scholarly journals Regime Transition Shapes the Composition, Assembly Processes and Co-Occurrence Pattern of Bacterioplankton Community in a Large Eutrophic Freshwater Lake

2021 ◽  
Author(s):  
Xinyi Cao ◽  
Dayong Zhao ◽  
Lisa Röttjers ◽  
Karoline Faust ◽  
Hongjie Zhang
Keyword(s):  
Community Composition ◽  
Regime Shift ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Nutrient Concentrations ◽  
Rrna Gene ◽  
Network Clustering ◽  
Regime Transition ◽  
Bacterioplankton Community ◽  
Occurrence Pattern

Abstract At certain nutrient concentrations, shallow freshwater lakes are generally characterized by two contrasting ecological regimes with disparate patterns of biodiversity and biogeochemical cycles: a macrophyte-dominated regime (MDR) and a phytoplankton-dominated regime (PDR).To reveal ecological mechanisms that affect bacterioplankton along the regime shift, Illumina MiSeq sequencing of the 16S rRNA gene combined with a novel network clustering tool (Manta) were used to identify patterns of bacterioplankton community composition across the regime shift in Taihu Lake, China. Marked divergence in the composition and ecological assembly processes of bacterioplankton community were observed under the regime shift. The alpha diversity of bacterioplankton community was observed to consistently and continuously decrease with the regime shift from MDR to PDR, while the beta diversity presents the opposite. Moreover, as the regime shifted from MDR to PDR, the contribution of deterministic processes first decreased and then increased again closer to the PDR, most likely as a consequence of differences in nutrient concentration. The topological properties of bacterioplankton co-occurrence networks along the regime shift differed, and the co-occurrences among species changed in structure and were significantly shaped by the environmental variables along the regime transition from MDR to PDR. The divergent environmental state of the regimes with diverse nutritional status may be the most important factor that contributes to the dissimilarity of bacterioplankton community composition along the regime shift and could be represented by phosphorus concentrations as well as several indicator species.

scholarly journals 22 Comparison of vaginal microbiome and concentrations of estradiol at artificial insemination in Brangus heifers

2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 41-42
Author(s):  
Riley D Messman ◽  
Zully Contreras-Correa ◽  
Henry A Paz ◽  
George Perry ◽  
Caleb O Lemley
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Artificial Insemination ◽  
Diversity Index ◽  
Bacterial Community Composition ◽  
Principal Component ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Rrna Gene ◽  
Vaginal Microbiome

Abstract The knowledge surrounding the bovine vaginal microbiome and its implications on fertility and reproductive traits remains incomplete. The objective of the current study was to characterize the bovine vaginal microbiome and estradiol concentrations at time of artificial insemination (AI). Brangus heifers (n = 78) underwent a 7-d Co-Synch + CIDR estrus synchronization protocol. At AI, a double guarded uterine culture swab was used to sample the anterior vaginal tract. Blood samples were collected by coccygeal venipuncture to determine concentrations of estradiol. Heifers were retrospectively classified as pregnant (n = 29) versus nonpregnant (n = 49) on day 35. Lastly, heifers were classified into low (1.1 - 2.5 pg/ml; n = 21), medium (2.6 - 6.7 pg/ml; n = 30), and high (7.2 - 17.6 pg/ml; n = 27) concentrations of estradiol. The vaginal bacterial community composition was determined through sequencing of the V4-V5 region from the 16S rRNA gene using the Illumina Miseq platform. ANOVA was used to compare the diversity metrics between treatment groups. PERMANOVA was utilized to determine variation in community structure. There were no statistical differences in the Shannon diversity index (alpha diversity; P = 0.336) or principal component analysis (beta diversity; P = 0.744) of pregnant versus nonpregnant animals. The vaginal microbiome of pregnant and nonpregnant animals was similar with the four most abundant phyla being Tenericutes, Proteobacteria, Fusobacteria, and Firmicutes. Overall bacterial community composition in animals with high, medium, or low concentrations of estradiol did not differ (P = 0.512). These results indicate that concentration of estradiol does not impact vaginal microbiome composition. In conclusion, the composition of the bovine vaginal microbiome, although dynamic, may not be directly linked to an animal’s reproductive ability.

scholarly journals 23 Comparison of vaginal microbiome and concentrations of estradiol at artificial insemination in Brangus heifers

2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 14-15
Author(s):  
Riley D Messman ◽  
Zully Contreras-Correa ◽  
Henry A Paz ◽  
George Perry ◽  
Caleb O Lemley
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Artificial Insemination ◽  
Diversity Index ◽  
Bacterial Community Composition ◽  
Principal Component ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Rrna Gene ◽  
Vaginal Microbiome

Abstract The knowledge surrounding the bovine vaginal microbiome and its implications on fertility and reproductive traits remains incomplete. The objective of the current study was to characterize the bovine vaginal microbiome and estradiol concentrations at time of artificial insemination (AI). Brangus heifers (n = 78) underwent a 7-day Co-Synch + CIDR estrus synchronization protocol. At AI, a double guarded uterine culture swab was used to sample the anterior vaginal tract. Blood samples were collected by coccygeal venipuncture to determine concentrations of estradiol. Heifers were retrospectively classified as pregnant (n = 29) versus nonpregnant (n = 49) on day 35. Lastly, heifers were classified into low (1.1 - 2.5 pg/ml; n = 21), medium (2.6 - 6.7 pg/ml; n = 30), and high (7.2 - 17.6 pg/ml; n = 27) concentrations of estradiol. The vaginal bacterial community composition was determined through sequencing of the V4-V5 region from the 16S rRNA gene using the Illumina Miseq platform. ANOVA was used to compare the diversity metrics between treatment groups. PERMANOVA was utilized to determine variation in community structure. There were no statistical differences in the Shannon diversity index (alpha diversity; P = 0.336) or principal component analysis (beta diversity; P = 0.744) of pregnant versus nonpregnant animals. The vaginal microbiome of pregnant and nonpregnant animals was similar with the four most abundant phyla being Tenericutes, Proteobacteria, Fusobacteria, and Firmicutes. Overall bacterial community composition in animals with high, medium, or low concentrations of estradiol did not differ (P = 0.512). These results indicate that concentration of estradiol does not impact vaginal microbiome composition. In conclusion, the composition of the bovine vaginal microbiome, although dynamic, may not be directly linked to an animal’s reproductive ability.

scholarly journals Comparative analysis of bacterioplankton assemblages from two subtropical karst reservoirs of southwestern China with contrasting trophic status

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qiang Li ◽  
Yadan Huang ◽  
Shenglin Xin ◽  
Zhongyi Li
Keyword(s):  
Trophic Status ◽  
Alpha Diversity ◽  
Decisive Role ◽  
Sensu Stricto ◽  
Karst Area ◽  
Southwestern China ◽  
Rrna Gene ◽  
Karst Water ◽  
Bacterioplankton Community ◽  
Generation Sequencing

AbstractAlthough bacterioplankton play an important role in aquatic ecosystems, less is known about bacterioplankton assemblages from subtropical karst reservoirs of southwestern China with contrasting trophic status. Here, 16S rRNA gene next-generation sequencing coupled with water chemistry analysis was applied to compare the bacterioplankton communities from a light eutrophic reservoir, DL Reservoir, and a mesotrophic reservoir, WL Reservoir, in subtropical karst area of southwestern China. Our findings indicated that Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, Cyanobacteria and Verrucomicrobia dominated bacterioplankton community with contrasting relative frequency in the two subtropical karst reservoirs. Proteobacteria and Bacteroidetes were the core communities, which played important roles in karst biogeochemical cycles. Though WT, TN and DOC play the decisive role in assembling karst aquatic bacterioplankton, trophic status exerted significantly negative direct effects on bacterioplankton community composition and alpha diversity. Due to contrasting trophic status in the two reservoirs, the dominant taxa such as Enterobacter, Clostridium sensu stricto, Candidatus Methylacidiphilum and Flavobacteriia, that harbor potential functions as valuable and natural indicators of karst water health status, differed in DL Reservoir and WL Reservoir.

scholarly journals Effect of Bovine MFGM and LF in Infant Formula on Gut Microbiome and Metabolome at Four Months of Age

2021 ◽  
Author(s):  
Maciej Chichlowski ◽  
Nicholas Bokulich ◽  
Cheryl L Harris ◽  
Jennifer L Wampler ◽  
Fei Li ◽  
...  
Keyword(s):  
Infant Formula ◽  
Beta Diversity ◽  
Milk Fat ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Rrna Gene ◽  
Term Infants ◽  
Linear Discriminant ◽  
Alpha And Beta Diversity ◽  
Metabolite Profiles

Abstract Background Milk fat globule membrane (MFGM) and lactoferrin (LF) are human milk bioactive components demonstrated to support gastrointestinal (GI) and immune development. Significantly fewer diarrhea and respiratory-associated adverse events through 18 months of age were previously reported in healthy term infants fed a cow's milk-based infant formula with added source of bovine MFGM and bovine LF through 12 months of age. Objectives To compare microbiota and metabolite profiles in a subset of study participants. Methods Stool samples were collected at Baseline (10–14 days of age) and Day 120 (MFGM + LF: 26, Control: 33). Bacterial community profiling was performed via16S rRNA gene sequencing (Illumina MiSeq) and alpha and beta diversity were analyzed (QIIME 2). Differentially abundant taxa were determined using Linear discriminant analysis effect size (LefSE) and visualized (Metacoder). Untargeted stool metabolites were analyzed (HPLC/mass spectroscopy) and expressed as the fold-change between group means (Control: MFGM + LF ratio). Results Alpha diversity increased significantly in both groups from baseline to 4 months. Subtle group differences in beta diversity were demonstrated at 4 months (Jaccard distance; R2 = 0.01, P = 0.042). Specifically, Bacteroides uniformis and Bacteroides plebeius were more abundant in the MFGM + LF group at 4 months. Metabolite profile differences for MFGM + LF vs Control included: lower fecal medium chain fatty acids, deoxycarnitine, and glycochenodeoxycholate, and some higher fecal carbohydrates and steroids (P < 0.05). After applying multiple test correction, the differences in stool metabolomics were not significant. Conclusions Addition of bovine MFGM and LF in infant formula was associated with subtle differences in stool microbiome and metabolome by four months of age, including increased prevalence of Bacteroides species. Stool metabolite profiles may be consistent with altered microbial metabolism. Trial registration:  https://clinicaltrials.gov/ct2/show/NCT02274883).

scholarly journals PSXIII-29 Farm of origin has a major influence on the colonic microbiome but alterations due to selection for feed efficiency are also evident

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 475-475
Author(s):  
Stafford Vigors ◽  
Torres Sweeney
Keyword(s):  
Feed Efficiency ◽  
Hypervariable Region ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Nutrient Digestibility ◽  
Major Influence ◽  
Rrna Gene ◽  
Diversity Analysis ◽  
Selection For

Abstract While the intestinal microbiota is functionally important in nutrient digestibility and animal performance, the role of the microbiome in influencing feed efficiency is not well characterised. The objective of this experiment was to determine the relative influence of feed efficiency and farm of origin on the pig colonic microbiome. Animals were sourced from two geographically distinct locations in Ireland (farm A + B) and evaluated to identify pigs divergent in feed efficiency. The 8 most efficient (LRFI) & 8 least efficient (HRFI) pigs from farm A and 12 LRFI & 12 HRFI pigs from farm B were slaughtered. Colonic digesta was collected for sequencing of the V3-V4 hypervariable region of the bacterial 16S rRNA gene was performed on the Illumina MiSeq. Alpha diversity differed between the farms in this study with pigs from farm A having greater diversity based on Shannon and InvSimpson measures compared to pigs from farm B (P < 0.05). In agreement with this observation, pigs grouped by farm of origin rather than RFI in the beta diversity analysis. However, despite variation between farms, interesting taxonomic differences were identified between RFI groups. Within the phylum Bacteroidetes, the LRFI pigs had increased abundance of two families BS11 (P < 0.05) and a tendency towards increased Bacteroidaceae (P < 0.10) relative to the HRFI group. At genus level, the LRFI pigs had a tendency towards increased Bacteroides and CF231 (P < 0.10). In conclusion, while farm of origin has a substantial influence on microbial diversity in the pig colon, a microbial signature indicative of feed efficiency status was evident.

Fecal microbiota in untreated children with Juvenile Idiopathic Arthritis – a comparison with healthy children and healthy siblings

2020 ◽  
pp. jrheum.200551
Author(s):  
Anders Öman ◽  
Johan Dicksved ◽  
Lars Engstrand ◽  
Lillemor Berntson
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
Community Composition ◽  
Alpha Diversity ◽  
Fecal Microbiota ◽  
Rrna Gene ◽  
Healthy Children ◽  
Healthy Controls ◽  
Α Diversity ◽  
Healthy Siblings ◽  
Relative Abundances

Objective Changes in the composition of gut microbiota has been suggested to be associated with Juvenile idiopathic arthritis (JIA). The objective in this study was to investigate if the diversity and composition of the fecal microbiota differed between children with JIA and healthy controls, and if the microbiota differed between children with JIA and their healthy siblings. Methods In this multicenter, case-control study, fecal samples were collected from 75 children with JIA and 32 healthy controls. Eight of the healthy controls were siblings to eight children with JIA and they were compared only pairwise with their siblings. The microbiota was determined using sequencing amplicons from the V3 and V4 regions of the 16S rRNA gene. Alpha diversity, community composition of microbiota and relative abundances of taxa were compared between children with JIA and healthy unrelated controls as well as between children with JIA and healthy siblings. Results Our data revealed no significant differences in α-diversity or community composition of microbiota between children with JIA, healthy unrelated controls or healthy siblings. Analyses of relative abundances of phyla, families and genera identified trends of differing abundances of some taxa in children with JIA, in comparison with both healthy controls and healthy siblings, but none of these findings were significant after adjustment for multiple comparisons. Conclusion There were no significant differences in the composition of fecal microbiota in children with JIA compared with healthy controls. The composition of microbiota in children with JIA did not differ significantly from that in their healthy siblings.

scholarly journals 83 Lifelong dynamics of the swine gut microbiome: from birth to market

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 48-48
Author(s):  
Xiaofan Wang ◽  
Tsung Cheng Tsai ◽  
Charles V Maxwell ◽  
Jiangchao Zhao
Keyword(s):  
Growth Performance ◽  
Gut Microbiome ◽  
Community Dynamics ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Shannon Index ◽  
Growth Stages ◽  
Rrna Gene ◽  
16 S Rrna

Abstract Despite the recent advances in the swine gut microbiomes during different growth stages, a comprehensive longitudinal study of the lifelong dynamics of the swine gut microbiome is lacking. To fill this gap of knowledge, we selected seventeen piglets (PIC29*380) that were born on the same date from three sows. We collected a total of 274 rectal swabs during lactation (d 0, 11, 20), nursery (d 27, 33, 41, 50, 61), growing (d 76, 90, 104, 116), and finishing (d 130, 146, 159, and 174) stages. Samples were extracted using the Powersoil DNA isolation kit (Qiagen, Hilden, Germany) and sequenced with an Illumina Miseq sequencer targeting the V4 region of the 16 S rRNA gene. Sequences were analyzed with the Deblur algorithm in the QIIME2 package. In general, alpha diversity including community richness (e.g., number of observed features, Chao1) and diversity (e.g., Shannon Index) showed an overall trend of increasing from lactation to the finishing stage (P < 0.01). Gradual and significant changes in community structures were also observed along the four growth stages (ANOSIM, R = 0.66; P < 0.01). Non-parametric permutational multivariate analysis of variance shows that main factors driving the lifelong community dynamics included age and diet. Seventeen phylum members were discovered in the lifelong pig gut microbiome with Firmicutes and Bacteroidetes being the most abundant phyla. LEfSe analysis revealed 63 bacterial features that are stage specific. By using a regressing tree based Random Forest model we identified five bacterial features that are associated with swine growth performance including features 26 (Turicibacteraceae Turicibacter), 27 (Clostridium butyricum), 18 (Clostridiaceae), 19 (Clostridium perfringens) and 4 (Clostridiaceae). Characterization of the lifelong dynamics of 17 healthy pigs from birth to market provides a foundation for gut microbiome studies focusing on swine development, health and growth performance.

scholarly journals Vaginal bacterial community composition and concentrations of estradiol at the time of artificial insemination in Brangus heifers

2020 ◽  
Vol 98 (6) ◽  
Author(s):  
Riley D Messman ◽  
Zully E Contreras-Correa ◽  
Henry A Paz ◽  
George Perry ◽  
Caleb O Lemley
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Artificial Insemination ◽  
Beta Diversity ◽  
Bacterial Community Composition ◽  
Alpha Diversity ◽  
Species Level ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Vaginal Tract

Abstract The knowledge surrounding the bovine vaginal microbiota and its implications on fertility and reproductive traits remains incomplete. The objective of the current study was to characterize the bovine vaginal bacterial community and estradiol concentrations at the time of artificial insemination (AI). Brangus heifers (n = 78) underwent a 7-d Co-Synch + controlled internal drug release estrus synchronization protocol. At AI, a double-guarded uterine culture swab was used to sample the anterior vaginal tract. Immediately after swabbing the vaginal tract, blood samples were collected by coccygeal venipuncture to determine concentrations of estradiol. Heifers were retrospectively classified as pregnant (n = 29) vs. nonpregnant (n = 49) between 41 and 57 d post-AI. Additionally, heifers were classified into low (1.1 to 2.5 pg/mL; n = 21), medium (2.6 to 6.7 pg/mL; n = 30), and high (7.2 to 17.6 pg/mL; n = 27) concentration of estradiol. The vaginal bacterial community composition was determined through sequencing of the V4 region from the 16S rRNA gene using the Illumina Miseq platform. Alpha diversity was compared via ANOVA and beta diversity was compared via PERMANOVA. There were no differences in the Shannon diversity index (alpha diversity; P = 0.336) or Bray–Curtis dissimilarity (beta diversity; P = 0.744) of pregnant vs. nonpregnant heifers. Overall, bacterial community composition in heifers with high, medium, or low concentrations of estradiol did not differ (P = 0.512). While no overall compositional differences were observed, species-level differences were present within pregnancy status and estradiol concentration groups. The implications of these species-level differences are unknown, but these differences could alter the vaginal environment thereby influencing fertility and vaginal health. Therefore, species-level changes could provide better insight rather than overall microbial composition in relation to an animal’s reproductive health.

scholarly journals Applications of Blocker Nucleic Acids and Non-Metazoan PCR Improves the Discovery of the Eukaryotic Microbiome in Ticks

2021 ◽  
Vol 9 (5) ◽  
pp. 1051
Author(s):  
Yurie Taya ◽  
Gohta Kinoshita ◽  
Wessam Mohamed Ahmed Mohamed ◽  
Mohamed Abdallah Mohamed Moustafa ◽  
Shohei Ogata ◽  
...  
Keyword(s):  
Nucleic Acids ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Miseq Platform ◽  
Pcr Method ◽  
Almost All ◽  
Tick Microbiome ◽  
Generation Sequencing

Ticks serve as important vectors of a variety of pathogens. Recently, the viral and prokaryotic microbiomes in ticks have been explored using next-generation sequencing to understand the physiology of ticks and their interactions with pathogens. However, analyses of eukaryotic communities in ticks are limited, owing to the lack of suitable methods. In this study, we developed new methods to selectively amplify microeukaryote genes in tick-derived DNA by blocking the amplification of the 18S rRNA gene of ticks using artificial nucleic acids: peptide nucleic acids (PNAs) and locked nucleic acids (LNAs). In addition, another PCR using non-metazoan primers, referred to as UNonMet-PCR, was performed for comparison. We performed each PCR using tick-derived DNA and sequenced the amplicons using the Illumina MiSeq platform. Almost all sequences obtained by conventional PCR were derived from ticks, whereas the proportion of microeukaryotic reads and alpha diversity increased upon using the newly developed method. Additionally, the PNA- or LNA-based methods were suitable for paneukaryotic analyses, whereas the UNonMet-PCR method was particularly sensitive to fungi. The newly described methods enable analyses of the eukaryotic microbiome in ticks. We expect the application of these methods to improve our understanding of the tick microbiome.

scholarly journals Resident microbes of lactation rooms and daycares

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8168
Author(s):  
Diana H. Taft ◽  
Samir Akre ◽  
Nicolas Madrid ◽  
Andre Knoesen ◽  
David A. Mills ◽  
...  
Keyword(s):  
Beta Diversity ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Shannon Index ◽  
Rrna Gene ◽  
Sample Collection ◽  
Unifrac Distance ◽  
Modern Development ◽  
Temperature And Humidity ◽  
The Impact

Dedicated lactation rooms are a modern development as mothers return to work while still providing breastmilk to their absent infants. This study describes the built environment microbiome of lactation rooms and daycares, and explores the influence of temperature and humidity on the microbiome of lactation rooms. Sterile swabs were used to collect samples from five different sites in lactation rooms at University of California, Davis and from five different sites in daycares located in Davis, California. DNA from the swabs was extracted and the V4 region of the 16S rRNA gene was sequenced using Illumina MiSeq. Temperature and relative humidity data were collected on a subset of the lactation rooms. Sampled lactation rooms could be either dedicated lactation rooms or could also serve other functions (e.g., combined lactation room and restroom lounge). The majority of sequence reads were identified as belonging to family Moraxellaceae, with 73% of all reads included in analysis identified as an unknown species of Acinetobacter. Alpha diversity was analyzed using the Shannon index, while beta diversity was analyzed using unweighted and weighted UniFrac distance. The Jaccard distance was used to measure amount of change at sampling locations between time points for analysis of the impact of temperature and humidity on the microbiome. There were significant differences in the beta diversity of the microbiome of lactation rooms by room type. There were also significant differences in the beta diversity of the microbiome by sample collection location. There were no significant differences in either alpha or beta diversity associated with room temperature or humidity. Additional studies are needed to understand if the differences in lactation room type may result in differences in the breastmilk microbiome of milk collected in those rooms, and to what extent any such differences may influence the infant microbiome.

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