including antibacterial, antiviral, and antitumor activity. Elaiophylin isolated from Streptomyces exhibited anticancer and cytotoxic activity in human epithelial cell tumors (HEp-2) and human leukemia (HL-60) cells. Future studies evaluating marine-derived sediment microbes should screen for the narrow segment of related peptides, particularly the anticancer peptide structure, mode of action [47], and selectivity inherent in the specific samples our study has discovered. This quest will require more investment in compound isolation of marine-derived Streptomyces.

4.1. Notable Secondary Metabolite Activity

Streptomyces hygroscopicus and rapamycinicus genomes continue to be studied within marine environments. In the present study, tyrosine-protein kinase was used as a search term in the datasets to cross-reference associations with S hygroscopicus and S. rapamycinicus, which were more abundant compared to the total Streptomyces species in the samples screened. These peptides can be found with BGC molecules present in our samples that inhibit tumor cell growth such as the metastatic tumor cell types and T-cells at the tumor sites [48]. Anticancer peptides have recently become a potentially viable source of interest in natural product discovery since they offer insight into pathways to develop new drugs [49]. Specifically, bioactive peptide candidates show promise, given that they have bioactive peptides encrypted within their sequences. Little is known about their biochemical mechanisms with respect to mediating cytotoxicity, for example, and thus producing anticancer effects. Therefore, exploring databases such as UniProt™ and AntiSMASH™ output is worthwhile for clues to elucidate their impact on cancer cells. For example, glutamine metabolism restriction has been proven to be effective in suppressing cancer cell growth, while glutamine supplementation can induce or inhibit cell death according to cell type [50]. In any case, extracellular glutamine level affects the susceptibility of cancer cells to different apoptotic triggers. Glutamine deprivation has been reported to sensitize Hela cells to Fas (CD95) ligand, TNF-α (tumor necrosis factor-α), and heat shock-mediated apoptosis [51]. Understanding the biosynthesis of glutamine, a key factor in cancer cell growth, is a crucial area that requires further study. Glutamine serves as a carbon source for the synthesis of metabolites via the TCA cycle, and a source of amino acid synthesis [47]. More research is needed to elucidate the biosynthesis of glutamine lipids, their pathways, and mechanisms [52]. According to the findings in the present study, glutamine amidotransferase enzymes are precise within marine-derived sediments of Streptomyces hygroscopicus bacteria. Glutamine has been readily studied due to its increased and fast consumption in most cancers compared to normal tissues.

4.2. Secondary Metabolites and Bioactive Compounds

After characterization of the abundance of SMs shown at SBNMS locations, the following steps quantify the structurally different types of polyketides, a class of secondary metabolites that exhibit a wide variety of bioactivities, such as antibiotic and anticancer properties. Polyketides, a large group of secondary metabolites, are known to possess remarkable variety, not only in their structure but also in their function. For example, metabolites exhibit bioactivities such as antibacterial activities that can produce compounds such as tetracycline [38] and anticancer agents (e.g., doxorubicin) [53]. Doxorubicin is a notable chemotherapeutic polyether ionorphore produced by Streptomyces. Polyether ionophores as potential anticancer molecules revealed that these agents might target both autophagy and apoptosis. Also effective is Nigericin free acid, which can exhibit cytotoxicity against cancer lines with IC50 values in the nanomolar range [18]. One example is evidence of potent activity against human leukemia (HL-60), colorectal carcinoma (HCT-116), and mastocytoma (P815) [54]. These case studies highlight the potential of bioactive compounds derived from marine environments. Within type I PKS activity, multifunctional enzyme modules are at work and at least three domains correspond to produce ketosynthases (KS), an acyltransferase (AT), and an acyl carrier protein (ACP). Type I, or macrocyclic polyketides, are synthesized by condensing acids such as acetate, propionate, and butyrate by type I polyketide synthases. Two examples of type I polyketides producing antibiotic medicine are pikromycin, discovered first, and azithromycin, both derived from Streptomyces [55]. Type II polyketides are instrumental in producing antibiotics associated with several types of Streptomyces species, for example, actinorhodin, an antibiotic produced by S. coelicolor, daunorubicin from Streptomyces peucetius, and griseorhodin produced by Streptomyces sp. JP95 [17].
High-level bioactivities from marine-derived microbes continue to be explored worldwide. For example, molecules such as polyether compounds are a class of antimicrobial and anticancer naturally occurring polyketides derived from Streptomyces species [56]. Salinomycin activates a distinct apoptotic pathway, which is not accompanied by cell cycle arrest and is independent of tumor suppressor proteins such as p53 and the proteasome. In cultured cells sampled from the marine environment, one study suggests that salinomycin (a polyether antibiotic) depletes human breast cancer stem cells in tumors and inhibits the growth and metastasis of human breast cancer cells injected into NOD/SCID mice [57].

5. Conclusions

Despite the challenges in elucidating medicinal compounds from environmental samples, there remains a need to continue this effort. Further research is needed to explore marine-derived strain isolates for antibiotic and chemotherapeutic compounds with the potential to combat pathogenic microorganisms (i.e., Staphylococcus) and tumor cells. Among these compounds, those that exhibit cytotoxic activity against cancer tumor cell lines should be investigated. It is crucial to emphasize the need for innovative efforts in this research, as they are the key to making significant breakthroughs. These efforts are needed to quantify natural peptides and potential candidates to mediate tumor cell death, especially those derived from the marine environment, such as Tyrosine and Tryptophan.
The characterization of sediment microbial species may have been limited by the relatively more extensive area of the SBNMS sampled. Despite that, the number of screened continuous hits was above 300 of the 11 sample sites processed. Discovering the diversity of microbial sediment communities and secondary metabolite potential from marine sanctuaries further emphasizes the importance of respecting these unique marine protected areas. It is crucial to promote their preservation to manage fisheries sustainably, as they play a significant role in the balance of our ecosystem.
Limitations inherent in this research warrant consideration to improve future studies. For example, programs and associated algorithms that predict BGC potential and cross-reference protein data may limit the discovery of novel gene sequence hits within the known NCBI informational library. Further research should minimize this bias with additional steps to culture isolates, sequence strains, and identify hidden biosynthetic clusters. Evidence suggests that the current methods used to characterize core BGCs (NCBI), and downstream bioinformatics algorithms are likely to identify biosynthetic genes that produce novel and active compounds [11]. The next step would be to include a more comprehensive array of BGCs in the predictive models. Although secondary metabolite gene clusters can be silent or cryptic in laboratory conditions, possibly due to environmental pressures and in vitro conditions [58], further study is needed to validate predicted results through strain isolation and whole genome sequencing of those isolates.
In conclusion, this study offers insights into the importance of characterizing sediment microbial biodiversity and drug discovery while promoting the establishment of marine protected areas. Additionally, this project reinforced the idea of preserving marine sanctuaries such as SBNMS, as these protected areas harbor novel and effective chemotherapeutic and antimicrobial compounds. Bacterial agents having anticancer, antimicrobial, and cellular toxicity properties that provide an alternative to conventional therapeutics. The specialized polyketides that these bacteria possess can yield a unique class of secondary metabolites with high biological activity, including Type I and II polyketides and polyether ionophores. Non-ribosomal peptide synthases are another class of multifunctional secondary metabolites that contain multi-modular structures that catalyze the non-ribosomal assembly of peptides from amino acids, exhibiting antimicrobial, antiviral, antitumor, and immunosuppressive activities [17]. More research is needed to understand how these polyketides catalyze the production of natural products that contribute to cell toxicity. The future of this project includes analyzing gene clusters associated with Streptomyces hygroscopicus and Streptomyces rapamycinicus. Future research includes advanced culture-based analysis with a high degree of compound isolation. The path to discovering viable natural products derived from marine-based Streptomyces accelerates the future of biomedical and ecological research, with applications to public health.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jmse12112076/s1, Table S1: Database I methods were used to categorize aligned sequenced hits with high likelihood with antibiotic and chemotherapeutic properties. The UniProt™ program was used to categorize of compounds and enzymes of interest. Table S2: Database II methods used to quantify cross-referenced contiguous hits of BGCs aligned according to NCBI BLAST accession IDs. Secondary metabolites were quantified using the AntiSMASH™ program predictions.

Author Contributions

J.P.B., the project director, was instrumental in conceptualizing, investigating, validating, writing, and final analysis. H.R.F. was instrumental in conceptualizing, analyzing, and validating methods. S.A.A. contributed to the conceptualization, design, supervision, visualization, and statistical analysis. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data supporting reported results can be found at the NCBI library. All the metagenomic raw sequencing data from this study has been deposited in the NCBI Sequence Read Archive (SRA). The BioProject accession numbers for the 2017 data are PRJNA524407 (BioSample SAMN10999726-SAMN10999731) and PRJNA837619 (BioSample SAMN28209579–28209594) for 2019, 2020 and 2022.

Acknowledgments

The authors are grateful for the support from the Marine Microverse Institute (MMI), Trevor Massey and Jacob Mischka for their assistance in the laboratory. They also extend they’re thanks to the University of New Hampshire, Hubbard Genome Center, especially Joe Sevigny, for their significant contributions to bioinformatics analysis. We also thank our citizen scientists. This project was possible thanks to the entire staff at the U.S. Stellwagen Bank National Marine Sanctuary, authorized as part of the National Marine Sanctuaries Act, passed into law in 1992 and regulated by the National Oceanic and Atmospheric Administration (NOAA).

Conflicts of Interest

No funding agencies played any role in this manuscript’s design, analysis, or writing. The authors are affiliated with MMI but have no financial conflicts of interest to declare.

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Jmse 12 02076 g001
Figure 1. Study site map (1–9) of the Gulf of Maine within the Massachusetts Bay area. Included are the borders of the Stellwagen Bank National Marine Sanctuary (black) with sample sites labeled with red (open to fishing) and black (closed to fishing) circles. The Western Gulf of Maine Closure area is marked with dashed markings. Note: Site 5 was retired in 2019 and is not shown on the map.
Figure 1. Study site map (1–9) of the Gulf of Maine within the Massachusetts Bay area. Included are the borders of the Stellwagen Bank National Marine Sanctuary (black) with sample sites labeled with red (open to fishing) and black (closed to fishing) circles. The Western Gulf of Maine Closure area is marked with dashed markings. Note: Site 5 was retired in 2019 and is not shown on the map.
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Figure 2. Metagenomic sequenced hits were quantified and matched by Streptomyces species sampled at locations within the SBNMS.
Figure 2. Metagenomic sequenced hits were quantified and matched by Streptomyces species sampled at locations within the SBNMS.
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Figure 3. Metagenomic sequences (hit-counts) aligned with Streptomyces hygroscopicus and rapamycinicus were quantified according to the UniPRot output.
Figure 3. Metagenomic sequences (hit-counts) aligned with Streptomyces hygroscopicus and rapamycinicus were quantified according to the UniPRot output.
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Figure 4. Contiguous hits for S. hygroscopicus, S. rapamycinicus, and all Streptomyces spp. corresponding to core BGCs and predicted by AntiSMASH™ analysis. Each sampling site is expressed for all years (8, 9 n/a). The Poisson data analysis was generated using SAS software, Version 9.4, SAS Institute Inc., Cary, NC, USA.
Figure 4. Contiguous hits for S. hygroscopicus, S. rapamycinicus, and all Streptomyces spp. corresponding to core BGCs and predicted by AntiSMASH™ analysis. Each sampling site is expressed for all years (8, 9 n/a). The Poisson data analysis was generated using SAS software, Version 9.4, SAS Institute Inc., Cary, NC, USA.
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Figure 5. The number of secondary metabolites were quantified using the AntiSMASH™ bioinformatics program predictions. All sample collection years and site locations were combined in this diagram (Table S2).
Figure 5. The number of secondary metabolites were quantified using the AntiSMASH™ bioinformatics program predictions. All sample collection years and site locations were combined in this diagram (Table S2).
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Figure 6. Map of study sites (1–9 black numbers) show total number of secondary metabolites identified in relation to surface to sediment depth (meters) as a heatmap corresponding to S. hygroscopicus and S. rapamycinicus by site. Spherical symbols: sparse to dense scale 0–100. Site 5 was retired in 2019 and is not shown on the map.
Figure 6. Map of study sites (1–9 black numbers) show total number of secondary metabolites identified in relation to surface to sediment depth (meters) as a heatmap corresponding to S. hygroscopicus and S. rapamycinicus by site. Spherical symbols: sparse to dense scale 0–100. Site 5 was retired in 2019 and is not shown on the map.
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Figure 7. Diagram of an S. hygroscopicus spp. (NCBI accession number NC_020895.1) identified by antiSMASH™ in study samples depicting prevalence of PKS and NRPS regions within BGGs aligned. This unique protein sequence record was identified in approximately 18% of all S. hygroscopicus and S. rapamycinicus contig samples analyzed.
Figure 7. Diagram of an S. hygroscopicus spp. (NCBI accession number NC_020895.1) identified by antiSMASH™ in study samples depicting prevalence of PKS and NRPS regions within BGGs aligned. This unique protein sequence record was identified in approximately 18% of all S. hygroscopicus and S. rapamycinicus contig samples analyzed.
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Figure 8. Identified secondary metabolite region of BGC search according to AntiSMASH output of multiple S. hygroscopicus strains (NZ_CP018627–Region 13; Location 1,553,101–1,683,344 nt). The select region within shows core BGCs (dark red) that encode for cytotoxic compounds such as Nigericin related and Type I Polyketides.
Figure 8. Identified secondary metabolite region of BGC search according to AntiSMASH output of multiple S. hygroscopicus strains (NZ_CP018627–Region 13; Location 1,553,101–1,683,344 nt). The select region within shows core BGCs (dark red) that encode for cytotoxic compounds such as Nigericin related and Type I Polyketides.
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Table 1. Coordinates of each sample site and their fishing status (open and closed to fishing) according to U.S. NOAA guidelines.
Table 1. Coordinates of each sample site and their fishing status (open and closed to fishing) according to U.S. NOAA guidelines.
Year CollectedSite IDFishing StatusLatitude NLongitude W
20171Open42°34′00.8″70°29′10.4″
20172Open42°33′01.3″70°29′01.3″
20173Open42°32′01.2″70°28′03.5″
2019 1Open42°34′00.8″70°29′10.4″
2019 3Open42°32′01.2″70°28′03.5″
20194Closed42°31′32.3″70°13′11.0″
2019 6Closed42°35′00.0″70°14′25.0″
2019 7Closed42°31′08.0″70°13′09.0″
20223Open42°32′01.2″70°28′03.5″
20228Open42°22′41.3″70°26′17.2″
20229Closed42°31′21.5″70°14′36.6″
Table 2. The total number of corresponding sequenced hits screened by site and year according to Database I methods and UniProt Paladin Output. Note: Site 2 2019 did not output a report for species.
Table 2. The total number of corresponding sequenced hits screened by site and year according to Database I methods and UniProt Paladin Output. Note: Site 2 2019 did not output a report for species.
Fishing ActivityYearSiteS. hygroscopicusS. rapamycinicus
open201714525
open20172310
open201732537
open20191216
open20193189
closed20194109
closed2019683
closed201972913
open20223106
open2022890
closed20229166
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Flaherty, H.R.; Aytur, S.A.; Bucci, J.P. Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites. J. Mar. Sci. Eng. 2024, 12, 2076. https://doi.org/10.3390/jmse12112076

AMA Style

Flaherty HR, Aytur SA, Bucci JP. Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites. Journal of Marine Science and Engineering. 2024; 12(11):2076. https://doi.org/10.3390/jmse12112076

Chicago/Turabian Style

Flaherty, Hannah R., Semra A. Aytur, and John P. Bucci. 2024. "Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites" Journal of Marine Science and Engineering 12, no. 11: 2076. https://doi.org/10.3390/jmse12112076

APA Style

Flaherty, H. R., Aytur, S. A., & Bucci, J. P. (2024). Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites. Journal of Marine Science and Engineering, 12(11), 2076. https://doi.org/10.3390/jmse12112076

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