Skip to main content
Download PDF

Metagenomic mining of two Egyptian Red Sea sponges associated microbial community

BMC Microbiology volume 24, Article number: 315 (2024) Cite this article

Abstract

The Red Sea is a promising habitat for the discovery of new bioactive marine natural products. Sponges associated microorganisms represent a wealthy source of compounds with unique chemical structures and diverse biological activities. Metagenomics is an important omics-based culture-independent technique that is used as an effective tool to get genomic and functional information on sponge symbionts. In this study, we used metagenomic analysis of two Egyptian Red Sea sponges Hyrtios erectus and Phorbas topsenti microbiomes to study the biodiversity and the biosynthetic potential of the Red Sea sponges to produce bioactive compounds. Our data revealed high biodiversity of the two sponges’ microbiota with phylum Proteobacteria as the most dominant phylum in the associated microbial community with an average of 31% and 70% respectively. The analysis also revealed high biosynthetic potential of sponge Hyrtios erectus microbiome through detecting diverse types of biosynthetic gene clusters (BGCs) with predicted cytotoxic, antibacterial and inhibitory action. Most of these BGCs were predicted to be novel as they did not show any similarity with any MIBiG database known cluster. This study highlights the importance of the microbiome of the collected Red Sea sponge Hyrtios erectus as a valuable source of new bioactive natural products.

Peer Review reports

Introduction

Marine environment is considered the most recent promising source of novel bioactive natural products with structural and chemical features not found in terrestrial environment [1]. It is a rich and diverse ecosystem inhabited by more than 1000 invertebrate species, 250 sponge species and 200 hard and soft coral species [2, 3]. One of the unique marine environment is Red Sea, which is characterized by extremely high temperatures and salinity. Its salinity is around 5% greater than the average salinity of the global seas and oceans [4]. It has an oligotrophic nature because of the lack of major nutrients, including nitrate, ammonium, phosphate and silica [5]. Such extreme harsh conditions stimulate marine organisms to produce a special structure of bioactive natural products [4].

The worldwide marine pharmaceutical clinical pipeline has already 48 compounds derived from different marine organisms. From these compounds, 15 approved by the most important approving organizations, 5 as phase III drug candidates, 12 in phase II, and 16 in phase I of drug development clinical phases [6, 7]. However, continuous discovery of new therapeutic agents, especially antimicrobial and anticancer agents, is required to overcome the side effects and drug resistance of the current drugs besides facing the new challenges of various diseases.

The discovery of marine natural products, especially those derived from sponges, grows at an accelerated rate. Till now, more than 18,149 new compounds with high chemical structure and therapeutic potential diversity have been isolated from sponges and the number is increasing annually by more than 200 new isolated compounds [8, 9]. A lot of these products showed various biological activities, such as anticancer, antifungal, antibacterial, antiviral, anti-inflammatory, antioxidant and antimalarial activity [8, 10, 11].

Sponges natural products which are mainly secondary metabolites are characterized by high chemical diversity as they are grouped according to their chemical structures into many classes such as alkaloids, terpenes, ribosomal peptides, polysaccharides, anthraquinones, polyketides and non-ribosomal peptides [12]. Non-ribosomal peptides (NRPs) and polyketides (PKs) are two of the most important, diverse and largest natural product families [13, 14]. They are widely applied as pharmaceutical drugs for the treatment of different diseases such as the antibacterial (erythromycin and vancomycin), the antifungal (amphotericin and griseofulvin) [15], the anti-parasitic avermectin [16], the anti-cholesterol lovastatin [17], the immunosuppressants (rapamycin and cyclosporine), and the anticancer drugs (epothilone, anthracycline, doxorubicin and bleomycin) [18,19,20,21,22,23]. The enzymatic machineries responsible for the biosynthesis of these metabolites are usually encoded by many locally clustered genes within the genome of the producing organism known as biosynthetic gene clusters (BGCs) [24].

Sponges are one of the most marine holobiont hosting diverse and complex microbial communities [25, 26]. Many primary research articles and reviews outline the hypothesis that most of the compounds isolated from marine sponges are produced by the sponge associated microorganisms, not from sponges themselves. Therefore, sponge associated microbial symbionts have become an attractive subject for discovering new drug leads [27].

Traditional culture-dependent method only provides limited information on the sponge community structure as most of the associated bacteria are challenging to be cultured under the frequent laboratory conditions [28, 29]. Therefore, culture-independent molecular approaches, which exceed the need for isolation and laboratory cultivation of sponge associated microbes, have been developed. Metagenomics is an important omics-based culture-independent technique that is used as an effective tool to get genomic and functional information on sponge symbionts [30,31,32,33] and allow the identification of the BGCs responsible for the biosynthesis of bioactive natural products within the marine sponge metagenome [34, 35]. This study aims to explore the diversity of two Egyptian Red Sea sponges’ microbiota in addition to investigating their potential to produce bioactive natural products through detecting BGCs responsible for their biosynthesis.

Methods

Sample collection, processing and metagenomic DNA extraction

In October 2021, three samples of two different marine sponges were collected from the Red Sea in Sharm El Sheikh, South Sinai, Egypt (Fig. 1) at a depth of 17–27 meters at GPS location (27054’30.45” N 34019’48.99” E). Sample processing and metagenomic DNA extraction were done according to EL Samak et al. [36].

Fig. 1
figure 1

Collected Red Sea sponges (d) Phorbas topsenti (e) Hyrtios erectus

Full size image

Shotgun metagenomic sequencing and sequence analysis

Library preparation and sequencing on NovaSeq 6000 in paired-end 150 bp mode were done in IGA TECHNOLOGY SERVICES S.R.L in Italy. FastQC v 0.11.8 and Trimmomatic v 0.38 were used for quality check and removing low quality leading and trailing bases as well as reads shorter than 100 bp [37].

After trimming, reads were denovo assembled using MEGAHIT V.1.2.9 [38] then the microbial contigs were separated from the eukaryotic contigs using Autometa v.2 [39] with the help of bowtie2 [40] and SAMtools as mentioned by EL Samak et al. [36]. MEGAN 6 was used to assign taxonomic classification to the assembled contigs [41].

Detection and annotation of BGCs in the microbiome of the collected sponges

In order to improve the detection of secondary metabolite BGCs in the sponge microbiome, the microbial assembled contigs of the three samples of each sponge species were co-assembled together with Megahit to give higher read depth. AntiSMASH 5 was used to detect the BGCs in the metagenomic co-assembled contigs [42] then the detected BGCs were grouped into Gene Cluster Families (GCFs) using BiG-SCAPE v1.1.0 (Biosynthetic Gene Similarity Clustering and Prospecting Engine) [43]. The bioactivity of these detected BGCs was predicted using DeepBGC v 0.1.30 [44].

The detected KS and C domains of PKS and NRPS, respectively, were analyzed by NaPDoS 2 pipeline [45]. Phylogenetic trees of these detected domains against the NaPDoS domain database were constructed by maximum likelihood using NaPDoS and visualized using FigTree v1.4.4, respectively.

Results

Sponges identification

Sponges were identified morphologically according to Colin & Arneson [46] as Hyrtios erectus and Phorbas topsenti.

Metagenomic sequencing analysis

Using NovaSeq 6000 in 150 bp paired-end mode for sequencing resulted in 26.345, 26.213 and 42.6 million reads for Phorbas topsenti sponge and 40.287, 43.074 and 41.515 million reads for Hyrtios erectus sponge.

The rarefaction curve generated by MEGAN6 for each sample displayed graphic curve plateaus (Fig. 2). These plateaus proved that the used sequencing depth was appropriate and no more depth was needed, as the used depth could detect most of the sponge associated taxa.

Fig. 2
figure 2

Taxonomy rarefaction curve for the collected sponge samples. d1, d2 and d3 are the three collected samples of sponge Phorbas topsenti. e1, e2 and e3 are the three samples of Hyrtios erectus sponge

Full size image

Upon using Trimmomatic, an average of 84.08% and 77.37% of the paired reads of Hyrtios erectus and Phorbas topsenti, respectively, were survived. Approximately 65% and 30% of assembled contigs of the sponge samples respectively remained as non-eukaryotic after removing host and eukaryotic sequences. Table 1. shows the evaluation of the assembled contigs after host removal.

Table 1 Analysis of metagenomic assembly of sponges Phorbas topsenti and Hyrtios erectus
Full size table

Taxonomic identification of bacterial communities associated with collected Red Sea sponges

The taxonomic analysis assigned by MEGAN 6 revealed a high diversity of the microbiota associated with the collected Red Sea sponges. Regarding sponge Hyrtios erectus, it was found to host 36 bacterial and 4 archaeal phyla. The most abundant associated phylum was Proteobacteria with an average of 31% followed by Chloroflexi (10.7%), Candidatus Poribacteria (7%), Acidobacteria (5%), Actinobacteria (4.5%), Gemmatimonadetes and Candidatus Tectomicrobia (1.2% for each). The other phyla were represented by only less than 1% for each one.

On the other side, sponge Phorbas topsenti microbiota showed lower diversity in comparison with Hyrtios erectus, as it was found to be composed of 15 bacterial and only two archaeal phyla. Proteobacteria is the most dominant phylum represented by an average of 70% then Candidate Phylum Tectomicrobia came in the second place with 7% followed by Cyanobacteria (5%), Bacteroidetes (1.7%) and Planctomycetes (1.1%) while all the remaining phyla were present at less than 1%. However, about 11.6 and 31.5% of sequences in sponges, Phorbas topsenti and Hyrtios erectus, respectively, could not be assigned to known bacterial phylum (Fig. 3).

Fig. 3
figure 3

Composition of the microbial community associated with the collected Egyptian Red Sea sponges at Phylum-level. d1, d2 and d3 are the three samples of sponge Phorbas topsenti. e1, e2 and e3 are the three samples of sponge Hyrtios erectus

Full size image

Principal coordinates analysis (PCoA) of microbial communities associated with the collected samples of the two Red Sea sponges showed clustering of the three replicate samples of each sponge, while it showed a clear separation and composition differences of the taxonomic profile between the two sponges (Fig. 4).

Fig. 4
figure 4

PCoA plot of the microbial communities associated with the collected samples of the two Red Sea sponges. Community ordinations were based on Bray-Curtis distances calculated by MEGAN 6 using the taxonomic abundances for the samples

Full size image

Detection of secondary metabolites BGCs in the microbiome of the collected Red Sea sponges

AntiSMASH 5 was used to mine the metagenomic co-assembled contigs for BGCs to estimate the potential of the collected Egyptian Red Sea sponges to be a source for bioactive secondary metabolites. In this aspect, Hyrtios erectus microbiome showed high richness in BGCs responsible for producing various types of secondary metabolites mainly terpenes, ribosomally synthesized and post-translationally modified peptides (RiPPs), polyketides (PKSs), non-ribosomal peptides (NRPs), hybrid compounds in addition to other types as illustrated in Fig. 5. On the other side, the microbiome of Phorbas topsenti was found to have only 5 BGCs having the potential ability to produce NRPS, RiPPs, betalactone and hybrid PKS-NRPS (Fig. 5).

Fig. 5
figure 5

Abundance of BGC types identified by AntiSMASH and gene cluster families (GCFs) grouped by BIG-SCAPE in the collected Red Sea sponges metagenomic co-assembled contigs

Full size image

Only approximately 8% of the detected BGCs in the Hyrtios erectus metagenomic data have shown some similarities to certain clusters in the MIBiG database which is considered a Repository of Known BGCs (Table 1. in the supplementary file) while none of the BGCs detected in the sponge Phorbas topsenti metagenome showed any similarity.

The major advantage of deepBGC pipeline is represented by its ability to assign product activities to the detected BGC. In this respect, 75% and 60% of the detected BGCs in sponges Hyrtios erectus and Phorbas topsenti respectively were found to have bioactivity. In sponge Hyrtios erectu., antibacterial activity was assigned to 278 clusters, cytotoxic activity to 7 clusters and 8 were predicted as inhibitors. For Phorbas topsenti sponge, only 2 BGCs out of 5 were predicted to have antibacterial activity and 1 as inhibitor.

The BiG-SCAPE algorithm was used to group the metagenomic BGCs detected with antiSMASH into GCFs (Fig. 5). For Hyrtios erectus sponge, the 389 BGCs were grouped into 371 GCFs classified as 71 T1PKS (Type I Polyketide synthase) GCFs with 67 singletons, 32 NRPS-like GCFs with 31 singletons, 8 GCFs of other PKS types represented in T3PKS and 153 terpene GCFs with 148 singletons. As well, RiPPS represented in lanthipeptides, bacteriocins, lassopeptides, thiopeptides and LAP (Linear azol(in)e-containing peptides) were grouped in 73 GCFs with 69 singletons and 34 GCFs of other BGCs types represented in arylpolyene, betalactone, phosphonate, ladderane and ectoin were detected with 34 singletons. On the side of Phorbas topsenti sponge, only 5 families of 5 singletons were detected; two NRPS families and one of RiPPs, betalactone and hybrid PKS-NRPS.

NaPDoS 2 pipeline was used to examine the C (condensation) and KS (keto-acyl synthase) domains of the two large modular BGC families (NRPS and PKS), respectively. According to PKS clusters, 2 and 80 KS domains were recovered from Phorbas topsenti and Hyrtios erectus co-assembled contigs, respectively. Regarding NRPS clusters, only 2 C domains were recovered from the Phorbas topsenti sponge, while no C domains were detected in the contigs of Hyrtios erectus. The absence of C domains in Hyrtios erectus was expected, as no NRPS was detected by antiSMASH in the microbiome of this sponge. Instead, only NRPS-like clusters that lack C domains were detected.

Interestingly, the phylogenetic analysis constructed between these detected C and KS domains against their closest matches in the NAPDOS reference database (Fig. 6) and (Fig. 7) showed low sequence identity scores as shown in Table 2 in supplementary file.

Fig. 6
figure 6

Maximum likelihood phylogenetic tree of KS domains of the collected Egyptian Red Sea sponge Hyrtios erectus microbiome against the NaPDoS domain database. Hyrtios erectus domains are colored with red

Full size image
Fig. 7
figure 7

Maximum likelihood phylogenetic tree of (A) KS domains and (B) C domains of the collected Egyptian Red Sea sponge Phorbas topsenti microbiome against the NaPDoS domain database. Phorbas topsenti domains are colored with red in both trees

Full size image

Taxonomic identification of the detected BGCs

The taxonomic identification of the detected BGCs revealed that species of Theonella swinhoei bacterial symbiont clone pSW1H8 was the most abundant in having BGCs in the collected Hyrtios erectus microbiome with 6.5% followed by Candidatus Poribacteria bacterium by 5.5% (Fig. 8). In addition, uncultrable bacteria were found to be the source of approximately 37% of the detected BGCs in this sponge. Approximately 42% could not be assigned to known specific species, while 27% could not be assigned to known specific taxa. According to Phorbas topsenti, all the detected BGCs were found to belong to phylum Proteobacteria but could not be assigned to specific species.

Fig. 8
figure 8

Taxonomic classification of BGCs detected in the microbiome of the collected Red Sea sponge Hyrtios erectus at species level. Others are the microbial species having only one detected BGC

Full size image

Discussion

Red Sea is one of the unique marine environments worldwide. It is considered an amazing target for discovering new bioactive natural products. Marine sponges associated microorganisms represent a wealthy source of compounds with unique chemical structures and diverse biological activities. Marine invertebrates, mostly sponges, collected from the Egyptian Red Sea coast have been reported to be rich in diverse and bioactive associated microbiota [47,48,49,50,51,52,53]. In this study, three samples of two different marine sponges were collected from the Red Sea at Sharm El Sheikh (south Gulf of Aqaba), Egypt, in October 2021. The sponges were identified morphologically as Hyrtios erectus and Phorbas topsenti. We use a metagenomic sequencing analysis to study the diversity of the two collected Egyptian Red Sea sponges’ microbiota and explore their potential to produce bioactive natural products through detecting BGCs in their microbiome.

The taxonomic analysis revealed a high diversity of the microbiota associated with the collected Red Sea sponges. Hyrtios erectus is a member of class Demospongiae, order Dictyoceratida [54]. Many species within this order have been identified as high microbial abundance (HMA) sponges which are known by hosting highly abundant and diverse symbiotic community [55,56,57,58,59,60]. In the present study, the presence of Proteobacteria as the most abundant phyla in Hyrtios erectus in addition to the presence of Chloroflexi, Acidobacteria, Actinobacteria, Gemmatimonadetes in the associated bacterial community was supported by the study of Radwan et al. who detected the presence of these phyla in Red Sea sponge Hyrtios erectus collected from Ras Mohamed [61]. In addition, the study of Voogd et al. also reported this community structure in Hyrtios erectus sponge inhabiting the remote western Indian Ocean island of Mayotte [60]. Candidate phylum Tectomicrobia present in association with our collected Egyptian Red Sea Hyrtios erectus was also reported in the Indian H. erectus. However, our sponge showed more diversity than the Indian sponge, as 36 bacterial phyla were detected in association with it, compared to only 17 in the Indian one. Although Candidatus Poribacteria was detected in our H. erectus, it was not reported in the Indian one, nor in the other Red Sea sponge collected from Ras Mohamed [60].

Phorbas topsenti is classified under class Demospongiae, order Poecilosclerida [62]. According to the study of Gloeckner et al., many species within this order were identified as low microbial abundant (LMA) sponges [55]. This may explain the low abundance of microbes associated with our collected Egyptian Red Sea Phorbas topsenti illustrated by the low number of its assembled microbial contigs compared to those of Hyrtios erectus as illustrated in Table 1. The microbial community structure of our collected Phorbas topsenti was found to be highly similar to that of Phorbas fictitious, another sponge from the same genus collected from Algarve in Portugal [63]. The samples of this Portuguese sponge had Proteobacteria as the most dominant phylum in their bacterial communities while Cyanobacteria, Bacteroidetes and Planctomycetes were the major phyla inhabiting the remaining associated community and this was found in consistence with the community composition of the collected Egyptian Red Sea sponge [63]. However, Candidate Phylum Tectomicrobia, that had the second highest relative abundance in the associated community of our collected sponge, was not reported in the Portuguese sponge [63]. But this seems logical because the study of the Portuguese sponge used the SILVA database (version 115, June 2013) for taxonomic analysis while Tectomicrobia was first discovered in 2014 [64]. In addition, few phyla, such as Poribacteria, were not detected in the Portuguese sponge despite their presence in our collected sponge [63].

Candidate phylum Poribacteria was found to be present in our two collected sponges, despite its absence in the same sponge species collected by Radwan et al., Voogd et al. and Soares et al. [60, 61, 63]. This finding could be the result of using whole shotgun metagenomic sequencing in our study rather than using16s rRNA metagenomic sequencing in their studies to explore the composition of sponges’ associated bacteria. The universal 16 S rRNA primer sets could not be used for the amplification of the members of Candidate phylum Poribacteria [65] as it was later reported that complete sequences of the Poribacteria 16 S rRNA gene have multiple mismatches to universal 16 S rRNA gene primer sets [66]. On the other side, presence of the unassigned sequences in the microbiome of the collected sponges suggests presence of novel associated microbes.

On the side of biosynthetic potential of collected sponges, the microbiome of sponge Hyrtios erectus was found to be rich in BGCs responsible for the production of diverse types of secondary metabolites. Terpenes were found to be the most abundant type in the detected BGCs and this was consistence with our previous study on Red Sea Theonella sp. sponge [36]. RiPPs was the second most abundant detected class, followed by T1PKS. In contrast to the collected Hyrtios erectus, only a few BGCs were detected in the microbiome of our collected Phorbas topsenti sponge, although many structurally unique compounds have been identified from sponges of the genus Phorbas in many other studies [67]. This may be due to that most of the bioactive compounds identified specifically from this species in other studies may have been produced by the sponge cells not by its associated bacterial community.

Only 8% of the detected BGCs in Hyrtios erectus metagenomic data have shown some similarities to certain clusters in the MIBiG database. We detected BGCs having certain similarity to other clusters producing compounds with reported inhibitory activity: Chejuenolides A and B with 7% similarity [68] and Salecan with 10% similarity [69], in addition to one BGC having 5% similarity to that of the antibiotic primycin [70].

Those detected BGCs in our Hyrtios erectus sponge may be responsible for the biosynthesis of new natural products with certain similarities to the above mentioned bioactive compounds. Alternatively, they may biosynthesize these compounds themselves despite the low similarity percentage, which may be explained by the cluster incompleteness, where the majority of the detected BGCs were found along the edge of the contigs. Therefore, it is better to use long-read sequencing in upcoming studies on these sponges for easily detecting the whole cluster. No similarities were found between the remaining detected BGCs of the collected Hyrtios erectus sponges and all detected BGCs in the collected Phorbas topsenti sponge with any MIBiG database known cluster recommending their ability to biosynthesis new compounds. Besides the novelty of most sponges’ microbiome BGCs, they also were suggested to be of high diversity as most of the GCFs constructed by BiG-SCAPE included only a single BGC (singletons).

The KS and C domains phylogenetic analysis of the PKSs and NRPSs in the collected sponges’ microbiome indicated the potential uniqueness in PKS and NRPS products in all collected sponges because of the low scores of sequence identity to their predicted natural products.

In the collected Hyrtios erectus microbiome, the majority of the detected BGCs were found to belong to Theonella swinhoei bacterial symbiont clone pSW1H8. This is consistence with many studies that reported the uncultivable symbiotic bacteria associated with Theonella swinhoei sponge as the true producer of many bioactive natural products [71, 72]. Most BGCs detected in the microbiome of our collected sponges, especially Hyrtios erectus were predicted to have different bioactivities indicating the importance of these collected sponges as a source for therapeutic natural products.

Conclusion

Egyptian Red Sea sponges are considered being highly promising for the discovery of new bioactive natural compounds. The microbiota of the collected Egyptian Red Sea sponges, Hyrtios erectus and Phorbas topsenti were found to be highly diverse. In addition, the Red Sea sponge Hyrtios erectus microbiome was revealed to be rich in BGCs with different predicted bioactivities. This indicates the high biosynthetic potential of the microbiota of this sponge to produce bioactive natural products. Certain similarities were found between some of the detected clusters and other known bioactive BGCs in the MIBiG database, while the majority of the detected BGCs showed no similarities with any known cluster, suggesting the novelty of these clusters. From this metagenomic study, we can highlight the high biodiversity of the Red Sea sponges’ microbiota in the Egyptian coast and highlight their importance, especially that of Hyrtios erectus as sources for new bioactive therapeutic natural products.

Data availability

All metagenomic raw data used in this study have been deposited in SRA-NCBI under BioProject accession numbers PRJNA972201.

Abbreviations

PKS:

Polyketide synthases

T1PKS:

Type I Polyketide synthase

LAP:

Linear azol(in)e-containing peptides

NRPSs:

Non-ribosomal peptide synthases

BGCs:

Biosynthetic Gene Clusters

MIBiG:

Minimum information about a biosynthetic gene cluster

KS:

Keto-acyl synthase

C:

Condensation

GCF:

Gene cluster family

HMA:

High microbial abundance

LMA:

Low microbial abundance

References

  1. Romano G, Costantini M, Sansone C, Lauritano C, Ruocco N, Ianora A. Marine Microorganisms as a Promising and sustainable source of Bioactive molecules. Mar Environ Res. 2017;128:58–69. https://doi.org/10.1016/j.marenvres.2016.05.002

    Article  CAS  PubMed  Google Scholar 

  2. Ilan M, Gugel J, Van Soest R, Taxonomy. Reproduction and Ecology of new and known Red Sea sponges. Sarsia. 2004;89(6):388–410. https://doi.org/10.1080/00364820410002659

    Article  Google Scholar 

  3. El-Hossary EM, Abdel-Halim M, Ibrahim ES, Pimentel-Elardo SM, Nodwell JR, Handoussa H, Abdelwahab MF, Holzgrabe U, Abdelmohsen UR. Natural products Repertoire of the Red Sea. Mar Drugs. 2020;18(9):457. https://doi.org/10.3390/md18090457

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Khan S, Al-Fadhli AA, Tilvi S. Discovery of Cytotoxic Natural products from Red Sea sponges: structure and synthesis. Eur J Med Chem. 2021;220:113491. https://doi.org/10.1016/j.ejmech.2021.113491

    Article  CAS  PubMed  Google Scholar 

  5. Acker J, Leptoukh G, Shen S, Zhu T, Kempler S. Remotely-sensed chlorophyll a observations of the Northern Red Sea Indicate Seasonal variability and influence of Coastal Reefs. J Mar Syst. 2008;69(3–4):191–204. https://doi.org/10.1016/j.jmarsys.2005.12.006

    Article  Google Scholar 

  6. Marine. Pharmacology. Mysite. https://www.marinepharmacology.org (accessed 2024-01-21).

  7. Rateb ME, Abdelmohsen UR. Bioactive Natural Products from the Red Sea. Mar Drugs. 2021;19(6):289. https://doi.org/10.3390/md19060289

    Article  PubMed  PubMed Central  Google Scholar 

  8. Carroll AR, Copp BR, Davis RA, Keyzers RA, Prinsep MR. Marine Natural products. Nat Prod Rep. 2022;39(6):1122–71. https://doi.org/10.1039/D1NP00076D

    Article  CAS  PubMed  Google Scholar 

  9. Hong L-L, Ding Y-F, Zhang W, Lin H-W. Chemical and Biological Diversity of New Natural products from Marine sponges: a review (2009–2018). Mar Life Sci Technol. 2022;4(3):356–72. https://doi.org/10.1007/s42995-022-00132-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Abraham RE, Alghazwi M, Liang Q, Zhang W. Advances on Marine-Derived Natural Radioprotection compounds: historic development and future perspective. Mar Life Sci Technol. 2021;3(4):474–87. https://doi.org/10.1007/s42995-021-00095-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Carroll AR, Copp BR, Davis RA, Keyzers RA, Prinsep MR. Marine Natural products. Nat Prod Rep. 2019;36(1):122–73. https://doi.org/10.1039/C8NP00092A

    Article  CAS  PubMed  Google Scholar 

  12. Varijakzhan D, Loh J-Y, Yap W-S, Yusoff K, Seboussi R, Lim S-HE, Lai K-S, Chong C-M. Bioactive compounds from Marine sponges: fundamentals and Applications. Mar Drugs. 2021;19(5). https://doi.org/10.3390/md19050246

  13. Staunton J, Weissman KJ. Polyketide Biosynthesis: a Millennium Review. Nat Prod Rep. 2001;18(4):380–416. https://doi.org/10.1039/A909079G

    Article  CAS  PubMed  Google Scholar 

  14. Süssmuth RD, Mainz A. Nonribosomal peptide synthesis—principles and prospects. Angew Chem Int Ed. 2017;56(14):3770–821. https://doi.org/10.1002/anie.201609079

    Article  CAS  Google Scholar 

  15. Klaus M, Grininger M. Engineering Strategies for Rational Polyketide Synthase Design. Nat Prod Rep. 2018;35(10):1070–81. https://doi.org/10.1039/C8NP00030A

    Article  CAS  PubMed  Google Scholar 

  16. Barajas JF, Blake-Hedges JM, Bailey CB, Curran S, Keasling JD. Engineered polyketides: synergy between protein and host Level Engineering. Synth Syst Biotechnol. 2017;2(3):147–66. https://doi.org/10.1016/j.synbio.2017.08.005

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sundaram S, Hertweck C. On-Line enzymatic tailoring of polyketides and peptides in Thiotemplate systems. Curr Opin Chem Biol. 2016;31:82–94. https://doi.org/10.1016/j.cbpa.2016.01.012

    Article  CAS  PubMed  Google Scholar 

  18. Altmann K-H. Epothilone B and its analogs - a New Family of Anticancer agents. MRMC. 2003;3(2):149–58. https://doi.org/10.2174/1389557033405269

    Article  CAS  Google Scholar 

  19. Katz L, Baltz RH. Natural product Discovery: past, Present, and Future. J Ind Microbiol Biotechnol. 2016;43(2–3):155–76. https://doi.org/10.1007/s10295-015-1723-5

    Article  CAS  PubMed  Google Scholar 

  20. Levine DP, Vancomycin. A history. Clin Infect Dis. 2006;42(Supplement1):S5–12. https://doi.org/10.1086/491709

    Article  CAS  PubMed  Google Scholar 

  21. Li J, Kim SG, Blenis J, Rapamycin. One drug, many effects. Cell Metabol. 2014;19(3):373–9. https://doi.org/10.1016/j.cmet.2014.01.001

    Article  CAS  Google Scholar 

  22. Ute Galm †, Martin H, Hager, †; Steven G, Van Lanen J, Ju JS, Thorson. *; Ben Shen*, †. Antitumor Antibiotics: Bleomycin, Enediynes, and Mitomycin. ACS Publications. https://doi.org/10.1021/cr030117g

  23. Washington JA, Wilson WR. Erythromycin: a microbial and clinical perspective after 30 years of clinical use (First of two parts)*. Mayo Clin Proc. 1985;60(3):189–203. https://doi.org/10.1016/S0025-6196(12)60219-5

    Article  CAS  PubMed  Google Scholar 

  24. Chen R, Wong HL, Kindler GS, MacLeod FI, Benaud N, Ferrari BC, Burns BP. Discovery of an abundance of biosynthetic gene clusters in Shark Bay Microbial Mats. Front Microbiol. 2020;0. https://doi.org/10.3389/fmicb.2020.01950

  25. Pita L, Rix L, Slaby BM, Franke A, Hentschel U. The Sponge Holobiont in a changing ocean: from microbes to ecosystems. Microbiome. 2018;6(1):1–18. https://doi.org/10.1186/s40168-018-0428-1

    Article  Google Scholar 

  26. Taylor MW, Radax R, Steger D, Wagner M, Sponge-Associated Microorganisms. Evolution, Ecology, and Biotechnological potential. Microbiol Mol Biol Rev. 2007;71(2):295–347. https://doi.org/10.1128/MMBR.00040-06

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. McCauley EP, Piña IC, Thompson AD, Bashir K, Weinberg M, Kurz SL, Crews P. Highlights of Marine Natural products having parallel scaffolds found from Marine-Derived Bacteria, sponges, and tunicates. J Antibiot. 2020;73(8):504–25. https://doi.org/10.1038/s41429-020-0330-5

    Article  CAS  Google Scholar 

  28. Dyda M, Decewicz P, Romaniuk K, Wojcieszak M, Sklodowska A, Dziewit L, Drewniak L, Laudy A. Application of metagenomic methods for selection of an Optimal Growth Medium for Bacterial Diversity Analysis of Microbiocenoses on historical Stone surfaces. International Biodeterioration Biodegradation. 2018;131:2–10. https://doi.org/10.1016/j.ibiod.2017.03.009

    Article  CAS  Google Scholar 

  29. Qaisrani MM, Zaheer A, Mirza MS, Naqqash T, Qaisrani TB, Hanif MK, Rasool G, Malik KA, Ullah S, Jamal MS, Mirza Z, Karim S, Rasool MA. Comparative study of bacterial diversity based on Culturable and Culture-Independent techniques in the Rhizosphere of Maize (Zea Mays L). Saudi J Biol Sci. 2019;26(7):1344–51. https://doi.org/10.1016/j.sjbs.2019.03.010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Boparai JK, Sharma PK. Metagenomics and Metatranscriptomics Approaches in understanding and discovering Novel molecules in Rhizosphere Environment. Omics Sci Rhizosphere Biology. 2021;41–52. https://doi.org/10.1007/978-981-16-0889-6_3

  31. Fan L, Reynolds D, Liu M, Stark M, Kjelleberg S, Webster NS, Thomas T. Functional equivalence and evolutionary convergence in Complex communities of Microbial Sponge symbionts. Proc Natl Acad Sci U S A. 2012;109(27). https://doi.org/10.1073/pnas.1203287109

  32. Radax R, Rattei T, Lanzen A, Bayer C, Rapp HT, Urich T, Schleper C. Metatranscriptomics of the Marine Sponge Geodia Barretti: tackling phylogeny and function of its Microbial Community: Metatranscriptomics in Geodia Barretti. Environ Microbiol. 2012;14(5):1308–24. https://doi.org/10.1111/j.1462-2920.2012.02714.x

    Article  CAS  PubMed  Google Scholar 

  33. Thomas T, Rusch D, DeMaere MZ, Yung PY, Lewis M, Halpern A, Heidelberg KB, Egan S, Steinberg PD, Kjelleberg S. Functional Genomic Signatures of Sponge Bacteria Reveal Unique and Shared features of Symbiosis. ISME J. 2010;4(12):1557–67. https://doi.org/10.1038/ismej.2010.74

    Article  CAS  PubMed  Google Scholar 

  34. Trindade M, van Zyl LJ, Navarro-Fernández J, Abd Elrazak A. Targeted Metagenomics as a Tool to Tap into Marine Natural Product Diversity for the Discovery and Production of Drug Candidates. Front. Microbiol 2015, 6. https://doi.org/10.3389/fmicb.2015.00890

  35. Banik JJ, Brady SF. Recent application of Metagenomic approaches toward the Discovery of antimicrobials and other Bioactive Small molecules. Curr Opin Microbiol. 2010;13(5):603–9. https://doi.org/10.1016/j.mib.2010.08.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. El Samak M, Zakeer S, Hanora A, Solyman SM. Metagenomic and metatranscriptomic exploration of the Egyptian Red Sea Sponge Theonella Sp. Associated Microbial Community. Mar Genom. 2023;70:101032. https://doi.org/10.1016/j.margen.2023.101032

    Article  CAS  Google Scholar 

  37. Bolger AM, Lohse M, Usadel B, Trimmomatic. A flexible Trimmer for Illumina Sequence Data. Bioinformatics. 2014;30(15):2114. https://doi.org/10.1093/bioinformatics/btu170

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li D, Liu C-M, Luo R, Sadakane K, Lam T-WMEGAHIT. An Ultra-fast single-node solution for large and Complex Metagenomics Assembly via Succinct De Bruijn Graph. Bioinformatics. 2015;31(10):1674–6. https://doi.org/10.1093/bioinformatics/btv033

    Article  CAS  PubMed  Google Scholar 

  39. Ij M, Er R, J R, I M, J B, J L, Rl K, Fe R, Jc K, Autometa. Automated extraction of Microbial genomes from Individual Shotgun Metagenomes. Nucleic Acids Res. 2019;47(10). https://doi.org/10.1093/nar/gkz148

  40. Langmead B, Salzberg SL. Fast Gapped-Read Alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. https://doi.org/10.1038/nmeth.1923

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Huson DH, Beier S, Flade I, Górska A, El-Hadidi M, Mitra S, Ruscheweyh H-J, Tappu RMEGAN. Community Edition - Interactive Exploration and Analysis of large-scale microbiome sequencing data. PLoS Comput Biol. 2016;12(6):e1004957. https://doi.org/10.1371/journal.pcbi.1004957

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, Medema MH, Weber T. antiSMASH 5.0: updates to the secondary Metabolite Genome Mining Pipeline. Nucleic Acids Res. 2019;47(W1):W81–7. https://doi.org/10.1093/nar/gkz310

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Navarro-Muñoz JC, Selem-Mojica N, Mullowney MW, Kautsar SA, Tryon JH, Parkinson EI, Santos ELCDL, Yeong M, Cruz-Morales P, Abubucker S, Roeters A, Lokhorst W, Fernandez-Guerra A, Cappelini LTD, Goering AW, Thomson RJ, Metcalf WW, Kelleher NL, Barona-Gomez F, Medema MH. A computational Framework to explore large-scale Biosynthetic Diversity. Nat Chem Biol. 2020;16(1):60. https://doi.org/10.1038/s41589-019-0400-9

    Article  CAS  PubMed  Google Scholar 

  44. Hannigan GD, Prihoda D, Palicka A, Soukup J, Klempir O, Rampula L, Durcak J, Wurst M, Kotowski J, Chang D, Wang R, Piizzi G, Temesi G, Hazuda DJ, Woelk CH, Bitton DA. A deep Learning Genome-Mining Strategy for Biosynthetic Gene Cluster Prediction. Nucleic Acids Res. 2019;47(18):e110–110. https://doi.org/10.1093/nar/gkz654

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Klau LJ, Podell S, Creamer KE, Demko AM, Singh HW, Allen EE, Moore BS, Ziemert N, Letzel AC, Jensen PR. The natural product domain Seeker Version 2 (NaPDoS2) Webtool relates Ketosynthase phylogeny to biosynthetic function. J Biol Chem. 2022;298(10):102480. https://doi.org/10.1016/j.jbc.2022.102480

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Colin PL, Arneson C. Tropical Pacific invertebrates: a Field Guide to the Marine invertebrates occurring on Tropical Pacific Coral Reefs, Seagrass beds, and mangroves. Beverly Hills, Calif: Coral Reef; 1995.

    Google Scholar 

  47. Abdelmohsen UR, Pimentel-Elardo SM, Hanora A, Radwan M, Abou-El-Ela SH, Ahmed S, Hentschel U, Isolation. Phylogenetic analysis and anti-infective activity screening of Marine Sponge-Associated Actinomycetes. Mar Drugs. 2010;8(3):399–412. https://doi.org/10.3390/md8030399

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Shreadah MA. Bacteria from Marine Sponges: A Source of Biologically Active Compounds. BJSTR 2018, 10 (5). https://doi.org/10.26717/BJSTR.2018.10.002025

  49. El Samak M, Solyman SM, Hanora A. Antimicrobial Activity of Bacteria Isolated from Red Sea Marine invertebrates. Biotechnol Rep. 2018;19:e00275. https://doi.org/10.1016/j.btre.2018.e00275

    Article  Google Scholar 

  50. Helal HS, Hanora A, Khattab RA, Hamouda H, Zedan H. Mining of Egypt’s Red Sea invertebrates for potential Bioactive Producers. Biotechnol Lett. 2018;40(11):1519–30. https://doi.org/10.1007/s10529-018-2600-x

    Article  CAS  PubMed  Google Scholar 

  51. Kamel HL, Hanora A, Solyman SM, Metataxanomic. Bioactivity and Microbiome Analysis of Red Sea Marine Sponges from Egypt. Mar Genom. 2022;61:100920. https://doi.org/10.1016/j.margen.2021.100920

    Article  CAS  Google Scholar 

  52. Elfeky HH, Hanora A, Solyman SM. Bioactivity of Bacteria Associated with Red Sea nudibranchs and Whole Genome sequence of Nocardiopsis Dassonvillei RACA-4. Mar Genom. 2023;67:101004. https://doi.org/10.1016/j.margen.2022.101004

    Article  CAS  Google Scholar 

  53. Elsaeed E, Enany S, Solyman S, Shohayeb M, Hanora A. Mining Chromodoris Quadricolor symbionts for Biosynthesis of Novel secondary metabolites. Mar Genom. 2023;68:101017. https://doi.org/10.1016/j.margen.2023.101017

    Article  CAS  Google Scholar 

  54. Hooper, J. N. A.; Soest, R. W. M. V. SYSTEMA PORIFERA. A GUIDE TO THE CLASSIFICATION OF SPONGES ?. THE END OF A BEGINNING. BMIB. 2004;68.

  55. Gloeckner V, Wehrl M, Moitinho-Silva L, Gernert C, Schupp P, Pawlik JR, Lindquist NL, Erpenbeck D, Wörheide G, Hentschel U. The HMA-LMA dichotomy revisited: an Electron Microscopical Survey of 56 sponge species. Biol Bull. 2014. https://doi.org/10.1086/BBLv227n1p78

    Article  PubMed  Google Scholar 

  56. Moitinho-Silva L, Nielsen S, Amir A, Gonzalez A, Ackermann GL, Cerrano C, Astudillo-Garcia C, Easson C, Sipkema D, Liu F, Steinert G, Kotoulas G, McCormack GP, Feng G, Bell JJ, Vicente J, Björk JR, Montoya JM, Olson JB, Reveillaud J, Steindler L, Pineda M-C, Marra MV, Ilan M, Taylor MW, Polymenakou P, Erwin PM, Schupp PJ, Simister RL, Knight R, Thacker RW, Costa R, Hill RT, Lopez-Legentil S, Dailianis T, Ravasi T, Hentschel U, Li Z, Webster NS. Thomas, T. The Sponge Microbiome Project. Gigascience. 2017;6(10). https://doi.org/10.1093/gigascience/gix077

  57. Moitinho-Silva L, Steinert G, Nielsen S, Hardoim CCP, Wu Y-C, McCormack GP, López-Legentil S, Marchant R, Webster N, Thomas T, Hentschel U. Predicting the HMA-LMA Status in Marine Sponges by Machine Learning. Front. Microbiol. 2017;8. https://doi.org/10.3389/fmicb.2017.00752

  58. Ruocco N, Esposito R, Zagami G, Bertolino M, De Matteo S, Sonnessa M, Andreani F, Crispi S, Zupo V, Costantini M. Microbial Diversity in Mediterranean Sponges as revealed by Metataxonomic Analysis. Sci Rep. 2021;11(1):1–12. https://doi.org/10.1038/s41598-021-00713-9

    Article  CAS  Google Scholar 

  59. Schmitt S, Tsai P, Bell J, Fromont J, Ilan M, Lindquist N, Perez T, Rodrigo A, Schupp PJ, Vacelet J, Webster N, Hentschel U, Taylor MW. Assessing the Complex Sponge Microbiota: core, variable and species-specific bacterial communities in Marine sponges. ISME J. 2012;6(3):564–76. https://doi.org/10.1038/ismej.2011.116

    Article  CAS  PubMed  Google Scholar 

  60. Voogd NJ. Assessing the bacterial communities of sponges inhabiting the Remote Western Indian Ocean Island of Mayotte. Mar Ecol. 2018;39(6):e12517. https://doi.org/10.1111/maec.12517. Gauvin-BialeckiA.Polónia, A. R. M.; Cleary, D. F. R.

    Article  CAS  Google Scholar 

  61. Radwan M, Hanora A, Zan J, Mohamed NM, Abo-Elmatty DM, Abou-El-Ela SH, Hill RT. Bacterial Community Analyses of Two Red Sea Sponges. Mar Biotechnol. 2010;12(3):350–60. https://doi.org/10.1007/s10126-009-9239-5

    Article  CAS  Google Scholar 

  62. Vacelet J, Perez T. Phorbas Topsenti and Phorbas Tailliezi (Demospongiae, Poecilosclerida), New names for the Mediterranean Phorbas Paupertas and Phorbas Coriaceus. Zootaxa. 2008;1873(1):26. https://doi.org/10.11646/zootaxa.1873.1.3

    Article  Google Scholar 

  63. Soares AR. Diversity and specificity of the Marine Sponge Microbiome as inspected by next generation sequencing. masterThesis, 2016. https://sapientia.ualg.pt/handle/10400.1/8240 (accessed 2023-04-25).

  64. Wilson MC, Mori T, Rückert C, Uria AR, Helf MJ, Takada K, Gernert C, Steffens UAE, Heycke N, Schmitt S, Rinke C, Helfrich EJN, Brachmann AO, Gurgui C, Wakimoto T, Kracht M, Crüsemann M, Hentschel U, Abe I, Matsunaga S, Kalinowski J, Takeyama H, Piel J. An environmental bacterial taxon with a large and distinct metabolic repertoire. Nature. 2014;506(7486):58–62. https://doi.org/10.1038/nature12959

    Article  CAS  PubMed  Google Scholar 

  65. Grozdanov L, Hentschel U. An Environmental Genomics Perspective on the diversity and function of Marine Sponge-Associated Microbiota. Curr Opin Microbiol. 2007;10(3):215–20. https://doi.org/10.1016/j.mib.2007.05.012

    Article  CAS  PubMed  Google Scholar 

  66. Podell S, Blanton JM, Neu A, Agarwal V, Biggs JS, Moore BS, Allen EE. Pangenomic Comparison of Globally Distributed Poribacteria Associated with Sponge hosts and Marine particles. ISME J. 2019;13(2):468–81. https://doi.org/10.1038/s41396-018-0292-9

    Article  CAS  PubMed  Google Scholar 

  67. Caso A, Da Silva FB, Esposito G, Teta R, Sala GD, Cavalcanti LPAN, Valverde AL, Martins RCC, Costantino V. Exploring Chemical Diversity of Phorbas sponges as a source of novel lead compounds in Drug Discovery. Mar Drugs. 2021;19(12):667. https://doi.org/10.3390/md19120667

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Choi Y-H, Sohn J-H, Lee D, Kim JK, Kong IS, Ahn SC, Oh H. Chejuenolides A and B, New Macrocyclic Tetraenes from the Marine Bacterium Hahella Chejuensis. Tetrahedron Lett. 2008;49(50):7128–31. https://doi.org/10.1016/j.tetlet.2008.09.143

    Article  CAS  Google Scholar 

  69. Xiu A, Zhou M, Zhu B, Wang S, Zhang J. Rheological Properties of Salecan as a New source of Thickening Agent. Food Hydrocolloids. 2011;25(7):1719–25. https://doi.org/10.1016/j.foodhyd.2011.03.013

    Article  CAS  Google Scholar 

  70. Vályi-Nagy T, Úri J, Szilágyi I. Primycin, a New Antibiotic. Nature. 1954;174(4441):1105–6. https://doi.org/10.1038/1741105b0

    Article  PubMed  Google Scholar 

  71. Bewley CA, Holland ND, Faulkner DJ. Two classes of metabolites fromTheonella Swinhoei are localized in distinct populations of bacterial symbionts. Experientia. 1996;52(7):716–22. https://doi.org/10.1007/BF01925581

    Article  CAS  PubMed  Google Scholar 

  72. Piel J, Hui D, Wen G, Butzke D, Platzer M, Fusetani N, Matsunaga S. Antitumor Polyketide Biosynthesis by an uncultivated bacterial symbiont of the Marine Sponge Theonella Swinhoei. Proc Natl Acad Sci U S A. 2004;101(46):16222–7. https://doi.org/10.1073/pnas.0405976101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Hossam H. Elfeky for his great efforts in collecting sponges samples and also Dr. Elsayed Abd ElAziz Hamed, for his help in the morphological identification of sponges.

Funding

The research was supported by projects: “Characterization of meta-genome and meta-transcriptome of Microbes associated with Marine Invertebrates”, (Project number 2020 59) research project awarded by the Academy of Scientific Research and Technology (ASRT), Egypt and ‘Fermentative Production of Antimicrobial Drug Leads from Red Sea Sponges-Associated Microbes (Project number 2009–6420, funded by SIDA, Sweden).

Author information

Authors and Affiliations

  1. Department of Microbiology and Immunology, Faculty of Pharmacy, Suez Canal University, Ismailia, Egypt

    Manar El Samak, Samar M. Solyman, Amro Hanora & Samira Zakeer

  2. Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai Unvirsity Elkantra Branch, Ismailia, Egypt

    Samar M. Solyman

Authors
  1. Manar El Samak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samar M. Solyman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amro Hanora
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Samira Zakeer
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study’s conception and design. Manar El Samak developed, optimized, and apply experiments, and wrote the draft of this manuscript. Amro Hanora, Samar Solyman and Samira Zakeer reviewed this draft, contributed, and approved the final manuscript.

Corresponding author

Correspondence to Amro Hanora.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Suez Canal University ethics board under the number 201810PHD2. This study doesn’t use any human samples.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Samak, M.E., Solyman, S.M., Hanora, A. et al. Metagenomic mining of two Egyptian Red Sea sponges associated microbial community. BMC Microbiol 24, 315 (2024). https://doi.org/10.1186/s12866-024-03299-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12866-024-03299-0

Keywords

BMC Microbiology

ISSN: 1471-2180

Contact us