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opencc-by-4.0Mar 2022View details →

Bacterial community composition of bulk soil from date palm (Phoenix dactylifera) farm depend on irrigation water salinity

Non-saline and saline ground water irrigation is extensively used in the arid regions of United Arab Emirates (UAE) for date palm (Phoenix dactylifera) cultivation without knowing its effect on bulk soil bacterial communities. Bulk soil acts as a supply base for microbes and nutrients that are accessed by date palm roots. We collected soil samples from date farms across UAE and performed V3-V4 16s rRNA metabarcoding analysis to understand how bulk soil bacterial diversity and communities respond to irrigation water sources (non-saline and saline groundwater irrigation). There was no significant variation in bulk bacterial diversity (Shannon diversity, richness as well as evenness). But bulk bacterial communities differed between irrigation water sources and irrigation water electrical conductivity was the significant factor that explained a part of community variation. Out of total 5089 OTUs, saline bulk soil harbored only 21.3% of total OTUs compared to 31.5% OTUs in non-saline bulk soil, while 47.15% OTUs shared between both types of irrigation. Proteobacteria abundance was higher in saline bulk soil, while Actinobacteriota abundance was enhanced in non-saline bulk soil. Similar selection was observed at genus level, wherein saline bulk soil showed increase in abundance of Subgroup_10, Nitrospira and Mycobacterium, whereas Microvirga, Ammoniphilus, Nitrospira and Lysinibacillus were elevated in non-saline bulk soil. Saline (Novibacillus and Bauldea) and non-saline bulk soil (Microvirga, Marmoricola, Domibacillus, Oceanobacillus, Bhargavaea and Solirubrobacter) showed significant selection of indicator taxa (P < 0.05). This indicate that bacterial communities colonizing bulk soil differ depending on irrigation water source and it is affected by irrigation water EC.

opencc-zeroOct 2022View details →

Different facets of bacterial and fungal communities drive soil multifunctionality in grasslands spanning a 3,500 km transect

1. Soil microbial communities are essential in regulating ecosystem functions and services. However, the importance of bacterial and fungal communities as predictors of multiple soil functions (i.e., soil multifunctionality) in grassland ecosystems has not been studied systematically. 2. Here, we measured soil microbial diversity, community composition, biomass, and multiple soil functions of 41 sites in five grassland ecosystems spanning a 3,500 km northeast–southwest transect. The random forest algorithm was adopted to determine the importance of geographical location, climatic, altitude, edaphic, plant, and microbial predictors in driving a proxy of soil multifunctionality (seven soil functions in this study). Moreover, structural equation models (SEMs) were employed to examine the direct and indirect effects of those predictors on soil multifunctionality. 3. Our results demonstrated that soil multifunctionality was positively driven by soil fungal diversity but not by bacterial diversity. Fungal phylogenetic diversity (presence of different evolutionary lineages) showed stronger positive relationships with soil multifunctionality than taxonomic diversity (richness of species). Dominant bacterial taxa, particularly of phyla Actinobacteria and Proteobacteria, were positively associated with soil multifunctionality, while none of the fungal taxa were found to regulate soil multifunctionality. Furthermore, both fungal and bacterial biomass had significant effects on soil multifunctionality, while the effect of microbial biomass was weaker than that of fungal diversity and bacterial taxa. Importantly, the direct positive effects of soil fungal diversity, dominant bacterial taxa, and fungal and bacterial biomass were maintained after accounting for multiple predictors in grassland ecosystems. 4. This study provided strong empirical evidence that soil multifunctionality was driven by different facets of the bacterial and fungal communities in the grassland ecosystems. Our results also highlighted that any loss of fungal diversity, dominant bacterial taxa and microbial biomass might reduce soil multifunctionality, exacerbating ecosystem functions and services such as soil fertility, primary production, and climate mitigation in grassland ecosystems.

opencc-by-4.0Apr 2024View details →

Bacterial Community Weighted rrn Operon Copy Numbers and Enzyme Activity in Costa Rica and Alaska Soils.

Datasets of bacterial community weighted rrn operon copy number and enzyme activity in Alaska and Costa Rica soils. The Alaska soils were collected from across four elevational terraces in a tidal wetland on the western coast. The Costa Rica soils were collected from plots subjected to precipitation manipulation treatments in La Selva Biological Research Station.  The variable descriptions for the Alaska dataset are as follows: simple_id: an identifier variable. id: an identifier variable that includes terrace identity. transect_id: a variable that identifies collection transect location. BG_umol_g_h: the activity rate of beta-glucosiadase in micromoles per gram soil per hour. NAG_umol_g_h: the activity rate of N-acetyl-glucosaminidase in micromoles per gram soil per hour. LAP_umol_g_h: activity rate of leucine-aminopeptidase in micromoles per grams soil per hour. AP_umol_g_h: the activity rate of acid phosphatase in micromoles per gram soil per hour. BG_g_C: the activity rate of beta-glucosiadase in micromoles per gram soil carbon per hour. NAG-g_N: activity rate of N-acetyl-glucosaminidase in micromoles per gram soil nitrogen per hour. LAP_g_N: activity rate of leucine-aminopeptidase in micromoles per gram soil nitrogen per hour. AP_mg_P: activity rate of acid-phosphatase in micromoles per gram soil phosphorus per hour. P_mg_kg: soil phosphorus concentration in milligrams phosphorus per kilogram soil. K_mg_kg: soil potassium concentration in milligrams potassium per kilogram soil. C_pct: soil carbon concentration in percent. N_pct: soil nitrogen concentration in percent. pH: soil pH. cn_ratio: the carbon-to-nitrogen ratio of soil. cp_ratio: the carbon-to-phosphorus ratio of soil. np_ratio: the nitrogen to phosphorus ratio of soil. weighted_copy_number: the bacterial community weighted rrn operon copy number. The variable descriptions for the Costa Rica dataset are as follows: ID: a variable that identifies the soil core collected. Plot: a variable that identifies the experimental plot from which soils were collected. Precip: a variable that describes the precipitation manipulation treatment applied. Core: a variable that identifies whether soil cores were enclosed in mesh or not. Moisture: the soil moisture of the collected core in grams water per grams dry soil. weighted copy_number: the bacterial community weighted rrn operon copy number. AP: activity rate of acid-phosphatase in micromoles per gram soil  per hour. BG: the activity rate of beta-glucosiadase in micromoles per gram soil per hour. Also included are files of the code used to analyze the data in the R Statistical Computing Environment.

opencc-by-4.0Jul 2018View details →

Data from: Rhizosphere bacterial community composition depends on plant species identity and soil legacy effects

This record contains supplementary information for the article "Rhizosphere bacterial community composition depends on plant diversity legacy in soil and plant species identity". Supplemental Table S1. The table contains the annotation for all the samples sequenced and analyzed. Supplemental Table S2. The table contains all primer sequences used in the study. Supplemental Table S3. The zip-file contains a table with the taxonomic annotation of the operational taxonomic units (OTUs) identified in the study. Supplemental Table S4.  The zip-file contains a table with sequence counts of the operational taxonomic units (OTUs) identified in the study. Supplemental Table S5. The workbook contains a sheet with the number of operational taxonomic units (OTUs) exhibiting differential abundance in any of the contrasts tested in this study. Note that “down/up” indicates whether the OTU was less (“down”) or more (“up”) abundant in the first group of the contrast. For example, given the contrast “PH_mix_vs_mon_”, “down” corresponds to higher abundance in the pots from the monoculture plant history. Conversely, “up” refers to higher abundance in the pots from the mixed culture plant history. In addition, the workbook contains one sheet per contrast with the logBaseMean (log2 of the average normalized abundance across all samples), the logFC (log2 of the fold-change), the P-value, and the adjusted P-value (FDR). Only OTUs with a P-value <= 0.05 or an adjusted P-value (FDR) <= 0.1 are given. Supplemental Table S6. The table contains the number of bacterial OTUs annotated with a given bacterial phylum. Supplemental Table S7. The table contains all phyla tested for enrichment/depletion in the set of OTUs with an increased abundance in monoculture and mixed culture soils respectively. “Total counts (all OTUs)” corresponds to the total number of all OTUs annotated with a given phyla (reference set). “Observed” corresponds to the number of OTUs annotated with a given phyla in the set OTUs with increased abundance in monoculture/mixed culture soils (test set). "Expected" gives the number of OTUs which would be expected to be annotated with a given phyla if the test set were randomly sampled from the reference set. Supplemental File S1. The zip-file contains a fasta file with the 10'205 OTU sequences identified in the study.

opencc-zeroMar 2023View details →

Data for: Heavy metal pollution impacts soil bacterial community structure and antimicrobial resistance at the Birmingham 35th Avenue Superfund Site

The data in this archive are the results of a study on the impact of heavy metals (HMs) on the soil microbiota of an urban Superfund site in Alabama. HMs are known to modify bacterial communities both in the laboratory and in situ. Consequently, soils in HM-contaminated sites such as the U.S. Environmental Protection Agency (EPA) Superfund sites are predicted to have altered ecosystem functioning, with potential ramifications for the health of organisms, including humans, that live nearby. Further, several studies have shown that heavy metal-resistant (HMR) bacteria often also display antimicrobial resistance (AMR), and therefore HM-contaminated soils could potentially act as reservoirs that could disseminate AMR genes into human-associated pathogenic bacteria. To explore this possibility, topsoil samples were collected from six public locations in the zip code 35207 (the home of the North Birmingham 35th Avenue Superfund Site) and in six public areas in the neighboring zip code, 35214. 35027 soils had significantly elevated levels of the HMs As, Mn, Pb, and Zn, and sequencing of the V4 region of the bacterial 16S rRNA gene revealed that elevated HM concentrations correlated with reduced microbial diversity and altered community structure. While there was no difference between zip codes in the proportion of total culturable HMR bacteria, bacterial isolates with HMR almost always also exhibited AMR. Metagenomes inferred using PICRUSt2 also predicted significantly higher mean relative frequencies in 35207 for several AMR genes related to both specific and broad-spectrum AMR phenotypes. Together, these results support the hypothesis that chronic HM pollution alters the soil bacterial community structure in ecologically meaningful ways and may also select for bacteria with increased potential to contribute to AMR in human disease.

opencc-zeroMay 2023View details →

Data from: Subtle responses of soil bacterial communities to corn-soybean-wheat rotation

Crop rotational diversity can improve crop productivity and soil health and boost soil microbial diversity. This research hypothesized that a three-year rotation of corn-soybean-wheat (CSW), compared to a two-year corn-soybean (CS) rotation, would result in a more diverse and more complex soil bacterial community, together with a greater abundance of beneficial bacteria. This was evaluated in a replicated experiment established in 2013 at two locations in Ohio (USA). The soil bacterial communities under soybean were compared between CS and CSW, at both studied sites, in 2018 and 2019, through 16S rDNA amplicon metabarcoding.

opencc-by-4.0Jul 2024View details →

Dataset for Phosphite as an Engineered Niche for Pseudomonas veronii in a Synthetic Soil Bacterial Community

Files containing the source data and analyses used in the manuscript "Phosphite as an Engineered Niche for Pseudomonas veronii in a Synthetic Soil Bacterial Community".   Clara Bailey (1), Philip Gwyther (2), Senka Čau&scaron;ević (2), Brandon L. Greene (1), and Jan Roelof van der Meer (2) 1) Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, California, United States 2) Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland   This dataset contains 16S rRNA gene amplicon sequencing data (in the form of an abundance table, "abund.csv" and combined with CFU counts in "abund_cfu.csv"), toluene quantification data, and CFU counts. All data analysis, statistical tests, and generated figures are contained in the relevant .R script. Refer to README files for data tables as well as the README section at the header of the R script. The dataset has been updated from version 1 to include manuscript revisions, and updated calculations and figures.

publicOct 2022View details →

Different facets of bacterial and fungal communities drive soil multifunctionality in grasslands spanning a 3,500 km transect

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publicMar 2023View details →

Data for: Heavy metal pollution impacts soil bacterial community structure and antimicrobial resistance at the Birmingham 35th Avenue Superfund Site

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publicMay 2023View details →

Data from: Subtle responses of soil bacterial communities to corn-soybean-wheat rotation

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zenodo36/100

Sequences, taxonomic assignments, and R script from Comparison of Lava Cave Bacterial Mat Communities to Overlying Surface Soil Bacterial Communities from Lava Beds National Monument, USA

This set of files contain the 16S rDNA, taxonomic assignments from the greengenes database, and the R script for processing the data.   Abstract Lava caves around the world often support extensive microbial mats on ceilings and walls in a range of colors. Little is known about lava cave microbial diversity and how these subsurface mats differ from microbial communities in overlying surface soils. We generated and analyzed bacterial 16S rDNA from 454 pyrosequencing from three colors of microbial mats (tan, white, and yellow) from seven lava caves in Lava Beds National Monument, CA, USA, and compared them with surface soils overlying each cave. Actinobacteria dominated in all samples, with 39% (caves) and 21% (surface soils). Proteobacteria made up 30% of phyla from caves and 36% from surface soil with Gamma- 20% and Alpha- 10% in the caves and Gamma- 18% with Alpha-17% in soil. Other major phyla in caves were Nitrospirae (7%) followed by Minor Phyla (7%), compared to surface soils with Bacteriodetes (8%) and Minor phyla (8%). A very high proportion (53.33%) of the most abundant sequences could not be identified to genus, indicating a high degree of novelty. Surface soil samples had more OTUs and greater diversity indices than cave samples. The same phyla were represented in both soils and cave microbial mats, but the overlap was only 11.2% at the operational taxonomic unit (OTU).  Although surface soil microbes immigrate into underlying caves, the environment selects for microbes able to live in the cave habitats, resulting in very different cave microbial communities. In terms of species richness, diversity by mat color differed, but not significantly. Number of entrances per cave, distance from an entrance, cave length, and temperature also contributed to observed differences in diversity. With high levels of novel microbes, caves may represent excellent habitats for the isolation of new bioactive compounds. This study is the first comprehensive comparisons of bacterial communities in lava caves with the overlying soil community.

opencc-by-4.0Jul 2016View details →

opencc-zeroApr 2024View details →

Data from: Effects of pesticides on soil bacterial, fungal and protist communities, soil functions and crop quality in vineyards

Pesticides can have unintentional effects on non-target organisms and change biotic communities. Such changes might be particularly important in soil microbial communities which drive many ecosystem functions and may affect crop quality. Here, we investigated, in a 3-year study, how vegetation control (by herbicide application) and soil copper content (from long-term copper-based fungicide application), affect biodiversity and the community structure of soil bacteria, fungi and protists and associated soil functions (respiration, decomposition) in Swiss vineyards. Furthermore, we determined the effects of these two management practices on grape quality as the most direct ecosystem service to farmers. Across all study years, the community composition of microorganisms was affected by herbicide application, however, a significant loss of operational taxonomic units (OTUs) was only observed in fungi and protists. Soil copper content reduced OTU richness of bacteria and protists in some years but had no significant effect on fungal richness. Copper changed the community composition in all three groups of soil microorganisms. While we found no effect of copper on soil functions, herbicide application reduced microbial respiration and biomass by about 39% and 45% respectively. However, decomposition rates remained virtually unchanged by any pesticide. Yeast assimilable nitrogen (YAN) levels in grape must were below the critical threshold of 140 mg/L in 40% of the vineyards without herbicide application and the variety Chasselas , whereas in vineyards with herbicide application it was only 20%. Synthesis and applications: Application of pesticides led to changes in richness and composition of soil microbial communities and directly reduced some soil functions (microbial biomass and respiration), but not all (decomposition). Some grape quality parameters can be indirectly enhanced by pesticide application, highlighting the trade-off between the interests of nature conservation and the interests of the farmer. Balancing these two diverging interests requires the establishment of alternative vineyard management allowing reduced pesticide application.

opencc-zeroOct 2022View details →

Data for: Can heavy metal pollution induce soil bacterial community resistance to antibiotics in boreal forests?

The emergence of microbial antibiotic resistance is a central threat to global health, food security, and development. It has been shown that heavy metal pollution can give rise to microbial resistance to antibiotics, but how wide-spread this phenomenon is remains an open question that urgently needs filling to enable appropriate environmental risk assessments. Here, we determined whether long-term differences in heavy metal pollution in boreal forests had affected soil microbial communities such that they had increased microbial resistance to antibiotics. First, we assessed variation in metal concentrations in samples collected across a distance trajectory from the pollution source, and also the microbial rates and levels of bacterial community resistance to the heavy metal Cu and the antibiotics tetracycline and vancomycin in those samples. Second, we tested if the exposure to Cu or tetracycline could increase bacterial community resistance to Cu and to antibiotics in soils with high versus low background levels of metal contamination. Metal pollution had affected microbial community structures and suppressed decomposer functioning. Importantly, bacterial community Cu resistance increased with higher metal concentrations, which coincided with an induced bacterial community resistance to tetracycline, but not to vancomycin. Laboratory experiments revealed that bacterial community Cu resistance could be further induced in both the low and high end of the pollution gradient, but also that these short-term inductions of community metal tolerance did not coincide with enhanced antibiotic resistance. This yielded a surprising negative correlation between long-term and short-term effects by metals on microbial metal and antibiotic resistances. One mechanism that could provide protection against both metal cations and tetracycline is the small multidrug resistance (SMR) family, which is an energy demanding physiological mechanism that may take time to confer protection. This may explain the different microbial responses to long-term gradients and metal addition experiments. Policy implications. We show that metal pollution in boreal forests will promote antibiotic resistance in soil bacterial communities, revealing an overlooked reservoir of antibiotic resistance. We recommend that environmental risk assessments for any activity giving rise to increased soil metal concentrations need to also consider the induction of microbial antibiotic resistance.

opencc-zeroMay 2023View details →

Correlations between dominant vegetation type and composition and diversity of soil bacterial communities in a subtropical forest

Single and mixed vegetation types have significant effects on soil parameters and the composition and diversity of soil bacterial communities. To understand the influence of different vegetation types on the structure of soil bacterial community across soil depth in a subtropical forest, we assessed the relative abundance of edaphic bacterial community and soil parameters, including pH, cation exchange capacity (CEC), and dissolved organic carbon (DOC) in Daiyun Mountain Nature Reserve in Fujian Province, southeastern China. The study area constitutes pine coniferous forest (CF) of pinus taiwanensis, broad-leaved forest (BF) of castanopsis fabri, and a mixed forest comprising CF and BF (MF). Quantitative PCR and Illumina sequencing of 16S rDNA were used to analyze the abundance, diversity, and composition of soil bacteria. The results showed that the pH, CEC and diversity of tree species are all associated with the composition of the bacterial community in the soil. It was found that CEC, soluble organic nitrogen (DON) and pH largely affected the structure of soil bacterial community in A horizon, whereas CEC, moisture content (MC) and organic phosphorus (OP) affected the structure of soil bacterial community in B horizon. We found that the dominant taxa in the CF and BF were Proteobacteria and Acidobacteria, respectively. The results of both mental and random forest (RF) analyses displayed groups according to vegetation types, indicating that the bacterial communities in the research site were significantly influenced by vegetation types in subtropical forests. The study highlights the ecological effects of forest management and elucidates the differences in the functional structure of soil bacterial communities under different vegetation types and soil depths.

opencc-zeroAug 2023View details →

Slow soil enzyme recovery following invasive tree removal through gradual changes in bacterial and fungal communities

Biological invasions of plants have profound effects on ecosystem functioning by directly and indirectly altering soil microbiota, especially when invasive plants co-invade with their associated microbiomes. Ecosystem functions may recover slowly following invader removal, with implications for restoration. We investigated the recovery of soil ecosystem function (measured as soil enzymes) following the removal, at different densities and times, of invasive Pinus spp. in New Zealand, and how different enzymatic activities responded to pine legacies. Enzymatic activities were driven by pine legacies via both abiotic (soil nutrients) and biotic (fungi and bacteria) soil properties, with different enzymes showing distinct patterns. The activity of the enzymes cellobiohydrolase (cellulose degrading), β-glucosidase (cellulose degrading), N-acetyl-glucosaminidase (chitin degrading), laccase (lignin oxidising) and acid phosphatase (organic phosphate hydrolysing) were influenced by time since pine removal and by pine density at removal via effects on biotic communities. In comparison, Mn-peroxidase (lignin oxidising) was positively correlated with density of pines at removal and was negatively correlated with time since removal and was only influenced by fungal communities. Synthesis. The recovery of soil enzymatic function following invasive species removal is slow, and dependent on pine legacies through the gradual changes in fungal and bacterial communities. The cascading effects of these changes suggest potential implications for the success of future plant establishment and restoration of co-invaded ecosystems.

opencc-zeroAug 2023View details →

Taxonomic and functional biogeographies of soil bacterial communities across the Tibet plateau are better explained by abiotic conditions than distance and plant community composition

The processes governing soil bacteria biogeography are still not fully understood. It remains unknown how the importance of environmental filtering and dispersal differs between bacterial taxonomic and functional biogeography, and whether their importance is scale-dependent. We sampled soils across the Tibet plateau, with distances among plots ranging from 20 m to 1,550 km. Taxonomic composition of bacterial community was characterized by 16S amplicon sequencing and functional community composition by qPCR targeting 9 functional groups involved in N dynamics. Factors representing climate, soil, and plant community were measured to assess different facets of environmental dissimilarity. Both bacterial taxonomic and functional dissimilarities were more related to abiotic dissimilarity than biotic (vegetation) dissimilarity or distance. Taxonomic dissimilarity was mostly explained by differences in soil pH and mean annual temperature (MAT), while functional dissimilarity was linked to differences in soil N and P availabilities and N:P ratio. Soil pH and MAT remained the main determinants of taxonomic dissimilarity across spatial scales. In contrast, the explanatory variables of N-related functional dissimilarity varied across the scales, with soil moisture and organic matter having the highest role across short distances (<~330 km), and available P, N:P ratio and distance being important over long distances (>~660 km). Our results demonstrate how biodiversity dimension (taxonomic versus functional aspects) and spatial scale influence the factors driving soil bacterial biogeography.