Soil available nitrogen and phosphorus affected by functional bacterial community composition and diversity as ecological restoration progressed

2020 ◽  
Vol 32 (1) ◽  
pp. 183-198
Author(s):  
Honglei Wang ◽  
Lianyan Bu ◽  
Fangqin Song ◽  
Jing Tian ◽  
Gehong Wei
Keyword(s):  
Bacterial Community ◽  
Ecological Restoration ◽  
Community Composition ◽  
Bacterial Community Composition ◽  
Nitrogen And Phosphorus ◽  
Available Nitrogen ◽  
Soil Available Nitrogen

scholarly journals Diversity and Metabolism of Marine Bacteria Cultivated on Dissolved DNA

2007 ◽  
Vol 73 (9) ◽  
pp. 2799-2805 ◽  
Author(s):  
Jay T. Lennon
Keyword(s):  
Molecular Weight ◽  
Bacterial Community ◽  
Community Composition ◽  
Marine Bacteria ◽  
Bacterial Community Composition ◽  
Primary Source ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Taxon Richness ◽  
Nitrogen And Phosphorus

ABSTRACT Dissolved DNA (dDNA) is a potentially important source of energy and nutrients in aquatic ecosystems. However, little is known about the identity, metabolism, and interactions of the microorganisms capable of consuming dDNA. Bacteria from Eel Pond (Woods Hole, MA) were cultivated on low-molecular-weight (LMW) or high-molecular-weight (HMW) dDNA, which served as the primary source of carbon, nitrogen, and phosphorus. Cloning and sequencing of 16S rRNA genes revealed that distinct bacterial assemblages with comparable levels of taxon richness developed on LMW and HMW dDNA. Since the LMW and HMW dDNA used in this study were stoichiometrically identical, the results confirm that the size alone of dissolved organic matter can influence bacterial community composition. Variation in the growth and metabolism of isolates provided insight into mechanisms that may have generated differences in bacterial community composition. For example, bacteria from LMW dDNA enrichments generally grew better on LMW dDNA than on HMW dDNA. In contrast, bacteria isolated from HMW dDNA enrichments were more effective at degrading HMW dDNA than bacteria isolated from LMW dDNA enrichments. Thus, marine bacteria may experience a trade-off between their ability to compete for LMW dDNA and their ability to access HMW dDNA via extracellular nuclease production. Together, the results of this study suggest that dDNA turnover in marine ecosystems may involve a succession of microbial assemblages with specialized ecological strategies.

scholarly journals Collection of Environmental Variables and Bacterial Community Compositions in Marian Cove, Antarctica, during Summer 2018

Data ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 27
Author(s):  
Hyo-Ryeon Kim ◽  
Jae-Hyun Lim ◽  
Ju-Hyoung Kim ◽  
Il-Nam Kim
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Marine Bacteria ◽  
Environmental Variables ◽  
Environmental Changes ◽  
Bacterial Community Composition ◽  
Composition Data ◽  
Decomposition Of Organic Matter ◽  
Class Level ◽  
Earth’S Climate

Marine bacteria, which are known as key drivers for marine biogeochemical cycles and Earth’s climate system, are mainly responsible for the decomposition of organic matter and production of climate-relevant gases (i.e., CO₂, N₂O, and CH₄). However, research is still required to fully understand the correlation between environmental variables and bacteria community composition. Marine bacteria living in the Marian Cove, where the inflow of freshwater has been rapidly increasing due to substantial glacial retreat, must be undergoing significant environmental changes. During the summer of 2018, we conducted a hydrographic survey to collect environmental variables and bacterial community composition data at three different layers (i.e., the seawater surface, middle, and bottom layers) from 15 stations. Of all the bacterial data, 17 different phylum level bacteria and 21 different class level bacteria were found and Proteobacteria occupy 50.3% at phylum level following Bacteroidetes. Gammaproteobacteria and Alphaproteobacteria, which belong to Proteobacteria, are the highest proportion at the class level. Gammaproteobacteria showed the highest relative abundance in all three seawater layers. The collection of environmental variables and bacterial composition data contributes to improving our understanding of the significant relationships between marine Antarctic regions and marine bacteria that lives in the Antarctic.

scholarly journals Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Danijela Šantić ◽  
Kasia Piwosz ◽  
Frano Matić ◽  
Ana Vrdoljak Tomaš ◽  
Jasna Arapov ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Analysis ◽  
Bacterial Community ◽  
Microbial Diversity ◽  
Community Composition ◽  
Adriatic Sea ◽  
Bacterial Community Composition ◽  
Environmental Data ◽  
Large Contribution ◽  
Neural Network Analysis

AbstractBacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was analysed, along with a depth profile, in the open Adriatic Sea using amplicon sequencing of bacterial 16S rRNA and the Neural gas algorithm. The performed analysis classified the sample into four best matching units representing heterogenic patterns of the bacterial community composition. The observed parameters were more differentiated by depth than by area, with temperature and identified salinity as important environmental variables. The highest diversity was observed at the deep chlorophyll maximum, while bacterial abundance and production peaked in the upper layers. The most of the identified genera belonged to Proteobacteria, with uncultured AEGEAN-169 and SAR116 lineages being dominant Alphaproteobacteria, and OM60 (NOR5) and SAR86 being dominant Gammaproteobacteria. Marine Synechococcus and Cyanobium-related species were predominant in the shallow layer, while Prochlorococcus MIT 9313 formed a higher portion below 50 m depth. Bacteroidota were represented mostly by uncultured lineages (NS4, NS5 and NS9 marine lineages). In contrast, Actinobacteriota were dominated by a candidatus genus Ca. Actinomarina. A large contribution of Nitrospinae was evident at the deepest investigated layer. Our results document that neural network analysis of environmental data may provide a novel insight into factors affecting picoplankton in the open sea environment.

Organic matter- and temperature-driven deterministic assembly processes govern bacterial community composition and functionality during manure composting

2021 ◽  
Vol 131 ◽  
pp. 31-40
Author(s):  
Yuanyuan Bao ◽  
Youzhi Feng ◽  
Chongwen Qiu ◽  
Jianwei Zhang ◽  
Yiming Wang ◽  
...  
Keyword(s):  
Organic Matter ◽  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Community Composition

scholarly journals Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 157-172
Author(s):  
Shankar G. Shanmugam ◽  
Normie W. Buehring ◽  
Jon D. Prevost ◽  
William L. Kingery
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
Community Composition ◽  
Production System ◽  
Soil Microbial Community ◽  
Production Systems ◽  
Bacterial Community Composition ◽  
Soybean Production ◽  
Soil Microbial ◽  
Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

scholarly journals Longitudinal assessment of the bovine ocular bacterial community dynamics in calves

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Alison C. Bartenslager ◽  
Nirosh D. Althuge ◽  
John Dustin Loy ◽  
Matthew M. Hille ◽  
Matthew L. Spangler ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Community Dynamics ◽  
Bacterial Community Composition ◽  
Clinical Signs ◽  
Sampling Time ◽  
Experimental Population ◽  
Opportunistic Pathogens ◽  
Time Periods ◽  
Over Time

Abstract Background Infectious Bovine Keratoconjunctivitis (IBK), commonly known as pinkeye, is one of the most significant diseases of beef cattle. As such, IBK costs the US beef industry at least 150 million annually. However, strategies to prevent IBK are limited, with most cases resulting in treatment with antibiotics once the disease has developed. Longitudinal studies evaluating establishment of the ocular microbiota may identify critical risk periods for IBK outbreaks or changes in the microbiota that may predispose animals to IBK. Results In an attempt to characterize the establishment and colonization patterns of the bovine ocular microbiota, we conducted a longitudinal study consisting of 227 calves and evaluated the microbiota composition over time using amplicon sequence variants (ASVs) based on 16S rRNA sequencing data and culture-based approaches. Beef calves on trial consisted of both male (intact) and females. Breeds were composed of purebred Angus and composites with varying percentages of Simmental, Angus, and Red Angus breeds. Average age at the start of the trial was 65 days ±15.02 and all calves remained nursing on their dam until weaning (day 139 of the study). The trial consisted of 139 days with four sampling time points on day 0, 21, 41, and 139. The experimental population received three different vaccination treatments (autogenous, commercial (both inactivated bacteria), and adjuvant placebo), to assess the effectiveness of different vaccines for IBK prevention. A significant change in bacterial community composition was observed across time periods sampled compared to the baseline (p < 0.001). However, no treatment effect of vaccine was detected within the ocular bacterial community. The bacterial community composition with the greatest time span between sampling time periods (98d span) was most similar to the baseline sample collected, suggesting re-establishment of the ocular microbiota to baseline levels over time after perturbation. The effect of IgA levels on the microbial community was investigated in a subset of cattle within the study. However, no significant effect of IgA was observed. Significant changes in the ocular microbiota were identified when comparing communities pre- and post-clinical signs of IBK. Additionally, dynamic changes in opportunistic pathogens Moraxella spp. were observed and confirmed using culture based methods. Conclusions Our results indicate that the bovine ocular microbiota is well represented by opportunistic pathogens such as Moraxella and Mycoplasma. Furthermore, this study characterizes the diversity of the ocular microbiota in calves and demonstrates the plasticity of the ocular microbiota to change. Additionally, we demonstrate the ocular microbiome in calves is similar between the eyes and the perturbation of one eye results in similar changes in the other eye. We also demonstrate the bovine ocular microbiota is slow to recover post perturbation and as a result provide opportunistic pathogens a chance to establish within the eye leading to IBK and other diseases. Characterizing the dynamic nature of the ocular microbiota provides novel opportunities to develop potential probiotic intervention to reduce IBK outbreaks in cattle.

Bacterial community analysis of purulent material from liver abscesses of crossbred cattle and Holstein steers fed finishing diets with or without tylosin

2021 ◽  
Vol 99 (4) ◽  
Author(s):  
Raghavendra G Amachawadi ◽  
Wesley A Tom ◽  
Michael P Hays ◽  
Samodha C Fernando ◽  
Philip R Hardwidge ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Community Composition ◽  
Feedlot Cattle ◽  
Crossbred Cattle ◽  
Sequence Analyses ◽  
Gram Negative ◽  
Treatment Groups ◽  
Finishing Diets ◽  
Liver Abscesses

Abstract Liver abscesses in feedlot cattle are polymicrobial infections. Culture-based studies have identified Fusobacterium necrophorum as the primary causative agent, but a number of other bacterial species are frequently isolated. The incidence of liver abscesses is highly variable and is affected by a number of factors, including cattle type. Holstein steers raised for beef production have a higher incidence than crossbred feedlot cattle. Tylosin is the commonly used antimicrobial feed additive to reduce the incidence of liver abscesses. The objective of this study was to utilize 16S ribosomal RNA amplicon sequence analyses to analyze the bacterial community composition of purulent material of liver abscesses of crossbred cattle (n = 24) and Holstein steers (n = 24), each fed finishing diet with or without tylosin. DNA was extracted and the V3 and V4 regions of the 16S rRNA gene were amplified, sequenced, and analyzed. The minimum, mean, and maximum sequence reads per sample were 996, 177,070, and 877,770, respectively, across all the liver abscess samples. Sequence analyses identified 5 phyla, 14 families, 98 genera, and 102 amplicon sequence variants (ASV) in the 4 treatment groups. The dominant phyla identified were Fusobacteria (52% of total reads) and Proteobacteria (33%). Of the top 25 genera identified, 17 genera were Gram negative and 8 were Gram positive. The top 3 genera, which accounted for 75% of the total reads, in the order of abundance, were Fusobacterium, Pseudomonas, and Bacteroides. The relative abundance, expressed as percent of total reads, of phyla, family, and genera did not differ (P &gt; 0.05) between the 4 treatment groups. Generic richness and evenness, determined by Shannon–Weiner and Simpson’s diversity indices, respectively, did not differ between the groups. The UniFrac distance matrices data revealed no clustering of the ASV indicating variance between the samples within each treatment group. Co-occurrence network analysis at the genus level indicated a strong association of Fusobacterium with 15 other genera, and not all of them have been previously isolated from liver abscesses. In conclusion, the culture-independent method identified the bacterial composition of liver abscesses as predominantly Gram negative and Fusobacterium as the dominant genus, followed by Pseudomonas. The bacterial community composition did not differ between crossbred and Holstein steers fed finishing diets with or without tylosin.

Soil physicochemical properties and bacterial community composition jointly affect crop yield

2020 ◽  
Vol 112 (5) ◽  
pp. 4358-4372
Author(s):  
Meiqi Chen ◽  
Jisheng Xu ◽  
Zengqiang Li ◽  
Bingzi Zhao ◽  
Jiabao Zhang
Keyword(s):  
Bacterial Community ◽  
Physicochemical Properties ◽  
Community Composition ◽  
Crop Yield ◽  
Bacterial Community Composition ◽  
Soil Physicochemical Properties
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