Priorities for ocean microbiome research

Distinct structure, assembly, and gene expression of microplankton in two Arctic estuaries with varied terrestrial inputs

The Laptev Sea is a major Marginal Sea in the Western Arctic Ocean. The Arctic amplification brought by global warming influences the hydrological properties of rivers passing through the permafrost zone, which would alter the biological community structure at continental margin. In this study, the structure, assembly, and gene expression of planktonic microbial communities in two estuaries (Protoka Ularovskaya River Estuary, PURE; Lena River Estuary, LRE) of Laptev Sea were examined to investigate the environmental effects of polar rivers. PURE and LRE exhibited distinct environmental characteristics: low temperature and high salinity for PURE, and high temperature and low salinity for LRE, influenced by runoff size. Salinity more closely influenced microbial communities in LRE, with freshwater species playing a significant role in community composition. The findings revealed differences between two estuaries in community composition and diversity. Prokaryotes and microeukaryotes had shown different assembly patterns in response to habitat changes caused by terrestrial freshwater input. Furthermore, compared with the PURE, the co-occurrence and inter-domain network of the LRE, which was more affected by terrestrial input, was more complex and stable. Functional gene prediction revealed a higher gene expression of methane metabolism in LRE than in PURE, particularly those related to methane oxidation, and this conclusion could help better explore the impact of global warming on the methane cycle in the Arctic Marginal Seas. This study explored the increased freshwater runoffs under the background of global warming dramatically affect Arctic microplankton communities from community structure, assembly and gene expression aspects.

Global biogeography of microbes driving ocean ecological status under climate change

Microbial communities play a crucial role in ocean ecology and global biogeochemical processes. However, understanding the intricate interactions among diversity, taxonomical composition, functional traits, and how these factors respond to climate change remains a significant challenge. Here, we propose seven distinct ecological statuses by systematically considering the diversity, structure, and biogeochemical potential of the ocean microbiome to delineate their biogeography. Anthropogenic climate change is expected to alter the ecological status of the surface ocean by influencing environmental conditions, particularly nutrient and oxygen contents. Our predictive model, which utilizes machine learning, indicates that the ecological status of approximately 32.44% of the surface ocean may undergo changes from the present to the end of this century, assuming no policy interventions. These changes mainly include poleward shifts in the main taxa, increases in photosynthetic carbon fixation and decreases in nutrient metabolism. However, this proportion can decrease significantly with effective control of greenhouse gas emissions. Our study underscores the urgent necessity for implementing policies to mitigate climate change, particularly from an ecological perspective.

Analysis of Microbiome Data

The microbiome represents a hidden world of tiny organisms populating not only our surroundings but also our own bodies. By enabling comprehensive profiling of these invisible creatures, modern genomic sequencing tools have given us an unprecedented ability to characterize these populations and uncover their outsize impact on our environment and health. Statistical analysis of microbiome data is critical to infer patterns from the observed abundances. The application and development of analytical methods in this area require careful consideration of the unique aspects of microbiome profiles. We begin this review with a brief overview of microbiome data collection and processing and describe the resulting data structure. We then provide an overview of statistical methods for key tasks in microbiome data analysis, including data visualization, comparison of microbial abundance across groups, regression modeling, and network inference. We conclude with a discussion and highlight interesting future directions.

The road forward to incorporate seawater microbes in predictive reef monitoring

Marine bacterioplankton underpin the health and function of coral reefs and respond in a rapid and sensitive manner to environmental changes that affect reef ecosystem stability. Numerous meta-omics surveys over recent years have documented persistent associations of opportunistic seawater microbial taxa, and their associated functions, with metrics of environmental stress and poor reef health (e.g. elevated temperature, nutrient loads and macroalgae cover). Through positive feedback mechanisms, disturbance-triggered heterotrophic activity of seawater microbes is hypothesised to drive keystone benthic organisms towards the limit of their resilience and translate into shifts in biogeochemical cycles which influence marine food webs, ultimately affecting entire reef ecosystems. However, despite nearly two decades of work in this space, a major limitation to using seawater microbes in reef monitoring is a lack of a unified and focused approach that would move beyond the indicator discovery phase and towards the development of rapid microbial indicator assays for (near) real-time reef management and decision-making. By reviewing the current state of knowledge, we provide a comprehensive framework (defined as five phases of research and innovation) to catalyse a shift from fundamental to applied research, allowing us to move from descriptive to predictive reef monitoring, and from reactive to proactive reef management.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Protecting the invisible: Establishing guideline values for copper toxicity to marine microbiomes

Understanding the rapid responses of marine microbiomes to environmental disturbances is paramount for supporting early assessments of harm to high-value ecosystems, such as coral reefs. Yet, management guidelines aimed at protecting aquatic life from environmental pollution remain exclusively defined for organisms at higher trophic levels. In this study, 16S rRNA gene amplicon sequencing was applied in conjunction with propidium monoazide for cell-viability assessment as a sensitive tool to determine taxon- and community-level changes in a seawater microbial community under copper (Cu) exposure. Bayesian model averaging was used to establish concentration-response relationships to evaluate the effects of copper on microbial composition, diversity, and richness for the purpose of estimating microbiome Hazard Concentration (mHCx) values. Predicted mHC5 values at which a 5 % change in microbial composition, diversity, and richness occurred were 1.05, 0.72, and 0.38 μg Cu L-1, respectively. Threshold indicator taxa analysis was applied across the copper concentrations to identify taxon-specific change points for decreasing taxa. These change points were then used to generate a Prokaryotic Sensitivity Distribution (PSD), from which mHCxdec values were derived for copper, suitable for the protection of 99, 95, 90, and 80 % of the marine microbiome. The mHC5dec guideline value of 0.61 μg Cu L-1, protective of 95 % of the marine microbial community, was lower than the equivalent Australian water quality guideline value based on eukaryotic organisms at higher trophic levels. This suggests that marine microbial communities might be more vulnerable, highlighting potential insufficiencies in their protection against copper pollution. The mHCx values proposed here provide approaches to quantitatively assess the effects of contaminants on microbial communities towards the inclusion of prokaryotes in future water quality guidelines.

Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3-V4 region to investigate whether the RC-PCR reveals more of the 'unseen' diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3-V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.

Mapping harmful microalgal species by eDNA monitoring: A large-scale survey across the southwestern South China Sea

A large-scale sampling was undertaken during a research cruise across the South China Sea in August 2016, covering an area of about 100,000 km2 to investigate the molecular diversity and distributions of micro-eukaryotic protists, with a focus on the potentially harmful microalgal (HAB) species along the east coast of Peninsular Malaysia. Environmental DNAs from 30 stations were extracted and DNA metabarcoding targeting the V4 and V9 markers in the 18S rDNA was performed. Many protistan molecular units, including previously unreported HAB taxa, were discovered for the first time in the water. Our findings also revealed interesting spatial distribution patterns, with a marked signal of compositional turnover between latitudinal regimes of water masses, where dinophytes and diatom compositions were among the most strongly enhanced at the fronts, leading to distinct niches. Our results further confirmed the widespread distribution of HAB species, such as the toxigenic Alexandrium tamiyavaichii and Pseudo-nitzschia species, and the fish-killing Margalefidinium polykrikoides and Karlodinium veneficum. The molecular information obtained from this study provides an updated HAB species inventory and a toolset that could facilitate existing HAB monitoring schemes in the region to better inform management decisions.

Unveiling abundance-dependent metabolic phenotypes of microbial communities

IMPORTANCE

In nature, organisms live in communities and not as isolated species, and their interactions provide a source of resilience to environmental disturbances. Despite their importance in ecology, human health, and industry, understanding how organisms interact in different environments remains an open question. In this work, we provide a novel approach that, only using genomic information, studies the metabolic phenotype exhibited by communities, where the exploration of suboptimal growth flux distributions and the composition of a community allows to unveil its capacity to respond to environmental changes, shedding light of the degrees of metabolic plasticity inherent to the community.

Planktonic ecological networks support quantification of changes in ecosystem health and functioning

Plankton communities are the foundation of marine food webs and have a large effect on the dynamics of entire ecosystems. Changes in physicochemical factors strongly influence planktonic organisms and their turnover rates, making their communities useful for monitoring ecosystem health. We studied and compared the planktonic food webs of Palude della Rosa (Venice Lagoon, Italy) in 2005 and 2007. The food webs were developed using a novel approach based on the Monte Carlo random sampling of parameters within specific and realistic ranges to derive 1000 food webs for July of each year. The consumption flows involving Strombididae, Evadne spp. and Podon spp. were identified as the most important in splitting food webs of the July of the two years. Although functional nodes (FNs) differed both in presence and abundance in July of the two years, the whole system indicators showed very similar results. Sediment resuspension acted as a source of stress for the Venice Lagoon, being the most used resource by consumers while inhibiting primary producers by increasing water turbidity. Primary production in the water column was mainly generated by benthic FNs. Although the system was near an equilibrium point, it tended to increase its resilience at the expense of efficiency due to stress. This study highlights the role of plankton communities, which can serve to assess ecosystem health.

A global atlas of marine antibiotic resistance genes and their expression

Oceans serve as global reservoirs of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). However, little is known about the traits and expression of ARGs in response to environmental factors. We analyzed 347 metagenomes and 182 metatranscriptomes to determine the distribution, hosts, and expression of ARGs in oceans. Our study found that the diversity and abundance of ARGs varied with latitude and depth. The core marine resistome mainly conferred glycopeptide and multidrug resistance. The hosts of this resistome were mainly limited to the core marine microbiome, with phylogenetic barriers to the horizontal transfer of ARGs, transfers being more frequent within species than between species. Sixty-five percent of the marine ARGs identified were expressed. More than 90% of high-risk ARGs were more likely to be expressed. Anthropogenic activity might affect the expression of ARGs by altering nitrate and phosphate concentrations and ocean temperature. Machine-learning models predict >97% of marine ARGs will change expression by 2100. High-risk ARGs will shift to low latitudes and regions with high anthropogenic activity, such as the Pacific and Atlantic Oceans. Certain ARGs serve a dual role in antibiotic resistance and potentially participate in element cycling, along with other unknown functions. Determining whether changes in ARG expression are beneficial to ecosystems and human health is challenging without comprehensive understanding of their functions. Our study identified a core resistome in the oceans and quantified the expression of ARGs for the development of future control strategies under global change.

Aquaculture ecosystem microbiome at the water-fish interface: the case-study of rainbow trout fed with Tenebrio molitor novel diets

BACKGROUND

Sustainable aquaculture relies on multiple factors, including water quality, fish diets, and farmed fish. Replacing fishmeal (FM) with alternative protein sources is key for improving sustainability in aquaculture and promoting fish health. Indeed, great research efforts have been made to evaluate novel feed formulations, focusing especially on the effects on the fish gut microbiome. Few studies have explored host-environment interactions. In the present study, we evaluated the influence of novel insect-based (Tenebrio molitor) fish diets on the microbiome at the water-fish interface in an engineered rainbow trout (Oncorhynchus mykiss) farming ecosystem. Using 16S rRNA gene metabarcoding, we comprehensively analyzed the microbiomes of water, tank biofilm, fish intestinal mucus, fish cutis, and feed samples.

RESULTS

Core microbiome analysis revealed the presence of a highly reduced core shared by all sample sources, constituted by Aeromonas spp., in both the control and novel feed test groups. Network analysis showed that samples were clustered based on the sample source, with no significant differences related to the feed formulation tested. Thus, the different diets did not seem to affect the environment (water and tank biofilm) and fish (cutis and intestinal mucus) microbiomes. To disentangle the contribution of feed at a finer scale, we performed a differential abundance analysis and observed differential enrichment/impoverishment in specific taxa, comparing the samples belonging to the control diet group and the insect-based diet group.

CONCLUSIONS

Omic exploration of the water-fish interface exposes patterns that are otherwise undetected. These data demonstrate a link between the environment and fish and show that subtle but significant differences are caused by feed composition. Thus, the research presented here is a step towards positively influencing the aquaculture environment and its microbiome.

Inter-comparison of marine microbiome sampling protocols

Research on marine microbial communities is growing, but studies are hard to compare because of variation in seawater sampling protocols. To help researchers in the inter-comparison of studies that use different seawater sampling methodologies, as well as to help them design future sampling campaigns, we developed the EuroMarine Open Science Exploration initiative (EMOSE). Within the EMOSE framework, we sampled thousands of liters of seawater from a single station in the NW Mediterranean Sea (Service d'Observation du Laboratoire Arago [SOLA], Banyuls-sur-Mer), during one single day. The resulting dataset includes multiple seawater processing approaches, encompassing different material-type kinds of filters (cartridge membrane and flat membrane), three different size fractionations (>0.22 µm, 0.22-3 µm, 3-20 µm and >20 µm), and a number of different seawater volumes ranging from 1 L up to 1000 L. We show that the volume of seawater that is filtered does not have a significant effect on prokaryotic and protist diversity, independently of the sequencing strategy. However, there was a clear difference in alpha and beta diversity between size fractions and between these and "whole water" (with no pre-fractionation). Overall, we recommend care when merging data from datasets that use filters of different pore size, but we consider that the type of filter and volume should not act as confounding variables for the tested sequencing strategies. To the best of our knowledge, this is the first time a publicly available dataset effectively allows for the clarification of the impact of marine microbiome methodological options across a wide range of protocols, including large-scale variations in sampled volume.

Global distribution of marine microplastics and potential for biodegradation

Microplastics are a growing marine environmental concern globally due to their high abundance and persistent degradation. We created a global map for predicting marine microplastic pollution using a machine-learning model based on 9445 samples and found that microplastics converged in zones of accumulation in subtropical gyres and near polar seas. The predicted global potential for the biodegradation of microplastics in 1112 metagenome-assembled genomes from 485 marine metagenomes indicated high potential in areas of high microplastic pollution, such as the northern Atlantic Ocean and the Mediterranean Sea. However, the limited number of samples hindered our prediction, a priority issue that needs to be addressed in the future. We further identified hosts with microplastic degradation genes (MDGs) and found that Proteobacteria accounted for a high proportion of MDG hosts, mainly Alphaproteobacteria and Gammaproteobacteria, with host-specific patterns. Our study is essential for raising awareness, identifying areas with microplastic pollution, providing a prediction method of machine learning to prioritize surveillance, and identifying the global potential of marine microbiomes to degrade microplastics, providing a reference for selecting bacteria that have the potential to degrade microplastics for further applied research.

Purification and biochemical characterization of SM14est, a PET-hydrolyzing enzyme from the marine sponge-derived Streptomyces sp. SM14

The successful enzymatic degradation of polyester substrates has fueled worldwide investigation into the treatment of plastic waste using bio-based processes. Within this realm, marine-associated microorganisms have emerged as a promising source of polyester-degrading enzymes. In this work, we describe the hydrolysis of the synthetic polymer PET by SM14est, a polyesterase which was previously identified from Streptomyces sp. SM14, an isolate of the marine sponge Haliclona simulans. The PET hydrolase activity of purified SM14est was assessed using a suspension-based assay and subsequent analysis of reaction products by UV-spectrophotometry and RP-HPLC. SM14est displayed a preference for high salt conditions, with activity significantly increasing at sodium chloride concentrations from 100 mM up to 1,000 mM. The initial rate of PET hydrolysis by SM14est was determined to be 0.004 s^-1 at 45°C, which was increased by 5-fold to 0.02 s^-1 upon addition of 500 mM sodium chloride. Sequence alignment and structural comparison with known PET hydrolases, including the marine halophile PET6, and the highly efficient, thermophilic PHL7, revealed conserved features of interest. Based on this work, SM14est emerges as a useful enzyme that is more similar to key players in the area of PET hydrolysis, like PHL7 and IsPETase, than it is to its marine counterparts. Salt-tolerant polyesterases such as SM14est are potentially valuable in the biological degradation of plastic particles that readily contaminate marine ecosystems and industrial wastewaters.

Diverse eukaryotic phytoplankton from around the Marquesas Islands documented by combined microscopy and molecular techniques

Oceanic phytoplankton serve as a base for the food webs within the largest planetary ecosystem. Despite this, surprisingly little is known about species composition, function and ecology of phytoplankton communities, especially for vast areas of the open ocean. In this study we focus on the marine phytoplankton microflora from the vicinity of the Marquesas Islands in the Southern Pacific Ocean collected during the Tara Oceans expedition. Multiple samples from four sites and two depths were studied in detail using light microscopy, scanning electron microscopy, and automated confocal laser scanning microscopy. In total 289 taxa were identified, with Dinophyceae and Bacillariophyceae contributing 60% and 32% of taxa, respectively, to phytoplankton community composition. Notwithstanding, a large number of cells could not be assigned to any known species. Coccolithophores and other flagellates together contributed less than 8% to the species list. Observed cell densities were generally low, but at sites of high autotrophic biomass, diatoms reached the highest cell densities (1.26 × 10⁴ cells L^-1). Overall, 18S rRNA metabarcode-based community compositions matched microscopy-based estimates, particularly for the main diatom taxa, indicating consistency and complementarity between different methods, while the wide range of microscopy-based methods permitted several unknown and poorly studied taxa to be revealed and identified.

Information Scale Correction for Varying Length Amplicons Improves Eukaryotic Microbiome Data Integration

The integration and reanalysis of big data provide valuable insights into microbiome studies. However, the significant difference in information scale between amplicon data poses a key challenge in data analysis. Therefore, reducing batch effects is crucial to enhance data integration for large-scale molecular ecology data. To achieve this, the information scale correction (ISC) step, involving cutting different length amplicons into the same sub-region, is essential. In this study, we used the Hidden Markov model (HMM) method to extract 11 different 18S rRNA gene v4 region amplicon datasets with 578 samples in total. The length of the amplicons ranged from 344 bp to 720 bp, depending on the primer position. By comparing the information scale correction of amplicons with varying lengths, we explored the extent to which the comparability between samples decreases with increasing amplicon length. Our method was shown to be more sensitive than V-Xtractor, the most popular tool for performing ISC. We found that near-scale amplicons exhibited no significant change after ISC, while larger-scale amplicons exhibited significant changes. After the ISC treatment, the similarity among the data sets improved, especially for long amplicons. Therefore, we recommend adding ISC processing when integrating big data, which is crucial for unlocking the full potential of microbial community studies and advancing our knowledge of microbial ecology.

Viruses in astrobiology

Viruses are the most abundant biological entities on Earth, and yet, they have not received enough consideration in astrobiology. Viruses are also extraordinarily diverse, which is evident in the types of relationships they establish with their host, their strategies to store and replicate their genetic information and the enormous diversity of genes they contain. A viral population, especially if it corresponds to a virus with an RNA genome, can contain an array of sequence variants that greatly exceeds what is present in most cell populations. The fact that viruses always need cellular resources to multiply means that they establish very close interactions with cells. Although in the short term these relationships may appear to be negative for life, it is evident that they can be beneficial in the long term. Viruses are one of the most powerful selective pressures that exist, accelerating the evolution of defense mechanisms in the cellular world. They can also exchange genetic material with the host during the infection process, providing organisms with capacities that favor the colonization of new ecological niches or confer an advantage over competitors, just to cite a few examples. In addition, viruses have a relevant participation in the biogeochemical cycles of our planet, contributing to the recycling of the matter necessary for the maintenance of life. Therefore, although viruses have traditionally been excluded from the tree of life, the structure of this tree is largely the result of the interactions that have been established throughout the intertwined history of the cellular and the viral worlds. We do not know how other possible biospheres outside our planet could be, but it is clear that viruses play an essential role in the terrestrial one. Therefore, they must be taken into account both to improve our understanding of life that we know, and to understand other possible lives that might exist in the cosmos.