16S rRNA Gene Copy Numbers Research Articles

Seasonal changes in soil biofilm microbial communities

Biofilm and planktonic prokaryotic communities were studied using a glass fibre filter as trapping material immersed in field soil at different times of the year (January, April, July, September) and incubated there for different periods (3, 6, 9, 12 months). The composition of biofilm and planktonic communities fluctuated over time, likely shaped by succession processes and varying environmental factors. This highlights soil biofilms as dynamic structures whose microbial community differs from that of soil plankton. Additionally, quantification of the biofilm-to-plankton 16S rRNA gene copy number ratio indicated that soil prokaryotes occur mainly as biofilm components.

Deep learning for predicting 16S rRNA gene copy number

Culture-independent 16S rRNA gene metabarcoding is a commonly used method for microbiome profiling. To achieve more quantitative cell fraction estimates, it is important to account for the 16S rRNA gene copy number (hereafter 16S GCN) of different community members. Currently, there are several bioinformatic tools available to estimate the 16S GCN values, either based on taxonomy assignment or phylogeny. Here we present a novel approach ANNA16, Artificial Neural Network Approximator for 16S rRNA gene copy number, a deep learning-based method that estimates the 16S GCN values directly from the 16S gene sequence strings. Based on 27,579 16S rRNA gene sequences and gene copy number data from the rrnDB database, we show that ANNA16 outperforms the commonly used 16S GCN prediction algorithms. Interestingly, Shapley Additive exPlanations (SHAP) shows that ANNA16 can identify unexpected informative positions in 16S rRNA gene sequences without any prior phylogenetic knowledge, which suggests potential applications beyond 16S GCN prediction.

Sustainable control of Microcystis aeruginosa, a harmful cyanobacterium, using Selaginella tamariscina extracts

Eco-friendly reagents derived from plants represent a promising strategy to mitigate the occurrence of toxic cyanobacterial blooms. The use of an amentoflavone-containing Selaginella tamariscina extract (STE) markedly decreased the number of Microcystis aeruginosa cells, thus demonstrating significant anti-cyanobacterial activity. In particular, the Microcystis-killing fraction obtained from pulverized S. tamariscina using hot-water-based extraction at temperatures of 40 °C induced cell disruption in both axenic and xenic M. aeruginosa. Liquid chromatographic analysis was also conducted to measure the concentration of amentoflavone in the STE, thus supporting the potential M. aeruginosa-specific killing effects of STE. Bacterial community analysis revealed that STE treatment led to a reduction in the relative abundance of Microcystis species while also increasing the 16S rRNA gene copy number in both xenic M. aeruginosa NIBR18 and cyanobacterial bloom samples isolated from a freshwater environment. Subsequent testing on bacteria, cyanobacteria, and algae isolated from freshwater revealed that STE was not toxic for other taxa. Furthermore, ecotoxicology assessment involving Aliivibrio fischeri, Daphnia magna, and Danio rerio found that high STE doses immobilized D. magna but did not impact the other organisms, while there was no change in the water quality. Overall, due to its effective Microcystis-killing capability and low ecotoxicity, aqueous STE represents a promising practical alternative for the management of Microcystis blooms.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling.

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

Cover crop monocultures and mixtures enhance bacterial abundance and functionality in the maize root zone.

Cover cropping is an effective method to protect agricultural soils from erosion, promote nutrient and moisture retention, encourage beneficial microbial activity, and maintain soil structure. Re-utilization of winter cover crop root channels by maize roots during summer allows the cash crop to extract resources from distal regions in the soil horizon. In this study, we investigated how cover cropping during winter followed by maize (Zea mays L.) during summer affects the spatiotemporal composition and function of the bacterial communities in the maize rhizosphere and surrounding soil samples using quantitative polymerase chain reaction (PCR), 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing, and metaproteomics. We found that the bacterial community differed significantly among cover crop species, soil depths, and maize growth stages. Bacterial abundance increased in reused root channels, and it continued to increase as cover crop diversity changed from monocultures to mixtures. Mixing Fabaceae with Brassicaceae or Poaceae enhanced the overall contributions of several steps of the bacterial carbon and nitrogen cycles, especially glycolysis and the pentose phosphate pathway. The deeper root channels of Fabaceae and Brassicaceae as compared to Poaceae corresponded to higher bacterial 16S rRNA gene copy numbers and improved community presence in the subsoil regimes, likely due to the increased availability of root exudates secreted by maize roots. In conclusion, root channel reuse improved the expression of metabolic pathways of the carbon and nitrogen cycles and the bacterial communities, which is beneficial to the soil and to the growing crops.

Microeukaryotic plankton evolutionary constraints in a subtropical river explained by environment and bacteria along differing taxonomic resolutions.

Microeukaryotic plankton communities are keystone components for keeping aquatic primary productivity. Currently, variations in microeukaryotic plankton diversity have often been explained by local ecological factors but not by evolutionary constraints. We used amplicon sequencing of 100 water samples across five years to investigate the ecological preferences of the microeukaryotic plankton community in a subtropical riverine ecosystem. We found that microeukaryotic plankton diversity was less associated with bacterial abundance (16S rRNA gene copy number) than bacterial diversity. Further, environmental effects exhibited a larger influence on microeukaryotic plankton community composition than bacterial community composition, especially at fine taxonomic levels. The evolutionary constraints of microeukaryotic plankton community increased with decreasing taxonomic resolution (from 97% to 91% similarity levels), but not significant change from 85% to 70% similarity levels. However, compared with the bacterial community, the evolutionary constraints were shown to be more affected by environmental variables. This study illustrated possible controlling environmental and bacterial drivers of microeukaryotic diversity and community assembly in a subtropical river, thereby indirectly reflecting on the quality status of the water environment by providing new clues on the microeukaryotic community assembly.

Hyperarid soil microbial community response to simulated rainfall.

The exceptionally long and protracted aridity in the Atacama Desert (AD), Chile, provides an extreme, terrestrial ecosystem that is ideal for studying microbial community dynamics under hyperarid conditions. Our aim was to characterize the temporal response of hyperarid soil AD microbial communities to ex situ simulated rainfall (5% g water/g dry soil for 4 weeks) without nutrient amendment. We conducted replicated microcosm experiments with surface soils from two previously well-characterized AD hyperarid locations near Yungay at 1242 and 1609 masl (YUN1242 and YUN1609) with distinct microbial community compositions and average soil relative humidity levels of 21 and 17%, respectively. The bacterial and archaeal response to soil wetting was evaluated by 16S rRNA gene qPCR, and amplicon sequencing. Initial YUN1242 bacterial and archaeal 16S rRNA gene copy numbers were significantly higher than for YUN1609. Over the next 4 weeks, qPCR results showed significant increases in viable bacterial abundance, whereas archaeal abundance decreased. Both communities were dominated by 10 prokaryotic phyla (Actinobacteriota, Proteobacteria, Chloroflexota, Gemmatimonadota, Firmicutes, Bacteroidota, Planctomycetota, Nitrospirota, Cyanobacteriota, and Crenarchaeota) but there were significant site differences in the relative abundances of Gemmatimonadota and Chloroflexota, and specific actinobacterial orders. The response to simulated rainfall was distinct for the two communities. The actinobacterial taxa in the YUN1242 community showed rapid changes while the same taxa in the YUN1609 community remained relatively stable until day 30. Analysis of inferred function of the YUN1242 microbiome response implied an increase in the relative abundance of known spore-forming taxa with the capacity for mixotrophy at the expense of more oligotrophic taxa, whereas the YUN1609 community retained a stable profile of oligotrophic, facultative chemolithoautotrophic and mixotrophic taxa. These results indicate that bacterial communities in extreme hyperarid soils have the capacity for growth in response to simulated rainfall; however, historic variations in long-term hyperaridity exposure produce communities with distinct putative metabolic capacities.

Validation of 16S rRNA gene sequencing and metagenomics for evaluating microbial immigration in a methanogenic bioreactor.

To quantitatively evaluate the impact of microbial immigration from an upstream community on the microbial assembly of a downstream community, an ecological genomics (ecogenomics)-based mass balance (EGMB) model coupled with 16S rRNA gene sequencing was previously developed. In this study, a mock community was used to further validate the EGMB models and demonstrate the feasibility of using metagenome-based EGMB model to reveal both microbial activity and function. The mock community consisting of Aeromonas, Escherichia, and Pseudomonas was fed into a lab-scale methanogenic bioreactor together with dissolved organic substrate. Using qPCR, 16S rRNA gene, 16S rRNA gene copy number normalization (GCN), and metagenome, results showed highly comparable community profiles in the feed. In the bioreactor, Aeromonas and Pseudomonas exhibited negative growth rates throughout the experiment by all approaches. Escherichia's growth rate was negative by most biomarkers but was slightly positive by 16S rRNA gene. Still, all approaches showed a decreasing trend toward negative in the growth rate of Escherichia as reactor operation time increased. Uncultivated populations of phyla Desulfobacterota, Chloroflexi, Actinobacteriota, and Spirochaetota were observed to increase in abundance, suggesting their contribution in degrading the feed biomass. Based on metabolic reconstruction of metagenomes, these populations possessed functions of hydrolysis, fermentation, fatty acid degradation, or acetate oxidation. Overall results supported the application of both 16S rRNA gene- and metagenome-based EGMB models to measure the growth rate of microbes in the bioreactor, and the latter had advantage in providing insights into the microbial functions of uncultivated populations.

The Effects of Long-Term Application of Stabilized and Coated Urea on Soil Chemical Properties, Microbial Community Structure, and Functional Genes in Paddy Fields

The addition of fertilizers is indispensable in agricultural production, and currently, there is a wide variety of new types of fertilizers available. For example, commonly used are stabilized fertilizers with inhibitors and coated slow-release fertilizers, among others. However, the long-term effects of these fertilizers, when applied continuously are still uncertain. This study will provide scientific and theoretical support for the development and promotion of these fertilizers. A 16-year paddy field with brown soil treated with different urease and nitrification inhibitors, sulfur-coated urea (SCU), and resin-coated urea (PCU) was studied. The study showed that long-term use of conventional urea nitrogen fertilizer resulted in a significant reduction in soil total phosphorus (TP). Long-term application of NBPT and conventional urea significantly increased soil organic matter (SOM). Moreover, except for HQ and NBPT+DMPP, the prolonged application of new urea fertilizers also significantly enhanced soil total potassium (TK). Application of SCU fertilizer in brown soil type paddy fields resulted in a significant decrease in soil pH over time. However, changes in pH had no effect on the abundance of ammonia-oxidizing bacteria (AOB), as AOB was mainly affected by soil-available N. DMPP, HQ+DCD, NBPT+DMPP, SCU, and PCU significantly reduced the 16S rRNA gene copy number of soil bacteria, with the greatest effect of coated urea fertilizer (SCU and PCU). Long-term application of stable urea fertilizer with HQ significantly reduced the bacterial community in paddy soil. Conversely, HQ+DCD-stabilizede urea fertilizer significantly increased the population structure and abundance of Basidiomycota fungi while decreasing the population structure and abundance of Rozellomycota fungi. DMPP-stabilized urea fertilizer notably increased the population structure and abundance of Ascomycota fungi while decreasing the population structure and abundance of Rozellomycota and Chytridiomycota fungi. Furthermore, HQ-stabilized urea fertilizer significantly reduced the population structure and abundance of Chytridiomycota fungi.

Assembly and co-occurrence patterns of rhizosphere bacterial communities are closely linked to soil fertility during continuous cropping of cut chrysanthemum (Chrysanthemum morifolium Ramat).

Continuous cropping is known to have profound effects on the soil microbial community in different planting systems. However, we lack an understanding of how different years of continuous cropping affects rhizosphere soil bacterial community co-occurrence pattern and assembly processes in the cut chrysanthemum (Chrysanthemum morifolium Ramat.) field. We collected the soils from cut chrysanthemum rhizospheres with planting for 1 year (PY1) and continuous cropping for 6 years (CY6) and 12 years (CY12). Real-time quantitative PCR and flow cytometry (FCM) techniques were used to test the 16S rRNA gene copy number and bacterial cell count, respectively. The bacterial community structure was analysed by using high-throughput sequencing technology. The CY12 had a significantly decreased soil fertility index and rhizosphere bacterial living cell counts and gene copy numbers compared to CY6 and PY1 (P <0.05). The rhizosphere bacterial community dissimilarity increased as the continuous cropping years increased. Three main ecological clusters (modules #1, #2, and #3) were observed in the bacterial co-occurrence network across all samples, and only the relative abundance of module #1 (enriched in the CY12) was significantly correlated with soil fertility (P <0.05). Moreover, the rhizosphere bacterial community assembly was primarily governed by the deterministic process under 12 years of continuous cropping. Soil fertility decline correlates with ecological network modularization and the deterministic assembly process of the rhizosphere bacterial community of cut chrysanthemum during continuous cropping.

Different in root exudates and rhizosphere microorganisms effect on nitrogen removal between three emergent aquatic plants in surface flow constructed wetlands

Swine wastewater contains high concentration of nitrogen (N), causing pollution of surrounding water bodies. Constructed wetlands (CWs) are considered as an effective ecological treatment measure to remove nitrogen. Some emergent aquatic plants could tolerate high ammonia, and play a crucial part in CWs to treat high concentration N wastewater. However, the mechanism of root exudates and rhizosphere microorganisms of emergent plants on nitrogen removal is still unclear. Effects of organic and amino acids on rhizosphere N cycle microorganisms and environmental factors across three emergent plants were investigated in this study. The highest TN removal efficiency were 81.20% in surface flow constructed wetlands (SFCWs) plant with Pontederia cordata. The root exudation rates results showed that organic and amino acids were higher in 56 d than that in 0 d in SFCWs plants with Iris pseudacorus and P. cordata. The highest ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) gene copy numbers were found in I. pseudacorus rhizosphere soil, while the highest nirS, nirK, hzsB and 16S rRNA gene copy numbers were detected in P. cordata rhizosphere soil. Regression analysis results demonstrated that organic and amino acids exudation rates were positive related to rhizosphere microorganisms. These results indicated that organic and amino acids secretion could stimulate growth of emergent plants rhizosphere microorganisms in SFCWs for swine wastewater treatment. In addition, the EC, TN, NH4+-N and NO3−-N were negatively correlated with organic and amino acids exudation rates, and abundances of rhizosphere microorganisms via Pearson correlation analysis. These results imply that organic and amino acids, and rhizosphere microorganisms synergically affected on the nitrogen removal in SFCWs.

A novel Gardnerella, Prevotella, and Lactobacillus standard that improves accuracy in quantifying bacterial burden in vaginal microbial communities.

Bacterial vaginosis (BV) is the most common vaginal dysbiosis. In this condition, a polymicrobial biofilm develops on vaginal epithelial cells. Accurately quantifying the bacterial burden of the BV biofilm is necessary to further our understanding of BV pathogenesis. Historically, the standard for calculating total bacterial burden of the BV biofilm has been based on quantifying Escherichia coli 16S rRNA gene copy number. However, E. coli is improper for measuring the bacterial burden of this unique micro-environment. Here, we propose a novel qPCR standard to quantify bacterial burden in vaginal microbial communities, from an optimal state to a mature BV biofilm. These standards consist of different combinations of vaginal bacteria including three common BV-associated bacteria (BVAB) Gardnerella spp. (G), Prevotella spp. (P), and Fannyhessea spp. (F) and commensal Lactobacillus spp. (L) using the 16S rRNA gene (G:P:F:L, G:P:F, G:P:L and 1G:9L). We compared these standards to the traditional E. coli (E) reference standard using known quantities of mock vaginal communities and 16 vaginal samples from women. The E standard significantly underestimated the copy numbers of the mock communities, and this underestimation was significantly greater at lower copy numbers of these communities. The G:P:L standard was the most accurate across all mock communities and when compared to other mixed vaginal standards. Mixed vaginal standards were further validated with vaginal samples. This new G:P:L standard can be used in BV pathogenesis research to enhance reproducibility and reliability in quantitative measurements of BVAB, spanning from the optimal to non-optimal (including BV) vaginal microbiota.

Accounting for 16S rRNA copy number prediction uncertainty and its implications in bacterial diversity analyses

16S rRNA gene copy number (16S GCN) varies among bacterial species and this variation introduces potential biases to microbial diversity analyses using 16S rRNA read counts. To correct the biases, methods have been developed to predict 16S GCN. A recent study suggests that the prediction uncertainty can be so great that copy number correction is not justified in practice. Here we develop RasperGade16S, a novel method and software to better model and capture the inherent uncertainty in 16S GCN prediction. RasperGade16S implements a maximum likelihood framework of pulsed evolution model and explicitly accounts for intraspecific GCN variation and heterogeneous GCN evolution rates among species. Using cross-validation, we show that our method provides robust confidence estimates for the GCN predictions and outperforms other methods in both precision and recall. We have predicted GCN for 592605 OTUs in the SILVA database and tested 113842 bacterial communities that represent an exhaustive and diverse list of engineered and natural environments. We found that the prediction uncertainty is small enough for 99% of the communities that 16S GCN correction should improve their compositional and functional profiles estimated using 16S rRNA reads. On the other hand, we found that GCN variation has limited impacts on beta-diversity analyses such as PCoA, NMDS, PERMANOVA and random-forest test.

Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial

The gut microbiome is emerging as a key modulator of human energy balance. Prior studies in humans lacked the environmental and dietary controls and precision required to quantitatively evaluate the contributions of the gut microbiome. Using a Microbiome Enhancer Diet (MBD) designed to deliver more dietary substrates to the colon and therefore modulate the gut microbiome, we quantified microbial and host contributions to human energy balance in a controlled feeding study with a randomized crossover design in young, healthy, weight stable males and females (NCT02939703). In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal and urinary). The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions [Control, Western Diet (WD) vs. MBD]. The secondary endpoints were enteroendocrine hormones, hunger/satiety, and food intake. Here we show that, compared to the WD, the MBD leads to an additional 116 ± 56 kcals (P < 0.0001) lost in feces daily and thus, lower metabolizable energy for the host (89.5 ± 0.73%; range 84.2-96.1% on the MBD vs. 95.4 ± 0.21%; range 94.1-97.0% on the WD; P < 0.0001) without changes in energy expenditure, hunger/satiety or food intake (P > 0.05). Microbial 16S rRNA gene copy number (a surrogate of biomass) increases (P < 0.0001), beta-diversity changes (whole genome shotgun sequencing; P = 0.02), and fermentation products increase (P < 0.01) on an MBD as compared to a WD along with significant changes in the host enteroendocrine system (P < 0.0001). The substantial interindividual variability in metabolizable energy on the MBD is explained in part by fecal SCFAs and biomass. Our results reveal the complex host-diet-microbiome interplay that modulates energy balance.

Diversity and distribution of archaeal and bacterial nitrifiers in deep oceans

Thaumarchaeota and Nitrospinae are the main drivers of nitrification in global oceans. However, their vertical and horizontal distributions throughout seawater columns remain unclear. Here, we conducted high-throughput sequencing of 16S rRNA genes and quantified putative nitrifying genes of microbial communities within seawater samples from the full depths of the Central Indian Ocean and the Western Pacific Ocean waters. Thaumarchaeota and Nitrospinae exhibited clear compositional distinctions between the two oceanic regions. Vertical variation in their assemblages was also apparent among all samples and within regions. However, their core operational taxonomic units (OTUs) were shared between the two regions and belonged to diverse phylogenetic clades that coincided with specific vertical niches. Further, their relative abundances were significantly and positively associated with Acidobacteriota, SAR324, Chloroflexi, and SAR406 phyla across and within regions, suggesting potential metabolic interactions. Regardless of oceanic regions, the maximal copy numbers of Thaumarchaeotal 16S rRNA and ammonia monooxygenase subunit A genes were both observed at 150–200 m depth, approximately overlapping with the primary nitrite maximum (PNM, 150 m), just below the deep chlorophyll a maximum (DCM, 125 m and 150 m); the maximal Nitrospina 16S rRNA gene copy numbers were located deeper (500 m), where nitrate concentrations had already increased.

Response of microbial communities to nutrient removal in coastal sediment by using ecological concrete.

Ecological concrete (eco-concrete) is a kind of environment-friendly material with porous characteristics. In this study, the eco-concrete was used to remove the total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC) in marine coastal sediment. The bacterial communities in sediment and on eco-concrete surface were also investigated by using high-throughput sequencing and quantitative PCR of 16S rRNA gene. We found that the mean removal efficiencies of TN, TP, and TOC in treatment group were 8.3%, 8.4%, and 12.3% after 28days. The bacterial community composition in the treatment group was significantly different from that in the control group on day 28. In addition, the bacterial community composition on eco-concrete surface was slightly different from that in sediment, and the copy numbers of 16S rRNA gene were higher on eco-concrete surface than in sediment. The types of eco-concrete aggregates (gravel, pebble, and zeolite) also had effects on the bacterial community composition and 16S rRNA gene copy numbers. Furthermore, we found the abundant genus Sulfurovum increased significantly on eco-concrete surface in the treatment group after 28days. Bacteria belonging to this genus were found having denitrification ability and were commonly detected in bioreactors for nitrate removal. Overall, our study expands the application scopes of eco-concrete and suggests that the bacterial communities in eco-concrete can potentially enhance the removal efficiency of nutrients in coastal sediment.

Microbial Diversity Biased Estimation Caused by Intragenomic Heterogeneity and Interspecific Conservation of 16S rRNA Genes.

The 16S rRNA gene has been extensively used as a molecular marker to explore evolutionary relationships and profile microbial composition throughout various environments. Despite its convenience and prevalence, limitations are inevitable. Variable copy numbers, intragenomic heterogeneity, and low taxonomic resolution have caused biases in estimating microbial diversity. Here, analysis of 24,248 complete prokaryotic genomes indicated that the 16S rRNA gene copy number ranged from 1 to 37 in bacteria and 1 to 5 in archaea, and intragenomic heterogeneity was observed in 60% of prokaryotic genomes, most of which were below 1%. The overestimation of microbial diversity caused by intragenomic variation and the underestimation introduced by interspecific conservation were calculated when using full-length or partial 16S rRNA genes. Results showed that, at the 100% threshold, microbial diversity could be overestimated by as much as 156.5% when using the full-length gene. The V4 to V5 region-based analyses introduced the lowest overestimation rate (4.4%) but exhibited slightly lower species resolution than other variable regions under the 97% threshold. For different variable regions, appropriate thresholds rather than the canonical value 97% were proposed for minimizing the risk of splitting a single genome into multiple clusters and lumping together different species into the same cluster. This study has not only updated the 16S rRNA gene copy number and intragenomic variation information for the currently available prokaryotic genomes, but also elucidated the biases in estimating prokaryotic diversity with quantitative data, providing references for choosing amplified regions and clustering thresholds in microbial community surveys. IMPORTANCE Microbial diversity is typically analyzed using marker gene-based methods, of which 16S rRNA gene sequencing is the most widely used approach. However, obtaining an accurate estimation of microbial diversity remains a challenge, due to the intragenomic variation and low taxonomic resolution of 16S rRNA genes. Comprehensive examination of the bias in estimating such prokaryotic diversity using 16S rRNA genes within ever-increasing prokaryotic genomes highlights the importance of the choice of sequencing regions and clustering thresholds based on the specific research objectives.

Ammonia-Oxidizing Bacteria Maintain Abundance but Lower amoA-Gene Expression during Cold Temperature Nitrification Failure in a Full-Scale Municipal Wastewater Treatment Plant.

In this study, we explore the relationship between community structure and transcriptional activity of ammonia-oxidizing bacteria during cold temperature nitrification failure in three parallel full-scale sequencing batch reactors (SBRs) treating municipal wastewater. In the three reactors, ammonia concentrations increased with declines in wastewater temperature below 15°C. We quantified and sequenced 16S rRNA and ammonia monooxygenase (amoA) gene fragments in DNA and RNA extracts from activated sludge samples collected from the SBRs during the warmer seasons (summer and fall) and when water temperatures were below 15°C (winter and spring). Taxonomic community composition of amoA genes and transcripts did not vary much between the warmer and colder seasons. However, we observed significant differences in amoA transcript copy numbers between fall (highest) and spring (lowest). Ammonia-oxidizing bacteria of the genus Nitrosomonas sp. could maintain their population abundance despite lowering their amoA gene expression during winter and spring. In spite of relatively low population abundance, an amoA amplicon sequence variant (ASV) cluster identified as most similar to the amoA gene of Nitrosospira briensis showed the highest amoA transcript-to-gene ratio throughout all four seasons, indicating that some nitrifiers remain active at wastewater temperatures below 15°C. Our results show that 16S rRNA and amoA gene copy numbers are limited predictors of cell activity. To optimize function and performance of mixed community bioprocesses, we need to collect high-resolution quantitative transcriptomic and potentially proteomic data to resolve the response of individual species to changes in environmental parameters in engineered systems. IMPORTANCE The diverse microbial community of activated sludge used in biological treatment systems exhibits dynamic seasonal shifts in community composition and activity. Many wastewater treatment plants in temperate/continental climates experience seasonal cold temperature nitrification failure. "Seasonal nitrification failure" is the discharge of elevated concentrations of ammonia (greater than 4 mg/liter) with treated wastewater during the winter (influent wastewater temperatures below 13°C). This study aims at expanding our understanding of how ammonia-oxidizing bacteria in activated sludge change in activity and growth across seasons. We quantified the ammonia monooxygenase (amoA) gene and transcript copy numbers using real-time PCR and sequenced the amoA amplicons to reveal community structure and activity changes of nitrifying microbial populations during seasonal nitrification failure in three full-scale sequencing batch reactors (SRBs) treating municipal wastewater. Relevant findings presented in this study contribute to explain seasonal nitrification performance variability in SRBs.

The influence of ZnO nanoparticles on horizontal transfer of resistance genes in lab and soil conditions

Antibiotic resistance is a severe problem that threatens the achievements of modern medicine. Metallic nanoparticles may promote the horizontal transfer of resistance genes due to their toxicity to bacterial cells and metal-induced co-selection mechanisms. In this study, we investigated the toxicity of ZnO nanoparticles to E. coli DH5α laboratory strain and the abundance of soil microbial community. Moreover, the influence of ZnO nanoparticles on resistance gene transfer in laboratory and soil conditions was evaluated. ZnO nanoparticles at concentrations up to 10 mg L−1 reduced the survival of E. coli cells by 14.6% and increased the transformation frequency by almost 1.8 fold. In soil, ZnO nanoparticles at a concentration of 1000 mg kg−1 affected the total abundance of bacteria, causing a decrease in the 16S rRNA gene copy number. We did not detect the presence of 11 target antibiotic resistance genes (sul1, sul2, imp2, imp5, blaCTX-M, ermB, mefA, strB, aadA1, tetA1, tetB), which confer resistance to five classes of antibiotics in soil treated with ZnO nanoparticles. No elevated conjugation frequency was observed in soil microbial communities treated with ZnO nanoparticles. However, the increase in czcA gene copies indicates the spread of genetic elements harbouring metal resistance. The data shows that metallic nanoparticles promote the spread of antibiotic and metal resistance genes. The broad implication of the present research is that the inevitable nanoparticles environmental pollution may lead to the further dissemination of antibiotic resistance and profoundly influence public health.

Evaluation and optimization of lysis method for microbial DNA extraction from epiphytic phyllosphere samples

Analysis of microbial communities in the epiphytic phyllosphere can be challenging, especially when applying sequencing-based techniques, owing to the interference of plant-derived biomolecules such as nucleic acids. A review of recent studies on the epiphytic microbiome revealed that both mechanical and enzymatic lysis methods are widely used. Here, we evaluated the effects of the two lysis methods on DNA extraction yield, purity, integrity, and microbial 16S rRNA gene copy number per ng of template genomic DNA under different extraction conditions. Furthermore, the effect on bacterial community composition, diversity, and reproducibility was examined using 16S rRNA gene amplicon sequencing. The enzymatic lysis method yielded one to two orders of magnitude more DNA, but the DNA quality was suboptimal. Conversely, the samples prepared using the mechanical method showed high DNA purity albeit lower yield. Unexpectedly, mechanical lysis showed a higher DNA integrity number (DIN) than enzymatic lysis. The 16S rRNA amplicon sequencing results demonstrated that the samples prepared via mechanical disruption exhibited reproducibly similar microbial community compositions regardless of the extraction conditions. In contrast, the enzymatic lysis method resulted in inconsistent taxonomic compositions under different extraction conditions. This study demonstrates that mechanical DNA disruption is more suitable for epiphytic phyllosphere samples than enzymatic disruption.