scholarly journals Differential impact of top-down and bottom-up forces in structuring freshwater bacterial communities

2020 ◽  
Vol 96 (2) ◽  
Author(s):  
A S Pradeep Ram ◽  
J Keshri ◽  
T Sime-Ngando
Keyword(s):  
Nucleic Acid ◽  
Community Composition ◽  
Bacterial Communities ◽  
Bacterial Community Composition ◽  
Host Community ◽  
Heterotrophic Nanoflagellates ◽  
Rrna Gene ◽  
Top Down ◽  
Bottom Up ◽  
Host Diversity

ABSTRACT Limited data exist on the simultaneous impact of bottom-up (nutrients) and top-down (viruses and heterotrophic nanoflagellates) forces in shaping freshwater bacterial communities. In our laboratory microcosms, nutrient additions (organic and inorganic) and viral reduction approach led to the proliferation of high nucleic acid (HNA) bacterial subpopulation without an increase in phage abundance. High viral-mediated bacterial lysis in the presence of nanoflagellates yielded high proportion of low nucleic acid bacterial subpopulation. 16S rRNA gene sequence analysis indicated that members of classes Proteobacteria and Bacteroidetes evoked differential responses to nutrients and mortality forces, thereby resulting in differences (P < 0.001) in bacterial community composition and diversity, as observed from analysis of similarities and UniFrac analysis. Bacterial species richness (Chao) and diversity (Shannon) index was significantly higher (P < 0.001) in the presence of both the top-down factors and viruses alone, whereas lower host diversity was observed under nutrient relaxation of growth-limiting substrates due to the explosive growth of opportunistic HNA bacterial subpopulation. Our results are in agreement with the theoretical model of ‘killing the winner’, where the availability of growth-limiting substrates can act as a stimulating factor for host community composition while top-down forces can operate in the control of host diversity.

scholarly journals Relationship between Bacterial Community Composition and Bottom-Up versus Top-Down Variables in Four Eutrophic Shallow Lakes

2002 ◽  
Vol 68 (10) ◽  
pp. 4740-4750 ◽  
Author(s):  
Koenraad Muylaert ◽  
Katleen Van der Gucht ◽  
Nele Vloemans ◽  
Luc De Meester ◽  
Moniek Gillis ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Shallow Lakes ◽  
Bacterial Community Composition ◽  
Top Down ◽  
Bottom Up ◽  
Rdna Genes ◽  
Explanatory Variables ◽  
High Nutrient ◽  
Eutrophic Shallow Lakes

ABSTRACT Bacterial community composition was monitored in four shallow eutrophic lakes during one year using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified prokaryotic rDNA genes. Of the four lakes investigated, two were of the clearwater type and had dense stands of submerged macrophytes while two others were of the turbid type characterized by the occurrence of phytoplankton blooms. One turbid and one clearwater lake had high nutrient levels (total phosphorus, >100 μg liter−1) while the other lakes had relatively low nutrient levels (total phosphorus, <100 μg liter−1). For each lake, seasonal changes in the bacterial community were related to bottom-up (resources) and top-down (grazers) variables by using canonical correspondence analysis (CCA). Using an artificial model dataset to which potential sources of error associated with the use of relative band intensities in DGGE analysis were added, we found that preferential amplification of certain rDNA genes over others does not obscure the relationship between bacterial community composition and explanatory variables. Besides, using this artificial dataset as well as our own data, we found a better correlation between bacterial community composition and explanatory variables by using relative band intensities compared to using presence/absence data. While bacterial community composition was related to phytoplankton biomass in the high-nutrient lakes no such relation was found in the low-nutrient lakes, where the bacterial community is probably dependent on other organic matter sources. We used variation partitioning to evaluate top-down regulation of bacterial community composition after bottom-up regulation has been accounted for. Using this approach, we found no evidence for top-down regulation of bacterial community composition in the turbid lakes, while grazing by ciliates and daphnids (Daphnia and Ceriodaphnia) was significantly related to changes in the bacterial community in the clearwater lakes. Our results suggest that in eutrophic shallow lakes, seasonality of bacterial community structure is dependent on the dominant substrate source as well as on the food web structure.

scholarly journals Fecal Bacterial Community of Allopatric Przewalski’s Gazelles and Their Sympatric Relatives

2021 ◽  
Vol 12 ◽  
Author(s):  
Ruoshuang Liu ◽  
Jianbin Shi ◽  
Susanne Shultz ◽  
Dongsheng Guo ◽  
Dingzhen Liu
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Communities ◽  
Bacterial Community Composition ◽  
Ecological Factors ◽  
Ovis Aries ◽  
Host Community ◽  
Tibetan Sheep ◽  
Fecal Bacterial Community ◽  
The Impact

Mammal gastrointestinal tracts harbor diverse bacterial communities that play important roles in digestion, development, behavior, and immune function. Although, there is an increasing understanding of the factors that affect microbial community composition in laboratory populations, the impact of environment and host community composition on microbiomes in wild populations is less understood. Given that the composition of bacterial communities can be shaped by ecological factors, particularly exposure to the microbiome of other individuals, inter-specific interactions should impact on microbiome community composition. Here, we evaluated inter-population and inter-specific similarity in the fecal microbiota of Przewalski’s gazelle (Procapra przewalskii), an endangered endemic ruminant around Qinghai Lake in China. We compared the fecal bacterial communities of three Przewalski’s gazelle populations, with those of two sympatric ruminants, Tibetan gazelle (Procapra picticaudata) and Tibetan sheep (Ovis aries). The fecal bacterial community richness (Chao1, ACE) did not vary across the three Przewalski’s gazelle populations, nor did the composition vary between species. In contrast, the managed Przewalski’s gazelle population had higher bacterial diversity (Shannon and Simpson) and was more similar to its sympatric Tibetan sheep in beta diversity than the wild Przewalski’s gazelle populations. These results suggest that ecological factors like host community composition or diet affect Przewalski’s gazelle’s gastrointestinal bacterial community. The role of bacterial community composition in maintaining gastrointestinal health should be assessed to improve conservation management of endangered Przewalski’s gazelle. More broadly, captive breeding and reintroduction efforts may be impeded, where captive management results in dysbiosis and introduction of pathogenic bacteria. In free ranging populations, where wildlife and livestock co-occur, infection by domestic pathogens and diseases may be an underappreciated threat to wild animals.

scholarly journals Impact of enzymatic digestion on bacterial community composition in CF airway samples

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3362 ◽  
Author(s):  
Kayla M. Williamson ◽  
Brandie D. Wagner ◽  
Charles E. Robertson ◽  
Emily J. Johnson ◽  
Edith T. Zemanick ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Dna Extraction ◽  
Community Composition ◽  
Bacterial Communities ◽  
Beta Diversity ◽  
Diversity Index ◽  
Bacterial Community Composition ◽  
Microbial Community Composition ◽  
Enzymatic Digestion ◽  
Rrna Gene

BackgroundPrevious studies have demonstrated the importance of DNA extraction methods for molecular detection ofStaphylococcus,an important bacterial group in cystic fibrosis (CF). We sought to evaluate the effect of enzymatic digestion (EnzD) prior to DNA extraction on bacterial communities identified in sputum and oropharyngeal swab (OP) samples from patients with CF.MethodsDNA from 81 samples (39 sputum and 42 OP) collected from 63 patients with CF was extracted in duplicate with and without EnzD. Bacterial communities were determined by rRNA gene sequencing, and measures of alpha and beta diversity were calculated. Principal Coordinate Analysis (PCoA) was used to assess differences at the community level and Wilcoxon Signed Rank tests were used to compare relative abundance (RA) of individual genera for paired samples with and without EnzD.ResultsShannon Diversity Index (alpha-diversity) decreased in sputum and OP samples with the use of EnzD. Larger shifts in community composition were observed for OP samples (beta-diversity, measured by Morisita-Horn), whereas less change in communities was observed for sputum samples. The use of EnzD with OP swabs resulted in significant increase in RA for the generaGemella(p < 0.01),Streptococcus(p < 0.01), andRothia(p < 0.01).Staphylococcus(p < 0.01) was the only genus with a significant increase in RA from sputum, whereas the following genera decreased in RA with EnzD:Veillonella(p < 0.01),Granulicatella(p < 0.01),Prevotella(p < 0.01), andGemella(p = 0.02). In OP samples, higher RA of Gram-positive taxa was associated with larger changes in microbial community composition.DiscussionWe show that the application of EnzD to CF airway samples, particularly OP swabs, results in differences in microbial communities detected by sequencing. Use of EnzD can result in large changes in bacterial community composition, and is particularly useful for detection ofStaphylococcusin CF OP samples. The enhanced identification ofStaphylococcus aureusis a strong indication to utilize EnzD in studies that use OP swabs to monitor CF airway communities.

Effects of geographic location and water quality on bacterial communities in full-scale biofilters across North America

2020 ◽  
Vol 96 (2) ◽  
Author(s):  
Ben Ma ◽  
Timothy M LaPara ◽  
Ashley N. Evans ◽  
Raymond M Hozalski
Keyword(s):  
Water Quality ◽  
North America ◽  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Community Composition ◽  
Bacterial Communities ◽  
Bacterial Community Composition ◽  
Geographic Location ◽  
Rrna Gene

ABSTRACT Spatial patterns of bacterial community composition often follow a distance–decay relationship in which community dissimilarity increases with geographic distance. Such a relationship has been commonly observed in natural environments, but less so in engineered environments. In this study, bacterial abundance and community composition in filter media samples (n = 57) from full-scale rapid biofilters at 14 water treatment facilities across North America were determined using quantitative polymerase chain reaction and Illumina HiSeq high-throughput sequencing targeting the 16S rRNA gene, respectively. Bacteria were abundant on the filter media (108.8±0.3 to 1010.7±0.2 16S rRNA gene copies/cm3 bed volume) and the bacterial communities were highly diverse (Shannon index: 5.3 ± 0.1 to 8.4 ± 0.0). Significant inter-filter variations in bacterial community composition were observed, with weighted UniFrac dissimilarity values following a weak but highly significant distance–decay relationship (z = 0.0057 ± 0.0006; P = 1.8 × 10−22). Approximately 50% of the variance in bacterial community composition was explained by the water quality parameters measured at the time of media sample collection (i.e. pH, temperature and dissolved organic carbon concentration). Overall, this study suggested that the microbiomes of biofilters are primarily shaped by geographic location and local water quality conditions but the influence of these factors on the microbiomes is tempered by filter design and operating conditions.

scholarly journals Machine learning for exploring microbial inter-kingdom associations in Cystic Fibrosis and Bronchiectasis

2022 ◽  
Author(s):  
Leah Cuthbertson ◽  
Jonathan Ish-horowicz ◽  
Imogen Felton ◽  
Phillip James ◽  
Elena Turek ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cystic Fibrosis ◽  
Community Composition ◽  
Fungal Community ◽  
Bacterial Communities ◽  
Bacterial Community Composition ◽  
Disease Status ◽  
Fungal Disease ◽  
Rrna Gene ◽  
Fungal Community Composition

Background: Cystic fibrosis (CF) and non-CF bronchiectasis (BX) are lung diseases characterised by severe chronic infections. Fungal and bacterial components of infection are both recognized. Recent molecular investigation of sputum from patients with CF and BX has revealed a complex mycobiome. However, little is known about how fungal and bacterial organisms interact or whether the interactions impact on disease outcomes. Methods: Quantitative PCR and next generation sequencing of ITS2 and 16S rRNA gene was carried out on 107 patients with CF and BX and defined clinical fungal infection status. Fungal and bacterial communities were explored using supervised and unsupervised machine learning to understand associations between fungal and bacterial communities and their relationship to disease. Results: Fungal and bacterial communities both had significantly higher biomass and lower diversity in CF compared to BX patients. Random forest modelling demonstrated that the fungal and bacterial communities were distinct between CF and BX patients. Within the CF group, bacterial communities contained no predictive signal for fungal disease status. Neither bacterial nor fungal community composition were predictive of the presence of CF pulmonary exacerbation (CFPE). Intra-kingdom correlations were far stronger than those between the two kingdoms. Dirichlet mixture components analysis identified two distinct clusters of bacteria related to the relative abundance of Pseudomonas. Fungal community composition contained no predictive signal for bacterial clusters. Conclusions: Clear changes in diversity were observed between patients with different clinical disease status. Although our results demonstrate that bacterial community composition differs in the presence of fungal disease, no direct relationship between bacterial and fungal OTUs was found.

scholarly journals Bottom-up and top-down control of bacterial community composition in the euphotic zone of a reservoir

2004 ◽  
Vol 35 ◽  
pp. 259-273 ◽  
Author(s):  
L Jardillier ◽  
M Basset ◽  
I Domaizon ◽  
A Belan ◽  
C Amblard ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Community Composition ◽  
Euphotic Zone ◽  
Top Down ◽  
Bottom Up

scholarly journals Rapid, inexpensive measurement of synthetic bacterial community composition by Sanger sequencing

2018 ◽  
Author(s):  
Nathan Cermak ◽  
Manoshi Sen Datta ◽  
Arolyn Conwill
Keyword(s):  
Bacterial Community ◽  
Microbial Ecology ◽  
Community Composition ◽  
Bacterial Communities ◽  
Sanger Sequencing ◽  
Bacterial Community Composition ◽  
Marker Gene ◽  
Compositional Analysis ◽  
Time Variability ◽  
Rrna Gene

AbstractSimple synthetic bacterial communities are powerful tools for studying microbial ecology and evolution, as they enable rapid iteration between controlled laboratory experiments and theoretical modeling. However, their utility is hampered by the lack of fast, inexpensive, and accurate methods for quantifying bacterial community composition. For instance, while next-generation amplicon sequencing can be very accurate, high costs (>$30 per sample) and turnaround times (>1 month) limit the nature and pace of experiments. Here, we introduce a new approach for quantifying composition in synthetic bacterial communities based on Sanger sequencing. First, for a given community, we PCR-amplify a universal marker gene (here, the 16S rRNA gene), which yields a mixture of amplicons. Second, we sequence this amplicon mixture in a single Sanger sequencing reaction, which produces a “mixed” electropherogram with contributions from each community member. We also sequence each community member’s marker gene individually to generate “individual” electropherograms. Third, we fit the mixed electropherogram as a linear combination of time-warped individual electropherograms, thereby allowing us to estimate the fractional amplicon abundance of each strain within the community. Importantly, our approach accounts for retention-time variability in electrophoretic signals, which is crucial for accurate compositional estimates. Using synthetic communities of marine bacterial isolates, we show that this approach yields accurate and reproducible abundance estimates for two-, four-, and seven-strain bacterial communities. Furthermore, this approach can provide results within one day and costs ~$5 USD per sample. We envision this approach will enable new insights in microbial ecology by increasing the number of samples that can be analyzed and enabling faster iteration between experiments and theory. We have implemented our method in a free and open-source R package called CASEU (“Compositional Analysis by Sanger Electropherogram Unmixing”), available at https://bitbucket.org/DattaManoshi/caseu.

scholarly journals The bacterial community composition and its environmental drivers in the rivers around eutrophic Chaohu Lake, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Keqiang Shao ◽  
Xin Yao ◽  
Zhaoshi Wu ◽  
Xingyu Jiang ◽  
Yang Hu ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Communities ◽  
Bacterial Community Composition ◽  
Cyanobacterial Blooms ◽  
Environmental Drivers ◽  
Chaohu Lake ◽  
Rrna Gene ◽  
Functional Profiles ◽  
16 S Rrna

Abstract Background Bacterial community play a key role in environmental and ecological processes in river ecosystems. Rivers are used as receiving body for treated and untreated urban wastewaters that brings high loads of sewage and excrement bacteria. However, little is known about the bacterial community structure and functional files in the rivers around the eutrophic Chaohu Lake, the fifth largest freshwater lake in China, has been subjected to severe eutrophication and cyanobacterial blooms over the past few decades. Therefore, understanding the taxonomic and functional compositions of bacterial communities in the river will contribute to understanding aquatic microbial ecology. The main aims were to (1) examine the structure of bacterial communities and functional profiles in this system; (2) find the environmental factors of bacterial community variations. Results We studied 88 sites at rivers in the Chaohu Lake basin, and determined bacterial communities using Illumina Miseq sequencing of the 16 S rRNA gene, and predicted functional profiles using PICRUSt2. A total of 3,390,497 bacterial 16 S rRNA gene sequences were obtained, representing 17 phyla, and 424 genera; The dominant phyla present in all samples were Bacteroidetes (1.4-82.50 %), followed by Proteobacteria (12.6–97.30 %), Actinobacteria (0.1–17.20 %). Flavobacterium was the most numerous genera, and accounted for 0.12–80.34 % of assigned 16 S reads, followed by Acinetobacter (0.33–49.28 %). Other dominant bacterial genera including Massilia (0.06–25.40 %), Psychrobacter (0-36.23 %), Chryseobacterium (0.01–22.86 %), Brevundimonas (0.01–12.82 %), Pseudomonas (0-59.73 %), Duganella (0.08–23.37 %), Unidentified Micrococcaceae (0-8.49 %). The functional profiles of the bacterial populations indicated an relation with many human diseases, including infectious diseases. Overall results, using the β diversity measures, coupled with heatmap and RDA showed that there were spatial variations in the bacterial community composition at river sites, and Chemical oxygen demand (CODMn) and (NH4+ )were the dominant environmental drivers affecting the bacterial community variance. Conclusions The high proportion of the opportunistic pathogens (Acinetobacter, Massilia, Brevundimonas) indicated that the discharge of sewage without adequate treatment into the rivers around Chaohu Lake. We propose that these bacteria could be more effective bioindicators for long-term sewage monitoring in eutrophic lakes.

scholarly journals Bacterial community composition and dynamics spanning five years in freshwater bog lakes

2017 ◽  
Author(s):  
Alexandra M. Linz ◽  
Benjamin C. Crary ◽  
Ashley Shade ◽  
Sarah Owens ◽  
Jack A. Gilbert ◽  
...  
Keyword(s):  
Time Series ◽  
Bacterial Community ◽  
Community Composition ◽  
Bacterial Communities ◽  
Community Dynamics ◽  
Bacterial Community Composition ◽  
Rrna Gene ◽  
Bacterial Community Dynamics ◽  
Bog Lakes

AbstractBacteria play a key role in freshwater biogeochemical cycling, but long-term trends in freshwater bacterial community composition and dynamics are not yet well characterized. We used a multi-year time series of 16S rRNA gene amplicon sequencing data from eight bog lakes to census the freshwater bacterial community and observe annual and seasonal trends in abundance. Multiple sites and sampling events were necessary to begin to fully describe the bacterial communities. Each lake and layer contained a distinct bacterial community, with distinct levels of richness and indicator taxa that likely reflected the environmental conditions of each site. The community present in each year and site was also unique. Despite high interannual variability in community composition, we detected a core community of ubiquitous freshwater taxa. Although trends in abundance did not repeat annually, each freshwater lineage within the communities had a consistent lifestyle, defined by persistence, abundance, and variability. The results of our analysis emphasize the importance of long-term observations, as analyzing only a single year of data would not have allowed us to describe the dynamics and composition of these freshwater bacterial communities to the extent presented here.ImportanceLakes are excellent systems for investigating bacterial community dynamics because they have clear boundaries and strong environmental gradients. The results of our research demonstrate that bacterial community dynamics operate on multi-year timescales, a finding which likely applies to other ecosystems, with implications for study design and interpretation. Understanding the drivers and controls of bacterial communities on long time scales would improve both our knowledge of fundamental properties of bacterial communities, and our ability to predict community states. In this specific ecosystem, bog lakes play a disproportionately large role in global carbon cycling, and the information presented here may ultimately help refine carbon budgets for these lakes. Finally, all data and code in this study are publicly available. We hope that this will serve as a resource to anyone seeking to answer their own microbial ecology questions using a multi-year time series.

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