Characteristics and key driving factors of nitrous oxide emissions from a full-scale landfill leachate treatment system.

The characteristics of N2O emission from a full-scale landfill leachate treatment system were investigated by in-situ monitoring over 1.4 years and driving factors responsible for these emissions were identified by statistical analysis of multidimensional environmental variables. The results showed that the maximum N2O emission flux of 2.21 × 107 mg N·h-1 occurred in the nitrification tanks, where 98.5 % of the total N2O was released, with only 1.5 % of the total N2O emitted from the denitrification tanks. Limited oxygen in nitrification tank was responsible for N2O hotspot. The N2O emissions from the parallel lines A and B (both comprising the primary biochemical system) accounted for 52.6 % and 46.6 %, respectively, while the secondary biochemical system contributed only 0.8 % to the total emissions. Higher nitrite concentration in line A and lower nitrogen loading in the secondary biochemical system caused these discrepancies. We found that during the steady state of leachate treatment, intensive N2O emissions of 253.4-1270.5 kg N·d-1 were measured. The corresponding N2O emission factor (EF) ranged from 8.86 to 49.6 %, much higher than those of municipal wastewater treatment. But N2O EF was inconceivably as low as 0.42 % averagely after system maintenance. Influent with low salinity was the key reason, followed by the high MLSS and varying microbial community after maintenance. The dominant genus shifted from Lentimicrobium and Thauera to Norank-F-Anaerolineaceae and Unclassified-F-Rhodocyclaceae. This study underscores the significance of landfill leachate treatment in urban nitrogen management and provides valuable insights into the characteristics and driving factors of N2O emissions from such systems. The findings offer important references for greenhouse gas emission inventories and strategies for N2O control in full-scale wastewater treatment plants.

Bioleaching of polymetallic sulphidic mining residues: influence of increasing solid concentration on microbial community dynamics and metal dissolution.

Within the European research project NEMO, a bioleaching strategy was developed for efficient metal extraction from bioleach residue currently heap-leached at Sotkamo (Finland) that still contains sulphidic minerals and valuable metals (Ni, Zn, Co, Cu). The strategy of gradually increasing the solid content with 5% steps allowed the adaptation of the consortium up to 20% (w/w) solid content, with efficient metal dissolution and same dominant bacteria. Largest proportions of Sulfobacillusthermosulfidooxidans while Eh increased suggested it to be most involved in iron oxidation. Acidithiobacilluscaldus was rather found when pH stabilized, in line with a production of protons from sulphur oxidation that maintained low pH. 'Acidithiomicrobium' P2 was favoured towards the end of the runs and at 20% (w/w) solids possibly due to its tolerance to Ni. The use of gene abundance to evaluate biomass in the pulp provided complementary results to classical cell counts in the liquid phase, and suggested a key role of bacteria associated to mineral particles in iron oxidation. Scaling-up in 21-L stirred-tank reactor at 20% (w/w) solids had no detrimental effect on bioleaching and confirmed metal extraction rates. 'Acidithiomicrobium' P2 and Sb. thermosulfidooxidans remained main actors. However, the biological activity was considerably reduced at 30% (w/w) solid concentration, which may be due to a too drastic environmental change for the bacteria to adapt to higher solid concentration. Efficient bioleaching of Sotkamo bioleaching residue at high solid concentration was demonstrated, as well as the robustness of the selected moderately thermophilic consortium, at laboratory and pilot scales.

Testing for the fitness benefits of natural transformation during community-embedded evolution.

Natural transformation is a process where bacteria actively take up DNA from the environment and recombine it into their genome or reconvert it into extra-chromosomal genetic elements. The evolutionary benefits of transformation are still under debate. One main explanation is that foreign allele and gene uptake facilitates natural selection by increasing genetic variation, analogous to meiotic sex. However, previous experimental evolution studies comparing fitness gains of evolved transforming- and isogenic non-transforming strains have yielded mixed support for the 'sex hypothesis.' Previous studies testing the sex hypothesis for natural transformation have largely ignored species interactions, which theory predicts provide conditions favourable to sex. To test for the adaptive benefits of bacterial transformation, the naturally transformable wild-type Acinetobacter baylyi and a transformation-deficient ∆comA mutant were evolved for 5 weeks. To provide strong and potentially fluctuating selection, A. baylyi was embedded in a community of five other bacterial species. DNA from a pool of different Acinetobacter strains was provided as a substrate for transformation. No effect of transformation ability on the fitness of evolved populations was found, with fitness increasing non-significantly in most treatments. Populations showed fitness improvement in their respective environments, with no apparent costs of adaptation to competing species. Despite the absence of fitness effects of transformation, wild-type populations evolved variable transformation frequencies that were slightly greater than their ancestor which potentially could be caused by genetic drift.

Does a history of population co-occurrence predict plant performance, community productivity, or invasion resistance?

A history of species co-occurrence in plant communities is hypothesized to lead to greater niche differentiation, more efficient resource partitioning, and more productive, resistant communities as a result of evolution in response to biotic interactions. A similar question can be asked of co-occurring populations: do individual species or community responses differ when communities are founded with plants sharing a history of population co-occurrence (sympatric) or originating from different locations (allopatric)? Using shrub, grass, and forb species from six locations in the western Great Basin, North America, we compared establishment, productivity, reproduction, phenology, and resistance to invaders for experimental communities with either sympatric or allopatric population associations. Each community type was planted with six taxa in outdoor mesocosms, measured over three growing seasons, and invaded with the annual grass Bromus tectorum in the final season. For most populations, the allopatric or sympatric status of neighbors was not important. However, in some cases, it was beneficial for some species from some locations to be planted with allopatric neighbors, while others benefited from sympatric neighbors, and some of these responses had large effects. For instance, the Elymus population that benefited the most from allopatry grew 50% larger with allopatric neighbors than in single origin mesocosms. This response affected invasion resistance, as B. tectorum biomass was strongly affected by productivity and phenology of Elymus spp., as well as Poa secunda. Our results demonstrate that, while community composition can affect plant performance in semi-arid plant communities, assembling communities from sympatric populations is not sufficient to ensure high productivity and invasion resistance. Instead, we observed an idiosyncratic interaction between sampling effects and evolutionary history, with the potential for seed source of individual populations to have community-level effects.

Microbial community evolution and functional trade-offs of biofilm in odor treatment biofilters.

Biofilters inoculated with activated sludge are widely used for odor control in WWTP. In this process, biofilm community evolution plays an important role in the function of reactor and is closely related to reactor performance. However, the trade-offs in biofilm community and bioreactor function during the operation are still unclear. Herein, an artificially constructed biofilter for odorous gas treatment was operated for 105 days to study the trade-offs in the biofilm community and function. Biofilm colonization was found to drive community evolution during the start-up phase (phase 1, days 0-25). Although the removal efficiency of the biofilter was unsatisfactory at this phase, the microbial genera related to quorum sensing and extracellular polymeric substance secretion led to the rapid accumulation of the biofilm (2.3 kg biomass/m3 filter bed /day). During the stable operation phase (phase 2, days 26-80), genera related to target-pollutant degradation showed increases in relative abundance, which accompanied a high removal efficiency and a stable accumulation of biofilm (1.1 kg biomass/m3 filter bed/day). At the clogging phase (phase 3, days 81-105), a sharp decline in the biofilm accumulation rate (0.5 kg biomass/m3 filter bed /day) and fluctuating removal efficiency were observed. The quorum quenching-related genera and quenching genes of signal molecules increased, and competition for resources among species drove the evolution of the community in this phase. The results of this study highlight the trade-offs in biofilm community and functions during the operation of bioreactors, which could help improve bioreactor performance from a biofilm community perspective.

Effect of temperature and storage methods on liquid digestate: Focusing on the stability, phytotoxicity, and microbial community.

Identifying the stability and phytotoxicity of liquid digestate (LD) is necessary for safe agricultural utilization. Storage temperature, method, and time are critical factors that affect the stability and phytotoxicity of LD. This study therefore aimed to explore the dynamics of stability, phytotoxicity, and microbial community of LD in cattle farms under different storage conditions. The results showed that the contents of solids, organic matter, nitrogen, and phosphorous decreased during storage and exhibited temperature dependency. Conversely, the seed germination index increased, which was negatively correlated with dissolved organic carbon and ammonium nitrogen and positively correlated with certain bacteria (Thermovirga and Fastidiosipila). Open storage and/or higher temperature were found to contribute to the stabilization efficiency and phytotoxicity disappearance of LD. Open storage of LD at 30 °C for 60 days and 20 °C for 90 days was safe for its agricultural utilization, while hermetic storage of LD at 30 °C for 120 days and 20 °C for 150 days was safe. However, for storage at 10 °C for 180 days, additional post-treatment is required.

Community diversity determines the evolution of synthetic bacterial communities under artificial selection.

Artificial selection can be conducted at the community level in the laboratory through a differential propagation of the communities according to their level of expression of a targeted function. Working with communities instead of individuals as selection units brings in additional sources of variation in the considered function that can influence the outcome of the artificial selection. In this study, we wanted to assess the effect of manipulating the initial community richness on artificial selection efficiency, defined as the change in the targeted function over time. We applied artificial selection for a high productivity on synthetic bacterial communities varying for their richness (from one to 16 strains). Overall, the selected communities were 16% more productive than the control communities, but a convergence of community composition might have limited the effect of diversity on artificial selection efficiency. Community richness positively influenced community productivity and metabolic capacities and was a strong determinant of the dynamics of community evolution. We propose that applying artificial selection on communities varying for their diversity could be a way to find communities differing for their level of expression of a function but also for their responsiveness to artificial selection, provided that their initial composition is different enough.

Fast formation of anammox granules using a nitrification-denitrification sludge and transformation of microbial community.

A lengthy start-up period has been one of the key obstacles limiting the application of the anammox process. In this investigation, a nitrification-denitrification sludge was used to start-up the anammox EGSB process. The transformation process from nitrification-denitrification sludge to anammox granule sludge was explored through the aspects of nitrogen removal performance, granule properties, microbial community structure, and evolution route. A successful start-up of the anammox process was achieved after 94 days of reactor operation. The highest nitrogen removal rate (NRR) obtained was 7.25±0.16 gN/L/d at a nitrogen loading rate (NLR) of 8.0 gN/L/d, and the corresponding nitrogen removal efficiency was a high 90.61±1.99%. The results of the microbial analysis revealed significant changes in anammox bacteria, nitrifying bacteria, and denitrifying bacteria in the sludge. Notably, the anammox bacteria abundance increased from 2.5% to 29.0% during the operation, and Candidatus Kuenenia and Candidatus Brocadia were the dominant genera. Distinct-different successions on Candidatus Brocadia and Candidatus Kuenenia were also observed over the long-term period. In addition, the settling performance, anammox activity and biomass retention capacity of the granules were significantly enhanced during this process, and the corresponding granule evolution route was also proposed. The results in this study indicate the feasibility of using available seed sludge source for the fast-transformation of anammox granules, it is beneficial to the large-scale application of anammox process and the utilization of excess sludge.

Simulating selection and evolution at the community level using common garden data.

A key issue in evolutionary biology is whether selection acting at levels higher than the individual can cause evolutionary change. If it can, then conceptual and empirical studies must consider how selection operates at multiple levels of biological organization. Here, we test the hypothesis that estimates of broad-sense community heritability, H C 2 , can be used to predict the evolutionary response by community-level phenotypes when community-level selection is imposed. Using an approach informed by classic quantitative genetics, we made three predictions. First, when we imposed community-level selection, we expected a significant change in the average phenotype of arthropod communities associated with individual tree genotypes [we imposed selection by favoring high and low NMDS (nonmetric multidimensional scaling) scores that reflected differences in arthropod species richness, abundance and composition]. Second, we expected H C 2 to predict the magnitude of the community-level response. Third, we expected no significant change in average NMDS scores with community-level selection imposed at random. We tested these hypotheses using three years of common garden data for 102 species comprising the arthropod communities, associated with nine clonally replicated Populus angustifolia genotypes. Each of our predictions were met. We conclude that estimates of H C 2 account for the resemblance among communities sharing common ancestry, the persistence of community composition over time, and the outcome of selection when it occurs at the community level. Our results provide a means for exploring how this process leads to large-scale community evolutionary change, and they identify the circumstances in which selection may routinely act at the community level.

Different characteristics of microbial diversity and special functional microbes in rainwater and topsoil before and after 2019 new coronavirus epidemic in Inner Mongolia Grassland.

Grassland ecosystems are vital terrestrial ecosystems. As areas sensitive to climate change, they are critical for assessing the effects of global climate change. In China, grasslands account for over 40% of the land area. There is currently limited information on microbial diversity evolution in different grassland areas, particularly microorganisms with ice nucleation activity (INA) and their potential resources with potential influence to regulate regional precipitation and climate. We used Illumina MiSeq to sequence the 16S rRNA V3-V4 hypervariable region and performed a simple droplet freezing experiment to determine the variation in the grassland microbial community species composition and community structure. Rainwater and topsoil samples from the Hulunbuir Grassland in Inner Mongolia collected over three years were characterized. The dominant bacterial genus in the rainwater was Massilia, and the dominant fungus was Cladosporium. Additionally, the dominant bacteria in the soil were Sphingomonas, and the dominant fungus was Gibberella. There were differences in the microbial communities before and after the coronavirus disease epidemic. Pathogenic microorganisms exhibited inconsistent responses to environmental changes. The low relative abundance of known high-INA microorganisms and the higher freezing temperature indicated that unknown high-efficiency biological ice nucleating particles may be present. We found significant differences in species diversity and richness between the rainwater and soil populations in grassland areas by analyzing the sample community structures. Our research results revealed the species composition and structure of the microbiota in grassland ecosystems in China, indicating that environmental media and human activities may affect the microbiota in the grassland area and indicating underlying microorganisms with high INA.

Can radicals-orientated chemical oxidation improve the reduction of antibiotic resistance genes (ARGs) by mesophilic anaerobic digestion of sludge?

The dissemination of antibiotic resistance genes (ARGs) increases risks towards human health and environmental safety. This work investigates the control of ARGs abundance and bacterial community evolution involved in waste activated sludge (WAS) treatment by chemical conditioning and subsequent mesophilic anaerobic digestion (MAD). The different chemical oxidation processes of ferrous iron-activated oxone and hydrogen peroxide (PMS-Fe2+ and H2O2-Fe2+) and thermal-activated oxone (PMS@80 â„ƒ) were investigated, and the ferric chloride (FeCl3) and inactivated oxone (PMS) were compared. PMS@80 â„ƒ decreased the absolute abundance of most ARGs by 10.6-99.3% and that of total ARGs by 66.3%. Interestingly, oxidation pretreatment increased rather than decreased the relative abundance of most ARGs. MAD with PMS@80 â„ƒ pretreatment increased the absolute abundance of total ARGs by 51.6%, and other MAD processes decreased it by 8.6-47.4%. PMS-Fe2+ and PMS@80 â„ƒ negatively inhibited methane production from 98.3 to 81.7 and 94.4 mL/g VSS in MAD. MAD effluent showed high abundance of Arcobacter genus in the range of 8.1-17.4% upon PMS-based pretreatment, possibly related to sulfur oxidation, nitrate reduction, and blaVEB enrichment. The radicals-orientated chemical oxidation can hardly improve the ARGs elimination by MAD due to the extremely high competitive organics in sludge.

Insights into nitrogen removal from seawater-based wastewater through marine anammox bacteria under ampicillin stress: Microbial community evolution and genetic response.

Global spread of ampicillin (AMP) in the aquatic environment have attracted much attention recently. Marine anammox bacteria (MAB) have potentials in saline wastewater treatment due to their good salt tolerance. However, to date, the effect resulting from AMP on MAB is still unknown. Herein, the effect of AMP on MAB, involving microbial community evolution and genetic response, was investigated for the first time. A lab-scale reactor inoculated by MAB sludge was operated under saline condition (35 g/L) and AMP stress of different gradients. Within 200 cycles, nitrogen removal performance was monitored and sludge samples were withdrawn for high-throughput sequencing analyses and qPCR. The results confirmed that the nitrogen removal capacity of MAB declined with increasing AMP dosage, and almost collapsed at 300 mg/L AMP. The total nitrogen removal rate and specific anammox activity finally dropped to 0.17 kg N m-3 d-1 and 101.86 mg N g-1VSS d-1, respectively. Pseudoalteromonas (38.13%) dominated the reactor on Cycle 190, which formed a new symbiosis with MAB. And the emergence of oleophilic bacteria such as Colwellia (2.53%) was also observed. Moreover, antibiotic resistance genes were detected with increased abundance and diversity, indicating the AMP dosing significantly promoted microbial community evolution and genetic response.

Evolution of topics and hate speech in retweet network communities.

Twitter data exhibits several dimensions worth exploring: a network dimension in the form of links between the users, textual content of the tweets posted, and a temporal dimension as the time-stamped sequence of tweets and their retweets. In the paper, we combine analyses along all three dimensions: temporal evolution of retweet networks and communities, contents in terms of hate speech, and discussion topics. We apply the methods to a comprehensive set of all Slovenian tweets collected in the years 2018-2020. We find that politics and ideology are the prevailing topics despite the emergence of the Covid-19 pandemic. These two topics also attract the highest proportion of unacceptable tweets. Through time, the membership of retweet communities changes, but their topic distribution remains remarkably stable. Some retweet communities are strongly linked by external retweet influence and form super-communities. The super-community membership closely corresponds to the topic distribution: communities from the same super-community are very similar by the topic distribution, and communities from different super-communities are quite different in terms of discussion topics. However, we also find that even communities from the same super-community differ considerably in the proportion of unacceptable tweets they post.

Mechanistic Insight into Yeast Bloom in a Lactic Acid Bacteria Relaying-Community in the Start of Sourdough Microbiota Evolution.

The spontaneous microbiota of wheat sourdough, often comprising one yeast species and several lactic acid bacteria (LAB) species, evolves over repeated fermentation cycles, which bakers call backslopping. The final product quality largely depends on the microbiota functions, but these fluctuate sometimes during the initial months of fermentation cycles due to microbiota evolution in which three phases of LAB relay occur. In this study, the understanding of yeast-LAB interactions in the start of the evolution of the microbiota was deepened by exploring the timing and trigger interactions when sourdough yeast entered a preestablished LAB-relaying community. Monitoring of 32 cycles of evolution of 6 batches of spontaneous microbiota in wheat sourdoughs revealed that sourdough yeasts affected the LAB community when the 2nd- or 3rd-relaying types of LAB genera emerged. In in vitro pairwise cocultures, all 12 LAB strains containing the 3 LAB-relaying types arrested the growth of a Saccharomyces cerevisiae strain, a frequently found species in sourdoughs, to various extents by sugar-related interactions. These findings suggest competition due to different affinities of each LAB and a S. cerevisiae strain for each sugar. In particular, maltose was the driver of S. cerevisiae growth in all pairwise cocultures. The functional prediction of sugar metabolism in sourdough LAB communities showed a positive correlation between maltose degradation and the yeast population. Our results suggest that maltose-related interactions are key factors that enable yeasts to enter and then settle in the LAB-relaying community during the initial part of evolution of spontaneous sourdough microbiota. IMPORTANCE Unpredictable evolution of spontaneous sourdough microbiota sometimes prevents bakers from making special-quality products because the unstable microbiota causes the product quality to fluctuate. Elucidation of the evolutionary mechanisms of the sourdough community, comprising yeast and lactic acid bacteria (LAB), is fundamental to control fermentation performance. This study investigated the mechanisms by which sourdough yeasts entered and settled in a bacterial community in which a three-phase relay of LAB occurred. Our results showed that all three layers of LAB restricted the cohabiting yeast population by competing for the sugar sources, particularly maltose. During the initial evolution of spontaneous sourdough microbiota, yeasts tended to grow synchronously with the progression of the lactic acid bacterial relay, which was predictably associated with changes in the maltose degradation functions in the bacterial community. Further study of ≥3 species' interactions while considering yeast diversity can uncover additional interaction mechanisms driving the initial evolution of sourdough microbiota.

Evolution of PM2.5 bacterial community structure in Beijing's suburban atmosphere.

Biosafety has become one of the greatest challenges facing humanity. Outbreaks of infectious diseases caused by bacteria and viruses have had a huge impact on public health. In addition, non-severe polluted air quality has gradually become the norm; however, literature on the impacts of bioaerosols under long-term exposure to low concentrations of PM2.5 in China is limited. This study analyzed the evolution of the PM2.5 bacterial community in the Huairou district of Beijing under different pollution conditions. We used high-throughput sequencing to seasonally analyze samples over a year (from July 2018 to May 2019) and winter samples from different years (2015, 2016, 2018, and 2019). The results showed that the bacterial diversity and community composition of PM2.5 were significantly different in different seasons, whereas under different pollution levels, there were no significant differences. During the observation period, the number of bacterial species decreased with the increase in pollution; however, a high proportion of bacteria can exist as core species under different pollution levels for a long time. Furthermore, bacteria can be relatively stable in the local environment during the same season but in different years. Although the relative abundances of different bacteria change differently with the variation in pollution level, there is no statistical difference. Importantly, there was a higher abundance of opportunistic pathogenic bacteria when the air quality index was 0-100 in winter. This study comprehensively revealed the characteristics of the evolution of bacterial communities under different pollution levels and in different years and emphasized the health effects of non-pollution air quality. This study can provide a theoretical basis for establishing a sound environmental microbial monitoring and defense system.

Multiple electron acceptor-mediated sulfur autotrophic denitrification: Nitrogen source competition, long-term performance and microbial community evolution.

Sulfur-driven autotrophic denitrification (SDAD) is feasible for the treatment of low-C/N-ratio and sulfur-laden wastewaters. The nitrite accumulated in SDAD will affect the performance and stability of the system but can be a potential electron acceptor. Thus, single- and multiple-electron acceptor-mediated SDAD systems were investigated. Batch assays revealed that nitrite and nitrate were the preferential options in the SDAD system with single and multiple electron acceptors, respectively. Synchronous nitrogen and sulfur removal was successfully achieved in continuous flow experiments with multiple electron acceptors, and the system could adapt well to high concentrations of sulfide, nitrate and nitrite (i.e., 720, 108 and 64.8 mg L-1, respectively), with the predominant genera shifting from Thiobacillus (48.88%) at the initial stage to unclassified_p_Firmicute (34.24%) and Syner-01 (12.31%) at the last stage. This work provides a fundamental basis for applying and regulating SDAD with multiple electron acceptors for the remediation of nitrogen- and sulfide- laden wastewaters.

Network Structure and Community Evolution Online: Behavioral and Emotional Changes in Response to COVID-19.

Background: The measurement and identification of changes in the social structure in response to an exceptional event like COVID-19 can facilitate a more informed public response to the pandemic and provide fundamental insights on how collective social processes respond to extreme events. Objective: In this study, we built a generalized framework for applying social media data to understand public behavioral and emotional changes in response to COVID-19. Methods: Utilizing a complete dataset of Sina Weibo posts published by users in Wuhan from December 2019 to March 2020, we constructed a time-varying social network of 3.5 million users. In combination with community detection, text analysis, and sentiment analysis, we comprehensively analyzed the evolution of the social network structure, as well as the behavioral and emotional changes across four main stages of Wuhan's experience with the epidemic. Results: The empirical results indicate that almost all network indicators related to the network's size and the frequency of social interactions increased during the outbreak. The number of unique recipients, average degree, and transitivity increased by 24, 23, and 19% during the severe stage than before the outbreak, respectively. Additionally, the similarity of topics discussed on Weibo increased during the local peak of the epidemic. Most people began discussing the epidemic instead of the more varied cultural topics that dominated early conversations. The number of communities focused on COVID-19 increased by nearly 40 percent of the total number of communities. Finally, we find a statistically significant "rebound effect" by exploring the emotional content of the users' posts through paired sample t-test (P = 0.003). Conclusions: Following the evolution of the network and community structure can explain how collective social processes changed during the pandemic. These results can provide data-driven insights into the development of public attention during extreme events.

Does evolution design robust food webs?

Theoretical works that use a dynamical approach to study the ability of ecological communities to resist perturbations are largely based on randomly generated ecosystem structures. By contrast, we ask here whether the evolutionary history of food webs matters for their robustness. Using a community evolution model, we first generate trophic networks by varying the level of energy supply (richness) of the environment in which species adapt and diversify. After placing our simulation outputs in perspective with present-day food webs empirical data, we highlight the complex, structuring role of this environmental condition during the evolutionary setting up of trophic networks. We then assess the robustness of food webs by studying their short-term ecological responses to swift changes in their customary environmental richness. We reveal that the past conditions have a crucial effect on the robustness of current food webs. Moreover, directly focusing on connectance of evolved food webs, it turns out that the most connected ones appear to be the least robust to sharp depletion in the environmental energy supply. Finally, we appraise the 'adaptation' of food webs themselves: generally poor, except in relation to a diversity of flux property.

Toward a dynamical understanding of microbial communities.

The challenge of moving beyond descriptions of microbial community composition to the point where understanding underlying eco-evolutionary dynamics emerges is daunting. While it is tempting to simplify through use of model communities composed of a small number of types, there is a risk that such strategies fail to capture processes that might be specific and intrinsic to complexity of the community itself. Here, we describe approaches that embrace this complexity and show that, in combination with metagenomic strategies, dynamical insight is increasingly possible. Arising from these studies is mounting evidence of rapid eco-evolutionary change among lineages and a sense that processes, particularly those mediated by horizontal gene transfer, not only are integral to system function, but are central to long-term persistence. That such dynamic, systems-level insight is now possible, means that the study and manipulation of microbial communities can move to new levels of inquiry. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Fate of sulfonamide resistance genes during sludge anaerobic fermentation: Roles of sludge components and fermentation pHs.

This study assessed potential effects of two neglected factors (sludge components and pH values) on the fate of sulfonamide (sul) resistance genes during sludge anaerobic fermentation. It was found that sludge with different contents of protein, carbohydrate and humic acid caused no significant changes in the abundances of sul genes. Nevertheless, sul genes were sensitive to pHs (4-10), and the maximum attenuations (0.8-1.1 log unit) were obtained at pH 10. Mechanism exploration indicated that pHs drove the community evolution of sulfonamide resistant bacteria (SRB), most of which were affiliated to the pH-enriched phyla but not the pH-enriched dominant genera. In addition, the relative abundances of SRB were decreased under both acidic and alkaline conditions. Furthermore, the abundances of intI 1 as well as the sul-carrying abilities of plasmid and extracellular DNA were all reduced at test pHs, indicating that the potential of horizontal gene transfer among bacteria was restricted.