Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates

Response of particle-attached and free-living bacterial communities to Microcystis blooms

The massive proliferation of Microcystis threatens freshwater ecosystems and degrades water quality globally. Understanding the mechanisms that contribute to Microcystis growth is crucial for managing Microcystis blooms. The lifestyles of bacteria can be classified generally into two groups: particle-attached (PA; > 3 µm) and free-living (FL; 0.2-3.0 µm). However, little is known about the response of PA and FL bacteria to Microcystis blooms. Using 16S rRNA gene high-throughput sequencing, we investigated the stability, assembly process, and co-occurrence patterns of PA and FL bacterial communities during distinct bloom stages. PA bacteria were phylogenetically different from their FL counterparts. Microcystis blooms substantially influenced bacterial communities. The time decay relationship model revealed that Microcystis blooms might increase the stability of both PA and FL bacterial communities. A contrasting community assembly mechanism was observed between the PA and FL bacterial communities. Throughout Microcystis blooms, homogeneous selection was the major assembly process that impacted the PA bacterial community, whereas drift explained much of the turnover of the FL bacterial community. Both PA and FL bacterial communities could be separated into modules related to different phases of Microcystis blooms. Microcystis blooms altered the assembly process of PA and FL bacterial communities. PA bacterial community appeared to be more responsive to Microcystis blooms than FL bacteria. Decomposition of Microcystis blooms may enhance cooperation among bacteria. Our findings highlight the importance of studying bacterial lifestyles to understand their functions in regulating Microcystis blooms. KEY POINTS: • Microcystis blooms alter the assembly process of PA and FL bacterial communities • Microcystis blooms increase the stability of both PA and FL bacterial communities • PA bacteria seem to be more responsive to Microcystis blooms than FL bacteria.

Effect of rainfall in shaping microbial community during Microcystis bloom in Nakdong River, Korea

Various environmental factors play a role in the formation and collapse of Microcystis blooms. This study investigates the impact of heavy rainfall on cyanobacterial abundance, microbial community composition, and functional dynamics in the Nakdong River, South Korea, during typical and exceptionally rainy years. The results reveal distinct responses to rainfall variations, particularly in cyanobacterial dominance and physicochemical characteristics. In 2020, characterized by unprecedented rainfall from mid-July to August, Microcystis blooms were interrupted significantly, exhibiting lower cell densities and decreased water temperature, compared to normal bloom patterns in 2019. Moreover, microbial community composition varied, with increases in Gammaproteobacteria and notably in genera of Limnohabitans and Fluviicola. These alterations in environmental conditions and bacterial community were similar to those of the post-bloom period in late September 2019. It shows that heavy rainfall during summer leads to changes in environmental factors, consequently causing shifts in bacterial communities akin to those observed during the autumn-specific post-bloom period in typical years. These changes also accompany shifts in bacterial functions, primarily involved in the degradation of organic matter such as amino acids, fatty acids, and terpenoids, which are assumed to have been released due to the significant collapse of cyanobacteria. Our results demonstrate that heavy rainfall in early summer induces changes in the environmental factors and subsequently microbial communities and their functions, similar to those of the post-bloom period in autumn, leading to the earlier breakdown of Microcystis blooms.

DeepMicroClass sorts metagenomic contigs into prokaryotes, eukaryotes and viruses

Sequence classification facilitates a fundamental understanding of the structure of microbial communities. Binary metagenomic sequence classifiers are insufficient because environmental metagenomes are typically derived from multiple sequence sources. Here we introduce a deep-learning based sequence classifier, DeepMicroClass, that classifies metagenomic contigs into five sequence classes, i.e. viruses infecting prokaryotic or eukaryotic hosts, eukaryotic or prokaryotic chromosomes, and prokaryotic plasmids. DeepMicroClass achieved high performance for all sequence classes at various tested sequence lengths ranging from 500 bp to 100 kbps. By benchmarking on a synthetic dataset with variable sequence class composition, we showed that DeepMicroClass obtained better performance for eukaryotic, plasmid and viral contig classification than other state-of-the-art predictors. DeepMicroClass achieved comparable performance on viral sequence classification with geNomad and VirSorter2 when benchmarked on the CAMI II marine dataset. Using a coastal daily time-series metagenomic dataset as a case study, we showed that microbial eukaryotes and prokaryotic viruses are integral to microbial communities. By analyzing monthly metagenomes collected at HOT and BATS, we found relatively higher viral read proportions in the subsurface layer in late summer, consistent with the seasonal viral infection patterns prevalent in these areas. We expect DeepMicroClass will promote metagenomic studies of under-appreciated sequence types.

Implications of PM2.5 chemical composition in modulating microbial community dynamics during spring in Seoul

Particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) harbors a diverse microbial community. To assess the ecological dynamics and potential health risks associated with airborne microorganisms, it is crucial to understand the factors influencing microbial communities within PM2.5. This study investigated the influence of abiotic parameters, including air pollutants, PM2.5 chemical composition (water-soluble ions and organics), and meteorological variables, on microbial communities in PM2.5 samples collected in Seoul during the spring season. Results revealed a significant correlation between air pollutants and water-soluble ions of PM2.5 with microbial α-diversity indices. Additionally, air pollutants exerted a dominant effect on the microbial community structure, with stronger correlations observed for fungi than bacteria, whereas meteorological variables including temperature, pressure, wind speed, and humidity exerted a limited influence on fungal α-diversity. Furthermore, the results revealed specific water-soluble ions, such as SO42-, NO3-, and NH4+, as important factors influencing fungal α-diversity, whereas K+ negatively correlated with both microbial α-diversity. Moreover, PM2.5 microbial diversity was affected by organic compounds within PM2.5, with fatty acids exhibited a positive correlation with fungal diversity, while dicarboxylic acids exhibited a negative correlation with it. Furthermore, network analysis revealed direct links between air pollutants and dominant bacterial and fungal genera. The air pollutants exhibited a strong correlation with bacterial genera, such as Arthrospira and Clostridium, and fungal genera, including Aureobasidium and Cladosporium. These results will contribute to our understanding of the ecological dynamics of airborne microorganisms and provide insights into the potential risks associated with PM2.5 exposure.

Taxonomic difference in marine bloom-forming phytoplanktonic species affects the dynamics of both bloom-responding prokaryotes and prokaryotic viruses

The production of dissolved organic matter during phytoplankton blooms and consumption by heterotrophic prokaryotes promote marine carbon biogeochemical cycling. Although prokaryotic viruses presumably affect this process, their dynamics during blooms are not fully understood. Here, we investigated the effects of taxonomic difference in bloom-forming phytoplankton on prokaryotes and their viruses. We analyzed the dynamics of coastal prokaryotic communities and viruses under the addition of dissolved intracellular fractions from taxonomically distinct phytoplankton, the diatom Chaetoceros sp. (CIF) and the raphidophycean alga Heterosigma akashiwo (HIF), using microcosm experiments. Ribosomal RNA gene amplicon and viral metagenomic analyses revealed that particular prokaryotes and prokaryotic viruses specifically increased in either CIF or HIF, indicating that taxonomic difference in bloom-forming phytoplankton promotes distinct dynamics of not only the prokaryotic community but also prokaryotic viruses. Furthermore, combining our microcosm experiments with publicly available environmental data mining, we identified both known and novel possible host-virus pairs. In particular, the growth of prokaryotes associating with phytoplanktonic organic matter, such as Bacteroidetes (Polaribacter and NS9 marine group), Vibrio spp., and Rhodobacteriales (Nereida and Planktomarina), was accompanied by an increase in viruses predicted to infect Bacteroidetes, Vibrio, and Rhodobacteriales, respectively. Collectively, our findings suggest that changes in bloom-forming species can be followed by an increase in a specific group of prokaryotes and their viruses and that elucidating these tripartite relationships among specific phytoplankton, prokaryotes, and prokaryotic viruses improves our understanding of coastal biogeochemical cycling in blooms.IMPORTANCEThe primary production during marine phytoplankton bloom and the consumption of the produced organic matter by heterotrophic prokaryotes significantly contribute to coastal biogeochemical cycles. While the activities of those heterotrophic prokaryotes are presumably affected by viral infection, the dynamics of their viruses during blooms are not fully understood. In this study, we experimentally demonstrated that intracellular fractions of taxonomically distinct bloom-forming phytoplankton species, the diatom Chaetoceros sp. and the raphidophycean alga Heterosigma akashiwo, promoted the growth of taxonomically different prokaryotes and prokaryotic viruses. Based on their dynamics and predicted hosts of those viruses, we succeeded in detecting already-known and novel possible host-virus pairs associating with either phytoplankton species. Altogether, we propose that the succession of bloom-forming phytoplankton would change the composition of the abundant prokaryotes, resulting in an increase in their viruses. These changes in viral composition, depending on bloom-forming species, would alter the dynamics and metabolism of prokaryotes, affecting biogeochemical cycling in blooms.

Gut microbial interactions based on network construction and bacterial pairwise cultivation

Association networks are widely applied for the prediction of bacterial interactions in studies of human gut microbiomes. However, the experimental validation of the predicted interactions is challenging due to the complexity of gut microbiomes and the limited number of cultivated bacteria. In this study, we addressed this challenge by integrating in vitro time series network (TSN) associations and co-cultivation of TSN taxon pairs. Fecal samples were collected and used for cultivation and enrichment of gut microbiome on YCFA agar plates for 13 days. Enriched cells were harvested for DNA extraction and metagenomic sequencing. A total of 198 metagenome-assembled genomes (MAGs) were recovered. Temporal dynamics of bacteria growing on the YCFA agar were used to infer microbial association networks. To experimentally validate the interactions of taxon pairs in networks, we selected 24 and 19 bacterial strains from this study and from the previously established human gut microbial biobank, respectively, for pairwise co-cultures. The co-culture experiments revealed that most of the interactions between taxa in networks were identified as neutralism (51.67%), followed by commensalism (21.67%), amensalism (18.33%), competition (5%) and exploitation (3.33%). Genome-centric analysis further revealed that the commensal gut bacteria (helpers and beneficiaries) might interact with each other via the exchanges of amino acids with high biosynthetic costs, short-chain fatty acids, and/or vitamins. We also validated 12 beneficiaries by adding 16 additives into the basic YCFA medium and found that the growth of 66.7% of these strains was significantly promoted. This approach provides new insights into the gut microbiome complexity and microbial interactions in association networks. Our work highlights that the positive relationships in gut microbial communities tend to be overestimated, and that amino acids, short-chain fatty acids, and vitamins are contributed to the positive relationships.

Re-oligotrophication and warming stabilize phytoplankton networks

Phytoplankton taxa are strongly interconnected as a network, which could show temporal dynamics and non-linear responses to changes in drivers at both seasonal and long-term scale. Using a high quality dataset of 20 Danish lakes (1989-2008), we applied extended Local Similarity Analysis to construct temporal network of phytoplankton communities for each lake, obtained sub-network for each sampling month, and then measured indices of network complexity and stability for each sub-network. We assessed how lake re-oligotrophication, climate warming and grazers influenced the temporal dynamics on network complexity and stability of phytoplankton community covering three aspects: seasonal trends, long-term trends and detrended variability. We found strong seasonality for the complexity and stability of phytoplankton network, an increasing trend for the average degree, modularity, nestedness, persistence and robustness, and a decreasing trend for connectance, negative:positive interactions and vulnerability. Our study revealed a cascading effect of lake re-oligotrophication, climate warming and zooplankton grazers on phytoplankton network stability through changes in network complexity characterizing diversity, interactions and topography. Network stability of phytoplankton increased with average degree, modularity, nestedness and decreased with connectance and negative:positive interactions. Oligotrophication and warming stabilized the phytoplankton network (enhanced robustness, persistence and decreased vulnerability) by enhancing its average degree, modularity, nestedness and by reducing its connectance, while zooplankton richness promoted stability of phytoplankton network through increases in average degree and decreases in negative interactions. Our results further indicate that the stabilization effects might lead to more closed, compartmentalized and nested interconnections especially in the deeper lakes, in the warmer seasons and during bloom periods. From a temporal dynamic network view, our findings highlight stabilization of the phytoplankton community as an adaptive response to lake re-oligotrophication, climate warming and grazers.

Virus-prokaryote infection pairs associated with prokaryotic production in a freshwater lake

Viruses infect and kill prokaryotic populations in a density- or frequency-dependent manner and affect carbon cycling. However, the effects of the stratification transition, including the stratified and de-stratified periods, on the changes in prokaryotic and viral communities and their interactions remain unclear. We conducted a monthly survey of the surface and deep layers of a large and deep freshwater lake (Lake Biwa, Japan) for a year and analyzed the prokaryotic production and prokaryotic and viral community composition. Our analysis revealed that, in the surface layer, 19 prokaryotic species, accounting for approximately 40% of the total prokaryotic abundance, could potentially contribute to the majority of prokaryotic production, which is the highest during the summer and is suppressed by viruses. This suggests that a small fraction of prokaryotes and phages were the key infection pairs during the peak period of prokaryotic activity in the freshwater lake. We also found that approximately 50% of the dominant prokaryotic and viral species in the deep layer were present throughout the study period. This suggests that the "kill the winner" model could explain the viral impact on prokaryotes in the surface layer, but other dynamics may be at play in the deep layer. Furthermore, we found that annual vertical mixing could result in a similar rate of community change between the surface and deep layers. These findings may be valuable in understanding how communities and the interaction among them change when freshwater lake stratification is affected by global warming in the future.IMPORTANCEViral infection associated with prokaryotic production occurs in a density- or frequency-dependent manner and regulates the prokaryotic community. Stratification transition and annual vertical mixing in freshwater lakes are known to affect the prokaryotic community and the interaction between prokaryotes and viruses. By pairing measurements of virome analysis and prokaryotic production of a 1-year survey of the depths of surface and deep layers, we revealed (i) the prokaryotic infection pairs associated with prokaryotic production and (ii) the reset in prokaryotic and viral communities through annual vertical mixing in a freshwater lake. Our results provide a basis for future work into changes in stratification that may impact the biogeochemical cycling in freshwater lakes.

Christensenella minuta interacts with multiple gut bacteria

Introduction

Gut microbes form complex networks that significantly influence host health and disease treatment. Interventions with the probiotic bacteria on the gut microbiota have been demonstrated to improve host well-being. As a representative of next-generation probiotics, Christensenella minuta (C. minuta) plays a critical role in regulating energy balance and metabolic homeostasis in human bodies, showing potential in treating metabolic disorders and reducing inflammation. However, interactions of C. minuta with the members of the networked gut microbiota have rarely been explored.

Methods

In this study, we investigated the impact of C. minuta on fecal microbiota via metagenomic sequencing, focusing on retrieving bacterial strains and coculture assays of C. minuta with associated microbial partners.

Results

Our results showed that C. minuta intervention significantly reduced the diversity of fecal microorganisms, but specifically enhanced some groups of bacteria, such as Lactobacillaceae. C. minuta selectively enriched bacterial pathways that compensated for its metabolic defects on vitamin B1, B12, serine, and glutamate synthesis. Meanwhile, C. minuta cross-feeds Faecalibacterium prausnitzii and other bacteria via the production of arginine, branched-chain amino acids, fumaric acids and short-chain fatty acids (SCFAs), such as acetic. Both metagenomic data analysis and culture experiments revealed that C. minuta negatively correlated with Klebsiella pneumoniae and 14 other bacterial taxa, while positively correlated with F. prausnitzii. Our results advance our comprehension of C. minuta's in modulating the gut microbial network.

Conclusions

C. minuta disrupts the composition of the fecal microbiota. This disturbance is manifested through cross-feeding, nutritional competition, and supplementation of its own metabolic deficiencies, resulting in the specific enrichment or inhibition of the growth of certain bacteria. This study will shed light on the application of C. minuta as a probiotic for effective interventions on gut microbiomes and improvement of host health.

Using solid phase adsorption toxin tracking and extended local similarity analysis to monitor lipophilic shellfish toxins in a mussel culture ranch in the Yangtze River Estuary

Harmful algal blooms (HABs) and their associated phycotoxins are increasing globally, posing great threats to local coastal ecosystems and human health. Nutrients have been carried by the freshwater Yangtze River and have entered the estuary, which was reported to be a biodiversity-rich but HAB-frequent region. Here, in situ solid phase adsorption toxin tracking (SPATT) was used to monitor lipophilic shellfish toxins (LSTs) in seawaters, and extended local similarity analysis (eLSA) was conducted to trace the temporal and special regions of those LSTs in a one-year trail in a mussel culture ranch in the Yangtze River Estuary. Nine analogs of LSTs, including okadaic acid (OA), dinophysistoxin-1 (DTX1), yessotoxin (YTX), homoyessotoxin (homoYTX), 45-OH-homoYTX, pectenotoxin-2 (PTX2), 7-epi-PTX2 seco acid (7-epi-PTX2sa), gymnodimine (GYM) and azaspiracids-3 (AZA3), were detected in seawater (SPATT) or rope farmed mussels. The concentrations of OA + DTX1 and homoYTX in mussels were positively correlated with those in SPATT samplers (Pearson test, p < 0.05), indicating that SPATT (with resin HP20) would be a good monitoring tool and potential indicator for OA + DTX1 and homoYTX in mussel Mytilus coruscus. The eLSA results indicated that late summer and early autumn were the most phycotoxin-contaminated seasons in the Yangtze River Estuary. OA + DTX1, homoYTX, PTX2 and GYM were most likely driven by the local growing HAB species in spring and summer, while Yangtze River diluted water may impact the accumulation of HAB species, causing potential phycotoxin contamination in the Yangtze River Estuary in autumn and winter. Together, the results showed that the mussel harvesting season, late summer and early autumn, would be the season with the greatest phycotoxin risk and would be the most contaminated by local growing toxic algae. Routine monitoring sites should be set up close to the local seawaters.

Ecological Interaction between Bacteriophages and Bacteria in Sub-Arctic Kongsfjorden Bay, Svalbard, Norway

Marine virus diversity and their relationships with their hosts in the marine environment remain unclear. This study investigated the co-occurrence of marine DNA bacteriophages (phages) and bacteria in the sub-Arctic area of Kongsfjorden Bay in Svalbard (Norway) in April and June 2018 using metagenomics tools. Of the marine viruses identified, 48-81% were bacteriophages of the families Myoviridae, Siphoviridae, and Podoviridae. Puniceispirillum phage HMO-2011 was dominant (7.61%) in April, and Puniceispirillum phage HMO-2011 (3.32%) and Pelagibacter phage HTVC008M (3.28%) were dominant in June. Gammaproteobacteria (58%), including Eionea flava (14.3%) and Pseudomonas sabulinigri (12.2%), were dominant in April, whereas Alphaproteobacteria (87%), including Sulfitobacter profundi (51.5%) and Loktanella acticola (32.4%), were dominant in June. The alpha diversity of the bacteriophages and bacterial communities exhibited opposite patterns. The diversity of the bacterial community was higher in April and lower in June. Changes in water temperature and light can influence the relationship between bacteria and bacteriophages.

Disturbance frequency directs microbial community succession in marine biofilms exposed to shear

IMPORTANCE

Disturbances are major drivers of community succession in many microbial systems; however, relatively little is known about marine biofilm community succession, especially under antifouling disturbance. Antifouling technologies exert strong local disturbances on marine biofilms, and resulting biomass losses can be accompanied by shifts in biofilm community composition and succession. We address this gap in knowledge by bridging microbial ecology with antifouling technology development. We show that disturbance by shear can strongly alter marine biofilm community succession, acting as a selective filter influenced by frequency of exposure. Examining marine biofilm succession patterns with and without shear revealed stable associations between key prokaryotic and eukaryotic taxa, highlighting the importance of cross-domain assessment in future marine biofilm research. Describing how compounded top-down and bottom-up disturbances shape the succession of marine biofilms is valuable for understanding the assembly and stability of these complex microbial communities and predicting species invasiveness.

Seasonal dynamics of a glycan-degrading flavobacterial genus in a tidally mixed coastal temperate habitat

Coastal marine habitats constitute hotspots of primary productivity. In temperate regions, this is due both to massive phytoplankton blooms and dense colonisation by macroalgae that mostly store carbon as glycans, contributing substantially to local and global carbon sequestration. Because they control carbon and energy fluxes, algae-degrading microorganisms are crucial for coastal ecosystem functions. Environmental surveys revealed consistent seasonal dynamics of alga-associated bacterial assemblages, yet resolving what factors regulate the in situ abundance, growth rate and ecological functions of individual taxa remains a challenge. Here, we specifically investigated the seasonal dynamics of abundance and activity for a well-known alga-degrading marine flavobacterial genus in a tidally mixed coastal habitat of the Western English Channel. We show that members of the genus Zobellia are a stable, low-abundance component of healthy macroalgal microbiota and can also colonise particles in the water column. This genus undergoes recurring seasonal variations with higher abundances in winter, significantly associated to biotic and abiotic variables. Zobellia can become a dominant part of bacterial communities on decaying macroalgae, showing a strong activity and high estimated in situ growth rates. These results provide insights into the seasonal dynamics and environmental constraints driving natural populations of alga-degrading bacteria that influence coastal carbon cycling.

Identifying local associations in biological time series: algorithms, statistical significance, and applications

Local associations refer to spatial-temporal correlations that emerge from the biological realm, such as time-dependent gene co-expression or seasonal interactions between microbes. One can reveal the intricate dynamics and inherent interactions of biological systems by examining the biological time series data for these associations. To accomplish this goal, local similarity analysis algorithms and statistical methods that facilitate the local alignment of time series and assess the significance of the resulting alignments have been developed. Although these algorithms were initially devised for gene expression analysis from microarrays, they have been adapted and accelerated for multi-omics next generation sequencing datasets, achieving high scientific impact. In this review, we present an overview of the historical developments and recent advances for local similarity analysis algorithms, their statistical properties, and real applications in analyzing biological time series data. The benchmark data and analysis scripts used in this review are freely available at http://github.com/labxscut/lsareview.

Contrasting response of microeukaryotic and bacterial communities to the interplay of seasonality and local stressors in shallow soda lakes

Seasonal environmental variation is a leading driver of microbial planktonic community assembly and interactions. However, departures from usual seasonal trends are often reported. To understand the role of local stressors in modifying seasonal succession, we sampled fortnightly, throughout three seasons, five nearby shallow soda lakes exposed to identical seasonal and meteorological changes. We characterised their microeukaryotic and bacterial communities by amplicon sequencing of the 16S and 18S rRNA gene, respectively. Biological interactions were inferred by analyses of synchronous and time-shifted interaction networks, and the keystone taxa of the communities were topologically identified. The lakes showed similar succession patterns during the study period with spring being characterised by the relevance of trophic interactions and a certain level of community stability followed by a more dynamic and variable summer-autumn period. Adaptation to general seasonal changes happened through shared core microbiome of the lakes. Stochastic events such as desiccation disrupted common network attributes and introduced shifts from the prevalent seasonal trajectory. Our results demonstrated that, despite being extreme and highly variable habitats, shallow soda lakes exhibit certain similarities in the seasonality of their planktonic communities, yet local stressors such as droughts instigate deviations from prevalent trends to a greater extent for microeukaryotic than for bacterial communities.

Long-term comparison of the performance of biostimulation and phytoextraction in soil contaminated with diesel and heavy metals

The long-term remediation performance under the natural conditions is required to establish the appropriate remediation strategy for contaminated soil. The objective of this study was to compare the long-term remediation efficiency of biostimulation and phytoextraction in contaminated soil containing petroleum hydrocarbons (PHs) and heavy metals. Two types of contaminated soil (soil contaminated with diesel only and co-contaminated with diesel and heavy metals) were prepared. For the biostimulation treatments, the soil was amended with compost, whereas maize, a representative phytoremediation plant, was cultivated for the phytoextraction treatments. There was no significant difference in remediation performance of biostimulation and phytoextraction in the diesel-contaminated soil, in which the maximum total petroleum hydrocarbon (TPH) removability was 94-96% (p < 0.05). However, phytoextraction exhibited the higher removability for TPH and heavy metals than biostimulation in the co-contaminated soil. There was no considerable change in the TPH removal in biostimulation (16-25%), while phytoextraction showed a 75% of TPH removal rate in the co-contaminated soil. Additionally, no significant changes were observed in heavy metals concentration of biostimulation, whereas the removability of heavy metals was 33-63% in phytoextraction. Meanwhile, maize, which is a suitable plant for phytoextraction, showed a translocation factor (translocating efficiency from roots to shoots) value of >1. Correlation analysis revealed that soil properties (pH, water content, and organic content) negatively correlated with pollutants removal. Additionally, the soil bacterial communities were changed over the investigated period, and the types of pollutants exerted a significant influence on the bacterial community dynamics. This study performed a pilot-scale comparison of two types of biological remediation technologies under natural environmental conditions and provided information on changes in the bacterial community structures. This study can be useful for establishing appropriate biological remediation methods to restore soil contaminated with PHs and heavy metals.

Symbiotic UCYN-A strains co-occurred with El Niño, relaxed upwelling, and varied eukaryotes over 10 years off Southern California

Biological nitrogen fixation, the conversion of N2 gas into a bioavailable form, is vital to sustaining marine primary production. Studies have shifted beyond traditionally studied tropical diazotrophs. Candidatus Atelocyanobacterium thalassa (or UCYN-A) has emerged as a focal point due to its streamlined metabolism, intimate partnership with a haptophyte host, and broad distribution. Here, we explore the environmental parameters that govern UCYN-A's presence at the San Pedro Ocean Time-series (SPOT), its host specificity, and statistically significant interactions with non-host eukaryotes from 2008-2018. 16S and 18S rRNA gene sequences were amplified by "universal primers" from monthly samples and resolved into Amplicon Sequence Variants, allowing us to observe multiple UCYN-A symbioses. UCYN-A1 relative abundances increased following the 2015-2016 El Niño event. This "open ocean ecotype" was present when coastal upwelling declined, and Ekman transport brought tropical waters into the region. Network analyses reveal all strains of UCYN-A co-occur with dinoflagellates including Lepidodinium, a potential predator, and parasitic Syndiniales. UCYN-A2 appeared to pair with multiple hosts and was not tightly coupled to its predominant host, while UCYN-A1 maintained a strong host-symbiont relationship. These biological relationships are particularly important to study in the context of climate change, which will alter UCYN-A distribution at regional and global scales.

The underappreciated role of biotic factors in controlling the bloom ecology of potentially harmful microalgae in the Hudson-Raritan Bay

Despite widespread distribution of harmful algal blooms (HABs) and new and improved methods for detecting and quantifying them, no unifying ecological explanation has been found. Improved understanding depends upon local, ecological studies that include analysis of phytoplankton species data in relation to both abiotic and biotic parameters. Ecological network analysis was used to detect co-occurrence patterns among abiotic and biotic parameters in a long-term monitoring dataset (i.e., 2010-2021) from the eutrophic Hudson-Raritan Estuary (HRE) between the states of New York and New Jersey. The regular co-occurrence of potentially harmful bloom-forming species with companion species observed through microscopy was supported by the results of ecological network analysis, which showed that there were far more associations between HAB species and biotic parameters (∼95%) than abiotic parameters (∼5%). Temperature was the environmental variable that was most associated with HAB species throughout the estuary. The numerous network associations of HAB species with one another and with diatoms, dinoflagellates, and zooplankton highlight the complexity of planktonic food webs and interactions. Results also suggest that some taxa may play a central role in structuring the HRE plankton communities. These findings demonstrate that biotic associations play an underappreciated role in plankton structure and the value of examining the ecology of HAB species within the breadth of their biological communities. While network analysis does not fully explain and confirm complex associations among species, it does provide fresh insights and testable hypotheses to strengthen understanding and improve prediction.

Disentangling temporal associations in marine microbial networks

BACKGROUND

Microbial interactions are fundamental for Earth's ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. Omics-based censuses are helpful in predicting microbial interactions through the statistical inference of single (static) association networks. Yet, microbial interactions are dynamic and we have limited knowledge of how they change over time. Here, we investigate the dynamics of microbial associations in a 10-year marine time series in the Mediterranean Sea using an approach inferring a time-resolved (temporal) network from a single static network.

RESULTS

A single static network including microbial eukaryotes and bacteria was built using metabarcoding data derived from 120 monthly samples. For the decade, we aimed to identify persistent, seasonal, and temporary microbial associations by determining a temporal network that captures the interactome of each individual sample. We found that the temporal network appears to follow an annual cycle, collapsing, and reassembling when transiting between colder and warmer waters. We observed higher association repeatability in colder than in warmer months. Only 16 associations could be validated using observations reported in literature, underlining our knowledge gap in marine microbial ecological interactions.

CONCLUSIONS

Our results indicate that marine microbial associations follow recurrent temporal dynamics in temperate zones, which need to be accounted for to better understand the functioning of the ocean microbiome. The constructed marine temporal network may serve as a resource for testing season-specific microbial interaction hypotheses. The applied approach can be transferred to microbiome studies in other ecosystems. Video Abstract.

Prevalence of Viral Frequency-Dependent Infection in Coastal Marine Prokaryotes Revealed Using Monthly Time Series Virome Analysis

Viruses infecting marine prokaryotes have a large impact on the diversity and dynamics of their hosts. Model systems suggest that viral infection is frequency dependent and constrained by the virus-host encounter rate. However, it is unclear whether frequency-dependent infection is pervasive among the abundant prokaryotic populations with different temporal dynamics. To address this question, we performed a comparison of prokaryotic and viral communities using 16S rRNA amplicon and virome sequencing based on samples collected monthly for 2 years at a Japanese coastal site, Osaka Bay. Concurrent seasonal shifts observed in prokaryotic and viral community dynamics indicated that the abundance of viruses correlated with that of their predicted host phyla (or classes). Cooccurrence network analysis between abundant prokaryotes and viruses revealed 6,423 cooccurring pairs, suggesting a tight coupling of host and viral abundances and their "one-to-many" correspondence. Although stable dominant species, such as SAR11, showed few cooccurring viruses, a fast succession of their viruses suggests that viruses infecting these populations changed continuously. Our results suggest that frequency-dependent viral infection prevails in coastal marine prokaryotes regardless of host taxa and temporal dynamics. IMPORTANCE There is little room for doubt that viral infection is prevalent among abundant marine prokaryotes regardless of their taxa or growth strategy. However, comprehensive evaluations of viral infections in natural prokaryotic communities are still technically difficult. In this study, we examined viral infection in abundant prokaryotes by monitoring the monthly dynamics of prokaryotic and viral communities at a eutrophic coastal site, Osaka Bay. We compared the community dynamics of viruses with those of their putative hosts based on genome-based in silico host prediction. We observed frequent cooccurrence among the predicted virus-host pairs, suggesting that viral infection is prevalent in abundant prokaryotes regardless of their taxa or temporal dynamics. This likely indicates that frequent lysis of the abundant prokaryotes via viral infection has a considerable contribution to the biogeochemical cycling and maintenance of prokaryotic community diversity.

Covariance of Marine Nucleocytoplasmic Large DNA Viruses with Eukaryotic Plankton Communities in the Sub-Arctic Kongsfjorden Ecosystem: A Metagenomic Analysis of Marine Microbial Ecosystems

Nucleocytoplasmic large DNA viruses (NCLDVs) infect various marine eukaryotes. However, little is known about NCLDV diversity and their relationships with eukaryotic hosts in marine environments, the elucidation of which will advance the current understanding of marine ecosystems. This study characterizes the interplay between NCLDVs and the eukaryotic plankton community (EPC) in the sub-Arctic area using metagenomics and metabarcoding to investigate NCLDVs and EPC, respectively, in the Kongsfjorden ecosystem of Svalbard (Norway) in April and June 2018. Gyrodinium helveticum (Dinophyceae) is the most prevalent eukaryotic taxon in the EPC in April, during which time Mimiviridae (31.8%), Poxviridae (25.1%), Phycodnaviridae (14.7%) and Pandoraviridae (13.1%) predominate. However, in June, the predominant taxon is Aureococcus anophagefferens (Pelagophyceae), and the NCLDVs, Poxviridae (32.9%), Mimiviridae (29.1%), and Phycodnaviridae (18.5%) appear in higher proportions with an increase in Pelagophyceae, Bacillariophyceae, and Chlorophyta groups. Thus, differences in NCLDVs may be caused by changes in EPC composition in response to environmental changes, such as increases in water temperature and light intensity. Taken together, these findings are particularly relevant considering the anticipated impact of NCLDV-induced EPC control mechanisms on polar regions and, therefore, improve the understanding of the Sub-Arctic Kongsfjorden ecosystem.

Ecosystem size-induced environmental fluctuations affect the temporal dynamics of community assembly mechanisms

Understanding processes that determine community membership and abundance is important for many fields from theoretical community ecology to conservation. However, spatial community studies are often conducted only at a single timepoint despite the known influence of temporal variability on community assembly processes. Here we used a spatiotemporal study to determine how environmental fluctuation differences induced by mesocosm volumes (larger volumes were more stable) influence assembly processes of aquatic bacterial metacommunities along a press disturbance gradient. By combining path analysis and network approaches, we found mesocosm size categories had distinct relative influences of assembly process and environmental factors that determined spatiotemporal bacterial community composition, including dispersal and species sorting by conductivity. These processes depended on, but were not affected proportionately by, mesocosm size. Low fluctuation, large mesocosms primarily developed through the interplay of species sorting that became more important over time and transient priority effects as evidenced by more time-delayed associations. High fluctuation, small mesocosms had regular disruptions to species sorting and greater importance of ecological drift and dispersal limitation indicated by lower richness and higher taxa replacement. Together, these results emphasize that environmental fluctuations influence ecosystems over time and its impacts are modified by biotic properties intrinsic to ecosystem size.

Daily dynamics of contrasting spring algal blooms in Santa Monica Bay (central Southern California Bight)

Protistan algae (phytoplankton) dominate coastal upwelling ecosystems where they form massive blooms that support the world's most important fisheries and constitute an important sink for atmospheric CO₂ . Bloom initiation is well understood, but the biotic and abiotic forces that shape short-term dynamics in community composition are still poorly characterized. Here, high-frequency (daily) changes in relative abundance dynamics of the metabolically active protistan community were followed via expressed 18S V4 rRNA genes (RNA) throughout two algal blooms during the spring of 2018 and 2019 in Santa Monica Bay (central Southern California Bight). A diatom bloom formed after wind-driven, nutrient upwelling events in both years, but different taxa dominated each year. Whereas diatoms bloomed following elevated nutrients and declined after depletion each year, a massive dinoflagellate bloom manifested under relatively low inorganic nitrogen conditions following diatom bloom senescence in 2019 but not 2018. Network analysis revealed associations between diatoms and cercozoan putative parasitic taxa and syndinean parasites during 2019 that may have influenced the demise of the diatoms, and the transition to a dinoflagellate-dominated bloom.

Selection pressure on the rhizosphere microbiome can alter nitrogen use efficiency and seed yield in Brassica rapa

Microbial experimental systems provide a platform to observe how networks of groups emerge to impact plant development. We applied selection pressure for microbiome enhancement of Brassica rapa biomass to examine adaptive bacterial group dynamics under soil nitrogen limitation. In the 9th and final generation of the experiment, selection pressure enhanced B. rapa seed yield and nitrogen use efficiency compared to our control treatment, with no effect between the random selection and control treatments. Aboveground biomass increased for both the high biomass selection and random selection plants. Soil bacterial diversity declined under high B. rapa biomass selection, suggesting a possible ecological filtering mechanism to remove bacterial taxa. Distinct sub-groups of interactions emerged among bacterial phyla such as Proteobacteria and Bacteroidetes in response to selection. Extended Local Similarity Analysis and NetShift indicated greater connectivity of the bacterial community, with more edges, shorter path lengths, and altered modularity through the course of selection for enhanced plant biomass. In contrast, bacterial communities under random selection and no selection showed less complex interaction profiles of bacterial taxa. These results suggest that group-level bacterial interactions could be modified to collectively shift microbiome functions impacting the growth of the host plant under soil nitrogen limitation.

Cronos: A Machine Learning Pipeline for Description and Predictive Modeling of Microbial Communities Over Time

Microbial time-series analysis, typically, examines the abundances of individual taxa over time and attempts to assign etiology to observed patterns. This approach assumes homogeneous groups in terms of profiles and response to external effectors. These assumptions are not always fulfilled, especially in complex natural systems, like the microbiome of the human gut. It is actually established that humans with otherwise the same demographic or dietary backgrounds can have distinct microbial profiles. We suggest an alternative approach to the analysis of microbial time-series, based on the following premises: 1) microbial communities are organized in distinct clusters of similar composition at any time point, 2) these intrinsic subsets of communities could have different responses to the same external effects, and 3) the fate of the communities is largely deterministic given the same external conditions. Therefore, tracking the transition of communities, rather than individual taxa, across these states, can enhance our understanding of the ecological processes and allow the prediction of future states, by incorporating applied effects. We implement these ideas into Cronos, an analytical pipeline written in R. Cronos’ inputs are a microbial composition table (e.g., OTU table), their phylogenetic relations as a tree, and the associated metadata. Cronos detects the intrinsic microbial profile clusters on all time points, describes them in terms of composition, and records the transitions between them. Cluster assignments, combined with the provided metadata, are used to model the transitions and predict samples’ fate under various effects. We applied Cronos to available data from growing infants’ gut microbiomes, and we observe two distinct trajectories corresponding to breastfed and formula-fed infants that eventually converge to profiles resembling those of mature individuals. Cronos is freely available at https://github.com/Lagkouvardos/Cronos.

Time-lagged interspecies interactions prevail during biofilm development in moving bed biofilm reactor

Clarifying the essential succession dynamics of interspecies interactions during biofilm development is crucial for the regulation and application of biofilm-based processes. In this study, regular and time-series phylogenetic molecular ecological networks (pMENs) were constructed to investigate ordinary and time-lagged interspecies interactions during biofilm development in a moving bed biofilm reactor (MBBR). Positive interactions dominated both regular (89.78%) and time-series (77.04%) ecological networks, suggesting that extensive cooperative behaviors facilitated biofilm development. The pronounced directional interactions (72.52%) in the time-series network further indicated that time-lagged interspecies interactions prevailed in the biofilm development process. Specifically, the proportion of directional negative interactions was higher than that of positive interactions, implying that interspecific competition preferred to be time-lagged. The time-series network revealed that module hubs exhibited extensive time-lagged positive interactions with their neighbors, and most of them exhibited altruistic behaviors. Keystone species possessing more positive interactions were positively correlated with biofilm biomass, NO₃ ^- -N concentrations, and the removal efficiencies of NH₄ ⁺ -N and COD. However, keystone species and peripherals that were negatively targeted by their neighbors showed positive correlations with the concentrations of NO₂ ^- -N, polysaccharides, and proteins in the soluble microbial products. The data highlight that the time-series network can provide directional microbial interactions along with the biofilm development process, which would help to predict the tendency of community shifts and propose efficient strategies for the regulation of biofilm-based processes. This article is protected by copyright. All rights reserved.

Abundance and diversity of antibiotic resistance genes and bacterial communities in the western Pacific and Southern Oceans

This study investigated the abundance and diversity of antibiotic resistance genes (ARGs) and the composition of bacterial communities along a transect covering the western Pacific Ocean (36°N) to the Southern Ocean (74°S) using the Korean icebreaker R/V Araon (total cruise distance: 14,942 km). The relative abundances of ARGs and bacteria were assessed with quantitative PCR and next generation sequencing, respectively. The absolute abundance of ARGs was 3.0 × 10⁶ ± 1.6 × 10⁶ copies/mL in the western Pacific Ocean, with the highest value (7.8 × 10⁶ copies/mL) recorded at a station in the Tasman Sea (37°S). The absolute abundance of ARGs in the Southern Ocean was 1.8-fold lower than that in the western Pacific Ocean, and slightly increased (0.7-fold) toward Terra Nova Bay in Antarctica, possibly resulting from natural terrestrial sources or human activity. β-Lactam and tetracycline resistance genes were dominant in all samples (88-99%), indicating that they are likely the key ARGs in the ocean. Correlation and network analysis showed that Bdellovibrionota, Bacteroidetes, Cyanobacteria, Margulisbacteria, and Proteobacteria were positively correlated with ARGs, suggesting that these bacteria are the most likely ARG carriers. This study highlights the latitudinal profile of ARG distribution in the open ocean system and provides insights that will help in monitoring emerging pollutants on a global scale.

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.

Seasonal Dynamics of Bacterial Community Structure in Diesel Oil-Contaminated Soil Cultivated with Tall Fescue (Festuca arundinacea)

The objective of this study was to explore the seasonal characteristics of rhizoremediation and the bacterial community structure over the course of a year in soil contaminated with diesel oil. The soil was contaminated with diesel oil at a total petroleum hydrocarbon (TPH) concentration of 30,000 mg-TPH·kg-soil⁻¹. Tall fescue seedlings were planted in the contaminated soil and rhizoremediation performance was monitored for 317 days. The TPH concentration gradually declined, reaching 75.6% after day 61. However, the TPH removability decreased by up to 30% after re-contamination in the fall and winter. The bacterial community structure exhibited distinct seasonal dynamics. Genus Pseudomonas significantly increased up to 55.7% in the winter, while the genera Immundisolibacter and Lysobacter, well-known petroleum hydrocarbon (PH)-degrading bacteria, were found to be positively linked to the TPH removal rate. Consequently, knowledge of this seasonal variation in rhizoremediation performance and the bacterial community structure is useful for the improvement of rhizoremediation in PH-contaminated environments.

Fecal DNA Virome Is Associated with the Development of Colorectal Neoplasia in a Murine Model of Colorectal Cancer

Alteration of the gut virome has been associated with colorectal cancer (CRC); however, when and how the alteration takes place has not been studied. Here, we employ a longitudinal study in mice to characterize the gut virome alteration in azoxymethane (AOM)-induced colorectal neoplasia and identify important viruses associated with tumor growth. The number and size of the tumors increased as the mice aged in the AOM treated group, as compared to the control group. Tumors were first observed in the AOM group at week 12. We observed a significantly lower alpha diversity and shift in viral profile when tumors first appeared. In addition, we identified novel viruses from the genera Brunovirus, Hpunavirus that are positively associated with tumor growth and enriched at a late time point in AOM group, whereas members from Lubbockvirus show a negative correlation with tumor growth. Moreover, network analysis revealed two clusters of viruses in the AOM virome, a group that is positively correlated with tumor growth and another that is negatively correlated with tumor growth, all of which are bacteriophages. Our findings suggest that the gut virome changes along with tumor formation and provides strong evidence of a potential role for bacteriophage in the development of colorectal neoplasia.

Network-based approaches for the investigation of microbial community structure and function using metagenomics-based data

Network-based approaches offer a powerful framework to evaluate microbial community organization and function as it relates to a variety of environmental processes. Emerging studies are exploring network theory as a method for data integration that is likely to be critical for the integration of 'omics' data using systems biology approaches. Intricacies of network theory and methodological and computational complexities in network construction, however, impede the use of these tools for translational science. We provide a perspective on the methods of network construction, interpretation and emerging uses for these techniques in understanding host-microbiota interactions.

NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data

Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. In addition, the GAM transformation increased the predictive power (F1 score) of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results.

Impacts of UV-C irradiation on marine biofilm community succession

Marine biofilms are diverse microbial communities and important ecological habitats forming on surfaces submerged in the ocean. Biofilm communities resist environmental disturbance, making them a nuisance to some human activities ('biofouling'). Anti-fouling solutions rarely address the underlying stability or compositional responses of these biofilms. Using bulk measurements and molecular analyses, we examined temporal and UV-C antifouling-based shifts in marine biofilms in the coastal Western North Atlantic Ocean during early fall. Over a 24-d period, bacterial communities shifted from early dominance of Gammaproteobacteria to increased proportions of Alphaproteobacteria, Bacteroidia and Acidimicrobiia. In a network analysis based on temporal covariance, Rhodobacteraceae (Alphaproteobacteria) nodes were abundant and densely connected with generally positive correlations. In the eukaryotic community, persistent algal, protistan, and invertebrate groups were observed, although consistent temporal succession was not detected. Biofilm UV-C treatment at 13 and 20 days resulted in losses of chlorophyll a and transparent exopolymer particles, indicating biomass disruption. Bacterial community shifts suggested that UV-C treatment decreased biofilm maturation rate and was associated with proportional shifts among diverse bacterial taxa. UV-C treatment was also associated with increased proportions of protists potentially involved in detritivory and parasitism. Older biofilm communities had increased resistance to UV-C, suggesting that early biofilms are more susceptible to UV-C based antifouling. The results suggest that UV-C irradiation is potentially an effective antifouling method in marine environments in terms of biomass removal and in slowing maturation. However, as they mature, biofilm communities may accumulate microbial members that are tolerant or resilient under UV-treatment. Importance Marine biofilms regulate processes from organic matter and pollutant turnover to eukaryotic settlement and growth. Biofilm growth and eukaryotic settlement interfering with human activities via growth on ship hulls, aquaculture operations, or other marine infrastructure are called 'biofouling'. There is a need to develop sustainable anti-fouling techniques by minimizing impacts to surrounding biota. We use the biofouling-antifouling framework to test hypotheses about marine biofilm succession and stability in response to disturbance, using a novel UV-C LED device. We demonstrate strong bacterial biofilm successional patterns and detect taxa potentially contributing to stability under UV-C stress. Despite UV-C-associated biomass losses and varying UV susceptibility of microbial taxa, we detected high compositional resistance among biofilm bacterial communities, suggesting decoupling of disruption in biomass and community composition following UV-C irradiation. We also report microbial covariance patterns over 24 days of biofilm growth, pointing to areas for study of microbial interactions and targeted antifouling.

Disentangling environmental effects in microbial association networks

BACKGROUND

Ecological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not.

RESULTS

We present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges-87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors.

CONCLUSIONS

To reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses. Video abstract.

Dynamics of marine bacterial biofouling communities after initial Alteromonas genovensis biofilm attachment to anti-fouling paint substrates

To determine how bacterial communities succeed after the initial attachment of the bacterial biofilm adhesion using 16S rDNA meta-barcoding in plates coated with copper-based anti-fouling (AF) and non-AF (control) coatings as well as ambient seawater, coated plates were submerged in a marine environment in situ. Alteromonas genovensis (Gammaproteobacteria) in AF coating and Pacificibacter sp. (Alphaproteobacteria) in the control plate were initially abundant. In the AF coating, the abundance of A. genovensis decreased rapidly, whereas that of genus Phaeobacter (Alphaproteobacteria), Serratia (Gammaproteobacteria) and Cupriavidus (Betaproteobacteria) increased. Bacterial community in the control plate had a strong connection to pathogenic Vibrio spp. associated with the growth of invertebrates. Therefore, in the in situ AF coating experiment, A. genovensis accumulation was initially and intensively increased, and the bacteria responded to chemical antagonism, induced the proliferation of specific biofilm bacteria and influenced the interactions and recruitment of additional bacterial communities.

Successional dynamics and alternative stable states in a saline activated sludge microbial community over 9 years

BACKGROUND

Microbial communities in both natural and applied settings reliably carry out myriads of functions, yet how stable these taxonomically diverse assemblages can be and what causes them to transition between states remains poorly understood. We studied monthly activated sludge (AS) samples collected over 9 years from a full-scale wastewater treatment plant to answer how complex AS communities evolve in the long term and how the community functions change when there is a disturbance in operational parameters.

RESULTS

Here, we show that a microbial community in activated sludge (AS) system fluctuated around a stable average for 3 years but was then abruptly pushed into an alternative stable state by a simple transient disturbance (bleaching). While the taxonomic composition rapidly turned into a new state following the disturbance, the metabolic profile of the community and system performance remained remarkably stable. A total of 920 metagenome-assembled genomes (MAGs), representing approximately 70% of the community in the studied AS ecosystem, were recovered from the 97 monthly AS metagenomes. Comparative genomic analysis revealed an increased ability to aggregate in the cohorts of MAGs with correlated dynamics that are dominant after the bleaching event. Fine-scale analysis of dynamics also revealed cohorts that dominated during different periods and showed successional dynamics on seasonal and longer time scales due to temperature fluctuation and gradual changes in mean residence time in the reactor, respectively.

CONCLUSIONS

Our work highlights that communities can assume different stable states under highly similar environmental conditions and that a specific disturbance threshold may lead to a rapid shift in community composition. Video Abstract.

Dynamics of bacterial functional genes and community structures during rhizoremediation of diesel-contaminated compost-amended soil

The objective of this study was to characterize the effects of organic soil amendment (compost) on bacterial populations associated with petroleum hydrocarbon (PH) degradation and nitrous oxide (N₂O) dynamics via pot experiments. Soil was artificially contaminated with diesel oil at total petroleum hydrocarbon (TPH) concentration of 30,000 mg·kg-soil^-1 and compost was mixed with the contaminated soil at a 1:9 ratio (w/w). Maize seedlings were planted in each pot and a total of ten pots with two treatments (compost-amended and unamended) were prepared. The pot experiment was conducted for 85 days. The compost-amended soil had a significantly higher TPH removal efficiency (51.1%) than unamended soil (21.4%). Additionally, the relative abundance of the alkB gene, which is associated with PH degradation, was higher in the compost-amended soil than in the unamended soil. Similarly, cnorB and nosZ (which are associated with nitric oxide (NO) and N₂O reduction, respectively) were also highly upregulated in the compost-amended soil. Moreover, the compost-amended soil exhibited higher richness and evenness indices, indicating that bacterial diversity was higher in the amended soil than in the unamended soil. Therefore, our findings may contribute to the development of strategies to enhance remediation efficiency and greenhouse gas mitigation during the rhizoremediation of diesel-contaminated soils.

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.

Recovery trajectories and community resilience of biofilms in receiving rivers after wastewater treatment plant upgrade

Wastewater treatment plant (WWTP) upgrades can reduce both nutrient and micropollutant emissions into receiving rivers, thus modifying the composition and function of biological communities. However, how microbial communities vary and whether they can be restored to levels found in less-polluted rivers remains uncertain. Aquatic biofilms are sensitive to environmental change and respond rapidly to bottom-up pressure. Thus, we used 12 flumes configured in three experimental treatments to mimic the dynamic processes of biofilm microbial communities occurring in a wastewater-receiving river following WWTP upgrade, with rivers containing two levels of nutrients and micropollutants used as references. We compared the biofilm microbial biomass, carbon source utilization, and community composition among the three "blocks". Results showed that the metabolic patterns of the carbon sources and composition of the biofilm bacterial communities in the flumes mimicking a receiving river with WWTP upgrade recovered over time to those mimicking a less-disturbed river. The restoration of potential carboxylic acid-consuming denitrifying bacteria (i.e., Zoogloea, Comamonas, Dechloromonas, and Acinetobacter) likely played a significant role in this process. Combining quantitative analysis of the denitrification genes nirS and nosZ, we confirmed that the denitrification function of the river biofilms recovered after WWTP upgrade, consistent with our previous field investigation.

Network analysis methods for studying microbial communities: A mini review

Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities in complex and contiguous environments. They engage in numerous inter- and intra- kingdom interactions which can be inferred from microbiome profiling data. In particular, network-based approaches have proven helpful in deciphering complex microbial interaction patterns. Here we give an overview of state-of-the-art methods to infer intra-kingdom interactions ranging from simple correlation- to complex conditional dependence-based methods. We highlight common biases encountered in microbial profiles and discuss mitigation strategies employed by different tools and their trade-off with increased computational complexity. Finally, we discuss current limitations that motivate further method development to infer inter-kingdom interactions and to robustly and comprehensively characterize microbial environments in the future.

Dynamic bacterial community response to Akashiwo sanguinea (Dinophyceae) bloom in indoor marine microcosms

We investigated the dynamics of the bacterial composition and metabolic function within Akashiwo sanguinea bloom using a 100-L indoor microcosm and metagenomic next-generation sequencing. We found that the bacterial community was classified into three groups at 54% similarity. Group I was associated with "during the A. sanguinea bloom stage" and mainly consisted of Alphaproteobacteria, Flavobacteriia and Gammaproteobacteria. Meanwhile, groups II and III were associated with the "late bloom/decline stage to post-bloom stage" with decreased Flavobacteriia and Gammaproteobacteria in these stages. Upon the termination of the A. sanguinea bloom, the concentrations of inorganic nutrients (particularly PO43-, NH4+ and dissolved organic carbon) increased rapidly and then decreased. From the network analysis, we found that the A. sanguinea node is associated with certain bacteria. After the bloom, the specific increases in NH4+ and PO43- nodes are associated with other bacterial taxa. The changes in the functional groups of the bacterial community from chemoheterotrophy to nitrogen association metabolisms were consistent with the environmental impacts during and after A. sanguinea bloom. Consequently, certain bacterial communities and the environments dynamically changed during and after harmful algal blooms and a rapid turnover within the bacterial community and their function can respond to ecological interactions.

Evaluation of rhizoremediation and methane emission in diesel-contaminated soil cultivated with tall fescue (Festuca arundinacea)

Rhizoremediation, CH₄ emission, and bacterial community dynamics were evaluated in diesel-contaminated soil cultivated with tall fescue via a pot experiment. At the beginning of the experiment, total petroleum hydrocarbons (TPHs) removal efficiency was 30.2% in tall fescue-cultivated soil, which was significantly higher than that of unplanted soil (19.4%). However, when compost was added as a soil amendment, TPHs removal efficiency increased to 39.2% in tall fescue-cultivated soil. Interestingly, potential CH₄ emissions were more affected by the initial diesel concentration than by compost addition or tall fescue planting. Specifically, the potential CH₄ emission was approximately 3.8 times higher in the treatment with the highest initial diesel concentration (T-WC38) than that of the treatment with the lowest initial diesel concentration (T-WC5). Functional gene analysis revealed that TPHs removal had a linear correlation with the alkB/16S gene ratio, whereas potential CH₄ emission had a linear correlation with pmoA gene copy numbers. Initial diesel concentrations in soil also affected bacterial community structures and the genera Rhizobium, Halothiobacillus, and Geobacter were found to be positively linked to diesel-contaminated soil rhizoremediation. Therefore, this study provides useful insights into the development of strategies to enhance rhizoremediation efficiency and CH₄ emission mitigation in diesel-contaminated soils.

Accumulation of detached kelp biomass in a subtidal temperate coastal ecosystem induces succession of epiphytic and sediment bacterial communities

Kelps are dominant primary producers in temperate coastal ecosystems. Large amounts of kelp biomass can be exported to the seafloor during the algal growth cycle or following storms, creating new ecological niches for the associated microbiota. Here, we investigated the bacterial community associated with the kelp Laminaria hyperborea during its accumulation and degradation on the seafloor. Kelp tissue, seawater and sediment were sampled during a 6-month in situ experiment simulating kelp detritus accumulation. Evaluation of the epiphytic bacterial community abundance, structure, taxonomic composition and predicted functional profiles evidenced a biphasic succession. Initially, dominant genera (Hellea, Litorimonas, Granulosicoccus) showed a rapid and drastic decrease in sequence abundance, probably outcompeted by algal polysaccharide-degraders such as Bacteroidia members which responded within 4 weeks. Acidimicrobiia, especially members of the Sva0996 marine group, colonized the degrading kelp biomass after 11 weeks. These secondary colonizers could act as opportunistic scavenger bacteria assimilating substrates exposed by early degraders. In parallel, kelp accumulation modified bacterial communities in the underlying sediment, notably favouring anaerobic taxa potentially involved in the sulfur and nitrogen cycles. Overall, this study provides insights into the bacterial degradation of algal biomass in situ, an important link in coastal trophic chains.

Depth Profile of Nitrifying Archaeal and Bacterial Communities in the Remote Oligotrophic Waters of the North Pacific

Nitrification is a vital ecosystem function in the open ocean that regenerates inorganic nitrogen and promotes primary production. Recent studies have shown that the ecology and physiology of nitrifying organisms is more complex than previously postulated. The distribution of these organisms in the remote oligotrophic ocean and their interactions with the physicochemical environment are relatively understudied. In this work, we aimed to evaluate the depth profile of nitrifying archaea and bacteria in the Eastern North Pacific Subtropical Front, an area with limited biological surveys but with intense trophic transferences and physicochemical gradients. Furthermore, we investigated the dominant physicochemical and biological relationships within and between ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB) as well as with the overall prokaryotic community. We used a 16S rRNA gene sequencing approach to identify and characterize the nitrifying groups within the first 500 m of the water column and to analyze their abiotic and biotic interactions. The water column was characterized mainly by two contrasting environments, warm O₂-rich surface waters with low dissolved inorganic nitrogen (DIN) and a cold O₂-deficient mesopelagic layer with high concentrations of nitrate (NO₃^–). Thaumarcheotal AOA and bacterial NOB were highly abundant below the deep chlorophyll maximum (DCM) and in the mesopelagic. In the mesopelagic, AOA and NOB represented up to 25 and 3% of the total prokaryotic community, respectively. Interestingly, the AOA community in the mesopelagic was dominated by unclassified genera that may constitute a novel group of AOA highly adapted to the conditions observed at those depths. Several of these unclassified amplicon sequence variants (ASVs) were positively correlated with NO₃^– concentrations and negatively correlated with temperature and O₂, whereas known thaumarcheotal genera exhibited the opposite behavior. Additionally, we found a large network of positive interactions within and between putative nitrifying ASVs and other prokaryotic groups, including 13230 significant correlations and 23 sub-communities of AOA, AOB, NOB, irrespective of their taxonomic classification. This study provides new insights into our understanding of the roles that AOA may play in recycling inorganic nitrogen in the oligotrophic ocean, with potential consequences to primary production in these remote ecosystems.

Seasonal Prevalence of Ammonia-Oxidizing Archaea in a Full-Scale Municipal Wastewater Treatment Plant Treating Saline Wastewater Revealed by a 6-Year Time-Series Analysis

Although several molecular-based studies have demonstrated the involvement of ammonia-oxidizing archaea (AOA) in ammonia oxidation in wastewater treatment plants (WWTPs), factors affecting the persistence and growth of AOA in these engineered systems have not been resolved. Here, we show a seasonal prevalence of AOA in a full-scale WWTP (Shatin, Hong Kong SAR) over a 6-year period of observation, even outnumbering ammonia-oxidizing bacteria in the seasonal peaks in 3 years, which may be due to the high bioavailable copper concentrations. Comparative analysis of three metagenome-assembled genomes of group I.1a AOA obtained from the activated sludge and 16S rRNA gene sequences recovered from marine sediments suggested that the seawater used for toilet flushing was the primary source of the WWTP AOA. A rare AOA population in the estuarine source water became transiently abundant in the WWTP with a metagenome-based relative abundance of up to 1.3% over three seasons of observation. Correlation-based network analysis revealed a robust co-occurrence relationship between these AOA and organisms potentially active in nitrite oxidation. Moreover, a strong correlation between the dominant AOA and an abundant proteobacterial organism suggested that capacity for extracellular polymeric substance production by the proteobacterium could provide a niche for AOA within bioaggregates. Together, the study highlights the importance of long-term observation in identifying biotic and abiotic factors governing population dynamics in open systems such as full-scale WWTPs.

Sludge digestibility and functionally active microorganisms in methanogenic sludge digesters revealed by E. coli-fed digestion and microbial source tracking

Methanogenic sludge digestion plays a pivotal role in attenuating and hygienizing the massively-produced waste activated sludge (WAS), which is predominantly composed of microbial cells and extracellular polymeric substances (EPS). The efficient sludge digestion requires a variety of functionally active microorganisms working together closely to convert sludge organic matter into biogas. Nonetheless, the digestion efficiency (or digestibility quantified as carbon removal efficiency) of major sludge constituents (i.e., microbial cells and EPS) and associated functionally active microorganisms in sludge digesters remain elusive. In this study, we identified the digestibility of sludge microbial cells and the associated functionally active microorganisms by using Escherichia coli (E. coli)-fed digestion and microbial source tracking. The average carbon removals in four digesters fed with fresh WAS (WAS-AD), thermal pretreated WAS (Thermal-WAS-AD), E. coli cells (E.coli-AD) and thermal pretreated E. coli cells (Thermal-E.coli-AD) were 30.6 ± 3.4%, 45.8 ± 2.9%, 69.0 ± 3.4% and 68.9 ± 4.6%, respectively. Compared to WAS-AD and Thermal-WAS-AD, the significantly higher carbon removals in E. coli-AD and Thermal-E. coli-AD suggested the remarkably higher digestibility of microbial cells than EPS, and releasing organic matter from EPS might be a rate-limiting step in sludge digestion. Functionally active microorganisms for microbial cell digestion predominantly included fermenters (e.g., Petrimonas and Lentimicrobium), syntrophic acetogens (e.g., Synergistaceae) and methanogens (e.g., Methanosaeta and Methanosarcina). Microbial source tracking estimation showed that the microbial cell-digesting populations accounted for 35.6 ± 9.1% and 70.3 ± 10.1% of total microbial communities in the WAS-AD and Thermal-WAS-AD, respectively. Accordingly, the functionally active microorganisms for digestion of both microbial cells and EPS accounted for 64.5 ± 12.1% and 97.3 ± 2.0% of total digestion sludge microbiome in WAS-AD and Thermal-WAS-AD, respectively. By contrast, feeding WAS-derived microorganisms accounted for 23.2 ± 4.4% and 2.3 ± 1.2% of total microbial communities in the WAS-AD and Thermal-WAS-AD, respectively.

Grazing pressure-induced shift in planktonic bacterial communities with the dominance of acIII-A1 actinobacterial lineage in soda pans

Astatic soda pans of the Pannonian Steppe are unique environments with respect to their multiple extreme physical and chemical characteristics (high daily water temperature fluctuation, high turbidity, alkaline pH, salinity, polyhumic organic carbon concentration, hypertrophic state and special ionic composition). However, little is known about the seasonal dynamics of the bacterial communities inhabiting these lakes and the role of environmental factors that have the main impact on their structure. Therefore, two soda pans were sampled monthly between April 2013 and July 2014 to reveal changes in the planktonic community. By late spring in both years, a sudden shift in the community structure was observed, the previous algae-associated bacterial communities had collapsed, resulting the highest ratio of Actinobacteria within the bacterioplankton (89%, with the dominance of acIII-A1 lineage) ever reported in the literature. Before these peaks, an extremely high abundance (> 10,000 individuum l-1) of microcrustaceans (Moina brachiata and Arctodiaptomus spinosus) was observed. OTU-based statistical approaches showed that in addition to algal blooms and water-level fluctuations, zooplankton densities had the strongest effect on the composition of bacterial communities. In these extreme environments, this implies a surprisingly strong, community-shaping top-down role of microcrustacean grazers.

Zooming on dynamics of marine microbial communities in the phycosphere of Akashiwo sanguinea (Dinophyta) blooms

Characterizing ecological relationships between viruses, bacteria and phytoplankton in the ocean is critical to understanding the ecosystem; however, these relationships are infrequently investigated together. To understand the dynamics of microbial communities and environmental factors in harmful algal blooms (HABs), we examined the environmental factors and microbial communities during Akashiwo sanguinea HABs in the Jangmok coastal waters of South Korea by metagenomics. Specific bacterial species showed complex synergistic and antagonistic relationships with the A. sanguinea bloom. The endoparasitic dinoflagellate Amoebophrya sp. 1 controlled the bloom dynamics and correlated with HAB decline. Among nucleocytoplasmic large DNA viruses (NCLDVs), two Pandoraviruses and six Phycodnaviruses were strongly and positively correlated with the HABs. Operational taxonomic units of microbial communities and environmental factors associated with A. sanguinea were visualized by network analysis: A. sanguinea-Amoebophrya sp. 1 (r = .59, time lag: 2 days) and A. sanguinea-Ectocarpus siliculosus virus 1 in Phycodnaviridae (0.50, 4 days) relationships showed close associations. The relationship between A. sanguinea and dissolved inorganic phosphorus relationship also showed a very close correlation (0.74, 0 day). Microbial communities and the environment changed dynamically during the A. sanguinea bloom, and the rapid turnover of microorganisms responded to ecological interactions. A. sanguinea bloom dramatically changes the environments by exuding dissolved carbohydrates via autotrophic processes, followed by changes in microbial communities involving host-specific viruses, bacteria and parasitoids. Thus, the microbial communities in HAB are composed of various organisms that interact in a complex manner.

Impact of Terrestrial Input on Deep-Sea Benthic Archaeal Community Structure in South China Sea Sediments

Archaea are widespread in marine sediments and play important roles in the cycling of sedimentary organic carbon. However, factors controlling the distribution of archaea in marine sediments are not well understood. Here we investigated benthic archaeal communities over glacial-interglacial cycles in the northern South China Sea and evaluated their responses to sediment organic matter sources and inter-species interactions. Archaea in sediments deposited during the interglacial period Marine Isotope Stage (MIS) 1 (Holocene) were significantly different from those in sediments deposited in MIS 2 and MIS 3 of the Last Glacial Period when terrestrial input to the South China Sea was enhanced based on analysis of the long-chain n-alkane C₃₁. The absolute archaeal 16S rRNA gene abundance in subsurface sediments was highest in MIS 2, coincident with high sedimentation rates and high concentrations of total organic carbon. Soil Crenarchaeotic Group (SCG; Nitrososphaerales) species, the most abundant ammonia-oxidizing archaea in soils, increased dramatically during MIS 2, likely reflecting transport of terrestrial archaea during glacial periods with high sedimentation rates. Co-occurrence network analyses indicated significant association of SCG archaea with benthic deep-sea microbes such as Bathyarchaeota and Thermoprofundales in MIS 2 and MIS 3, suggesting potential interactions among these archaeal groups. Meanwhile, Thermoprofundales abundance was positively correlated with total organic carbon (TOC), along with n-alkane C₃₁ and sedimentation rate, indicating that Thermoprofundales may be particularly important in processing of organic carbon in deep-sea sediments. Collectively, these results demonstrate that the composition of heterotrophic benthic archaea in the South China Sea may be influenced by terrestrial organic input in tune with glacial-interglacial cycles, suggesting a plausible link between global climate change and microbial population dynamics in deep-sea marine sediments.