Recurrent microbial community types driven by nearshore and seasonal processes in coastal Southern California

Suspended detrital particles support a distinct microbial ecosystem in Palmer Canyon, Antarctica, a coastal biological hotspot

The coastal region of the Western Antarctic Peninsula is considered a biological hotspot with high levels of phytoplankton productivity and krill biomass. Recent in situ observations and particle modeling studies of Palmer Canyon, a deep bathymetric feature in the region, demonstrated the presence of a recirculating eddy that traps particles, retaining a distinct particle layer over the summer season. We applied metagenomic sequencing and Imaging Flow Cytobot (IFCB) analysis to characterize the microbial community in the particle layer. We sampled across the upper water column (< 200 m) along a transect to identify the locations of increased particle density, categorizing particles into either living cells or cellular detritus via IFCB. An indicator species analysis of community composition demonstrated the diatom Corethron and the bacteria Sulfitobacter were significantly highly abundant in samples with high levels of living cells, while the mixotrophic dinoflagellate Prorocentrum texanum and prokaryotes Methanomassiliicoccales and Fluviicola taffensis were significantly more abundant in samples with high detritus within the particle layer. From our metagenomic analysis, the significantly differentially abundant metabolic pathway genes in the particle layer of Palmer Canyon included pathways for anaerobic metabolism, such as methanogenesis and sulfate reduction. Overall, our results indicate that distinct microbial species and metabolic pathway genes are present in the retained particle layer of Palmer Canyon.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00300-025-03380-y.

Novel oil-associated bacteria in Arctic seawater exposed to different nutrient biostimulation regimes

The Arctic Ocean is an oligotrophic ecosystem facing escalating threats of oil spills as ship traffic increases owing to climate change-induced sea ice retreat. Biostimulation is an oil spill mitigation strategy that involves introducing bioavailable nutrients to enhance crude oil biodegradation by endemic oil-degrading microbes. For bioremediation to offer a viable response for future oil spill mitigation in extreme Arctic conditions, a better understanding of the effects of nutrient addition on Arctic marine microorganisms is needed. Controlled experiments tracking microbial populations revealed a significant decline in community diversity along with changes in microbial community composition. Notably, differential abundance analysis highlighted the significant enrichment of the unexpected genera Lacinutrix, Halarcobacter and Candidatus Pseudothioglobus. These groups are not normally associated with hydrocarbon biodegradation, despite closer inspection of genomes from closely related isolates confirming the potential for hydrocarbon metabolism. Co-occurrence analysis further revealed significant associations between these genera and well-known hydrocarbon-degrading bacteria, suggesting potential synergistic interactions during oil biodegradation. While these findings broaden our understanding of how biostimulation promotes enrichment of endemic hydrocarbon-degrading genera, further research is needed to fully assess the suitability of nutrient addition as a stand-alone oil spill mitigation strategy in this sensitive and remote polar marine ecosystem.

Identification of keystone taxa in rhizosphere microbial communities using different methods and their effects on compounds of the host Cinnamomum migao

Exploring keystone taxa affecting microbial community stability and host function is crucial for understanding ecosystem functions. However, identifying keystone taxa from humongous microbial communities remains challenging. We collected 344 rhizosphere and bulk soil samples from the endangered plant C. migao for 2 years consecutively. Used high-throughput sequencing 16S rDNA and ITS to obtain the composition of bacterial and fungal communities. We explored keystone taxa and the applicability and limitations of five methods (SPEC-OCCU, Zi-Pi, Subnetwork, Betweenness, and Module), as well as the impact of microbial community domain, time series, and rhizosphere boundary on the identification of keystone taxa in the communities. Our results showed that the five methods, identified abundant keystone taxa in rhizosphere and bulk soil microbial communities. However, the keystone taxa shared by the rhizosphere and bulk soil microbial communities over time decreased rapidly decrease in the five methods. Among five methods on the identification of keystone taxa in the rhizosphere community, Module identified 113 taxa, SPEC-OCCU identified 17 taxa, Betweenness identified 3 taxa, Subnetwork identified 3 taxa, and Zi-Pi identified 4 taxa. The keystone taxa are mainly conditionally rare taxa, and their ecological functions include chemoheterotrophy, aerobic chemoheterotrophy, nitrate reduction, and anaerobic photoautotrophy. The results of the random forest model and structural equation model predict that keystone taxa Mortierella and Ellin6513 may have an effects on the accumulation of 1, 4, 7, - Cycloundecatriene, 1, 5, 9, 9-tetramethyl-, Z, Z, Z-, beta-copaene, bicyclogermacrene, 1,8-Cineole in C. migao fruits, but their effects still need further evidence. Our study evidence an unstable microbial community in the bulk soil, and the definition of microbial boundary and ecologically functional affected the identification of keystone taxa in the community. Subnetwork and Module are more in line with the definition of keystone taxa in microbial ecosystems in terms of maintaining community stability and hosting function.

Microbial community composition predicts bacterial production across ocean ecosystems

Microbial ecological functions are an emergent property of community composition. For some ecological functions, this link is strong enough that community composition can be used to estimate the quantity of an ecological function. Here, we apply random forest regression models to compare the predictive performance of community composition and environmental data for bacterial production (BP). Using data from two independent long-term ecological research sites-Palmer LTER in Antarctica and Station SPOT in California-we found that community composition was a strong predictor of BP. The top performing model achieved an R2 of 0.84 and RMSE of 20.2 pmol L-1 hr-1 on independent validation data, outperforming a model based solely on environmental data (R2 = 0.32, RMSE = 51.4 pmol L-1 hr-1). We then operationalized our top performing model, estimating BP for 346 Antarctic samples from 2015 to 2020 for which only community composition data were available. Our predictions resolved spatial trends in BP with significance in the Antarctic (P value = 1 × 10-4) and highlighted important taxa for BP across ocean basins. Our results demonstrate a strong link between microbial community composition and microbial ecosystem function and begin to leverage long-term datasets to construct models of BP based on microbial community composition.

Stochasticity-driven weekly fluctuations distinguished the temporal pattern of particle-associated microorganisms from its free-living counterparts in temperate coastal seawater

Microbial community dynamics directly determine their ecosystem functioning. Despite the well-known annual recurrence pattern, little is known how different lifestyles affect the temporal variation and how community assembly mechanisms change over different temporal scales. Here, through a high-resolution observation of size fractionated samples over 60 consecutive weeks, we investigate the distinction in weekly distribution pattern and assembly mechanism between free-living (FL) and particle-associated (PA) communities in highly dynamic coastal environments. A clear pattern of annual recurrence was observed, which was more pronounced in FL compared to PA, resulting in higher temporal specificity in the former samples. Both the two size fractions displayed significant temporal distance-decay patterns, yet the PA community showed a higher magnitude of community variation between adjacent weeks, likely caused by sudden, drastic and long-lived blooms of heterotrophic bacteria. Generally, determinism (environmental selection) had a greater effect on the community assembly than stochasticity (random birth, death, and dispersal events), with significant contributions from temperature and inorganic nutrients. However, a clear shift in the temporal assembly pattern was observed, transitioning from a prevalence of stochastic processes driving short-term (within a month) fluctuations to a dominance of deterministic processes over longer time intervals. Between adjacent weeks, stochasticity was more important in the community assembly of PA than FL. This study revealed that stochastic processes can lead to rapid, dramatic and irregular PA community fluctuations, indicating weak resistance and resilience to disturbances, which considering the role of PA microbes in carbon processing would significantly affect the coastal carbon cycle. Our results provided a new insight into the microbial community assembly mechanisms in the temporal dimension.

Predicting the performance of chain elongating microbiomes through flow cytometric fingerprinting

As part of the circular bio-economy paradigm shift, waste management and valorisation practices have moved away from sanitation and towards the production of added-value compounds. Recently, the development of mixed culture bioprocess for the conversion of waste(water) to platform chemicals, such as medium chain carboxylic acids, has attracted significant interest. Often, the microbiology of these novel bioprocesses is less diverse and more prone to disturbances, which can lead to process failure. This issue can be tackled by implementing an advanced monitoring strategy based on the microbiology of the process. In this study, flow cytometry was used to monitor the microbiology of lactic acid chain elongation for the production of caproic acid, and assess its performance both qualitatively and quantitatively. Two continuous stirred tank reactors for chain elongation were monitored flow cytometrically for over 336 days. Through community typing, four specific community types could be identified and correlated to both a specific functionality and genotypic diversity. Additionally, the machine-learning algorithms trained in this study demonstrated the ability to predict production rates of, amongst others, caproic acid with high accuracy in the present (R² > 0.87) and intermediate accuracy in the near future (R² > 0.63). The identification of specific community types and the development of predictive algorithms form the basis of advanced bioprocess monitoring based on flow cytometry, and have the potential to improve bioprocess control and optimization, leading to better product quality and yields.

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.

Engineering an incubation environment that mimics in situ conditions for in vitro coastal microbiome studies

Coastal environments are dynamic and can vary widely on short- or long-term scales depending on location and weather. Incubation equipment that reflects these changes through programmable gradient light and temperature cycles would permit more precise in vitro coastal microbiome studies. Here we present an open-source incubation environment that mimics in situ conditions for in vitro coastal microbiome studies using a modified shaking water bath that has fully customizable temperature and light gradients that can also mimic real-time field conditions. We compared coastal microbial community profiles incubated in situ and in our build mimicking field conditions over 48 h. Analyses of congruence indicated significant overlap (p > 0.2) between microbial communities incubated in situ and in vitro at each time point.

Seasonal bacterial niche structures and chemolithoautotrophic ecotypes in a North Atlantic fjord

Quantifying the temporal change of bacterial communities is essential to understanding how both natural and anthropogenic pressures impact the functions of coastal marine ecosystems. Here we use weekly microbial DNA sampling across four years to show that bacterial phyla have distinct seasonal niches, with a richness peak in winter (i.e., an inverse relationship with daylength). Our results suggest that seasonal fluctuations, rather than the kinetic energy or resource hypotheses, dominated the pattern of bacterial diversity. These findings supplement those from global analyses which lack temporal replication and present few data from winter months in polar and temperate regions. Centered log-ratio transformed data provided new insights into the seasonal niche partitioning of conditionally rare phyla, such as Modulibacteria, Verrucomicrobiota, Synergistota, Deinococcota, and Fermentibacterota. These patterns could not be identified using the standard practice of ASV generation followed by rarefaction. Our study provides evidence that five globally relevant ecotypes of chemolithoautotrophic bacteria from the SUP05 lineage comprise a significant functional group with varying seasonal dominance patterns in the Bedford Basin.

Improving environmental monitoring of Vibrionaceae in coastal ecosystems through 16S rRNA gene amplicon sequencing

The Vibrionaceae family groups genetically and metabolically diverse bacteria thriving in all marine environments. Despite often representing a minor fraction of bacterial assemblages, members of this family can exploit a wide variety of nutritional sources, which makes them important players in biogeochemical dynamics. Furthermore, several Vibrionaceae species are well-known pathogens, posing a threat to human and animal health. Here, we applied the phylogenetic placement coupled with a consensus-based approach using 16S rRNA gene amplicon sequencing, aiming to reach a reliable and fine-level Vibrionaceae characterization and identify the dynamics of blooming, ecologically important, and potentially pathogenic species in different sites of the northern Adriatic Sea. Water samples were collected monthly at a Long-Term Ecological Research network site from 2018 to 2021, and in spring and summer of 2019 and 2020 at two sites affected by depurated sewage discharge. The 41 identified Vibrionaceae species represented generally below 1% of the sampled communities; blooms (up to ~ 11%) mainly formed by Vibrio chagasii and Vibrio owensii occurred in summer, linked to increasing temperature and particulate matter concentration. Pathogenic species such as Vibrio anguilllarum, Vibrio tapetis, and Photobacterium damselae were found in low abundance. Depuration plant samples were characterized by a lower abundance and diversity of Vibrionaceae species compared to seawater, highlighting that Vibrionaceae dynamics at sea are unlikely to be related to wastewater inputs. Our work represents a further step to improve the molecular approach based on short reads, toward a shared, updated, and curated phylogeny of the Vibrionaceae family.

From microbial community structure to metabolic inference using paprica

Microbial taxonomic marker gene studies using 16S rRNA gene amplicon sequencing provide an understanding of microbial community structure and diversity; however, it can be difficult to infer the functionality of microbes in the ecosystem from these data. Here, we show how to predict metabolism from phylogeny using the paprica pipeline. This approach allows resolution at the strain and species level for select regions on the prokaryotic phylogenetic tree and provides an estimate of gene and metabolic pathway abundance. For complete details on the use and execution of this protocol, please refer to Erazo and Bowman (2021).