Co-occurrence patterns for abundant marine archaeal and bacterial lineages in the deep chlorophyll maximum of coastal California

Distinct patterns of distribution, community assembly and cross-domain co-occurrence of planktonic archaea in four major estuaries of China

BACKGROUND

Archaea are key mediators of estuarine biogeochemical cycles, but comprehensive studies comparing archaeal communities among multiple estuaries with unified experimental protocols during the same sampling periods are scarce. Here, we investigated the distribution, community assembly, and cross-domain microbial co-occurrence of archaea in surface waters across four major estuaries (Yellow River, Yangtze River, Qiantang River, and Pearl River) of China cross climatic zones (~ 1,800 km) during the winter and summer cruises.

RESULTS

The relative abundance of archaea in the prokaryotic community and archaeal community composition varied with estuaries, seasons, and stations (reflecting local environmental changes such as salinity). Archaeal communities in four estuaries were overall predominated by ammonia-oxidizing archaea (AOA) (aka. Marine Group (MG) I; primarily Nitrosopumilus), while the genus Poseidonia of Poseidoniales (aka. MGII) was occasionally predominant in Pearl River estuary. The cross-estuary dispersal of archaea was largely limited and the assembly mechanism of archaea varied with estuaries in the winter cruise, while selection governed archaeal assembly in all estuaries in the summer cruise. Although the majority of archaea taxa in microbial networks were peripherals and/or connectors, extensive and distinct cross-domain associations of archaea with bacteria were found across the estuaries, with AOA as the most crucial archaeal group. Furthermore, the expanded associations of MGII taxa with heterotrophic bacteria were observed, speculatively indicating the endogenous demand for co-processing high amount and diversity of organic matters in the estuarine ecosystem highly impacted by terrestrial/anthropogenic input, which is worthy of further study.

CONCLUSIONS

Our results highlight the lack of common patterns in the dynamics of estuarine archaeal communities along the geographic gradient, expanding the understanding of roles of archaea in microbial networks of this highly dynamic ecosystem.

Roles of sulfate-reducing bacteria in sustaining the diversity and stability of marine bacterial community

Microbes play central roles in ocean food webs and global biogeochemical processes. Yet, the information available regarding the highly diverse bacterial communities in these systems is not comprehensive. Here we investigated the diversity, assembly process, and species coexistence frequency of bacterial communities in seawater and sediment across ∼600 km of the eastern Chinese marginal seas using 16S rRNA gene amplicon sequencing. Our analyses showed that compared with seawater, bacterial communities in sediment possessed higher diversity and experienced tight phylogenetic distribution. Neutral model analysis showed that the relative contribution of stochastic processes to the assembly process of bacterial communities in sediment was lower than that in seawater. Functional prediction results showed that sulfate-reducing bacteria (SRB) were enriched in the core bacterial sub-communities. The bacterial diversities of both sediment and seawater were positively associated with the relative abundance of SRB. Co-occurrence analysis showed that bacteria in seawater exhibited a more complex interaction network and closer co-occurrence relationships than those in sediment. The SRB of seawater were centrally located in the network and played an essential role in sustaining the complex network. In addition, further analysis indicated that the SRB of seawater helped maintain the high stability of the bacterial network. Overall, this study provided further comprehensive information regarding the characteristics of bacterial communities in the ocean, and provides new insights into keystone taxa and their roles in sustaining microbial diversity and stability in ocean.

Spatiotemporal Dynamics of Bacterial Taxonomic and Functional Profiles in Estuarine Intertidal Soils of China Coastal Zone

Bacteria play an important role in regulating carbon (C), nitrogen (N), and sulfur (S) in estuarine intertidal wetlands. To gain insights into the ecological and metabolic modes possessed by bacteria in estuarine intertidal wetlands, a total of 78 surface soil samples were collected from China's coastal intertidal wetlands to examine the spatial and seasonal variations of bacterial taxonomic composition, assembly processes, and ecological system functions through shotgun metagenomic and 16S rRNA gene sequencing. Obvious spatiotemporal dynamic patterns in the bacterial community structure were identified, with more pronounced seasonal rather than spatial variations. Dispersion limitation was observed to act as a critical factor affecting community assembly, explaining approximately half of the total variation in the bacterial community. Functional bacterial community structure exhibited a more significant latitudinal change than seasonal variability, highlighting that functional stability of the bacterial communities differed with their taxonomic variability. Identification of biogeochemically related links between C, N, and S cycles in the soils showed the adaptive routed metabolism of the bacterial communities and the strong interactions between coupled metabolic pathways. Our study broadens the insights into the taxonomic and functional profiles of bacteria in China's estuarine intertidal soils and helps us understand the effects exerted by environmental factors on the ecological health and microbial diversity of estuarine intertidal flats.

Changes in Temporal Dynamics and Factors Influencing the Environment of the Bacterial Community in Mangrove Rhizosphere Sediments in Hainan

The structural characteristics of the rhizosphere soil’s microbial community is crucial to understanding the ecological function of mangroves. However, the mechanism influencing mangrove plants in soil microbial communities has yet to be determined. Here, the mangrove ecosystem of Xinying Mangrove National Wetland Park in Hainan Province was taken as the research object. The microbial communities, external regulatory factors, and the relationship between communities were analyzed using 16S rRNA high-throughput sequencing in the rhizosphere and non-rhizosphere sediments of mangrove forests under different spatiotemporal conditions. The results showed that there was no significant difference in the α-diversity of the bacterial community between the rhizosphere and non-rhizosphere sediments. However, β-diversity was significantly different. Redundancy analysis (RDA) showed that other environmental factors besides sulfide and Fe2+ affected the bacterial community structure in sediments. The co-occurrence pattern analysis of bacteria in the mangrove ecosystem indicates that the bacteria in rhizosphere sediments were more closely related than those in non-rhizosphere sediments. The results reveal significant differences between the rhizosphere and non-rhizosphere bacterial community diversity, structure, and their interaction in the mangrove ecosystem. Therefore, the ecological system of the mangrove wetland needs to be preserved and rehabilitated, which would have a tremendous impact on the sustainable development.

Efficient Approximation of Statistical Significance in Local Trend Analysis of Dependent Time Series

Biological time series data plays an important role in exploring the dynamic changes of biological systems, while the determinate patterns of association between various biological factors can further deepen the understanding of biological system functions and the interactions between them. At present, local trend analysis (LTA) has been commonly conducted in many biological fields, where the biological time series data can be the sequence at either the level of gene expression or OTU abundance, etc., A local trend score can be obtained by taking the similarity degree of the upward, constant or downward trend of time series data as an indicator of the correlation between different biological factors. However, a major limitation facing local trend analysis is that the permutation test conducted to calculate its statistical significance requires a time-consuming process. Therefore, the problem attracting much attention from bioinformatics scientists is to develop a method of evaluating the statistical significance of local trend scores quickly and effectively. In this paper, a new approach is proposed to evaluate the efficient approximation of statistical significance in the local trend analysis of dependent time series, and the effectiveness of the new method is demonstrated through simulation and real data set analysis.

Chemical-Mediated Microbial Interactions Can Reduce the Effectiveness of Time-Series-Based Inference of Ecological Interaction Networks

Network-based assessments are important for disentangling complex microbial and microbial–host interactions and can provide the basis for microbial engineering. There is a growing recognition that chemical-mediated interactions are important for the coexistence of microbial species. However, so far, the methods used to infer microbial interactions have been validated with models assuming direct species-species interactions, such as generalized Lotka–Volterra models. Therefore, it is unclear how effective existing approaches are in detecting chemical-mediated interactions. In this paper, we used time series of simulated microbial dynamics to benchmark five major/state-of-the-art methods. We found that only two methods (CCM and LIMITS) were capable of detecting interactions. While LIMITS performed better than CCM, it was less robust to the presence of chemical-mediated interactions, and the presence of trophic competition was essential for the interactions to be detectable. We show that the existence of chemical-mediated interactions among microbial species poses a new challenge to overcome for the development of a network-based understanding of microbiomes and their interactions with hosts and the environment.

Seasonal succession of microbes in different size-fractions and their modular structures determined by both macro- and micro-environmental filtering in dynamic coastal waters

Microbes interact with each other in response to various environmental changes in coastal marine ecosystems. To explore how the macroenvironment (environmental filtering) and species-engineered microenvironment (niche construction) affect the ecological network of the marine microbiome in the highly dynamic coastal waters of Korea, we analyzed the modular structures of the microbial community and identified microbial interconnections in different size fractions for a year. Fluctuations in the macroenvironment, such as temperature and nutrient concentrations driven by seasonal changes, are the major factors in determining successive microbial modules. Compared to particle-associated (PA) microbes, free-living (FL) microbes seemed to be more affected by macroenvironmental filtering. Modules related to nutrients were further divided into various modules according to different lifestyles. In addition, a large transient discharge of the Changjiang (Yangtze River) in summer also formed a distinct microbial module, which was related to the high ammonia concentration arising from phytoplankton degradation. Microbes belonging to the SAR11, SAR86, and SAR116 clades, Flavobacteriaceae, and MG IIa-L showed repeated interconnections in temperature-related modules, while the SAR202 clade, Marinimicrobia, DEV007 clade, and Arctic97B-4 and Sva0996 marine groups displayed repeated connections in nutrient-related modules. These 'skeleton'-forming microbes created species-engineered microenvironments, further fine-tuning microbial modular structures. Furthermore, they serve as keystone species for module stability by linking interdependent microbial partners within their own modules through universally beneficial metabolic activities. Therefore, they could reinforce the ecological resilience of microbial communities under abiotic and biotic perturbations in dynamic coastal waters. In conclusion, both macro- and micro-environmental filtering were important for determining the seasonal succession of microbial community structures.

Seasonal marine microorganisms change neighbours under contrasting environmental conditions

Marine picoplankton contribute to global carbon sequestration and nutrient recycling. These processes are directly related to the composition of communities, which in turn depends on microbial interactions and environmental forcing. Under regular seasonal cycles, marine communities show strong predictable patterns of annual re-occurrences, but little is known about the effect of environmental perturbation on their organization. The aim of our study was to investigate the co-occurrence patterns of planktonic picoeukaryote, bacteria and archaea under contrasting environmental conditions. The study was designed to have high sampling frequency that could match both the biological rhythm of marine microbes and the short time scale of extreme weather events. Our results show that microbial networks changed from year to year depending on conditions. In addition, individual taxa became less interconnected and changed neighbours, which revealed an unfaithful relationship between marine microorganisms. This unexpected pattern suggests possible switches between organisms that have similar specific functions, or hints at the presence of organisms that share similar environmental niches without interacting. Despite the observed annual changes, the time series showed re-occurring communities that appear to recover from perturbations. Changing co-occurrence patterns between marine microorganisms may allow the long-term stability of ecosystems exposed to contrasting meteorological events.

Biogeochemistry and hydrography shape microbial community assembly and activity in the eastern tropical North Pacific Ocean oxygen minimum zone

Oceanic oxygen minimum zones (OMZs) play a pivotal role in biogeochemical cycles due to extensive microbial activity. How OMZ microbial communities assemble and respond to environmental variation is therefore essential to understanding OMZ functioning and ocean biogeochemistry. Sampling along depth profiles at five stations in the eastern tropical North Pacific Ocean (ETNP), we captured systematic variations in dissolved oxygen (DO) and associated variables (nitrite, chlorophyll, and ammonium) with depth and between stations. We quantitatively analysed relationships between oceanographic gradients and microbial community assembly and activity based on paired 16S rDNA and 16S rRNA sequencing. Overall microbial community composition and diversity were strongly related to regional variations in density, DO, and other variables (regression and redundancy analysis r²  = 0.68-0.82), displaying predictable patterns with depth and between stations. Although similar factors influenced the active community, diversity was substantially lower within the OMZ. We also identified multiple active microbiological networks that tracked specific gradients or features - particularly subsurface ammonium and nitrite maxima. Our findings indicate that overall microbial community assembly is consistently shaped by hydrography and biogeochemistry, while active segments of the community form discrete networks inhabiting distinct portions of the water column, and that both are tightly tuned to environmental conditions in the ETNP.

Seasonal Niche Partitioning of Surface Temperate Open Ocean Prokaryotic Communities

Surface microbial communities are exposed to seasonally changing environmental conditions, resulting in recurring patterns of community composition. However, knowledge on temporal dynamics of open ocean microbial communities remains scarce. Seasonal patterns and associations of taxa and oligotypes from surface and chlorophyll maximum layers in the western Mediterranean Sea were studied over a 2-year period. Summer stratification versus winter mixing governed not only the prokaryotic community composition and diversity but also the temporal dynamics and co-occurrence association networks of oligotypes. Flavobacteriales, Rhodobacterales, SAR11, SAR86, and Synechococcales oligotypes exhibited contrasting seasonal dynamics, and consequently, specific microbial assemblages and potential inter-oligotype connections characterized the different seasons. In addition, oligotypes composition and dynamics differed between surface and deep chlorophyll maximum (DCM) prokaryotic communities, indicating depth-related environmental gradients as a major factor affecting association networks between closely related taxa. Taken together, the seasonal and depth specialization of oligotypes suggest temporal dynamics of community composition and metabolism, influencing ecosystem function and global biogeochemical cycles. Moreover, our results indicate highly specific associations between microbes, pointing to keystone ecotypes and fine-tuning of the microbes realized niche.

Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: From bacteria to marine mammals

As the largest semi-closed marine ecosystem in the world, the Black Sea has been heavily affected by human activities for a long time. Describing the biodiversity of multi-trophic biota in pelagic zone of the Black Sea and identifying the dominant environmental factors are prerequisites for protecting the sustainability of ecosystems. However, up to now, the taxonomic and distributional information about the Black Sea biota is not clear. Here, we employed a Tree-of-Life metabarcoding to analyze the biodiversity of eight communities in the Black Sea, investigated their biogeographical distribution, and further analyzed the influence of biological and abiotic factors on biota on large scales. We found that, (1) Over 8900 OTUs were detected in the Black Sea, of which 630 species were identified, covering the holistic biota from single-celled (bacteria 5620 OTUs 141 species; algae 1096 OTUs 185 species; protozoa 546 OTUs 146 species) to multicellular organisms (invertebrate metazoans 150 OTUs 34 species; fishes 1369 OTUs 76 species; large marine mammals 39 OTUs 5 species). (2) Higher trophic organisms (fishes and large mammals) distributed more evenly in space than the lower (microorganisms, protozoa and invertebrates). For lower trophic organisms, the vertical stratification was more obvious than the horizontal stratification (vertical p < 0.02, horizontal p < 0.05). (3) The bottom trophic organisms (bacteria and algae) of the food web significantly affected the distribution and composition of the others through biological interactions (Mantel p < 0.05). (4) At the level of abiotic factors, the effect of local species sorting on the composition of communities was 15% higher than that of mass dispersal effect. For the first time, this study monitored and profiled the holistic biodiversity in the pelagic zone of the Black Sea, and provided technological advances and preliminary knowledge for the ongoing Black Sea ecosystem protection efforts.

Statistical significance approximation for local similarity analysis of dependent time series data

Background

Local similarity analysis (LSA) of time series data has been extensively used to investigate the dynamics of biological systems in a wide range of environments. Recently, a theoretical method was proposed to approximately calculate the statistical significance of local similarity (LS) scores. However, the method assumes that the time series data are independent identically distributed, which can be violated in many problems.

Results

In this paper, we develop a novel approach to accurately approximate statistical significance of LSA for dependent time series data using nonparametric kernel estimated long-run variance. We also investigate an alternative method for LSA statistical significance approximation by computing the local similarity score of the residuals based on a predefined statistical model. We show by simulations that both methods have controllable type I errors for dependent time series, while other approaches for statistical significance can be grossly oversized. We apply both methods to human and marine microbial datasets, where most of possible significant associations are captured and false positives are efficiently controlled.

Conclusions

Our methods provide fast and effective approaches for evaluating statistical significance of dependent time series data with controllable type I error. They can be applied to a variety of time series data to reveal inherent relationships among the different factors.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2595-x) contains supplementary material, which is available to authorized users.

Planktonic Marine Archaea

Archaea are ubiquitous and abundant members of the marine plankton. Once thought of as rare organisms found in exotic extremes of temperature, pressure, or salinity, archaea are now known in nearly every marine environment. Though frequently referred to collectively, the planktonic archaea actually comprise four major phylogenetic groups, each with its own distinct physiology and ecology. Only one group-the marine Thaumarchaeota-has cultivated representatives, making marine archaea an attractive focus point for the latest developments in cultivation-independent molecular methods. Here, we review the ecology, physiology, and biogeochemical impact of the four archaeal groups using recent insights from cultures and large-scale environmental sequencing studies. We highlight key gaps in our knowledge about the ecological roles of marine archaea in carbon flow and food web interactions. We emphasize the incredible uncultivated diversity within each of the four groups, suggesting there is much more to be done.

A novel method to accurately calculate statistical significance of local similarity analysis for high-throughput time series

In recent years, a large number of time series microbial community data has been produced in molecular biological studies, especially in metagenomics. Among the statistical methods for time series, local similarity analysis is used in a wide range of environments to capture potential local and time-shifted associations that cannot be distinguished by traditional correlation analysis. Initially, the permutation test is popularly applied to obtain the statistical significance of local similarity analysis. More recently, a theoretical method has also been developed to achieve this aim. However, all these methods require the assumption that the time series are independent and identically distributed. In this paper, we propose a new approach based on moving block bootstrap to approximate the statistical significance of local similarity scores for dependent time series. Simulations show that our method can control the type I error rate reasonably, while theoretical approximation and the permutation test perform less well. Finally, our method is applied to human and marine microbial community datasets, indicating that it can identify potential relationship among operational taxonomic units (OTUs) and significantly decrease the rate of false positives.

Characterization of bacterial and microbial eukaryotic communities associated with an ephemeral hypoxia event in Taihu Lake, a shallow eutrophic Chinese lake

While the important roles of microbial communities in oceanic hypoxic zones were beginning to be understood, little is known about microbial community associated with this phenomenon in shallow lakes. To address this deficit, both the bacterial and microbial eukaryotic communities of an ephemeral hypoxic area of Taihu Lake were characterized. The hypoxia provided nutritional niches for various bacteria, which results in high abundance and diversity. Specific bacterial groups, such as vadinBC27 subgroup of Bacteroidetes, Burkholderiales, Rhodocyclales, Pseudomonas, and Parcubacteria, were dominated in hypoxic sites and relevant to the fermentation, denitrification, nitrification, and sulfur metabolism. Conversely, most of microbial eukaryotes disappeared along with the decline of DO. An unexpected dominance of fungi was observed during hypoxia, which partly explained by the accumulation of toxic algae. Mucor was the single dominant genus in the hypoxic zone. We proposed that this group might cooperate with bacterial communities in the anaerobic degradation of algal biomass and woody materials. Generally, the hypoxic microbiome in shallow lakes is mainly involved in fermentative metabolism depending on phytodetritus and is potentially influenced by terrestrial sources. This study provided new insights into the unique microbiome in short-term hypoxia in shallow lakes and lays the foundation for studies that will enhance our understanding of the microbial players associated with hypoxia and their adaption strategy on the global scale.

Inference of Significant Microbial Interactions From Longitudinal Metagenomics Data

Data of next-generation sequencing (NGS) and their analysis have been facilitating advances in our understanding of microbial ecosystems such as human gut microbiota. However, inference of microbial interactions occurring within an ecosystem is still a challenge mainly due to sequencing data (e.g., 16S rDNA sequences) providing relative abundance of microbes instead of absolute cell count. In order to describe growtth dynamics of microbial communities and estimate the involved microbial interactions, we introduce a procedure by integrating generalized Lotka-Volterra equations, forward stepwise regression and bootstrap aggregation. First, we successfully identify experimentally confirmed microbial interactions based on relative abundance data of a cheese microbial community. Then, we apply the procedure to time-series of 16S rDNA sequences of gut microbiomes of children who were progressing to Type 1 diabetes (T1D progressors), and compare their gut microbial interactions to a healthy control group. Our results suggest that the number of inferred microbial interactions increased over time during the first 3 years of life. More microbial interactions are found in the gut flora of healthy children than that of T1D progressors. The inhibitory effects from Actinobacteria and Bacilli to Bacteroidia, from Bacteroidia to Clostridia, and the beneficial effect from Clostridia to Bacteroidia are shared between healthy children and T1D progressors. An inhibition of Clostridia by Gammaproteobacteria is found in healthy children that maintains through their first 3 years of life. This suppression appears in T1D progressors during the first year of life, which transforms to a commensalism relationship at the age of 3 years old. Gammaproteobacteria is found exerting an inhibition on Bacteroidia in the T1D progressors, which is not identified in the healthy controls.

Microbial community networks associated with variations in community respiration rates during upwelling in nearshore Monterey Bay, California

Respiration of organic material is a central process in the global carbon (C) cycle catalysed by diverse microbial communities. In the coastal ocean, upwelling can drive variation in both community respiration (CR) and the microbial community, but linkages between the two are not well-understood. We measured CR rates and analysed microbial dynamics via 16S rRNA gene sequencing, to assess whether CR correlated with upwelling irrespective of changes in the microbial community, or if the particular microbial community present was a factor in explaining variations in CR. CR varied significantly over time as a function of temperature, dissolved oxygen (DO) and chlorophyll-all of which are altered by upwelling-but also varied with a 'subnetwork' (i.e., a group of microbial taxa that covaried with one another) of the whole community. One subnetwork was associated with higher CR and warmer temperatures, while another was associated with lower CR and DO. Our results suggest that CR in the coastal ocean varies with both environmental variables, and a portion of the microbial community that is not directly correlated with upwelling intensity.

Contribution of Bicarbonate Assimilation to Carbon Pool Dynamics in the Deep Mediterranean Sea and Cultivation of Actively Nitrifying and CO2-Fixing Bathypelagic Prokaryotic Consortia

Covering two-thirds of our planet, the global deep ocean plays a central role in supporting life on Earth. Among other processes, this biggest ecosystem buffers the rise of atmospheric CO2. Despite carbon sequestration in the deep ocean has been known for a long time, microbial activity in the meso- and bathypelagic realm via the "assimilation of bicarbonate in the dark" (ABD) has only recently been described in more details. Based on recent findings, this process seems primarily the result of chemosynthetic and anaplerotic reactions driven by different groups of deep-sea prokaryoplankton. We quantified bicarbonate assimilation in relation to total prokaryotic abundance, prokaryotic heterotrophic production and respiration in the meso- and bathypelagic Mediterranean Sea. The measured ABD values, ranging from 133 to 370 μg C m-3 d-1, were among the highest ones reported worldwide for similar depths, likely due to the elevated temperature of the deep Mediterranean Sea (13-14°C also at abyssal depths). Integrated over the dark water column (≥200 m depth), bicarbonate assimilation in the deep-sea ranged from 396 to 873 mg C m-2 d-1. This quantity of produced de novo organic carbon amounts to about 85-424% of the phytoplankton primary production and covers up to 62% of deep-sea prokaryotic total carbon demand. Hence, the ABD process in the meso- and bathypelagic Mediterranean Sea might substantially contribute to the inorganic and organic pool and significantly sustain the deep-sea microbial food web. To elucidate the ABD key-players, we established three actively nitrifying and CO2-fixing prokaryotic enrichments. Consortia were characterized by the co-occurrence of chemolithoautotrophic Thaumarchaeota and chemoheterotrophic proteobacteria. One of the enrichments, originated from Ionian bathypelagic waters (3,000 m depth) and supplemented with low concentrations of ammonia, was dominated by the Thaumarchaeota "low-ammonia-concentration" deep-sea ecotype, an enigmatic and ecologically important group of organisms, uncultured until this study.

Geographical patterns of denitrifying bacterial communities associated with different urban lakes

The geographical variation of denitrifying bacterial communities and water quality parameters in urban lakes distributed across nine provinces in China were determined. The Illumina sequencing data of the denitrifying encoding gene nirS was examined in the samples collected from nine localities (pairwise geographical distance: 200–2600 km). The results showed that fundamental differences in water quality were observed among different urban lakes. The highest nitrate (2.02 mg L⁻¹) and total nitrogen (3.82 mg L⁻¹) concentrations were observed in Pingzhuang (P < 0.01). The algal cell concentration ranged from 1.29 × 10⁸ to 3.0 × 10⁹ cell per L. The sequencing data generated a total of 421058 high quality nirS gene reads that resulted in 6369 OTUs (97% cutoff), with Proteobacteria and Firmicutes being the dominant taxa. A co-occurrence network analysis indicated that the top five genera identified as keystone taxa were Dechlorospirillum sp., Alicycliphilus sp., Dechloromonas sp., Pseudogulbenkiania sp., and Paracoccus sp. A redundancy analysis (RDA) further revealed that distinct denitrifying bacterial communities inhabited the different urban lakes, and influenced by urban lake water ammonia nitrogen, manganese and algal cell concentrations. A variance partitioning analysis (VPA) also showed that geographic location was more important than water quality factors in structuring the denitrifying bacterial communities. Together, these results provide new insight into understanding of denitrifying bacterial communities associated with geographically distributed urban lakes on a larger scale, and these results also expand our exploration of aquatic microbial ecology in freshwater bodies.

The geographical variation of denitrifying bacterial communities and water quality parameters in urban lakes distributed across nine provinces in China were determined.

Marine archaeal dynamics and interactions with the microbial community over 5 years from surface to seafloor

Marine archaea are critical contributors to global carbon and nitrogen redox cycles, but their temporal variability and microbial associations across the water column are poorly known. We evaluated seasonal variability of free living (0.2-1 μm size fraction) Thaumarchaea Marine Group I (MGI) and Euryarchaea Marine Group II (MGII) communities and their associations with the microbial community from surface to seafloor (890 m) over 5 years by 16S rRNA V4-V5 gene sequencing. MGI and MGII communities demonstrated distinct compositions at different depths, and seasonality at all depths. Microbial association networks at 150 m, 500 m and 890 m, revealed diverse assemblages of MGI (presumed ammonia oxidizers) and Nitrospina taxa (presumed dominant nitrite oxidizers, completing the nitrification process), suggesting distinct MGI-Nitrospina OTUs are responsible for nitrification at different depths and seasons, and depth- related and seasonal variability in nitrification could be affected by alternating MGI-Nitrospina assemblages. MGII taxa also showed distinct correlations to possibly heterotrophic bacteria, most commonly to members of Marine Group A, Chloroflexi, Marine Group B, and SAR86. Thus, both MGI and MGII likely have dynamic associations with bacteria based on similarities in activity or other interactions that select for distinct microbial assemblages over time. The importance of MGII taxa as members of the heterotrophic community previously reported for photic zone appears to apply throughout the water column.

Ecological diversity and co-occurrence patterns of bacterial community through soil profile in response to long-term switchgrass cultivation

Switchgrass (Panicum virgatum L.) is a cellulosic biofuel feedstock and their effects on bacterial communities in deep soils remain poorly understood. To reveal the responses of bacterial communities to long-term switchgrass cultivation through the soil profile, we examined the shift of soil microbial communities with depth profiles of 0–60 cm in five-year switchgrass cultivation and fallow plots. The Illumina sequencing of the 16S rRNA gene showed that switchgrass cultivation significantly increased microbial OTU richness, rather than microbial Shannon diversity; however, there was no significant difference in the structure of microbial communities between switchgrass cultivation and fallow soils. Both switchgrass cultivation and fallow soils exhibited significant negative vertical spatial decay of microbial similarity, indicating that more vertical depth distant soils had more dissimilar communities. Specifically, switchgrass cultivation soils showed more beta-diversity variations across soil depth profile. Through network analysis, more connections and closer relationships of microbial taxa were observed in soils under switchgrass cultivation, suggesting that microbial co-occurrence patterns were substantially influenced by switchgrass cultivation. Overall, our study suggested that five-year switchgrass cultivation could generated more beta-diversity variations across soil depth and more complex inter-relationships of microbial taxa, although did not significantly shape the structure of soil microbial community.

Distinct distribution patterns of prokaryotes between sediment and water in the Yellow River estuary

There are close exchanges between sediment and water in estuaries; however, the patterns of prokaryotic community assembly in these two habitat types are still unclear. This study investigated the bacterial and archaeal abundance, diversity, and community composition in the sediment and the overlying water of the Yellow River estuary. Notably higher prokaryotic abundance and diversity were detected in the sediment than in the water, and bacterial abundance and diversity were remarkably higher than those of archaea. Furthermore, the ratio of bacterial to archaeal 16S rRNA gene abundance was significantly lower in the sediment than in the water. Bacterial communities at different taxonomic levels were apparently distinct between the sediment and water, but archaeal communities were not. The most dominant bacteria were affiliated with Deltaproteobacteria and Gammaproteobacteria in sediment and with Alphaproteobacteria and Betaproteobacteria in water. Euryarchaeota and Thaumarchaeota were the most abundant archaea in both habitats. Although distinct prokaryotic distribution patterns were observed, most of the dominant bacteria and archaea present were related to carbon, nitrogen, and sulfur cycling processes, such as methanogenesis, ammonia oxidation, and sulfate reduction. Unexpectedly, prokaryotes from the water showed a higher sensitivity to environmental factors, while only a few factors affected sediment communities. Additionally, some potential co-occurrence relationships between prokaryotes were also found in this study. These results suggested distinct distribution patterns of bacterial and archaeal communities between sediment and overlying water in this important temperate estuary, which may serve as a useful community model for the further ecological and evolutionary study of prokaryotes in estuarine ecosystems.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

Correlation detection strategies in microbial data sets vary widely in sensitivity and precision

Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.

Diversity of Pico- to Mesoplankton along the 2000 km Salinity Gradient of the Baltic Sea

Microbial plankton form the productive base of both marine and freshwater ecosystems and are key drivers of global biogeochemical cycles of carbon and nutrients. Plankton diversity is immense with representations from all major phyla within the three domains of life. So far, plankton monitoring has mainly been based on microscopic identification, which has limited sensitivity and reproducibility, not least because of the numerical majority of plankton being unidentifiable under the light microscope. High-throughput sequencing of taxonomic marker genes offers a means to identify taxa inaccessible by traditional methods; thus, recent studies have unveiled an extensive previously unknown diversity of plankton. Here, we conducted ultra-deep Illumina sequencing (average 10⁵ sequences/sample) of rRNA gene amplicons of surface water eukaryotic and bacterial plankton communities sampled in summer along a 2000 km transect following the salinity gradient of the Baltic Sea. Community composition was strongly correlated with salinity for both bacterial and eukaryotic plankton assemblages, highlighting the importance of salinity for structuring the biodiversity within this ecosystem. In contrast, no clear trends in alpha-diversity for bacterial or eukaryotic communities could be detected along the transect. The distribution of major planktonic taxa followed expected patterns as observed in monitoring programs, but groups novel to the Baltic Sea were also identified, such as relatives to the coccolithophore Emiliana huxleyi detected in the northern Baltic Sea. This study provides the first ultra-deep sequencing-based survey on eukaryotic and bacterial plankton biogeography in the Baltic Sea.

Co-occurrence Analysis of Microbial Taxa in the Atlantic Ocean Reveals High Connectivity in the Free-Living Bacterioplankton

We determined the taxonomic composition of the bacterioplankton of the epipelagic zone of the Atlantic Ocean along a latitudinal transect (51°S–47°N) using Illumina sequencing of the V5-V6 region of the 16S rRNA gene and inferred co-occurrence networks. Bacterioplankon community composition was distinct for Longhurstian provinces and water depth. Free-living microbial communities (between 0.22 and 3 μm) were dominated by highly abundant and ubiquitous taxa with streamlined genomes (e.g., SAR11, SAR86, OM1, Prochlorococcus) and could clearly be separated from particle-associated communities which were dominated by Bacteroidetes, Planktomycetes, Verrucomicrobia, and Roseobacters. From a total of 369 different communities we then inferred co-occurrence networks for each size fraction and depth layer of the plankton between bacteria and between bacteria and phototrophic micro-eukaryotes. The inferred networks showed a reduction of edges in the deepest layer of the photic zone. Networks comprised of free-living bacteria had a larger amount of connections per OTU when compared to the particle associated communities throughout the water column. Negative correlations accounted for roughly one third of the total edges in the free-living communities at all depths, while they decreased with depth in the particle associated communities where they amounted for roughly 10% of the total in the last part of the epipelagic zone. Co-occurrence networks of bacteria with phototrophic micro-eukaryotes were not taxon-specific, and dominated by mutual exclusion (~60%). The data show a high degree of specialization to micro-environments in the water column and highlight the importance of interdependencies particularly between free-living bacteria in the upper layers of the epipelagic zone.

Microbial succession in response to pollutants in batch-enrichment culture

As a global problem, environmental pollution is an important factor to shape the microbial communities. The elucidation of the succession of microbial communities in response to pollutants is essential for developing bioremediation procedures. In the present study, ten batches of soil-enrichment subcultures were subjected to four treatments: phenanthrene, n-octadecane, phenanthrene + n-octadecane, or phenanthrene + n-octadecane + CdCl₂. Forty pollutant-degrading consortia, corresponding to each batch of the four treatments were obtained. High-throughput sequencing of the 16S rRNA gene revealed that the diversity, richness and evenness of the consortia decreased throughout the subculturing procedure. The well-known hydrocarbon degraders Acinetobacter, Gordonia, Sphingobium, Sphingopyxis, and Castellaniella and several other genera, including Niabella and Naxibacter, were detected in the enriched consortia. The predominant microbes varied and the microbial community in the consortia gradually changed during the successive subculturing depending on the treatment, indicating that the pollutants influenced the microbial successions. Comparison of the networks in the treatments indicated that organic pollutants and CdCl₂ affected the co-occurrence patterns in enriched consortia. In conclusion, single environmental factors, such as the addition of nutrients or selection pressure, can shape microbial communities and partially explain the extensive differences in microbial community structures among diverse environments.

Using "Omics" and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called "omics," are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov-Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.

Diversity of Pico- to Mesoplankton along the 2000 km Salinity Gradient of the Baltic Sea

Microbial plankton form the productive base of both marine and freshwater ecosystems and are key drivers of global biogeochemical cycles of carbon and nutrients. Plankton diversity is immense with representations from all major phyla within the three domains of life. So far, plankton monitoring has mainly been based on microscopic identification, which has limited sensitivity and reproducibility, not least because of the numerical majority of plankton being unidentifiable under the light microscope. High-throughput sequencing of taxonomic marker genes offers a means to identify taxa inaccessible by traditional methods; thus, recent studies have unveiled an extensive previously unknown diversity of plankton. Here, we conducted ultra-deep Illumina sequencing (average 10(5) sequences/sample) of rRNA gene amplicons of surface water eukaryotic and bacterial plankton communities sampled in summer along a 2000 km transect following the salinity gradient of the Baltic Sea. Community composition was strongly correlated with salinity for both bacterial and eukaryotic plankton assemblages, highlighting the importance of salinity for structuring the biodiversity within this ecosystem. In contrast, no clear trends in alpha-diversity for bacterial or eukaryotic communities could be detected along the transect. The distribution of major planktonic taxa followed expected patterns as observed in monitoring programs, but groups novel to the Baltic Sea were also identified, such as relatives to the coccolithophore Emiliana huxleyi detected in the northern Baltic Sea. This study provides the first ultra-deep sequencing-based survey on eukaryotic and bacterial plankton biogeography in the Baltic Sea.

Physiological and genomic characterization of two novel marine thaumarchaeal strains indicates niche differentiation

Ammonia-oxidizing Archaea (AOA) are ubiquitous throughout the oceanic water column; however, our knowledge on their physiological and ecological diversity in different oceanic regions is rather limited. Here, we report the cultivation and characterization of two novel Nitrosopumilus strains, originating from coastal surface waters of the Northern Adriatic Sea. The combined physiological and genomic information revealed that each strain exhibits different metabolic and functional traits, potentially reflecting contrasting life modes. Strain NF5 contains many chemotaxis-related genes and is able to express archaella, suggesting that it can sense and actively seek favorable microenvironments such as nutrient-rich particles. In contrast, strain D3C is non-motile and shows higher versatility in substrate utilization, being able to use urea as an alternative substrate in addition to ammonia. Furthermore, it encodes a divergent, second copy of the AmoB subunit of the key enzyme ammonia monooxygenase, which might have an additional catalytic function and suggests further metabolic versatility. However, the role of this gene requires further investigation. Our results provide evidence for functional diversity and metabolic versatility among phylogenetically closely related thaumarchaeal strains, and point toward adaptations to free-living versus particle-associated life styles and possible niche differentiation among AOA in marine ecosystems.

Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples

Microbial community analysis via high-throughput sequencing of amplified 16S rRNA genes is an essential microbiology tool. We found the popular primer pair 515F (515F-C) and 806R greatly underestimated (e.g. SAR11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F-Y (5'-GTGYCAGCMGCCGCGGTAA) and 926R (5'-CCGYCAATTYMTTTRAGTTT) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with 515F-C/806R, and amplify eukaryotic 18S rRNA. Mock communities amplified with 515F-Y/926R yielded closer observed community composition versus expected (r(2)  = 0.95) compared with 515F-Y/806R (r(2)  ∼ 0.5). Unexpectedly, biases with 515F-Y/806R against SAR11 in field samples (∼4-10-fold) were stronger than in mock communities (∼2-fold). Correcting a mismatch to Thaumarchaea in the 515F-C increased their apparent abundance in field samples, but not as much as using 926R rather than 806R. With plankton samples rich in eukaryotic DNA (> 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond in silico predictions, testing with mock communities and field samples is important in primer selection.

No apparent correlation between honey bee forager gut microbiota and honey production

One of the best indicators of colony health for the European honey bee (Apis mellifera) is its performance in the production of honey. Recent research into the microbial communities naturally populating the bee gut raise the question as to whether there is a correlation between microbial community structure and colony productivity. In this work, we used 16S rRNA amplicon sequencing to explore the microbial composition associated with forager bees from honey bee colonies producing large amounts of surplus honey (productive) and compared them to colonies producing less (unproductive). As supported by previous work, the honey bee microbiome was found to be dominated by three major phyla: the Proteobacteria, Bacilli and Actinobacteria, within which we found a total of 23 different bacterial genera, including known “core” honey bee microbiome members. Using discriminant function analysis and correlation-based network analysis, we identified highly abundant members (such as Frischella and Gilliamella) as important in shaping the bacterial community; libraries from colonies with high quantities of these Orbaceae members were also likely to contain fewer Bifidobacteria and Lactobacillus species (such as Firm-4). However, co-culture assays, using isolates from these major clades, were unable to confirm any antagonistic interaction between Gilliamella and honey bee gut bacteria. Our results suggest that honey bee colony productivity is associated with increased bacterial diversity, although this mechanism behind this correlation has yet to be determined. Our results also suggest researchers should not base inferences of bacterial interactions solely on correlations found using sequencing. Instead, we suggest that depth of sequencing and library size can dramatically influence statistically significant results from sequence analysis of amplicons and should be cautiously interpreted.

Ocean plankton. Determinants of community structure in the global plankton interactome

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

Spatial distribution patterns of benthic microbial communities along the Pearl Estuary, China

In the present study, benthic microbial communities along the Pearl Estuary, a typical subtropical estuary in China subjected to extensive anthropogenic disturbance, were investigated using 16S rRNA gene-based pyrosequencing. The results showed that microbial communities in freshwater samples were clearly distinct from those in saltwater samples, since the relative sequence abundances of Deltaproteobacteria, Thermoplasmata and Marine Group I (MG-I) were higher in saltwater sediments, whereas Chloroflexi, Spirochaetes, Betaproteobacteria and methanogens were more prevalent in freshwater sediments. In addition, bacterial communities showed vertical stratifications in saltwater sediments, but remained constant with depth in freshwater sediments. The total organic carbon and carbon/nitrogen ratio in sediments correlated significantly with the overall community variations. The predominance of various microorganisms in specific niches led to efforts to identify their functional couplings by exploring their co-occurrence patterns. Using network analysis, strong positive correlations were observed between sulfate-reducing bacteria (SRB) and sulfur-oxidizing bacteria, and between SRB and nitrite-oxidizing bacteria, indicating the potential interactions of intra-sulfur cycle processes, as well as sulfur and nitrogen cycles, in coastal sediments. Archaeal clades revealed strong and wide correlations between the Miscellaneous Crenarchaeotal Group (MCG) and other groups, suggesting a central role of MCG in the coastal benthic environment. Inversely, MG-I displayed negative correlations with other clades, which might indicate that the lifestyles of heterotrophic and autotrophic clades were mutually exclusive. This study presented a detailed outline of the biogeographic patterns of benthic microbial communities along the Pearl Estuary and provided new information regarding the potential interactions of various biogeochemical cycles in coastal sediments.

Niche distribution and influence of environmental parameters in marine microbial communities: a systematic review

Associations between microorganisms occur extensively throughout Earth’s oceans. Understanding how microbial communities are assembled and how the presence or absence of species is related to that of others are central goals of microbial ecology. Here, we investigate co-occurrence associations between marine prokaryotes by combining 180 new and publicly available metagenomic datasets from different oceans in a large-scale meta-analysis. A co-occurrence network was created by calculating correlation scores between the abundances of microorganisms in metagenomes. A total of 1,906 correlations amongst 297 organisms were detected, segregating them into 11 major groups that occupy distinct ecological niches. Additionally, by analyzing the oceanographic parameters measured for a selected number of sampling sites, we characterized the influence of environmental variables over each of these 11 groups. Clustering organisms into groups of taxa that have similar ecology, allowed the detection of several significant correlations that could not be observed for the taxa individually.

Cross-depth analysis of marine bacterial networks suggests downward propagation of temporal changes

Interactions among microbes and stratification across depths are both believed to be important drivers of microbial communities, though little is known about how microbial associations differ between and across depths. We have monitored the free-living microbial community at the San Pedro Ocean Time-series station, monthly, for a decade, at five different depths: 5 m, the deep chlorophyll maximum layer, 150 m, 500 m and 890 m (just above the sea floor). Here, we introduce microbial association networks that combine data from multiple ocean depths to investigate both within- and between-depth relationships, sometimes time-lagged, among microbes and environmental parameters. The euphotic zone, deep chlorophyll maximum and 890 m depth each contain two negatively correlated 'modules' (groups of many inter-correlated bacteria and environmental conditions) suggesting regular transitions between two contrasting environmental states. Two-thirds of pairwise correlations of bacterial taxa between depths lagged such that changes in the abundance of deeper organisms followed changes in shallower organisms. Taken in conjunction with previous observations of seasonality at 890 m, these trends suggest that planktonic microbial communities throughout the water column are linked to environmental conditions and/or microbial communities in overlying waters. Poorly understood groups including Marine Group A, Nitrospina and AEGEAN-169 clades contained taxa that showed diverse association patterns, suggesting these groups contain multiple ecological species, each shaped by different factors, which we have started to delineate. These observations build upon previous work at this location, lending further credence to the hypothesis that sinking particles and vertically migrating animals transport materials that significantly shape the time-varying patterns of microbial community composition.

Marine microbial community dynamics and their ecological interpretation

Recent advances in studying the dynamics of marine microbial communities have shown that the composition of these communities follows predictable patterns and involves complex network interactions, which shed light on the underlying processes regulating these globally important organisms. Such 'holistic' (or organism- and system-based) studies of these communities complement popular reductionist, often culture-based, approaches for understanding organism function one gene or protein at a time. In this Review, we summarize our current understanding of marine microbial community dynamics at various scales, from hours to decades. We also explain how the data illustrate community resilience and seasonality, and reveal interactions among microorganisms.

Seasonal dynamics of active SAR11 ecotypes in the oligotrophic Northwest Mediterranean Sea

A seven-year oceanographic time series in NW Mediterranean surface waters was combined with pyrosequencing of ribosomal RNA (16S rRNA) and ribosomal RNA gene copies (16S rDNA) to examine the environmental controls on SAR11 ecotype dynamics and potential activity. SAR11 diversity exhibited pronounced seasonal cycles remarkably similar to total bacterial diversity. The timing of diversity maxima was similar across narrow and broad phylogenetic clades and strongly associated with deep winter mixing. Diversity minima were associated with periods of stratification that were low in nutrients and phytoplankton biomass and characterised by intense phosphate limitation (turnover time<5 h). We propose a conceptual framework in which physical mixing of the water column periodically resets SAR11 communities to a high diversity state and the seasonal evolution of phosphate limitation competitively excludes deeper-dwelling ecotypes to promote low diversity states dominated (>80%) by SAR11 Ia. A partial least squares (PLS) regression model was developed that could reliably predict sequence abundances of SAR11 ecotypes (Q(2)=0.70) from measured environmental variables, of which mixed layer depth was quantitatively the most important. Comparison of clade-level SAR11 rRNA:rDNA signals with leucine incorporation enabled us to partially validate the use of these ratios as an in-situ activity measure. However, temporal trends in the activity of SAR11 ecotypes and their relationship to environmental variables were unclear. The strong and predictable temporal patterns observed in SAR11 sequence abundance was not linked to metabolic activity of different ecotypes at the phylogenetic and temporal resolution of our study.

A modular organization of the human intestinal mucosal microbiota and its association with inflammatory bowel disease

Abnormalities of the intestinal microbiota are implicated in the pathogenesis of Crohn's disease (CD) and ulcerative colitis (UC), two spectra of inflammatory bowel disease (IBD). However, the high complexity and low inter-individual overlap of intestinal microbial composition are formidable barriers to identifying microbial taxa representing this dysbiosis. These difficulties might be overcome by an ecologic analytic strategy to identify modules of interacting bacteria (rather than individual bacteria) as quantitative reproducible features of microbial composition in normal and IBD mucosa. We sequenced 16S ribosomal RNA genes from 179 endoscopic lavage samples from different intestinal regions in 64 subjects (32 controls, 16 CD and 16 UC patients in clinical remission). CD and UC patients showed a reduction in phylogenetic diversity and shifts in microbial composition, comparable to previous studies using conventional mucosal biopsies. Analysis of weighted co-occurrence network revealed 5 microbial modules. These modules were unprecedented, as they were detectable in all individuals, and their composition and abundance was recapitulated in an independent, biopsy-based mucosal dataset 2 modules were associated with healthy, CD, or UC disease states. Imputed metagenome analysis indicated that these modules displayed distinct metabolic functionality, specifically the enrichment of oxidative response and glycan metabolism pathways relevant to host-pathogen interaction in the disease-associated modules. The highly preserved microbial modules accurately classified IBD status of individual patients during disease quiescence, suggesting that microbial dysbiosis in IBD may be an underlying disorder independent of disease activity. Microbial modules thus provide an integrative view of microbial ecology relevant to IBD.

Temporal variability and coherence of euphotic zone bacterial communities over a decade in the Southern California Bight

Time-series are critical to understanding long-term natural variability in the oceans. Bacterial communities in the euphotic zone were investigated for over a decade at the San Pedro Ocean Time-series station (SPOT) off southern California. Community composition was assessed by Automated Ribosomal Intergenic Spacer Analysis (ARISA) and coupled with measurements of oceanographic parameters for the surface ocean (0-5 m) and deep chlorophyll maximum (DCM, average depth ≈ 30 m). SAR11 and cyanobacterial ecotypes comprised typically more than one-third of the measured community; diversity within both was temporally variable, although a few operational taxonomic units (OTUs) were consistently more abundant. Persistent OTUs, mostly Alphaproteobacteria (SAR11 clade), Actinobacteria and Flavobacteria, tended to be abundant, in contrast to many rarer yet intermittent and ephemeral OTUs. Association networks revealed potential niches for key OTUs from SAR11, cyanobacteria, SAR86 and other common clades on the basis of robust correlations. Resilience was evident by the average communities drifting only slightly as years passed. Average Bray-Curtis similarity between any pair of dates was ≈ 40%, with a slight decrease over the decade and obvious near-surface seasonality; communities 8-10 years apart were slightly more different than those 1-4 years apart with the highest rate of change at 0-5 m between communities <4 years apart. The surface exhibited more pronounced seasonality than the DCM. Inter-depth Bray-Curtis similarities repeatedly decreased as the water column stratified each summer. Environmental factors were better predictors of shifts in community composition than months or elapsed time alone; yet, the best predictor was community composition at the other depth (that is, 0-5 m versus DCM).

High-throughput sequencing: a roadmap toward community ecology

High-throughput sequencing is becoming increasingly important in microbial ecology, yet it is surprisingly under-used to generate or test biogeographic hypotheses. In this contribution, we highlight how adding these methods to the ecologist toolbox will allow the detection of new patterns, and will help our understanding of the structure and dynamics of diversity. Starting with a review of ecological questions that can be addressed, we move on to the technical and analytical issues that will benefit from an increased collaboration between different disciplines.

Intra- and intergenomic variation of ribosomal RNA operons in concurrent Alteromonas macleodii strains

Biodiversity estimates based on ribosomal operon sequence diversity rely on the premise that a sequence is characteristic of a single specific taxon or operational taxonomic unit (OTU). Here, we have studied the sequence diversity of 14 ribosomal RNA operons (rrn) contained in the genomes of two isolates (five operons in each genome) and four metagenomic fosmids, all from the same seawater sample. Complete sequencing of the isolate genomes and the fosmids establish that they represent strains of the same species, Alteromonas macleodii, with average nucleotide identity (ANI) values >97 %. Nonetheless, we observed high levels of intragenomic heterogeneity (i.e., variability between operons of a single genome) affecting multiple regions of the 16S and 23S rRNA genes as well as the internally transcribed spacer 1 (ITS-1) region. Furthermore, the ribosomal operons exhibited intergenomic heterogeneity (i.e., variability between operons located in separate genomes) in each of these regions, compounding the variability. Our data reveal the extensive heterogeneity observed in natural populations of A. macleodii at a single point in time and support the idea that distinct lineages of A. macleodii exist in the deep Mediterranean. These findings highlight the potential of rRNA fingerprinting methods to misrepresent species diversity while simultaneously failing to recognize the ecological significance of individual strains.

Efficient statistical significance approximation for local similarity analysis of high-throughput time series data

MOTIVATION

Local similarity analysis of biological time series data helps elucidate the varying dynamics of biological systems. However, its applications to large scale high-throughput data are limited by slow permutation procedures for statistical significance evaluation.

RESULTS

We developed a theoretical approach to approximate the statistical significance of local similarity analysis based on the approximate tail distribution of the maximum partial sum of independent identically distributed (i.i.d.) random variables. Simulations show that the derived formula approximates the tail distribution reasonably well (starting at time points > 10 with no delay and > 20 with delay) and provides P-values comparable with those from permutations. The new approach enables efficient calculation of statistical significance for pairwise local similarity analysis, making possible all-to-all local association studies otherwise prohibitive. As a demonstration, local similarity analysis of human microbiome time series shows that core operational taxonomic units (OTUs) are highly synergetic and some of the associations are body-site specific across samples.

AVAILABILITY

The new approach is implemented in our eLSA package, which now provides pipelines for faster local similarity analysis of time series data. The tool is freely available from eLSA's website: http://meta.usc.edu/softs/lsa.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CONTACT

fsun@usc.edu.

Metagenomic exploration of viruses throughout the Indian Ocean

The characterization of global marine microbial taxonomic and functional diversity is a primary goal of the Global Ocean Sampling Expedition. As part of this study, 19 water samples were collected aboard the Sorcerer II sailing vessel from the southern Indian Ocean in an effort to more thoroughly understand the lifestyle strategies of the microbial inhabitants of this ultra-oligotrophic region. No investigations of whole virioplankton assemblages have been conducted on waters collected from the Indian Ocean or across multiple size fractions thus far. Therefore, the goals of this study were to examine the effect of size fractionation on viral consortia structure and function and understand the diversity and functional potential of the Indian Ocean virome. Five samples were selected for comprehensive metagenomic exploration; and sequencing was performed on the microbes captured on 3.0-, 0.8- and 0.1 µm membrane filters as well as the viral fraction (<0.1 µm). Phylogenetic approaches were also used to identify predicted proteins of viral origin in the larger fractions of data from all Indian Ocean samples, which were included in subsequent metagenomic analyses. Taxonomic profiling of viral sequences suggested that size fractionation of marine microbial communities enriches for specific groups of viruses within the different size classes and functional characterization further substantiated this observation. Functional analyses also revealed a relative enrichment for metabolic proteins of viral origin that potentially reflect the physiological condition of host cells in the Indian Ocean including those involved in nitrogen metabolism and oxidative phosphorylation. A novel classification method, MGTAXA, was used to assess virus-host relationships in the Indian Ocean by predicting the taxonomy of putative host genera, with Prochlorococcus, Acanthochlois and members of the SAR86 cluster comprising the most abundant predictions. This is the first study to holistically explore virioplankton dynamics across multiple size classes and provides unprecedented insight into virus diversity, metabolic potential and virus-host interactions.

Geographic specific coral-associated ammonia-oxidizing archaea in the northern Gulf of Eilat (Red Sea)

Coral holobionts are densely populated with microorganisms that are essential for their well-being. Here we compared the diversity of the archaeal ammonia monooxygenase alpha subunit (amoA) gene from three coral genera, Acanthastrea sp., Favia sp., and Fungia granulosa, from the Gulf of Eilat, Red Sea. At 99% similarity, archaeal amoA from the three coral genera shared 71% of their cloned sequences, while the Favia and Acanthastrea presented a few genus-specific clones. In addition, the sequences retrieved in our samples displayed lower similarity to amoA sequences previously found in association with other coral species from different geographic regions. This finding suggests that the populations of ammonia-oxidizing archaea are less host-specific and more geographically dependent.

Basin-scale patterns in the abundance of SAR11 subclades, marine Actinobacteria (OM1), members of the Roseobacter clade and OCS116 in the South Atlantic

Bacterioplankton are major biogeochemical agents responsible for mediating the flux of dissolved organic matter (DOM) and subsequent cycling of nutrients in the oceans. Most information about the composition of bacterioplankton communities has come from studies along well-defined biogeochemical gradients in the northern hemisphere. This study extends observations of spatial and temporal dynamics for SAR11, Actinobacteria and OCS116 in the North Atlantic by demonstrating distinct spatial variability in the abundance and distribution of these and other lineages across the South Atlantic gyre and in the Benguela upwelling system. We identified shifts in SAR11, Actinobacteria, OCS116, SAR86, SAR116 and members of the Roseobacter clade along basin-scale gradients in nutrients, chlorophyll and dissolved organic carbon (DOC). Distinct SAR11 subclades dominated the western and eastern regions of the gyre, and Actinobacteria, OCS116 and members of the Roseobacter lineages were most abundant at the deep chlorophyll maxima. SAR86 and SAR116 accounted for a significant fraction of coastal and open ocean communities, respectively, and members of the gamma sulfur oxidizer (GSO) clade persisted in the Benguela upwelling system. These data suggest that distinct communities are partitioned along basin-scale biogeochemical gradients, that SAR11 community structure varies across the gyre and that Actinobacteria, OCS116, and members of the Roseobacter clade are closely associated with phytoplankton in the gyre.