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At least 19 records

Host-specific and tissue-dependent orchestration of microbiome community structure in traditional rice paddy ecosystems

Abstract Background and aim Rice and duckweed are two monocotyledonous plants that naturally coexist in paddy fields. While the presence of duckweed in paddy fields significantly improves rice productivity, the interplay between soil microbes and the two plant hosts in this agroecosystem remains unexplored. Methods We compared the bacterial community structure between duckweed, rice and soil from multiple rice paddies. We also isolated bacteria from these communities and characterized their modes of bacterial colonization and plant growth-promotion using model plants. Results Our data indicate that host-specific and tissue-dependent factors reproducibly orchestrate the bacterial community structure associated with their plant hosts. This is corroborated by results from culture-dependent approaches in which the dominant genus Pantoea isolated from rice aerial tissues can strongly attach and colonize gnotobiotic duckweed in spite of the low representation of this bacterial genus in the natural duckweed microbiome. Our study identified a core of 254 bacterial taxa that are consistently found in all rice and duckweed tissue samples from rice paddy fields. Furthermore, characterizing auxin-producing bacteria isolates from both plant species identified potential plant growth-promoting bacteria that may improve growth for both duckweed and rice in paddy fields. Conclusions Results from this work provide evidence for the importance of the host tissue and species context in determining plant colonization by microbes in the paddy field system. The resources generated in this study could facilitate the agronomic deployment of microbes for more sustainable rice production.

Agriculture↗

Impacts of nitrogen addition on switchgrass root-associated diazotrophic community structure and function

ABSTRACT Cellulosic bioenergy crops, like switchgrass (Panicum virgatum), have potential for growth on lands unsuitable for food production coupled with potential for climate mitigation. Sustainability of these systems lies in identifying conditions that promote high biomass yields on marginal lands under low-input agricultural practices. Associative nitrogen fixation (ANF) is a potentially important nitrogen (N) source for these crops, yet ANF contributions to plant N, especially under fertilizer N addition are unclear. In this study, we assess structure (nifH) and function (ANF) of switchgrass root-associated diazotrophic communities to long-term and short-term N additions using soil from three marginal land sites. ANF rates were variable and often unexpectedly high, sometimes 10× greater than reported in the literature, and did not respond in repeatable ways to long-term or short-term N. We found few impacts of N addition on root-associated diazotrophic community structure or membership. Instead, we found a very consistent root-associated diazotrophic community even though switchgrass seeds were germinated in soil from field sites with distinct diazotrophic communities. Ultimately, this work demonstrates that root-associated diazotrophic communities have the potential to contribute to switchgrass N demands, independent of N addition, and this may be driven by selection of the diazotrophic community by switchgrass roots.

Microbiology↗

On the Robustness of Network Community Structure Under Addition of Edges

Communities represent important functional modules in networked systems. A key goal in preserving such communities is understanding their robustness under perturbations. Previous research has studied the impact of node removals and edge removals on the community structure. However, the impact of edge additions on the robustness of the community structure is relatively unknown. Edge additions or false positive edges may simulate measurement errors or external exceptional events that threaten the functionality of networked systems. Here, we study the impact of edge additions on the community structure using Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks. We show that, for a fixed network size, the impact of edge additions is greater on networks with initially weak community structure than on networks with strongly clustered structures. In addition, we find that the perception of the impact is also dependent on the community detection algorithm used to uncover communities. In particular, we found that modularity-based methods such as Leiden and Louvain are less affected than information-theoretic and message passing-based methods such as Infomap and Label Propagation. Our results demonstrate that edge addition can (a) significantly impact the community structure of networks based on their initial conditions, and (b) the perception of the impact is dependent on the community detection algorithm used. We describe limitations, open challenges, and how this methodology can inform the design of resilient networked systems under edge additions.

97 MATHEMATICS AND COMPUTING↗

The effects of warming and soil chemistry on bacterial community structure in Arctic tundra soils

Soil microbial communities in the Arctic play a critical role in regulating the global carbon (C) cycle. Vast amounts of C are stored in northern latitude soils, and rising temperatures in the Arctic threaten to thaw permafrost, making relatively inaccessible C sources more available for mineralization by soil microbes. Few studies have characterized how microbial community structure responds to thawing permafrost in the context of varying soil chemistries associated with contrasting tundra landscapes. Here, we subjected active layer and permafrost soils from upland and lowland tundra sites on the North Slope of Alaska to a soil-warming incubation experiment and compared soil bacterial community profiles (obtained by 16S rRNA amplicon sequencing) before and after incubation. The influence of soil composition (characterized by mid-infrared [MIR] spectroscopy) on bacterial community structure and class abundance was analyzed using redundancy and correlation analyses. We found increased abundances of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes [Sphingobacteriia] post incubation, particularly in permafrost soils. The categorical descriptors site and soil layer had the most explanatory power in our predictive models of bacterial community structure, highlighting the close relationship between soil bacteria and the soil environment. Specific soil chemical attributes characterizing the soil environments that were found to be the best predictors include MIR spectral bands associated with inorganic C, silicates, amide II (C=N stretch), and carboxylics (C-O stretch), and MIR peak ratios representing C substrate quality. Overall, these results further characterize soil bacterial community shifts that may occur as a frozen environment with limited access to C sources, such as is found in undisturbed permafrost, transitions to warmer and more C-available environments, such as is predicted in thawing permafrost due to climate change.

16S rRNA sequencing↗

Quorum sensing modulates microbial community structure through regulation of secondary metabolites

Bacteria are recognized for their diverse metabolic capabilities, yet the impact of microbe-microbe interactions on multispecies community structure and dynamics is poorly understood. Cell-to-cell signaling in the form of quorum sensing (QS) often regulates secondary metabolite production and microbial interactions. Here, we examine how acylhomoserine lactone (AHL)-mediated QS impacts microbial community structure in a 10-member synthetic community of isolates from Populus deltoides . To explore the role of QS in microbial community structure and dynamics, we disrupted AHL signaling by exogenous addition of AiiA-lactonase, an enzyme that cleaves the lactone ring. Microbial community structure resulting from signal inactivation, as measured by 16S rRNA amplicon sequencing and secondary metabolite production, was assessed after successive passaging of the community. Further, we investigated the impact of quorum quenching on specific microbe-microbe interactions using pairwise inhibition assays. Our results indicate that AHL inactivation alters the relative abundance of dominant community members at later passages but does not impact the overall membership in the community. Quorum quenching significantly alters the metabolic profile in lactonase-treated communities. This metabolic alteration impacts microbe-microbe interactions through decreased inhibition of other community members. Together, these results indicate that QS impacts microbial community structure through the regulation of secondary metabolites in dominant members and that the membership of microbial communities can be relatively stable despite changes in metabolic profiles.

59 BASIC BIOLOGICAL SCIENCES↗

Performance and community structure dynamics of microbial electrolysis cells operated on multiple complex feedstocks

Microbial electrolysis is a promising technology for converting aqueous wastes into hydrogen. However, substrate adaptability is an important feature, seldom documented in microbial electrolysis cells (MECs). In addition, the correlation between substrate composition and community structure has not been well established. This study used an MEC capable of producing over 10 L/L-day of hydrogen from a switchgrass-derived bio-oil aqueous phase and investigated four additional substrates, tested in sequence on a mature biofilm. The additional substrates included a red oak-derived bio-oil aqueous phase, a corn stover fermentation product, a mixture of phenol and acetate, and acetate alone. The MECs fed with the corn stover fermentation product resulted in the highest performance among the complex feedstocks, producing an average current density of 7.3 ± 0.51 A/m 2 , although the acetate fed MECs outperformed complex substrates, producing 12.3 ± 0.01 A/m 2 . 16S rRNA gene sequencing showed that community structure and community diversity were not predictive of performance, and replicate community structures diverged despite identical inoculum and enrichment procedure. The trends in each replicate, however, were indicative of the influence of the substrates. Geobacter was the most dominant genus across most of the samples tested, but its abundance did not correlate strongly to current density. High-performance liquid chromatography (HPLC) showed that acetic acid accumulated during open circuit conditions when MECs were fed with complex feedstocks and was quickly degraded once closed circuit conditions were applied. The largest net acetic acid removal rate occurred when MECs were fed with red oak bio-oil aqueous phase, consuming 2.93 ± 0.00 g/L-day. Principal component analysis found that MEC performance metrics such as current density, hydrogen productivity, and chemical oxygen demand removal were closely correlated. Net acetic acid removal was also found to correlate with performance. However, no bacterial genus appeared to correlated to these performance metrics strongly, and the analysis suggested that less than 70% of the variance was accounted for by the two components. This study demonstrates the robustness of microbial communities to adapt to a range of feedstocks and conditions without relying on specific species, delivering high hydrogen productivities despite differences in community structure. The results indicate that functional adaptation may play a larger role in performance than community composition. Further investigation of the roles each microbe plays in these communities will help MECs to become integral in the 21st-century bioeconomy to produce zero-emission fuels.

09 BIOMASS FUELS↗

Long-term integrated soil-crop management improves soil microbial community structure to reduce GHG emission and increase yield

Integrated soil-crop management (ISCM) has been shown as an effective strategy to increase efficiency and yield while its soil microbial community structure and function remain unclear. We evaluated changes in soil physicochemical factors, bacterial community structure responses, and the contributions of soil properties and bacterial communities to summer maize-winter wheat yield and GHG emissions through an ISCM experiment [T1 (local smallholder farmers practice system), T2 (improved management system), T3 (high–yield production system), and T4 (optimized management system)], which could provide scientific guidance for sustainable development of soil in summer maize-winter wheat rotation system. The results showed that the optimized ISCM could improve the soil quality, which significantly changed the soil bacterial community structure to reduce GHG emissions and increase yield. The co-occurrence network density of T3 was increased significantly. The Acidobacteria (class) and OM190 (class) were enriched in T2 and T4. The Frankiales (order) and Gaiellales (order) were enriched in T3. However, the changes in different crop growth stages were different. At the wheat jointing stage and maize mature stage, T4 could enhance carbon-related functional groups, such as aromatic hydrocarbon degradation and hydrocarbon degradation, to increase the soil organic carbon content. And at the maize tasseling stage, T4 could enhance nitrogen-related functional groups. And soil bacteria structure and function indirectly affected annual yield and GHG emission. T2 and T4 exhibited a similar soil microbial community. However, the yield and nitrogen use efficiency of T2 were reduced compared to those of T4. The yield of T3 was the highest, but the GHG emission increased and soil pH and nitrogen use efficiency decreased significantly. Therefore, T4 was a suitable management system to improve soil quality and soil bacterial community structure and function to decrease GHG emissions and increase the yield of the summer maize-winter wheat rotation system.

Yu, Ningning↗

Evaluation of changes in the microbial community structure in the sediments of a constructed wetland over the years

This study presents the results of the long term (2007–2014) monitoring of the microbial community structure in the surface sediments of the H-02 constructed wetland system, which was built on the Savannah River Site in Aiken, SC, USA, to treat the waste water generated at the Tritium facility. Microbial community structure provides valuable information about the functioning of constructed wetlands and helps understand the biogeochemical cycling of nutrients and contaminants. Phospholipids fatty acid (PLFA) analysis and qPCR were used to identify major bacterial phyla in the sediments. The physiochemical properties of the sediments were also used to deduce potential effects on the microbial community structure over the years. Sulfate-reducing bacteria (SRB) were the most dominant bacterial groups, and their prevalence was progressively increasing throughout the years most likely on the account of methane producers. Concentrations of trace metals (copper and zinc) were negatively associated with methane producers and oxidizer while positively correlated with SRB. Overall, the H-02 wetland system was efficient in immobilizing copper and zinc through the anaerobic respiration of sulfate by SRB and minimizing methane emission through the progressive elimination of methane producers by SRB and Geobacter. Furthermore, the aim of this study was to monitor the changes in the microbial community structure in the surface sediments of a constructed wetland during the first 7 years of operation.

59 BASIC BIOLOGICAL SCIENCES↗

In anaerobic reactors the microbial community structure depends on feed type, with no “keystone” species tied to COD removal

Two-stage anaerobic digestion (AD) systems provide treatment for high strength wastewater with high stability and performance. Encapsulation technology can intensify AD to facilitate the separation of the solids retention time from the hydraulic retention time (HRT), offering lower HRTs, smaller reactors, and high effluent quality. To support successful deployment, however, the encapsulated community must contain all the needed microorganisms for successful treatment and be flexible enough to treat a variety of wastewaters. Here, a two-stage system was investigated in which microbial cultures were enriched on various high-strength wastewaters in suspended flow-through systems to determine how feed type influenced performance and microbial community structure. The hypothesis was that specific genera, or so-called “keystone species” would positively correlate to organic carbon degradation for a given feed, enabling construction of a well-functioning community for encapsulation. Results showed that the number of total bacteria (as 16S rRNA gene copies) did not correlate to soluble chemical oxygen demand (sCOD) removal, indicating that the community structure and/or members were important for good performance. Results also showed that feed type strongly influenced carbon removal and microbial community structure for 1st-stage fermenting communities, but not 2nd-stage methanogenic communities. In this study, the “core” community members were defined as organisms common to all of either the 1st- or 2nd-stage reactors irrespective of the feed they received and were present in at least 50% of the samples throughout the entire experiment. “Unique” community members were specific to a single feed, and hence, only present in either the 1st- or 2nd-stage reactors receiving that feed. In both 1st- and 2nd-stage communities, only one core genera and no unique genera were positively and significantly correlated to sCOD removal. Verification experiments performed with encapsulated communities showed that organisms identified in flow-through system and correlated with carbon degradation, though not significantly, seemed to be important for performance. Our results suggest that one cannot construct a community containing specific populations in lieu of enrichment. Nevertheless, a single diverse encapsulated anaerobic community should provide good (>80%) carbon removal when fed a variety of influents, if time is provided for enrichment after deployment.

54 ENVIRONMENTAL SCIENCES↗

Needle bacterial community structure across the species range of limber pine

Abstract Bacteria on and inside leaves can influence forest tree health and resilience. The distribution and limits of a tree species’ range can be influenced by various factors, with biological interactions among the most significant. We investigated the processes shaping the bacterial needle community across the species distribution of limber pine, a widespread Western conifer inhabiting a range of extreme habitats. We tested four hypotheses: (i) Needle community structure varies across sites, with site-specific factors more important to microbial assembly than host species selection; (ii) dispersal limitation structures foliar communities across the range of limber pine; (iii) the relative significance of dispersal and selection differs across sites in the tree species range; and (iv) needle age structures bacterial communities. We characterized needle communities from the needle surface and tissue of limber pine and co-occurring conifers across 16 sites in the limber pine distribution. Our findings confirmed that site characteristics shape the assembly of bacterial communities across the host species range and showed that these patterns are not driven by dispersal limitation. Furthermore, the strength of selection by the host varied by site, possibly due to differences in available microbes. Our study, by focusing on trees in their natural setting, reveals real needle bacterial dynamics in forests, which is key to understanding the balance between stochastic and deterministic processes in shaping forest tree-microbe interactions. Such understanding will be necessary to predict or manipulate these interactions to support forest ecosystem productivity or assist plant migration and adaptation in the face of global change.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of Cinnamomum camphora coppice planting on soil fertility, microbial community structure and enzyme activity in subtropical China

Cinnamomum camphora ( C. camphora ) is a broad-leaved evergreen tree cultivated in subtropical China. Currently, the use of C. camphora clonal cuttings for coppice management has become popular. However, the effects of C. camphora coppice planting on soil abiotic and biotic variances remained unclear. In this study, we collected soil from three points in the seven-year C. camphora coppice planting land: under the tree canopy (P15), between trees (P50), and abandoned land (Control) to investigate the effects of C. camphora coppice planting on soil fertility, microbial community structure and enzyme activity. The results revealed that C. camphora coppice planting significantly increased soil fertility in the point under the tree canopy (P15) and point between trees (P50), and P15 had more significant effects than P50. Meanwhile, in P15 and P50, soil bacterial, fungal alpha-diversity were improved and microbial community structures were also changed. And the changes of soil organic carbon and total nitrogen promote the transformation of soil bacterial, fungal community structures, respectively. In addition, C. camphora coppice planting significantly ( p < 0.05) increased soil urease (UE), polyphenol oxidase, and peroxidase activities, while significantly decreased soil ACP activity. This study demonstrated that the C. camphora coppice planting could improve soil fertility in subtropical China, which promoted the transformation of soil microbial community from oligotrophs ( K -strategist) to copiotrophs ( r -strategist). Thus, this work can provide a theoretical basis for soil nutrient variation and productive management of C. camphora coppice plantation in subtropical China.

Sun, Luyuan↗

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗

Rhizosphere microbial community structure in high-producing, low-input switchgrass families

Switchgrass ( Panicum virgatum L.) is a native, low-input North American perennial crop primarily grown for bioenergy, livestock forage, and industrial fiber. To achieve no-input switchgrass production that meets biomass needs, several switchgrass genotypes have been identified that have a low or negative response to nitrogen fertilizer, i . e ., the biomass accumulation with added nitrogen is less than or equal to that when grown without nitrogen. In order to improve the viability of low-input switchgrass production, a more detailed understanding of the biogeochemical mechanisms active in these select genotypes is needed. 16S and ITS amplicon sequencing and qPCR of key functional genes were applied to switchgrass rhizospheres to elucidate microbial community structure in high-producing, no-input switchgrass families. Rhizosphere microbial community structure differed strongly between sites, and nitrogen responsiveness.

Stonoha-Arther, Christina (ORCID:0000000263964507)↗

Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil

Abstract. The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (> 50 % of the soil organic carbon stocks are below 30 cm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4 ∘C warming in the whole-soil profile to 100 cm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30 cm) by 28 % but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources.

54 ENVIRONMENTAL SCIENCES↗

Subsurface microbial community structure shifts along the geological features of the Central American Volcanic Arc

Subduction of the Cocos and Nazca oceanic plates beneath the Caribbean plate drives the upward movement of deep fluids enriched in carbon, nitrogen, sulfur, and iron along the Central American Volcanic Arc (CAVA). These compounds fuel diverse subsurface microbial communities that in turn alter the distribution, redox state, and isotopic composition of these compounds. Microbial community structure and functions vary according to deep fluid delivery across the arc, but less is known about how microbial communities differ along the axis of a convergent margin as geological features (e.g., extent of volcanism and subduction geometry) shift. Here, we investigate changes in bacterial 16S rRNA gene amplicons and geochemical analysis of deeply-sourced seeps along the southern CAVA, where subduction of the Cocos Ridge alters the geological setting. We find shifts in community composition along the convergent margin, with communities in similar geological settings clustering together independently of the proximity of sample sites. Microbial community composition correlates with geological variables such as host rock type, maturity of hydrothermal fluid and slab depth along different segments of the CAVA. This reveals tight coupling between deep Earth processes and subsurface microbial activity, controlling community distribution, structure and composition along a convergent margin.

Science & Technology - Other Topics↗

MCS+: An Efficient Algorithm for Crawling the Community Structure in Multiplex Networks

In this article, we consider the problem of crawling a multiplex network to identify the community structure of a layer-of-interest. A multiplex network is one where there are multiple types of relationships between the nodes. In many multiplex networks, some layers might be easier to explore (in terms of time, money etc.). We propose MCS+, an algorithm that can use the information from the easier to explore layers to help in the exploration of a layer-of-interest that is expensive to explore. We consider the goal of exploration to be generating a sample that is representative of the communities in the complete layer-of-interest. This work has practical applications in areas such as exploration of dark (e.g., criminal) networks, online social networks, biological networks, and so on. For example, in a terrorist network, relationships such as phone records, e-mail records, and so on are easier to collect; in contrast, data on the face-to-face communications are much harder to collect, but also potentially more valuable. We perform extensive experimental evaluations on real-world networks, and we observe that MCS+ consistently outperforms the best baseline—the similarity of the sample that MCS+ generates to the real network is up to three times that of the best baseline in some networks. We also perform theoretical and experimental evaluations on the scalability of MCS+ to network properties, and find that it scales well with the budget, number of layers in the multiplex network, and the average degree in the original network.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Blodgett Forest CA Warming Experiment phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data 2018 from: "Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil".

This data package contains phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data used for the paper: “Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil”. SOIL, https://doi.org/10.5194/soil-2021-14.On April 2018 (after 4.5 years of warming), we collected soil cores down to 90 cm depth from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This data package includes a file in .csv format and a file in .xlsx format, which can be accessed and processed using MS Excel or R. Phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers concentrations are provided as processed data files.

54 ENVIRONMENTAL SCIENCES↗

Microbial Community Structure and Ecological Networks during Simulation of Diatom Sinking

Microbial-mediated utilization of particulate organic matter (POM) during its downward transport from the surface to the deep ocean constitutes a critical component of the global ocean carbon cycle. However, it remains unclear as to how high hydrostatic pressure (HHP) and low temperature (LT) with the sinking particles affects community structure and network interactions of the particle-attached microorganisms (PAM) and those free-living microorganisms (FLM) in the surrounding water. In this study, we investigated microbial succession and network interactions in experiments simulating POM sinking in the ocean. Diatom-derived 13C- and 12C-labeled POM were used to incubate surface water microbial communities from the East China Sea (ECS) under pressure (temperature) of 0.1 (25 °C), 20 (4 °C), and 40 (4 °C) MPa (megapascal). Our results show that the diversity and species richness of the PAM and FLM communities decreased significantly with HHP and LT. Microbial community analysis indicated an increase in the relative abundance of Bacteroidetes at high pressure (40 MPa), mostly at the expense of Gammaproteobacteria, Alphaproteobacteria, and Gracilibacteria at atmospheric pressure. Hydrostatic pressure and temperature affected lifestyle preferences between particle-attached (PA) and free-living (FL) microbes. Ecological network analysis showed that HHP and LT enhanced microbial network interactions and resulted in higher vulnerability to networks of the PAM communities and more resilience of those of the FLM communities. Most interestingly, the PAM communities occupied most of the module hubs of the networks, whereas the FLM communities mainly served as connectors of the modules, suggesting their different ecological roles of the two groups of microbes. These results provided novel insights into how HHP and LT affected microbial community dynamics, ecological networks during POM sinking, and the implications for carbon cycling in the ocean.

59 BASIC BIOLOGICAL SCIENCES↗