scholarly journals Uncovering a hidden diversity: optimized protocols for the extraction of bacteriophages from soil

2019 ◽  
Author(s):  
Pauline C. Göller ◽  
Jose M. Haro-Moreno ◽  
Francisco Rodriguez-Valera ◽  
Martin J. Loessner ◽  
Elena Gómez-Sanz
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Ecological Model ◽  
Extraction Process ◽  
Extraction Methods ◽  
Soil Samples ◽  
Rrna Gene ◽  
Optimization Strategy ◽  
Data Set ◽  
Soil Matrix

AbstractBackgroundBacteriophages are the most numerous biological entities on earth and play a crucial role in shaping microbial communities. Investigating the bacteriophage community from soil samples will shed light not only on the yet largely unknown phage diversity, but also may result in novel insights into phage biology and functioning. Unfortunately, the study of soil viromes lags far behind any other ecological model system, due to the heterogeneous soil matrix that rises major technical difficulties in the extraction process. Resolving these technical challenges and establishing a standardized extraction protocol is therefore a fundamental prerequisite for replicable results and comparative virome studies.ResultsWe here report the optimization of protocols for extraction of bacteriophage DNA from soil preceding metagenomic analysis such that the protocol can equally be harnessed for phage isolation. As an optimization strategy, soil samples were spiked with a viral community consisting of phages from different families (106 PFU/g soil): Listeria phage ΦA511 (Myovirus), Staphylococcus phage Φ2638AΔLCR (Siphovirus), and Escherichia phage ΦT7 (Podovirus). The efficacy of bacteriophage (i) elution, (ii) filtration, (iii) concentration, and (iv) DNA extraction methods was tested. Successful extraction routes were selected based on spiked phage recovery and low bacterial 16S rRNA gene contaminants. Natural agricultural soil viromes were then extracted with the optimized methods and shotgun sequenced. Our approach yielded sufficient amounts of inhibitor-free viral DNA for non-amplification dependent sequencing and low 16S rRNA gene contamination levels (≤ 0.2 ‰). Compared to previously published protocols, the number of bacterial read contamination was decreased by 65 %. In addition, 468 novel circularized soil phage genomes in size up to 235 kb were obtained from over 29,000 manually identified viral contigs, promising the discovery of a large, previously inaccessible viral diversity.ConclusionWe have shown a dramatically enhanced extraction of the soil phage community by protocol optimization that has proven robustness in both a culture-depended as well as through metaviromic analysis. Our huge data set of manually curated soil viral contigs roughly doubles the amount of currently available soil virome data, and provide insights into the yet largely undescribed soil viral sequence space.

scholarly journals The Termite Group I Phylum Is Highly Diverse and Widespread in the Environment

2007 ◽  
Vol 73 (20) ◽  
pp. 6682-6685 ◽  
Author(s):  
Daniel P. R. Herlemann ◽  
Oliver Geissinger ◽  
Andreas Brune
Keyword(s):  
Phylogenetic Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Gene Sequences ◽  
16S Rrna Gene Sequences ◽  
Specific Primers ◽  
Environmental Distribution ◽  
Data Set ◽  
Group I

ABSTRACT The bacterial candidate phylum Termite Group I (TG-1) presently consists mostly of “Endomicrobia,” which are endosymbionts of flagellate protists occurring exclusively in the hindguts of termites and wood-feeding cockroaches. Here, we show that public databases contain many, mostly undocumented 16S rRNA gene sequences from other habitats that are affiliated with the TG-1 phylum but are only distantly related to “Endomicrobia.” Phylogenetic analysis of the expanded data set revealed several diverse and deeply branching lineages comprising clones from many different habitats. In addition, we designed specific primers to explore the diversity and environmental distribution of bacteria in the TG-1 phylum.

Soil aggregate-based nucleic acid analyses of the impact of maize roots and their root hairs on the structural diversity of microbial communities

2021 ◽  
Author(s):  
Christoph Tebbe ◽  
Damini Damini ◽  
Damien Finn ◽  
Nataliya Bilyera ◽  
Minh Ganther ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Root Hair ◽  
Soil Aggregates ◽  
Root Hairs ◽  
Soil Samples ◽  
Plant Roots ◽  
Bulk Soil ◽  
Rrna Gene ◽  
The Impact

<p>The deposition of energy rich carbon sources released by plant roots during their growth fuels microbially driven ecosystem processes in soil, but there is a lack of understanding how microorganisms interact and collaborate. The objective of this research was therefore to characterize microbial networks as they assemble under the influence of plant roots. To identify the specific importance of root hairs, we compared the impact of a maize wild-type to a root-air defective mutant (rth3; (1).</p><p>The microbial community structure was analyzed by qPCR and 16S rRNA gene amplicon sequencing from soil DNA. In order to increase the probability of detecting truly interacting microbial partners as a basis for network analyses, we first evaluated a new protocol to obtain DNA from as little as 1 mg instead of the usual 250 mg soil samples, thereby approaching the aggregate level (2). While the diversity of bacterial 16S rRNA gene amplicons of 250-mg samples taken from the same soil was not distinct, DNA analyses from individual aggregates clearly differed from each other underlining that soil aggregates represent distinct microbial habitats.</p><p>Soil column experiments with maize grown in a loam soil (3) revealed distinct communities between rhizosphere and bulk soil. The community composition of individual aggregates showed more differences in bulk soil compared to rhizosphere. Less elaborated networks were seen in bulk soil and a profound effect of root hairs could be unravelled. Null model testing demonstrated that Actinobacteria were equally important for network connectivity independent of the root hair mutation, but for networks of the wildtype, Acidobacteria were essential for synergistic interactions and overall network structure. In contrast, Proteobacteria and Firmicutes connectivity became more important. The observed differences in community composition and interactions suggests carbon cycling, and perhaps other microbially-driven functions, are markedly affected by the presence of root hairs.</p><p>Utilizing maize root soil microcosms for studying soil zymography in the rhizosphere allowed to obtain soil samples from regions with distinct specific enzyme activities. In order to enhance the detection of actively metabolizing bacterial community members, we studied rRNA sequences and compared it to rRNA gene sequences from the same samples. Currently the data are under analysis.</p><p>References</p><p>(1) Wen, T-J, Schnable PS (1994) Analyses of mutants of three genes that influence root hair development in Zea mays (Gramineae) suggest that root hairs are dispensable. Am. J. Bot. 81, 833–842.</p><p>(2) Szoboszlay M, Tebbe CC (2020) Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates. Microbiol. Open, e1144. DOI: 10.1002/mbo3.1144</p><p>(3) Vetterlein D et al. (2020) Experimental platforms for the investigation of spatiotemporal patterns in the rhizosphere – laboratory and field scale. J. Plant Nutr. Soil Sci., 000, 1–16 DOI: 10.1002/jpln.202000079</p>

scholarly journals 16S rRNA Gene Amplicon Profiling of Baby and Adult Captive Elephants in Thailand

2020 ◽  
Vol 9 (24) ◽  
Author(s):  
Sangam Kandel ◽  
Supaphen Sripiboon ◽  
Piroon Jenjaroenpun ◽  
David W. Ussery ◽  
Intawat Nookaew ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Bacterial Diversity ◽  
Sequence Data ◽  
Rrna Gene ◽  
Data Set ◽  
Geographical Locations

ABSTRACT Here, we present a 16S rRNA gene amplicon sequence data set and profiles demonstrating the bacterial diversity of baby and adult elephants from four different geographical locations in Thailand. The dominant phyla among baby and adult elephants were Bacteroidetes, Firmicutes, Proteobacteria, Kiritimatiellaeota, Euryarchaeota, and Tenericutes.

scholarly journals Allometry and Ecology of the Bilaterian Gut Microbiome

mBio ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. e00319-18 ◽  
Author(s):  
Scott Sherrill-Mix ◽  
Kevin McCormick ◽  
Abigail Lauder ◽  
Aubrey Bailey ◽  
Laurie Zimmerman ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Island Biogeography ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Data Set ◽  
Community Construction ◽  
Wide Range ◽  
Niche Diversification ◽  
Bacterial Lineages

ABSTRACT Classical ecology provides principles for construction and function of biological communities, but to what extent these apply to the animal-associated microbiota is just beginning to be assessed. Here, we investigated the influence of several well-known ecological principles on animal-associated microbiota by characterizing gut microbial specimens from bilaterally symmetrical animals (Bilateria) ranging from flies to whales. A rigorously vetted sample set containing 265 specimens from 64 species was assembled. Bacterial lineages were characterized by 16S rRNA gene sequencing. Previously published samples were also compared, allowing analysis of over 1,098 samples in total. A restricted number of bacterial phyla was found to account for the great majority of gut colonists. Gut microbial composition was associated with host phylogeny and diet. We identified numerous gut bacterial 16S rRNA gene sequences that diverged deeply from previously studied taxa, identifying opportunities to discover new bacterial types. The number of bacterial lineages per gut sample was positively associated with animal mass, paralleling known species-area relationships from island biogeography and implicating body size as a determinant of community stability and niche complexity. Samples from larger animals harbored greater numbers of anaerobic communities, specifying a mechanism for generating more-complex microbial environments. Predictions for species/abundance relationships from models of neutral colonization did not match the data set, pointing to alternative mechanisms such as selection of specific colonists by environmental niche. Taken together, the data suggest that niche complexity increases with gut size and that niche selection forces dominate gut community construction. IMPORTANCE The intestinal microbiome of animals is essential for health, contributing to digestion of foods, proper immune development, inhibition of pathogen colonization, and catabolism of xenobiotic compounds. How these communities assemble and persist is just beginning to be investigated. Here we interrogated a set of gut samples from a wide range of animals to investigate the roles of selection and random processes in microbial community construction. We show that the numbers of bacterial species increased with the weight of host organisms, paralleling findings from studies of island biogeography. Communities in larger organisms tended to be more anaerobic, suggesting one mechanism for niche diversification. Nonselective processes enable specific predictions for community structure, but our samples did not match the predictions of the neutral model. Thus, these findings highlight the importance of niche selection in community construction and suggest mechanisms of niche diversification.

scholarly journals Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors

mBio ◽  
2018 ◽  
Vol 9 (3) ◽  
Author(s):  
Marc A. Sze ◽  
Patrick D. Schloss
Keyword(s):  
Colorectal Cancer ◽  
Random Forest ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Meta Analysis ◽  
Tumor Diagnosis ◽  
Rrna Gene ◽  
Modeling Framework ◽  
Data Set ◽  
Colonic Microbiota

ABSTRACTAn increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to identify the associations that are the most predictive of disease progression is warranted. We analyzed previously published 16S rRNA gene sequencing data collected from feces and colon tissue. We quantified the odds ratios (ORs) for individual bacterial taxa that were associated with an individual having tumors relative to a normal colon. Among the fecal samples, there were no taxa that had significant ORs associated with adenoma and there were 8 taxa with significant ORs associated with carcinoma. Similarly, among the tissue samples, there were no taxa that had a significant OR associated with adenoma and there were 3 taxa with significant ORs associated with carcinoma. Among the significant ORs, the association between individual taxa and tumor diagnosis was equal to or below 7.11. Because individual taxa had limited association with tumor diagnosis, we trained Random Forest classification models using only the taxa that had significant ORs, using the entire collection of taxa found in each study, and using operational taxonomic units defined based on a 97% similarity threshold. All training approaches yielded similar classification success as measured using the area under the curve. The ability to correctly classify individuals with adenomas was poor, and the ability to classify individuals with carcinomas was considerably better using sequences from feces or tissue.IMPORTANCEColorectal cancer is a significant and growing health problem in which animal models and epidemiological data suggest that the colonic microbiota have a role in tumorigenesis. These observations indicate that the colonic microbiota is a reservoir of biomarkers that may improve our ability to detect colonic tumors using noninvasive approaches. This meta-analysis identifies and validates a set of 8 bacterial taxa that can be used within a Random Forest modeling framework to differentiate individuals as having normal colons or carcinomas. When models trained using one data set were tested on other data sets, the models performed well. These results lend support to the use of fecal biomarkers for the detection of tumors. Furthermore, these biomarkers are plausible candidates for further mechanistic studies into the role of the gut microbiota in tumorigenesis.

scholarly journals Substrate-Specific Clades of Active Marine Methylotrophs Associated with a Phytoplankton Bloom in a Temperate Coastal Environment

2008 ◽  
Vol 74 (23) ◽  
pp. 7321-7328 ◽  
Author(s):  
Josh D. Neufeld ◽  
Rich Boden ◽  
Hélène Moussard ◽  
Hendrik Schäfer ◽  
J. Colin Murrell
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Atmospheric Chemistry ◽  
Methyl Bromide ◽  
Dimethyl Sulfide ◽  
Phytoplankton Bloom ◽  
Stable Isotope Probing ◽  
Rrna Gene ◽  
Surface Seawater ◽  
Data Set

ABSTRACT Marine microorganisms that consume one-carbon (C1) compounds are poorly described, despite their impact on global climate via an influence on aquatic and atmospheric chemistry. This study investigated marine bacterial communities involved in the metabolism of C1 compounds. These communities were of relevance to surface seawater and atmospheric chemistry in the context of a bloom that was dominated by phytoplankton known to produce dimethylsulfoniopropionate. In addition to using 16S rRNA gene fingerprinting and clone libraries to characterize samples taken from a bloom transect in July 2006, seawater samples from the phytoplankton bloom were incubated with 13C-labeled methanol, monomethylamine, dimethylamine, methyl bromide, and dimethyl sulfide to identify microbial populations involved in the turnover of C1 compounds, using DNA stable isotope probing. The [13C]DNA samples from a single time point were characterized and compared using denaturing gradient gel electrophoresis (DGGE), fingerprint cluster analysis, and 16S rRNA gene clone library analysis. Bacterial community DGGE fingerprints from 13C-labeled DNA were distinct from those obtained with the DNA of the nonlabeled community DNA and suggested some overlap in substrate utilization between active methylotroph populations growing on different C1 substrates. Active methylotrophs were affiliated with Methylophaga spp. and several clades of undescribed Gammaproteobacteria that utilized methanol, methylamines (both monomethylamine and dimethylamine), and dimethyl sulfide. rRNA gene sequences corresponding to populations assimilating 13C-labeled methyl bromide and other substrates were associated with members of the Alphaproteobacteria (e.g., the family Rhodobacteraceae), the Cytophaga-Flexibacter-Bacteroides group, and unknown taxa. This study expands the known diversity of marine methylotrophs in surface seawater and provides a comprehensive data set for focused cultivation and metagenomic analyses in the future.

scholarly journals TaxAss: Leveraging a Custom Freshwater Database Achieves Fine-Scale Taxonomic Resolution

mSphere ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Robin R. Rohwer ◽  
Joshua J. Hamilton ◽  
Ryan J. Newton ◽  
Katherine D. McMahon
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Microbial Community Composition ◽  
Taxonomic Resolution ◽  
Rrna Gene ◽  
Data Sets ◽  
Data Set ◽  
Comprehensive Database ◽  
Fine Resolution

ABSTRACT Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater data sets using the comprehensive SILVA database and the freshwater-specific FreshTrain database. TaxAss increased the percentage of the data set classified compared to using only SILVA, especially at fine-resolution family to species taxon levels, while across the freshwater test data sets classifications increased by as much as 11 to 40% of total reads. A similar increase in classifications was not observed in a control mouse gut data set, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxon levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxon levels, incorrect classifications became significant. We validated TaxAss using simulated amplicon data derived from full-length clone libraries and found that 96 to 99% of test sequences were correctly classified at fine resolution. TaxAss splits a data set’s sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source and is available at https://www.github.com/McMahonLab/TaxAss. IMPORTANCE Microbial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon data sets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at the phylum, class, and order levels lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are data set dependent and cannot be compared between data sets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus, and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between data sets.

scholarly journals Assessment of two DNA extraction kits for profiling poultry respiratory microbiota from multiple sample types

2020 ◽  
Author(s):  
Michael E.C. Abundo ◽  
John M. Ngunjiri ◽  
Kara J.M. Taylor ◽  
Hana Ji ◽  
Amir Ghorbani ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Dna Extraction ◽  
Extraction Process ◽  
Production Performance ◽  
Rrna Gene ◽  
Sample Type ◽  
Alpha And Beta Diversity ◽  
Gene Copies ◽  
Diversity Metrics

AbstractCharacterization of poultry microbiota is becoming increasingly important due to the growing need for microbiome-based interventions to improve poultry health and production performance. However, the lack of standardized protocols for sampling, sample processing, DNA extraction, sequencing, and bioinformatic analysis can hinder data comparison between studies. Here, we investigated how the DNA extraction process affects microbial community compositions and diversity metrics in different chicken respiratory sample types including choanal and tracheal swabs, nasal cavity and tracheal washes, and lower respiratory lavage. We did a side-by-side comparison of the performances of Qiagen DNeasy blood and tissue (BT) and ZymoBIOMICS DNA Miniprep (ZB) kits. In general, samples extracted with the BT kit yielded higher concentrations of total DNA while those extracted with the ZB kit contained higher numbers of bacterial 16S rRNA gene copies per unit volume. Therefore, the samples were normalized to equal amounts of 16S rRNA gene copies prior to sequencing. For each sample type, all predominant taxa detected in samples extracted with one kit were present in replicate samples extracted with the other kit and did not show significant differences at the class level. Furthermore, between-kit differences in alpha and beta diversity metrics were statistically indistinguishable. Therefore, both kits perform similarly with regard to 16S rRNA gene-based poultry microbiome analysis.

scholarly journals Genomics of the Uncultivated, Periodontitis-Associated BacteriumTannerellasp. BU045 (Oral Taxon 808)

mSystems ◽  
2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Clifford J. Beall ◽  
Alisha G. Campbell ◽  
Ann L. Griffen ◽  
Mircea Podar ◽  
Eugene J. Leys
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Chronic Periodontitis ◽  
Bacterial Species ◽  
The United States ◽  
Oral Microbiome ◽  
Rrna Gene ◽  
Bacterial Cells ◽  
Data Set ◽  
Content Type

ABSTRACTDespite decades of research into the human oral microbiome, many species remain uncultivated. The technique of single-cell whole-genome amplification and sequencing provides a means of deriving genome sequences for species that can be informative on biological function and suggest pathways to cultivation.Tannerella forsythiahas long been known to be highly associated with chronic periodontitis and to cause periodontitis-like symptoms in experimental animals, andTannerellasp. BU045 (human oral taxon 808) is an uncultivated relative of this organism. In this work, we extend our previous sequencing of theTannerellasp. BU063 (human oral taxon 286) genome by sequencing amplified genomes from 11 cells ofTannerellasp. BU045, including 3 genomes that are at least 90% complete.Tannerellasp. BU045 is more closely related toTannerellasp. BU063 than toT. forsythiaby gene content and average nucleotide identity. However, two independent data sets of association with periodontitis, one based on 16S rRNA gene abundance and the other based on gene expression in a metatranscriptomic data set, show thatTannerellasp. BU045 is more highly associated with disease thanTannerellasp. BU063. Comparative genomics shows genes and functions that are shared or unique to the different species, which may direct further research of the pathogenesis of chronic periodontitis.IMPORTANCEPeriodontitis (gum disease) affects 47% of adults over 30 in the United States (P. I. Eke, B. A. Dye, L. Wei, G. O. Thornton-Evans, R. J. Genco, et al., J Dent Res 91:914–920, 2012), and it cost between $39 and $396 billion worldwide in 2015 (A. J. Righolt, M. Jevdjevic, W. Marcenes, and S. Listl, J Dent Res, 17 January 2018, https://doi.org/10.1177/0022034517750572). Many bacteria associated with the disease are known only by the DNA sequence of their 16S rRNA gene. In this publication, amplification and sequencing of DNA from single bacterial cells are used to obtain nearly complete genomes ofTannerellasp. BU045, a species of bacteria that is more prevalent in patients with periodontitis than in healthy patients. Comparing the complete genome of this bacterium to genomes of related bacterial species will help to better understand periodontitis and may help to grow this organism in pure culture, which would allow a better understanding of its role in the mouth.

scholarly journals Influence of Soil Characteristics on the Diversity of Bacteria in the Southern Brazilian Atlantic Forest

2010 ◽  
Vol 76 (14) ◽  
pp. 4744-4749 ◽  
Author(s):  
H. Faoro ◽  
A. C. Alves ◽  
E. M. Souza ◽  
L. U. Rigo ◽  
L. M. Cruz ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Atlantic Forest ◽  
16S Rrna Gene Sequencing ◽  
Diversity Indices ◽  
Physicochemical Characteristics ◽  
Soil Samples ◽  
Rrna Gene ◽  
Brazilian Atlantic Forest ◽  
Bacterial Biodiversity

ABSTRACT The Brazilian Atlantic Forest is one of the 25 biodiversity hot spots in the world. Although the diversity of its fauna and flora has been studied fairly well, little is known of its microbial communities. In this work, we analyzed the Atlantic Forest ecosystem to determine its bacterial biodiversity, using 16S rRNA gene sequencing, and correlated changes in deduced taxonomic profiles with the physicochemical characteristics of the soil. DNAs were purified from soil samples, and the 16S rRNA gene was amplified to construct libraries. Comparison of 754 independent 16S rRNA gene sequences from 10 soil samples collected along a transect in an altitude gradient showed the prevalence of Acidobacteria (63%), followed by Proteobacteria (25.2%), Gemmatimonadetes (1.6%), Actinobacteria (1.2%), Bacteroidetes (1%), Chloroflexi (0.66%), Nitrospira (0.4%), Planctomycetes (0.4%), Firmicutes (0.26%), and OP10 (0.13%). Forty-eight sequences (6.5%) represented unidentified bacteria. The Shannon diversity indices of the samples varied from 4.12 to 3.57, indicating that the soils have a high level of diversity. Statistical analysis showed that the bacterial diversity is influenced by factors such as altitude, Ca2+/Mg2+ ratio, and Al3+ and phosphorus content, which also affected the diversity within the same lineage. In the samples analyzed, pH had no significant impact on diversity.

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