Predicting the HMA-LMA Status in Marine Sponges by Machine Learning

Metagenomic mining of two Egyptian Red Sea sponges associated microbial community

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.

Transcriptomic responses of Mediterranean sponges upon encounter with symbiont microbial consortia

BACKGROUND

Sponges (phylum Porifera) constantly interact with microbes. They graze on microbes from the water column by filter-feeding and they harbor symbiotic partners within their bodies. In experimental setups, sponges take up symbionts at lower rates compared with seawater microbes. This suggests that sponges have the capacity to differentiate between microbes and preferentially graze in non-symbiotic microbes, although the underlying mechanisms of discrimination are still poorly understood. Genomic studies showed that, compared to other animal groups, sponges present an extended repertoire of immune receptors, in particular NLRs, SRCRs, and GPCRs, and a handful of experiments showed that sponges regulate the expression of these receptors upon encounter with microbial elicitors. We hypothesize that sponges may rely on differential expression of their diverse repertoire of poriferan immune receptors to sense different microbial consortia while filter-feeding. To test this, we characterized the transcriptomic response of two sponge species, Aplysina aerophoba and Dysidea avara, upon incubation with microbial consortia extracted from A. aerophoba in comparison with incubation with seawater microbes. The sponges were sampled after 1 h, 3 h, and 5 h for RNA-Seq differential gene expression analysis.

RESULTS

D. avara incubated with A. aerophoba-symbionts regulated the expression of genes related to immunity, ubiquitination, and signaling. Within the set of differentially-expressed immune genes we identified different families of Nucleotide Oligomerization Domain (NOD)-Like Receptors (NLRs). These results represent the first experimental evidence that different types of NLRs are involved in microbial discrimination in a sponge. In contrast, the transcriptomic response of A. aerophoba to its own symbionts involved comparatively fewer genes and lacked genes encoding for immune receptors.

CONCLUSION

Our work suggests that: (i) the transcriptomic response of sponges upon microbial exposure may imply "fine-tuning" of baseline gene expression as a result of their interaction with microbes, (ii) the differential response of sponges to microbial encounters varied between the species, probably due to species-specific characteristics or related to host's traits, and (iii) immune receptors belonging to different families of NLR-like genes played a role in the differential response to microbes, whether symbionts or food bacteria. The regulation of these receptors in sponges provides further evidence of the potential role of NLRs in invertebrate host-microbe interactions. The study of sponge responses to microbes exemplifies how investigating different animal groups broadens our knowledge of the evolution of immune specificity and symbiosis.

Diversity and structure of the deep-sea sponge microbiome in the equatorial Atlantic Ocean

Sponges (phylum Porifera) harbour specific microbial communities that drive the ecology and evolution of the host. Understanding the structure and dynamics of these communities is emerging as a primary focus in marine microbial ecology research. Much of the work to date has focused on sponges from warm and shallow coastal waters, while sponges from the deep ocean remain less well studied. Here, we present a metataxonomic analysis of the microbial consortia associated with 23 individual deep-sea sponges. We identify a high abundance of archaea relative to bacteria across these communities, with certain sponge microbiomes comprising more than 90 % archaea. Specifically, the archaeal family Nitrosopumilaceae is prolific, comprising over 99 % of all archaeal reads. Our analysis revealed that sponge microbial communities reflect the host sponge phylogeny, indicating a key role for host taxonomy in defining microbiome composition. Our work confirms the contribution of both evolutionary and environmental processes to the composition of microbial communities in deep-sea sponges.

Prokaryotic communities of the French Polynesian sponge Dactylospongia metachromia display a site-specific and stable diversity during an aquaculture trial

Dynamics of microbiomes through time are fundamental regarding survival and resilience of their hosts when facing environmental alterations. As for marine species with commercial applications, such as marine sponges, assessing the temporal change of prokaryotic communities allows us to better consider the adaptation of sponges to aquaculture designs. The present study aims to investigate the factors shaping the microbiome of the sponge Dactylospongia metachromia, in a context of aquaculture development in French Polynesia, Rangiroa, Tuamotu archipelago. A temporal approach targeting explants collected during farming trials revealed a relative high stability of the prokaryotic diversity, meanwhile a complementary biogeographical study confirmed a spatial specificity amongst samples at different longitudinal scales. Results from this additional spatial analysis confirmed that differences in prokaryotic communities might first be explained by environmental changes (mainly temperature and salinity), while no significant effect of the host phylogeny was observed. The core community of D. metachromia is thus characterized by a high spatiotemporal constancy, which is a good prospect for the sustainable exploitation of this species towards drug development. Indeed, a microbiome stability across locations and throughout the farming process, as evidenced by our results, should go against a negative influence of sponge translocation during in situ aquaculture.

High microbiome and metabolome diversification in coexisting sponges with different bio-ecological traits

Marine Porifera host diverse microbial communities, which influence host metabolism and fitness. However, functional relationships between sponge microbiomes and metabolic signatures are poorly understood. We integrate microbiome characterization, metabolomics and microbial predicted functions of four coexisting Mediterranean sponges -Petrosia ficiformis, Chondrosia reniformis, Crambe crambe and Chondrilla nucula. Microscopy observations reveal anatomical differences in microbial densities. Microbiomes exhibit strong species-specific trends. C. crambe shares many rare amplicon sequence variants (ASV) with the surrounding seawater. This suggests important inputs of microbial diversity acquired by selective horizontal acquisition. Phylum Cyanobacteria is mainly represented in C. nucula and C. crambe. According to putative functions, the microbiome of P. ficiformis and C. reniformis are functionally heterotrophic, while C. crambe and C. nucula are autotrophic. The four species display distinct metabolic profiles at single compound level. However, at molecular class level they share a "core metabolome". Concurrently, we find global microbiome-metabolome association when considering all four sponge species. Within each species still, sets of microbe/metabolites are identified driving multi-omics congruence. Our findings suggest that diverse microbial players and metabolic profiles may promote niche diversification, but also, analogous phenotypic patterns of "symbiont evolutionary convergence" in sponge assemblages where holobionts co-exist in the same area.

Unveiling microbial guilds and symbiotic relationships in Antarctic sponge microbiomes

Marine sponges host diverse microbial communities. Although we know many of its ecological patterns, a deeper understanding of the polar sponge holobiont is still needed. We combine high-throughput sequencing of ribosomal genes, including the largest taxonomic repertoire of Antarctic sponge species analyzed to date, functional metagenomics, and metagenome-assembled genomes (MAGs). Our findings show that sponges harbor more exclusive bacterial and archaeal communities than seawater, while microbial eukaryotes are mostly shared. Furthermore, bacteria in Antarctic sponge holobionts establish more cooperative interactions than in sponge holobionts from other environments. The bacterial classes that established more positive relations were Bacteroidia, Gamma- and Alphaproteobacteria. Antarctic sponge microbiomes contain microbial guilds that encompass ammonia-oxidizing archaea, ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and sulfur-oxidizing bacteria. The retrieved MAGs showed a high level of novelty and streamlining signals and belong to the most abundant members of the main microbial guilds in the Antarctic sponge holobiont. Moreover, the genomes of these symbiotic bacteria contain highly abundant functions related to their adaptation to the cold environment, vitamin production, and symbiotic lifestyle, helping the holobiont survive in this extreme environment.

The archaeome in metaorganism research, with a focus on marine models and their bacteria-archaea interactions

Metaorganism research contributes substantially to our understanding of the interaction between microbes and their hosts, as well as their co-evolution. Most research is currently focused on the bacterial community, while archaea often remain at the sidelines of metaorganism-related research. Here, we describe the archaeome of a total of eleven classical and emerging multicellular model organisms across the phylogenetic tree of life. To determine the microbial community composition of each host, we utilized a combination of archaea and bacteria-specific 16S rRNA gene amplicons. Members of the two prokaryotic domains were described regarding their community composition, diversity, and richness in each multicellular host. Moreover, association with specific hosts and possible interaction partners between the bacterial and archaeal communities were determined for the marine models. Our data show that the archaeome in marine hosts predominantly consists of Nitrosopumilaceae and Nanoarchaeota, which represent keystone taxa among the porifera. The presence of an archaeome in the terrestrial hosts varies substantially. With respect to abundant archaeal taxa, they harbor a higher proportion of methanoarchaea over the aquatic environment. We find that the archaeal community is much less diverse than its bacterial counterpart. Archaeal amplicon sequence variants are usually host-specific, suggesting adaptation through co-evolution with the host. While bacterial richness was higher in the aquatic than the terrestrial hosts, a significant difference in diversity and richness between these groups could not be observed in the archaeal dataset. Our data show a large proportion of unclassifiable archaeal taxa, highlighting the need for improved cultivation efforts and expanded databases.

Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology

Due to the complex nature of microbiome data, the field of microbial ecology has many current and potential uses for machine learning (ML) modeling. With the increased use of predictive ML models across many disciplines, including microbial ecology, there is extensive published information on the specific ML algorithms available and how those algorithms have been applied. Thus, our goal is not to summarize the breadth of ML models available or compare their performances. Rather, our goal is to provide more concrete and actionable information to guide microbial ecologists in how to select, run, and interpret ML algorithms to predict the taxa or genes associated with particular sample categories or environmental gradients of interest. Such microbial data often have unique characteristics that require careful consideration of how to apply ML models and how to interpret the associated results. This review is intended for practicing microbial ecologists who may be unfamiliar with some of the intricacies of ML models. We provide examples and discuss common opportunities and pitfalls specific to applying ML models to the types of data sets most frequently collected by microbial ecologists.

Impacts of humic substances, elevated temperature, and UVB radiation on bacterial communities of the marine sponge Chondrilla sp

Sponges are abundant components of coral reefs known for their filtration capabilities and intricate interactions with microbes. They play a crucial role in maintaining the ecological balance of coral reefs. Humic substances (HS) affect bacterial communities across terrestrial, freshwater, and marine ecosystems. However, the specific effects of HS on sponge-associated microbial symbionts have largely been neglected. Here, we used a randomized-controlled microcosm setup to investigate the independent and interactive effects of HS, elevated temperature, and UVB radiation on bacterial communities associated with the sponge Chondrilla sp. Our results indicated the presence of a core bacterial community consisting of relatively abundant members, apparently resilient to the tested environmental perturbations, alongside a variable bacterial community. Elevated temperature positively affected the relative abundances of ASVs related to Planctomycetales and members of the families Pseudohongiellaceae and Hyphomonadaceae. HS increased the relative abundances of several ASVs potentially involved in recalcitrant organic matter degradation (e.g., the BD2-11 terrestrial group, Saccharimonadales, and SAR202 clade). There was no significant independent effect of UVB and there were no significant interactive effects of HS, heat, and UVB on bacterial diversity and composition. The significant, independent impact of HS on the composition of sponge bacterial communities suggests that alterations to HS inputs may have cascading effects on adjacent marine ecosystems.

High compositional and functional similarity in the microbiome of deep-sea sponges

Sponges largely depend on their symbiotic microbes for their nutrition, health, and survival. This is especially true in high microbial abundance (HMA) sponges, where filtration is usually deprecated in favor of a larger association with prokaryotic symbionts. Sponge-microbiome association is substantially less understood for deep-sea sponges than for shallow water species. This is most unfortunate, since HMA sponges can form massive sponge grounds in the deep sea, where they dominate the ecosystems, driving their biogeochemical cycles. Here, we assess the microbial transcriptional profile of three different deep-sea HMA sponges in four locations of the Cantabrian Sea and compared them to shallow water HMA and LMA (low microbial abundance) sponge species. Our results reveal that the sponge microbiome has converged in a fundamental metabolic role for deep-sea sponges, independent of taxonomic relationships or geographic location, which is shared in broad terms with shallow HMA species. We also observed a large number of redundant microbial members performing the same functions, likely providing stability to the sponge inner ecosystem. A comparison between the community composition of our deep-sea sponges and another 39 species of HMA sponges from deep-sea and shallow habitats, belonging to the same taxonomic orders, suggested strong homogeneity in microbial composition (i.e. weak species-specificity) in deep sea species, which contrasts with that observed in shallow water counterparts. This convergence in microbiome composition and functionality underscores the adaptation to an extremely restrictive environment with the aim of exploiting the available resources.

Profiling Prokaryotic Communities and Aaptamines of Sponge Aaptos suberitoides from Tulamben, Bali

Sponges (Porifera) harbor a diversity of microorganisms that contribute largely to the production a vast array of bioactive compounds. The microorganisms associated with sponge have an important impact on the chemical diversity of the natural products. Herein, our study focuses on an Aaptos suberitoides commonly found in Indonesia. The objective of this study was to investigate the profile of prokaryotic community and the presence of aaptamine metabolites in sponge Aaptos suberitoides. Sponges were collected from two site locations (Liberty Wreck and Drop Off) in Tulamben, Bali. The sponges were identified by barcoding DNA cytochrome oxidase subunit I (COI) gene. The profile of prokaryotic composition was investigated by amplifying the 16S rRNA gene using primers 515f and 806r to target the V4 region. The metabolites were analyzed using LC-MS, and dereplication was done to identify the aaptamines and its derivates. The barcoding DNA of the sponges confirmed the identity of samples as Aaptos suberitoides. The prokaryotic communities of samples A. suberitoides were enriched and dominated by taxa Proteobacteria, Chloroflexi, Actinobacteria, and Acidobacteria. The chemical analysis showed that all sponges produce aaptamine and isoaaptamine except A. suberitoides S2421 produce analog of aaptamines. This is the first report on the profile of prokaryotic community and the aaptamine of tropical marine sponges, A. suberitoides, from Tulamben, Bali.

MiTree: A Unified Web Cloud Analytic Platform for User-Friendly and Interpretable Microbiome Data Mining Using Tree-Based Methods

The advent of next-generation sequencing has greatly accelerated the field of human microbiome studies. Currently, investigators are seeking, struggling and competing to find new ways to diagnose, treat and prevent human diseases through the human microbiome. Machine learning is a promising approach to help such an effort, especially due to the high complexity of microbiome data. However, many of the current machine learning algorithms are in a "black box", i.e., they are difficult to understand and interpret. In addition, clinicians, public health practitioners and biologists are not usually skilled at computer programming, and they do not always have high-end computing devices. Thus, in this study, we introduce a unified web cloud analytic platform, named MiTree, for user-friendly and interpretable microbiome data mining. MiTree employs tree-based learning methods, including decision tree, random forest and gradient boosting, that are well understood and suited to human microbiome studies. We also stress that MiTree can address both classification and regression problems through covariate-adjusted or unadjusted analysis. MiTree should serve as an easy-to-use and interpretable data mining tool for microbiome-based disease prediction modeling, and should provide new insights into microbiome-based diagnostics, treatment and prevention. MiTree is an open-source software that is available on our web server.

A Study of Sponge Symbionts from Different Light Habitats

The amount of available light plays a key role in the growth and development of microbial communities. In the present study, we tested to what extent sponge-associated prokaryotic communities differed between specimens of the sponge species Cinachyrella kuekenthali and Xestospongia muta collected in dimly lit (caves and at greater depths) versus illuminated (shallow water) habitats. In addition to this, we also collected samples of water, sediment, and another species of Cinachyrella, C. alloclada. Overall, the biotope (sponge host species, sediment, and seawater) proved the major driver of variation in prokaryotic community composition. The light habitat, however, also proved a predictor of compositional variation in prokaryotic communities of both C. kuekenthali and X. muta. We used an exploratory technique based on machine learning to identify features (classes, orders, and OTUs), which distinguished X. muta specimens sampled in dimly lit versus illuminated habitat. We found that the classes Alphaproteobacteria and Rhodothermia and orders Puniceispirillales, Rhodospirillales, Rhodobacterales, and Thalassobaculales were associated with specimens from illuminated, i.e., shallow water habitat, while the classes Dehalococcoidia, Spirochaetia, Entotheonellia, Nitrospiria, Schekmanbacteria, and Poribacteria, and orders Sneathiellales and Actinomarinales were associated with specimens sampled from dimly lit habitat. There was, however, considerable variation within the different light habitats highlighting the importance of other factors in structuring sponge-associated bacterial communities.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

Microbiome diversity from sponges biogeographically distributed between South America and Antarctica

Sponges from South America and Antarctica are evolutionarily closely related. Specific symbiont signatures that could differentiate these two geographic regions are unknown. This study aimed to investigate the microbiome diversity of sponges from South America and Antarctica. In total 71 sponge specimens were analyzed (Antarctica: N = 59, 13 different species; South America: N = 12, 6 different species). Illumina 16S rRNA sequences were generated (2.88 million sequences; 40K ± 29K/sample). The most abundant symbionts were heterotrophic (94.8 %) and belonged mainly to Proteobacteria and Bacteroidota. EC94 was the most abundant symbiont and dominated the microbiome of some species (70-87 %), comprising at least 10 phylogroups. Each of the EC94 phylogroups was specific to one genus or species of sponge. Furthermore, South America sponges had higher abundance of photosynthetic microorganisms (2.3 %) and sponges from Antarctica, the highest abundance of chemosynthetic (5.5 %). Sponge symbionts may contribute to the function of their hosts. The unique features from each of these two regions (e.g., light, temperature, and nutrients) possibly stimulate distinct microbiome diversity from sponges biogeographically distributed across continents.

V, Vijayan NT, Subramanian M, Gauns MU. Applications of Machine Learning in Chemical and Biological Oceanography

Machine learning (ML) refers to computer algorithms that predict a meaningful output or categorize complex systems based on a large amount of data. ML is applied in various areas including natural science, engineering, space exploration, and even gaming development. This review focuses on the use of machine learning in the field of chemical and biological oceanography. In the prediction of global fixed nitrogen levels, partial carbon dioxide pressure, and other chemical properties, the application of ML is a promising tool. Machine learning is also utilized in the field of biological oceanography to detect planktonic forms from various images (i.e., microscopy, FlowCAM, and video recorders), spectrometers, and other signal processing techniques. Moreover, ML successfully classified the mammals using their acoustics, detecting endangered mammalian and fish species in a specific environment. Most importantly, using environmental data, the ML proved to be an effective method for predicting hypoxic conditions and harmful algal bloom events, an essential measurement in terms of environmental monitoring. Furthermore, machine learning was used to construct a number of databases for various species that will be useful to other researchers, and the creation of new algorithms will help the marine research community better comprehend the chemistry and biology of the ocean.

Sponge organic matter recycling: Reduced detritus production under extreme environmental conditions

Sponges are a key component of coral reef ecosystems and play an important role in carbon and nutrient cycles. Many sponges are known to consume dissolved organic carbon and transform this into detritus, which moves through detrital food chains and eventually to higher trophic levels via what is known as the sponge loop. Despite the importance of this loop, little is known about how these cycles will be impacted by future environmental conditions. During two years (2018 and 2020), we measured the organic carbon, nutrient recycling, and photosynthetic activity of the massive HMA, photosymbiotic sponge Rhabdastrella globostellata at the natural laboratory of Bouraké in New Caledonia, where the physical and chemical composition of seawater regularly change according to the tide. We found that while sponges experienced acidification and low dissolved oxygen at low tide in both sampling years, a change in organic carbon recycling whereby sponges stopped producing detritus (i.e., the sponge loop) was only found when sponges also experienced higher temperature in 2020. Our findings provide new insights into how important trophic pathways may be affected by changing ocean conditions.

Diversity and structure of bacterial and archaeal communities associated with the vulnerable sponge Halichondria cebimarensis

Sponges are essential components of the marine benthos and well known for their complex and abundant associated microbial communities. There are five endemic species of the genus Halichondria on the Brazilian coast and H. cebimarensis is one of the least studied. This sponge has a very limited geographic distribution and is classified as vulnerable. In order to understand the bacterial and archaeal communities associated with this sponge, samples of H. cebimarensis were collected from the southwestern Atlantic coast (Brazil, São Paulo state). Choanosome samples were separated and processed to be (i) inoculated in three different culture media; (ii) investigated by transmission electron microscopy; (iii) submitted to 16S rRNA metabarcoding. Forty isolates were obtained and 12 were identified as belonging to the Bacilli class. The culture-dependent approaches allowed us to access unique members of the microbial community. Our analyses revealed that this animal belongs to the Low Microbial Abundance group of sponges. Culture-independent approaches showed that the H. cebimarensis microbiome is dominated by the heterotrophic Gammaproteobacteria AqS2 ("Ca. Amphirhobacter heronislandensis"). This is the first study to reveal details of the microbiome of this vulnerable sponge and is an important step in understanding how this sponge functions, its biotechnological potential and a contribution to conservation efforts.

Impact of Marine Chemical Ecology Research on the Discovery and Development of New Pharmaceuticals

Diverse ecologically important metabolites, such as allelochemicals, infochemicals and volatile organic chemicals, are involved in marine organismal interactions. Chemically mediated interactions between intra- and interspecific organisms can have a significant impact on community organization, population structure and ecosystem functioning. Advances in analytical techniques, microscopy and genomics are providing insights on the chemistry and functional roles of the metabolites involved in such interactions. This review highlights the targeted translational value of several marine chemical ecology-driven research studies and their impact on the sustainable discovery of novel therapeutic agents. These chemical ecology-based approaches include activated defense, allelochemicals arising from organismal interactions, spatio-temporal variations of allelochemicals and phylogeny-based approaches. In addition, innovative analytical techniques used in the mapping of surface metabolites as well as in metabolite translocation within marine holobionts are summarized. Chemical information related to the maintenance of the marine symbioses and biosyntheses of specialized compounds can be harnessed for biomedical applications, particularly in microbial fermentation and compound production. Furthermore, the impact of climate change on the chemical ecology of marine organisms—especially on the production, functionality and perception of allelochemicals—and its implications on drug discovery efforts will be presented.

A comparison of free-living and sponge-associated bacterial communities from a remote oceanic island with a focus on calcareous sponges

Calcareous sponges are an often overlooked element of sponge communities. In contrast to most other sponges, calcareous sponges produce calcium carbonate spicules, as opposed to the siliceous spicules of most sponges. Here, we investigated the bacterial communities of 17 sponge species, including type and paratype specimens of recently described calcareous species, sampled off the remote island of Rodrigues, in the Indian Ocean. The main axis of variation in a PCO analysis of all samples separated noncalcareous sponge species, including Axinyssa aplysinoides, Cinachyrella aff. australiensis, Petrosia seychellensis, Ircinia aff. variabilis, Spongia ceylonensis, Plakinastrella aff. clipptertonensis, Agelas aff. ceylonica, Agelas aff. mauritiana, and Hyrtios erectus from calcareous sponges, the noncalcareous Biemna tubulata, sediment, and seawater. Overall, the bacterial communities of calcareous sponges revealed unique prokaryotic profiles with low abundances of several bacterial phyla, and relatively high abundances of other taxa, for example, the phyla Fibrobacterota, Proteobacteria, and the SAR324 clade, the class Alphaproteobacteria, and orders Cytophagales and Cyanobacteriales, although there was considerable variation among species. Calcareous sponges also had a high dominance of unknown bacterial operational taxonomic units (OTUs). Considering the unique nature of these communities, further studies are needed to better understand the environmental and ecological drivers of calcareous sponge-associated bacterial communities and their relevance as potential sources of novel microbes of biotechnological interest.

Uncovering the Microbial Diversity of Two Exotic Calcareous Sponges

Sponges-associated microorganisms play important roles in their health and ecology; consequently, they may be crucial in the successful adaptation of exotic species to novel environments. However, few studies have focused on the microbial diversity of exotic sponges, especially those with calcium carbonate spicules (class Calcarea). Therefore, this is the first in situ characterization of the microbiota of the exotic calcareous sponges Sycettusa hastifera and Paraleucilla magna. Our results suggest that S. hastifera has a more stable microbiota than P. magna, as there were no differences in its beta diversity among sampling sites. Conversely, P. magna showed significant differences in its microbial communities, perhaps related to its adhesion to artificial substrate and/or shellfish mariculture activities. Each sponge species presented a single dominant proteobacterial OTU potentially active in the nitrogen cycle, which could help sponge detoxification, especially in polluted areas where exotic species usually establish. Our results show the importance of assessing the microbial diversity to unveil host-microorganism relationships and suggest that these associated nitrogen-cycling microorganisms could favor the success of exotic sponges in new environments.

Limited Metabolomic Overlap between Commensal Bacteria and Marine Sponge Holobionts Revealed by Large Scale Culturing and Mass Spectrometry-Based Metabolomics: An Undergraduate Laboratory Pedagogical Effort at Georgia Tech

Sponges are the richest source of bioactive organic small molecules, referred to as natural products, in the marine environment. It is well established that laboratory culturing-resistant symbiotic bacteria residing within the eukaryotic sponge host matrix often synthesize the natural products that are detected in the sponge tissue extracts. However, the contributions of the culturing-amenable commensal bacteria that are also associated with the sponge host to the overall metabolome of the sponge holobiont are not well defined. In this study, we cultured a large library of bacteria from three marine sponges commonly found in the Florida Keys. Metabolomes of isolated bacterial strains and that of the sponge holobiont were compared using mass spectrometry to reveal minimal metabolomic overlap between commensal bacteria and the sponge hosts. We also find that the phylogenetic overlap between cultured commensal bacteria and that of the sponge microbiome is minimal. Despite these observations, the commensal bacteria were found to be a rich resource for novel natural product discovery. Mass spectrometry-based metabolomics provided structural insights into these cryptic natural products. Pedagogic innovation in the form of laboratory curricula development is described which provided undergraduate students with hands-on instruction in microbiology and natural product discovery using metabolomic data mining strategies.

Stability of a dominant sponge-symbiont in spite of antibiotic-induced microbiome disturbance

Marine sponges are known for their complex and stable microbiomes. However, the lack of a gnotobiotic sponge-model and experimental methods to manipulate both the host and the microbial symbionts currently limit our mechanistic understanding of sponge-microbial symbioses. We have used the North Atlantic sponge species Halichondria panicea to evaluate the use of antibiotics to generate gnotobiotic sponges. We further asked whether the microbiome can be reestablished via recolonization with the natural microbiome. Experiments were performed in marine gnotobiotic facilities equipped with a custom-made, sterile, flow-through aquarium system. Bacterial abundance dynamics were monitored qualitatively and quantitatively by 16 S rRNA gene amplicon sequencing and qPCR, respectively. Antibiotics induced dysbiosis by favouring an increase of opportunistic, antibiotic-resistant bacteria, resulting in more complex, but less specific bacteria-bacteria interactions than in untreated sponges. The abundance of the dominant symbiont, Candidatus Halichondribacter symbioticus, remained overall unchanged, reflecting its obligately symbiotic nature. Recolonization with the natural microbiome could not reverse antibiotic-induced dysbiosis. However, single bacterial taxa that were transferred, successfully recolonized the sponge and affected bacteria-bacteria interactions. By experimentally manipulating microbiome composition, we could show the stability of a sponge-symbiont clade despite microbiome dysbiosis. This study contributes to understanding both host-bacteria and bacteria-bacteria interactions in the sponge holobiont.

Microbiome diversity and metabolic capacity determines the trophic ecology of the holobiont in Caribbean sponges

Sponges are increasingly recognized as an ecologically important taxon on coral reefs, representing significant biomass and biodiversity where sponges have replaced scleractinian corals. Most sponge species can be divided into two symbiotic states based on symbiont community structure and abundance (i.e., the microbiome), and are characterized as high microbial abundance (HMA) or low microbial abundance (LMA) sponges. Across the Caribbean, sponge species of the HMA or LMA symbiotic states differ in metabolic capacity, as well as their trophic ecology. A metagenetic analysis of symbiont 16 S rRNA and metagenomes showed that HMA sponge microbiomes are more functionally diverse than LMA microbiomes, offer greater metabolic functional capacity and redundancy, and encode for the biosynthesis of secondary metabolites. Stable isotope analyses showed that HMA and LMA sponges primarily consume dissolved organic matter (DOM) derived from external autotrophic sources, or live particulate organic matter (POM) in the form of bacterioplankton, respectively, resulting in a low degree of resource competition between these symbiont states. As many coral reefs have undergone phase shifts from coral- to macroalgal-dominated reefs, the role of DOM, and the potential for future declines in POM due to decreased picoplankton productivity, may result in an increased abundance of chemically defended HMA sponges on tropical coral reefs.

Environmental DNA persistence and fish detection in captive sponges

Large and hyperdiverse marine ecosystems pose significant challenges to biodiversity monitoring. While environmental DNA (eDNA) promises to meet many of these challenges, recent studies suggested that sponges, as "natural samplers" of eDNA, could further streamline the workflow for detecting marine vertebrates. However, beyond pilot studies demonstrating the ability of sponges to capture eDNA, little is known about the dynamics of eDNA particles in sponge tissue, and the effectiveness of the latter compared to water samples. Here, we present the results of a controlled aquarium experiment to examine the persistence and detectability of eDNA captured by three encrusting sponge species and compare the sponge's eDNA capturing ability with established water filtration techniques. Our results indicate that sponges and water samples have highly similar detectability for fish of different sizes and abundances, but different sponge species exhibit considerable variance in performance. Interestingly, one sponge appeared to mirror the eDNA degradation profile of water samples, while another sponge retained eDNA throughout the experiment. A third sponge yielded virtually no DNA sequences at all. Overall, our study suggests that some sponges will be suitable as natural samplers, while others will introduce significant problems for laboratory processing. We suggest that an initial optimization phase will be required in any future studies aiming to employ sponges for biodiversity assessment. With time, factoring in technical and natural accessibility, it is expected that specific sponge taxa may become the "chosen" natural samplers in certain habitats and regions.

Global patterns in symbiont selection and transmission strategies in sponges

Sponges host dense and diverse communities of microbes (known as the microbiome) beneficial for the host nutrition and defense. Symbionts in turn receive shelter and metabolites from the sponge host, making their relationship beneficial for both partners. Given that sponge-microbes associations are fundamental for the survival of both, especially the sponge, such relationship is maintained through their life and even passed on to the future generations. In many organisms, the microbiome has profound effects on the development of the host, but the influence of the microbiome on the reproductive and developmental pathways of the sponges are less understood. In sponges, microbes are passed on to oocytes, sperm, embryos, and larvae (known as vertical transmission), using a variety of methods that include direct uptake from the mesohyl through phagocytosis by oocytes to indirect transmission to the oocyte by nurse cells. Such microbes can remain in the reproductive elements untouched, for transfer to offspring, or can be digested to make the yolky nutrient reserves of oocytes and larvae. When and how those decisions are made are fundamentally unanswered questions in sponge reproduction. Here we review the diversity of vertical transmission modes existent in the entire phylum Porifera through detailed imaging using electron microscopy, available metabarcoding data from reproductive elements, and macroevolutionary patterns associated to phylogenetic constraints. Additionally, we examine the fidelity of this vertical transmission and possible reasons for the observed variability in some developmental stages. Our current understanding in marine sponges, however, is that the adult microbial community is established by a combination of both vertical and horizontal (acquisition from the surrounding environment in each new generation) transmission processes, although the extent in which each mode shapes the adult microbiome still remains to be determined. We also assessed the fundamental role of filtration, the cellular structures for acquiring external microbes, and the role of the host immune system, that ultimately shapes the stable communities of prokaryotes observed in adult sponges.

Machine learning and deep learning applications in microbiome research

The many microbial communities around us form interactive and dynamic ecosystems called microbiomes. Though concealed from the naked eye, microbiomes govern and influence macroscopic systems including human health, plant resilience, and biogeochemical cycling. Such feats have attracted interest from the scientific community, which has recently turned to machine learning and deep learning methods to interrogate the microbiome and elucidate the relationships between its composition and function. Here, we provide an overview of how the latest microbiome studies harness the inductive prowess of artificial intelligence methods. We start by highlighting that microbiome data - being compositional, sparse, and high-dimensional - necessitates special treatment. We then introduce traditional and novel methods and discuss their strengths and applications. Finally, we discuss the outlook of machine and deep learning pipelines, focusing on bottlenecks and considerations to address them.

Spatial and environmental variables structure sponge symbiont communities

Understanding the maintenance and origin of beta diversity is a central topic in ecology. However, the factors that drive diversity patterns and underlying processes remain unclear, particularly for host-prokaryotic associations. Here, beta diversity patterns were studied in five prokaryotic biotopes, namely, two high microbial abundance (HMA) sponge taxa (Xestospongia spp. and Hyrtios erectus), one low microbial abundance (LMA) sponge taxon (Stylissa carteri), sediment and seawater sampled across thousands of kilometres. Using multiple regression on distance matrices (MRM), spatial (geographic distance) and environmental (sea surface temperature and chlorophyll α concentrations) variables proved significant predictors of beta diversity in all five biotopes and together explained from 54% to 82% of variation in dissimilarity of both HMA species, 27% to 43% of variation in sediment and seawater, but only 20% of variation of the LMA S. carteri. Variance partitioning was subsequently used to partition the variation into purely spatial, purely environmental and spatially-structured environmental components. The amount of variation in dissimilarity explained by the purely spatial component was lowest for S. carteri at 11% and highest for H. erectus at 55%. The purely environmental component, in turn, only explained from 0.15% to 2.83% of variation in all biotopes. In addition to spatial and environmental variables, a matrix of genetic differences between pairs of sponge individuals also proved a significant predictor of variation in prokaryotic dissimilarity of the Xestospongia species complex. We discuss the implications of these results for the HMA-LMA dichotomy and compare the MRM results with results obtained using constrained ordination and zeta diversity.

Biodiversity, environmental drivers, and sustainability of the global deep-sea sponge microbiome

In the deep ocean symbioses between microbes and invertebrates are emerging as key drivers of ecosystem health and services. We present a large-scale analysis of microbial diversity in deep-sea sponges (Porifera) from scales of sponge individuals to ocean basins, covering 52 locations, 1077 host individuals translating into 169 sponge species (including understudied glass sponges), and 469 reference samples, collected anew during 21 ship-based expeditions. We demonstrate the impacts of the sponge microbial abundance status, geographic distance, sponge phylogeny, and the physical-biogeochemical environment as drivers of microbiome composition, in descending order of relevance. Our study further discloses that fundamental concepts of sponge microbiology apply robustly to sponges from the deep-sea across distances of >10,000 km. Deep-sea sponge microbiomes are less complex, yet more heterogeneous, than their shallow-water counterparts. Our analysis underscores the uniqueness of each deep-sea sponge ground based on which we provide critical knowledge for conservation of these vulnerable ecosystems.

This study presents a large-scale analysis of microbial diversity in deep-sea sponges. They show that sponge microbial abundance status, geographic distance, sponge phylogeny and the physical-biogeochemical environment drive microbiome composition, in descending order of relevance. The uniqueness of each deep-sea sponge ground stresses the need for their strategic preservation.

Comparative Metagenomic Analysis of Biosynthetic Diversity across Sponge Microbiomes Highlights Metabolic Novelty, Conservation, and Diversification

Marine sponges and their microbial symbiotic communities are rich sources of diverse natural products (NPs) that often display biological activity, yet little is known about the global distribution of NPs and the symbionts that produce them. Since the majority of sponge symbionts remain uncultured, it is a challenge to characterize their NP biosynthetic pathways, assess their prevalence within the holobiont, and measure the diversity of NP biosynthetic gene clusters (BGCs) across sponge taxa and environments. Here, we explore the microbial biosynthetic landscapes of three high-microbial-abundance (HMA) sponges from the Atlantic Ocean and the Mediterranean Sea. This data set reveals striking novelty, with <1% of the recovered gene cluster families (GCFs) showing similarity to any characterized BGC. When zooming in on the microbial communities of each sponge, we observed higher variability of specialized metabolic and taxonomic profiles between sponge species than within species. Nonetheless, we identified conservation of GCFs, with 20% of sponge GCFs being shared between at least two sponge species and a GCF core comprised of 6% of GCFs shared across all species. Within this functional core, we identified a set of widespread and diverse GCFs encoding nonribosomal peptide synthetases that are potentially involved in the production of diversified ether lipids, as well as GCFs putatively encoding the production of highly modified proteusins. The present work contributes to the small, yet growing body of data characterizing NP landscapes of marine sponge symbionts and to the cryptic biosynthetic potential contained in this environmental niche. IMPORTANCE Marine sponges and their microbial symbiotic communities are a rich source of diverse natural products (NPs). However, little is known about the sponge NP global distribution landscape and the symbionts that produce them. Here, we make use of recently developed tools to perform untargeted mining and comparative analysis of sponge microbiome metagenomes of three sponge species in the first study considering replicate metagenomes of multiple sponge species. We present an overview of the biosynthetic diversity across these sponge holobionts, which displays extreme biosynthetic novelty. We report not only the conservation of biosynthetic and taxonomic diversity but also a core of conserved specialized metabolic pathways. Finally, we highlight several novel GCFs with unknown ecological function, and observe particularly high biosynthetic potential in Acidobacteriota and Latescibacteria symbionts. This study paves the way toward a better understanding of the marine sponge holobionts' biosynthetic potential and the functional and ecological role of sponge microbiomes.

Microbiome composition of the marine sponge Cliona varians at the Neotropical Southern Caribbean Sea displays a predominant core of Rhizobiales and Nitrosopumilaceae

AIMS

This work aims to characterize the microbial diversity of the encrusting sponge Cliona varians, a pore-forming and coral reef bioeroding marine sponge of emerging spread related to ocean acidification.

METHODS AND RESULTS

We analyzed the microbiome composition by 16S V4 amplicon next-generation sequencing in a community of the bioeroding coral-reef encrusting/excavating marine sponge Cliona varians thriving at the Southern Caribbean Sea. 87.21% and 6.76% of the sequences retrieved were assigned to the domain Bacteria and Archaea. The most predominant operational taxonomic units were classified as members of the order Rhizobiales and family Nitrosopumilaceae, representing members of not yet characterized genera. Features found strictly conserved in the strain/genomic representatives reported in those microbial taxa are nitrogen fixation and transformation.

CONCLUSION

Our results suggest, in accordance with recent results, that these microbiome members and associated functions could be contributing to the biological fitness of the sponge to be able to colonize and bioerode in environments with low access and scarce availability of nitrogen source.

SIGNIFICANCE AND IMPACT OF STUDY

Coral reefs bioresources such as sponge holobionts are intriguing and complex ecosystems units. This study contributes to the knowledge of how C. varians microbiota is composed or shaped, which is crucial to understand its ecological functions.

Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India

The recent advancement in data science coupled with the revolution in digital and satellite technology has improved the potential for artificial intelligence (AI) applications in the forestry and wildlife sectors. India shares 7% of global forest cover and is the 8th most biodiverse region in the world. However, rapid expansion of developmental projects, agriculture, and urban areas threaten the country’s rich biodiversity. Therefore, the adoption of new technologies like AI in Indian forests and biodiversity sectors can help in effective monitoring, management, and conservation of biodiversity and forest resources. We conducted a systematic search of literature related to the application of artificial intelligence (AI) and machine learning algorithms (ML) in the forestry sector and biodiversity conservation across globe and in India (using ISI Web of Science and Google Scholar). Additionally, we also collected data on AI-based startups and non-profits in forest and wildlife sectors to understand the growth and adoption of AI technology in biodiversity conservation, forest management, and related services. Here, we first provide a global overview of AI research and application in forestry and biodiversity conservation. Next, we discuss adoption challenges of AI technologies in the Indian forestry and biodiversity sectors. Overall, we find that adoption of AI technology in Indian forestry and biodiversity sectors has been slow compared to developed, and to other developing countries. However, improving access to big data related to forest and biodiversity, cloud computing, and digital and satellite technology can help improve adoption of AI technology in India. We hope that this synthesis will motivate forest officials, scientists, and conservationists in India to explore AI technology for biodiversity conservation and forest management.

Explainable Machine Learning for Longitudinal Multi-Omic Microbiome

Over the years, research studies have shown there is a key connection between the microbial community in the gut, genes, and immune system. Understanding this association may help discover the cause of complex chronic idiopathic disorders such as inflammatory bowel disease. Even though important efforts have been put into the field, the functions, dynamics, and causation of dysbiosis state performed by the microbial community remains unclear. Machine learning models can help elucidate important connections and relationships between microbes in the human host. Our study aims to extend the current knowledge of associations between the human microbiome and health and disease through the application of dynamic Bayesian networks to describe the temporal variation of the gut microbiota and dynamic relationships between taxonomic entities and clinical variables. We develop a set of preprocessing steps to clean, filter, select, integrate, and model informative metagenomics, metatranscriptomics, and metabolomics longitudinal data from the Human Microbiome Project. This study accomplishes novel network models with satisfactory predictive performance (accuracy = 0.648) for each inflammatory bowel disease state, validating Bayesian networks as a framework for developing interpretable models to help understand the basic ways the different biological entities (taxa, genes, metabolites) interact with each other in a given environment (human gut) over time. These findings can serve as a starting point to advance the discovery of novel therapeutic approaches and new biomarkers for precision medicine.

Cophylogeny and convergence shape holobiont evolution in sponge-microbe symbioses

Symbiotic microbial communities of sponges serve critical functions that have shaped the evolution of reef ecosystems since their origins. Symbiont abundance varies tremendously among sponges, with many species classified as either low microbial abundance (LMA) or high microbial abundance (HMA), but the evolutionary dynamics of these symbiotic states remain unknown. This study examines the LMA/HMA dichotomy across an exhaustive sampling of Caribbean sponge biodiversity and predicts that the LMA symbiotic state is the ancestral state among sponges. Conversely, HMA symbioses, consisting of more specialized microorganisms, have evolved multiple times by recruiting similar assemblages, mostly since the rise of scleractinian-dominated reefs. Additionally, HMA symbioses show stronger signals of phylosymbiosis and cophylogeny, consistent with stronger co-evolutionary interaction in these complex holobionts. These results indicate that HMA holobionts are characterized by increased endemism, metabolic dependence and chemical defences. The selective forces driving these patterns may include the concurrent increase in dissolved organic matter in reef ecosystems or the diversification of spongivorous fishes.

BiGAMi: Bi-Objective Genetic Algorithm Fitness Function for Feature Selection on Microbiome Datasets

The relationship between the host and the microbiome, or the assemblage of microorganisms (including bacteria, archaea, fungi, and viruses), has been proven crucial for its health and disease development. The high dimensionality of microbiome datasets has often been addressed as a major difficulty for data analysis, such as the use of machine-learning (ML) and deep-learning (DL) models. Here, we present BiGAMi, a bi-objective genetic algorithm fitness function for feature selection in microbial datasets to train high-performing phenotype classifiers. The proposed fitness function allowed us to build classifiers that outperformed the baseline performance estimated by the original studies by using as few as 0.04% to 2.32% features of the original dataset. In 35 out of 42 performance comparisons between BiGAMi and other feature selection methods evaluated here (sequential forward selection, SelectKBest, and GARS), BiGAMi achieved its results by selecting 6-93% fewer features. This study showed that the application of a bi-objective GA fitness function against microbiome datasets succeeded in selecting small subsets of bacteria whose contribution to understood diseases and the host state was already experimentally proven. Applying this feature selection approach to novel diseases is expected to quickly reveal the microbes most relevant to a specific condition.

Symbiont transmission in marine sponges: reproduction, development, and metamorphosis

Marine sponges (phylum Porifera) form symbioses with diverse microbial communities that can be transmitted between generations through their developmental stages. Here, we integrate embryology and microbiology to review how symbiotic microorganisms are transmitted in this early-diverging lineage. We describe that vertical transmission is widespread but not universal, that microbes are vertically transmitted during a select developmental window, and that properties of the developmental microbiome depends on whether a species is a high or low microbial abundance sponge. Reproduction, development, and symbiosis are thus deeply rooted, but why these partnerships form remains the central and elusive tenet of these developmental symbioses.

Depth effect on the prokaryotic community assemblage associated with sponges from different rocky reefs

Background

Sponge microbiomes are essential for the function and survival of their host and produce biologically active metabolites, therefore, they are ideal candidates for ecological, pharmacologic and clinical research. Next-generation sequencing (NGS) has revealed that many factors, including the environment and host, determine the composition and structure of these symbiotic communities but the controls of this variation are not well described. This study assessed the microbial communities associated with two marine sponges of the genera Aplysina (Nardo, 1834) and Ircinia (Nardo, 1833) in rocky reefs from Punta Arena de la Ventana (Gulf of California) and Pichilingue (La Paz Bay) in the coast of Baja California Sur, México to determine the relative importance of environment and host in structuring the microbiome of sponges.

Methods

Specimens of Aplysina sp were collected by scuba diving at 10 m and 2 m; Ircinia sp samples were collected at 2 m. DNA of sponge-associated prokaryotes was extracted from 1 cm³ of tissue, purified and sent for 16S amplicon sequencing. Primer trimmed pair-ended microbial 16S rDNA gene sequences were merged using Ribosomal Database Project (RDP) Paired-end Reads Assembler. Chao1, Shannon and Simpson (alpha) biodiversity indices were estimated, as well permutational analysis of variance (PERMANOVA), and Bray-Curtis distances.

Results

The most abundant phyla differed between hosts. Those phyla were: Proteobacteria, Acidobacteria, Cyanobacteria, Chloroflexi, Actinobacteria, Bacteroidetes, and Planctomycetes. In Ircinia sp the dominant phylum was Acidobacteria. Depth was the main factor influencing the microbial community, as analysis of similarities (ANOSIM) showed a significant difference between the microbial communities from different depths.

Conclusion

Microbial diversity analysis showed that depth was more important than host in structuring the Aplysina sp and Ircinia sp microbiome. This observation contrast with previous reports that the sponge microbiome is highly host specific.

Stability of the Microbiome of the Sponge Mycale (Oxymycale) acerata in the Western Antarctic Peninsula

The sponge microbiome, especially in Low Microbial Abundance (LMA) species, is expected to be influenced by the local environment; however, contrasting results exist with evidence showing that host specificity is also important, hence suggesting that the microbiome is influenced by host-specific and environmental factors. Despite sponges being important members of Southern Ocean benthic communities, their relationships with the microbial communities they host remain poorly studied. Here, we studied the spatial and temporal patterns of the microbiota associated with the ecologically important LMA sponge M. acerata at sites along ∼400 km of the Western Antarctic Peninsula (WAP) to assess patterns in the core and variable microbial components of the symbiont communities of this sponge species. The analyses of 31 samples revealed that the microbiome of M. acerata is composed of 35 prokaryotic phyla (3 Archaea, 31 Bacteria, and one unaffiliated), being mainly dominated by Proteobacteria with Gammaproteobacteria as the most dominant class. The core community was composed of six prokaryotic OTUs, with gammaproteobacterial OTU (EC94 Family), showing a mean abundance over 65% of the total abundance. Despite some differences in rare OTUs, the core community did not show clear patterns in diversity and abundance associated with specific sites/environmental conditions, confirming a low variability in community structure of this species along the WAP. The analysis at small scale (Doumer Island, Palmer Archipelago) showed no differences in space and time in the microbiome M. acerata collected at sites around the island, sampled in three consecutive years (2016-2018). Our results highlight the existence of a low spatial and temporal variability in the microbiome of M. acerata, supporting previous suggestions based on limited studies on this and other Antarctic sponges.

Adaptive strategies of sponges to deoxygenated oceans

Ocean deoxygenation is one of the major consequences of climate change. In coastal waters, this process can be exacerbated by eutrophication, which is contributing to an alarming increase in the so-called 'dead zones' globally. Despite its severity, the effect of reduced dissolved oxygen has only been studied for a very limited number of organisms, compared to other climate change impacts such as ocean acidification and warming. Here, we experimentally assessed the response of sponges to moderate and severe simulated hypoxic events. We ran three laboratory experiments on four species from two different temperate oceans (NE Atlantic and SW Pacific). Sponges were exposed to a total of five hypoxic treatments, with increasing severity (3.3, 1.6, 0.5, 0.4 and 0.13 mg O₂  L^-1 , over 7-12-days). We found that sponges are generally very tolerant of hypoxia. All the sponges survived in the experimental conditions, except Polymastia crocea, which showed significant mortality at the lowest oxygen concentration (0.13 mg O₂  L^-1 , lethal median time: 286 h). In all species except Suberites carnosus, hypoxic conditions do not significantly affect respiration rate down to 0.4 mg O₂  L^-1 , showing that sponges can uptake oxygen at very low concentrations in the surrounding environment. Importantly, sponges displayed species-specific phenotypic modifications in response to the hypoxic treatments, including physiological, morphological and behavioural changes. This phenotypic plasticity likely represents an adaptive strategy to live in reduced or low oxygen water. Our results also show that a single sponge species (i.e., Suberites australiensis) can display different strategies at different oxygen concentrations. Compared to other sessile organisms, sponges generally showed higher tolerance to hypoxia, suggesting that sponges could be favoured and survive in future deoxygenated oceans.

Oceanographic setting influences the prokaryotic community and metabolome in deep-sea sponges

Marine sponges (phylum Porifera) are leading organisms for the discovery of bioactive compounds from nature. Their often rich and species-specific microbiota is hypothesised to be producing many of these compounds. Yet, environmental influences on the sponge-associated microbiota and bioactive compound production remain elusive. Here, we investigated the changes of microbiota and metabolomes in sponges along a depth range of 1232 m. Using 16S rRNA gene amplicon sequencing and untargeted metabolomics, we assessed prokaryotic and chemical diversities in three deep-sea sponge species: Geodia barretti, Stryphnus fortis, and Weberella bursa. Both prokaryotic communities and metabolome varied significantly with depth, which we hypothesized to be the effect of different water masses. Up to 35.5% of microbial ASVs (amplicon sequence variants) showed significant changes with depth while phylum-level composition of host microbiome remained unchanged. The metabolome varied with depth, with relative quantities of known bioactive compounds increasing or decreasing strongly. Other metabolites varying with depth were compatible solutes regulating osmolarity of the cells. Correlations between prokaryotic community and the bioactive compounds in G. barretti suggested members of Acidobacteria, Proteobacteria, Chloroflexi, or an unclassified prokaryote as potential producers.

Data scaling performance on various machine learning algorithms to identify abalone sex

This study aims to analyze the performance of machine learning algorithms with the data scaling process to show the method's effectiveness. It uses min-max (normalization) and zero-mean (standardization) data scaling techniques in the abalone dataset. The stages carried out in this study included data normalization on the data of abalone physical measurement features. The model evaluation was carried out using k-fold cross-validation with the number of k-fold 10. Abalone datasets were normalized in machine learning algorithms: Random Forest, Naïve Bayesian, Decision Tree, and SVM (RBF kernels and linear kernels). The eight features of the abalone dataset show that machine learning algorithms did not too influence data scaling. There is an increase in the performance of SVM, while Random Forest decreases when the abalone dataset is applied to data scaling. Random Forest has the highest average balanced accuracy (74.87%) without data scaling.

Variability in Host Specificity and Functional Potential of Antarctic Sponge-Associated Bacterial Communities

Sponge-associated microorganisms are essential for sponge survival. They play an important role in recycling nutrients and, therefore, in the maintenance of the ecosystem. These microorganisms are diverse, species-specific, and different from those in the surrounding seawater. Bacterial sponge symbionts have been extensively studied in the tropics; however, little is known about these microorganisms in sponges from high-latitude environments. Sponges can cover up to 80% of the benthos in Antarctica and are crucial architects for the marine food web. In this study, we present analyses of the bacterial symbionts of three sponges: Haliclona (Rhizoniera) sp., Hymeniacidon torquata, and Isodictya kerguelenensis from the Western Antarctic Peninsula (WAP) with the aim to determine variations on the specificity of the bacteria–sponge interactions and potential signatures on their predicted functional profiles. We use high-throughput 16S rRNA gene sequencing of 30 sponge individuals inhabiting South Bay (Palmer Archipelago, WAP) to describe their microbiome taxonomy and diversity and predict potential functional profiles based on this marker gene. Our work shows similar bacterial community composition profiles among the same sponge species, although the symbiotic relationship is not equally conserved among the three Antarctic sponges. The number of species-specific core operational taxonomic units (OTUs) of these Antarctic sponges was low, with important differences between the total abundance accounted for these OTUs. Only eight OTUs were shared between the three sponge species. Analyses of the functional potential revealed that despite the high host–symbiont specificity, the inferred functions are conserved among these microbiomes, although with differences in the abundance of specific functions. H. torquata showed the highest level of intra-specificity and a higher potential of pathways related to energy metabolism, metabolisms of terpenoids and polyketides, and biosynthesis of other secondary metabolites. Overall, this work shows variations in the specificity of the sponge-associated bacterial communities, differences in how hosts and symbionts establish their relations, and in their potential functional capabilities.

A Multi-Species Investigation of Sponges' Filtering Activity towards Marine Microalgae

Chronic discharge of surplus organic matter is a typical side effect of fish aquaculture, occasionally leading to coastal eutrophication and excessive phytoplankton growth. Owing to their innate filter-feeding capacity, marine sponges could mitigate environmental impact under integrated multitrophic aquaculture (IMTA) scenarios. Herein, we investigated the clearance capacity of four ubiquitous Mediterranean sponges (Agelas oroides, Axinella cannabina, Chondrosia reniformis and Sarcotragus foetidus) against three microalgal substrates with different size/motility characteristics: the nanophytoplankton Nannochloropsis sp. (~3.2 μm, nonmotile) and Isochrysis sp. (~3.8 μm, motile), as well as the diatom Phaeodactylum tricornutum (~21.7 μm, nonmotile). In vitro cleaning experiments were conducted using sponge explants in 1 L of natural seawater and applying different microalgal cell concentrations under light/dark conditions. The investigated sponges exhibited a wide range of retention efficiencies for the different phytoplankton cells, with the lowest average values found for A. cannabina (37%) and the highest for A. oroides (70%). The latter could filter up to 14.1 mL seawater per hour and gram of sponge wet weight, by retaining 100% of Isochrysis at a density of 10⁵ cells mL⁻¹, under darkness. Our results highlight differences in filtering capacity among sponge species and preferences for microalgal substrates with distinct size and motility traits.

Stereochemical Assignment and Absolute Abundance of Nonproteinogenic Amino Acid Homoarginine in Marine Sponges

Together with arginine, the nonproteinogenic amino acid homoarginine is a substrate for the production of vasodilator nitric oxide in the human body. In marine sponges, homoarginine has been postulated to serve as a precursor for the biosynthesis of pyrrole-imidazole alkaloid and bromotyrosine alkaloid classes of natural products. The absolute abundance of homoarginine, its abundance relative to arginine, and its stereochemical assignment in marine sponges are not known. Here, using stable isotope dilution mass spectrometry, we quantify the absolute abundances of homoarginine and arginine in marine sponges. We find that the abundance of homoarginine is highly variable and can far exceed the concentration of arginine, even in sponges where incorporation of homoarginine in natural products cannot be rationalized. The [homoarginine]/[arginine] ratio in marine sponges is greater than that in human analytes. By derivatization of sponge extracts with Marfey's reagent and comparison with authentic standards, we determine the l-isomer of homoarginine to be exclusively present in sponges. Our results shed light on the presence of the high abundance of homoarginine in marine sponge metabolomes and provide the foundation to investigate the biosynthetic routes and physiological roles of this nonproteinogenic amino acid in sponge physiology.

Comparative Genomics Provides Insight into the Function of Broad-Host Range Sponge Symbionts

The fossil record indicates that the earliest evidence of extant marine sponges (phylum Porifera) existed during the Cambrian explosion and that their symbiosis with microbes may have begun in their extinct ancestors during the Precambrian period. Many symbionts have adapted to their sponge host, where they perform specific, specialized functions. There are also widely distributed bacterial taxa such as Poribacteria, SAUL, and Tethybacterales that are found in a broad range of invertebrate hosts. Here, we added 11 new genomes to the Tethybacterales order, identified a novel family, and show that functional potential differs between the three Tethybacterales families. We compare the Tethybacterales with the well-characterized Entoporibacteria and show that these symbionts appear to preferentially associate with low-microbial abundance (LMA) and high-microbial abundance (HMA) sponges, respectively. Within these sponges, we show that these symbionts likely perform distinct functions and may have undergone multiple association events, rather than a single association event followed by coevolution. IMPORTANCE Marine sponges often form symbiotic relationships with bacteria that fulfil a specific need within the sponge holobiont, and these symbionts are often conserved within a narrow range of related taxa. To date, there exist only three known bacterial taxa (Entoporibacteria, SAUL, and Tethybacterales) that are globally distributed and found in a broad range of sponge hosts, and little is known about the latter two. We show that the functional potential of broad-host range symbionts is conserved at a family level and that these symbionts have been acquired several times over evolutionary history. Finally, it appears that the Entoporibacteria are associated primarily with high-microbial abundance sponges, while the Tethybacterales associate with low-microbial abundance sponges.

Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a given environmental state. As proof of the principle, our goal was to assess the opportunities and limitations of machine learning to detect microbial fingerprints indicating the presence of the munition compound 2,4,6-trinitrotoluene (TNT) in southwestern Baltic Sea sediments. Over 40 environmental variables including grain size distribution, elemental composition, and concentration of munition compounds (mostly at pmol⋅g^–1 levels) from 150 sediments collected at the near-to-shore munition dumpsite Kolberger Heide by the German city of Kiel were combined with 16S rRNA gene amplicon sequencing libraries. Prediction was achieved using Random Forests (RFs); the robustness of predictions was validated using Artificial Neural Networks (ANN). To facilitate machine learning with microbiome data we developed the R package phyloseq2ML. Using the most classification-relevant 25 bacterial genera exclusively, potentially representing a TNT-indicative fingerprint, TNT was predicted correctly with up to 81.5% balanced accuracy. False positive classifications indicated that this approach also has the potential to identify samples where the original TNT contamination was no longer detectable. The fact that TNT presence was not among the main drivers of the microbial community composition demonstrates the sensitivity of the approach. Moreover, environmental variables resulted in poorer prediction rates than using microbial fingerprints. Our results suggest that microbial communities can predict even minor influencing factors in complex environments, demonstrating the potential of this approach for the discovery of contamination events over an integrated period of time. Proven for a distinct environment future studies should assess the ability of this approach for environmental monitoring in general.

Marine sponges maintain stable bacterial communities between reef sites with different coral to algae cover ratios

Marine sponges play a major ecological role in recycling resources on coral reef ecosystems. The cycling of resources may largely depend on the stability of the host-microbiome interactions and their susceptibility to altered environmental conditions. Given the current coral to algal phase shift on coral reefs, we investigated whether the sponge-associated bacterial communities of four sponge species, with either high or low microbial abundances (HMA and LMA), remain stable at two reefs sites with different coral to algae cover ratios. Additionally, we assessed the bacterial community composition of two of these sponge species before and after a reciprocal transplantation experiment between the sites. An overall stable bacterial community composition was maintained across the two sites in all sponge species, with a high degree of host-specificity. Furthermore, the core bacterial communities of the sponges remained stable also after a 21-day transplantation period, although a minor shift was observed in less abundant taxa (< 1%). Our findings support the conclusion that host identity and HMA-LMA status are stronger traits in shaping bacterial community composition than habitat. Nevertheless, long-term microbial monitoring of sponges along with benthic biomass and water quality assessments are needed for identifying ecosystem tolerance ranges and tipping points in ongoing coral reef phase shifts.

Enzymatic Synthesis Assisted Discovery of Proline-Rich Macrocyclic Peptides in Marine Sponges

Proline-rich macrocyclic peptides (PRMPs) are natural products present in geographically and phylogenetically dispersed marine sponges. The large diversity and low abundance of PRMPs in sponge metabolomes precludes isolation and structure elucidation of each individual PRMP congener. Here, using standards developed via biomimetic enzymatic synthesis of PRMPs, a mass spectrometry-based workflow to sequence PRMPs was developed and validated to reveal that the diversity of PRMPs in marine sponges is much greater than that has been realized by natural product isolation-based strategies. Findings are placed in the context of diversity-oriented transamidative macrocyclization of peptide substrates in sponge holobionts.

Stress response of the marine sponge Scopalina sp.. Can microbial community composition predict sponge disease?

Disease has become an increasingly recognised problem in the marine environment, but our understanding of the factors that drive disease or our ability to predict its occurrence is limited. Marine sponges are known for their close associations with microorganisms, which are generally accepted to underpin sponge health and function. The aim of this study is to explore whether the microbial community composition of sponges can act as a predictor of disease occurrence under stressful environmental conditions. The development of a naturally occurring disease in the temperate sponge species Scopalina sp. was reproducibly recreated in a flow-through aquarium environment using increasing temperature stress. Throughout the experiments, four morphological health states were observed and described. Fingerprinting based on terminal restriction fragment length polymorphism of the bacterial community uncovered a statistically significant signature in healthy sponges prior to stress or apparent symptoms that correlated with the time it took for the disease to occur. This shows that the bacterial community composition of individual sponges can act as predictors of necrotic disease development. To the best of our knowledge, this is the first time a microbial signature of this nature has been reported in marine sponges and this finding can contribute to unravelling cause-effect pathways for stress-related dysbiosis and disease.