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Microbiota Transplantation, Health Implications, and the Way Forward
Published in Nwadiuto (Diuto) Esiobu, James Chukwuma Ogbonna, Charles Oluwaseun Adetunji, Olawole O. Obembe, Ifeoma Maureen Ezeonu, Abdulrazak B. Ibrahim, Benjamin Ewa Ubi, Microbiomes and Emerging Applications, 2022
Olugbenga Samuel Michael, Olufemi Idowu Oluranti, Ayomide Michael Oshinjo, Charles Oluwaseun Adetunji, Juliana Bunmi Adetunji, Nwadiuto (Diuto) Esiobu
The human microbiome composition may now be fully characterized due to the recent advances in the microbiome research. The Human Microbiome Project (NIH HMP, 2009) makes use of sequencing methods to determine the genetic makeup of different gut microbiota. Hence, the entire intestinal microbes can now be elucidated from species to the phyla. Furthermore, the alpha diversity or mean species distribution present in a community can be determined in various ways such as rarefaction curves and species richness indices (Jost, 2007). Also, beta diversity meaning species difference between two varying microbial communities has been employed to show the variation of species in different communities of microbes. Therefore, the microbiota distribution and features have been connected to health status of host. Likewise, disturbed or distorted microbiome (dysbiosis) has been linked to various disease conditions like CDI, metabolic diseases, and fatty liver (van Nood et al., 2013; Lee et al., 2016; Youngster et al., 2016). New therapeutic approaches have emerged for the correction of impaired microbial homeostasis and they include prebiotics, probiotics, and fecal microbiota transplantation (FMT) which has the most potential and efficacy.
Design Options, Implementation Issues and Evaluating Success of Ecologically Engineered Shorelines
Published in S.J. Hawkins, A.L. Allcock, A.E. Bates, L.B. Firth, I.P. Smith, S.E. Swearer, P.A. Todd, Oceanography and Marine Biology, 2019
Rebecca L. Morris, Eliza C. Heery, Lynette H.L. Loke, Edward Lau, Elisabeth M.A. Strain, Laura Airoldi, Karen A. Alexander, Melanie J. Bishop, Ross A. Coleman, Jeffery R. Cordell, Yun-Wei Dong, Louise B. Firth, Stephen J. Hawkins, Tom Heath, Michael Kokora, Shing Yip Lee, Jon K. Miller, Shimrit Perkol-Finkel, Andrew Rella, Peter D. Steinberg, Ichiro Takeuchi, Richard C. Thompson, Peter A. Todd, Jason D. Toft, Kenneth M.Y. Leung
Diversity is a key theme in ecology, which underpins both the goals and assessment of many ecoengineered shoreline projects. It is frequently estimated as species richness (i.e. the total number of species present) and can be quantified at multiple spatial scales. While species richness within a habitat (alpha diversity) is useful in many instances, the compositional difference in species assemblages among habitats (beta diversity) is essential for achieving high diversity in a region (gamma diversity; Figure 1; Whittaker 1960, 1972). Specifying the scale at which ecoengineered shoreline designs aim to enhance diversity is crucial, as strategies for improving alpha and beta diversity may differ. Designs focussed on enhancing large-scale (landscape and regional scale—hundreds of metres—tens of kilometres) spatial heterogeneity and creation of various medium-scale habitat types (1–100 m) will have a positive effect on beta diversity. Those strategies focussed on increasing local-scale (<1 m) topographic and/or structural complexity (e.g. Coombes et al. 2015, Loke and Todd 2016) and ameliorating abiotic stressors (e.g. Browne & Chapman 2011, Evans et al. 2016) are more likely to have a positive effect on alpha diversity. Patches of more complex habitat, especially if they are of different types, among a background landscape of less complex habitats will also increase beta diversity (Firth et al. 2014, Evans et al. 2016).
Changes in Species Diversity in Peatlands Drained for Forestry
Published in Carl C. Trettin, Martin F. Jurgensen, David F. Grigal, Margaret R. Gale, John K. Jeglum, Northern Forested Wetlands, 2018
Harri Vasander, Raija Laiho, Jukka Laine
The diversity in Material 1 was measured using the Shannon index (H′ =−∑pilnpi, where pi is the proportion of the total biomass contributed by each species) (Shannon and Weaver, 1948). In Materials 2 and 3, the inverse of the Simpson diversity index (N2 = 1/∑pi where pi is the proportion of the total coverage contributed by each species) (Hill, 1973) was used. Both of these diversity indices measure the alpha-diversity (within-community diversity) of the sites. We used the beta- and gamma-diversity concepts (Whittaker, 1972; Figure 1) for the effect of species change on diversity. Beta-diversity in general is defined as the change in species composition along the environmental gradients within a habitat hyperspace (Whittaker, 1972). We determined beta-diversity as the difference (or separation in ordination diagrams) between the plant communities within a set of communities sampled from various peatlands within a particular geographical area. Gamma-diversity is an extension of the alpha-diversity to a regional (or landscape) level (Figure 1). Determined in this way, there is no need to analyze the distances between individual sites and the types of possible barrier (e.g., rivers, highways, etc.) existing between sites.
Effect of microaeration combined with ferric chloride pretreatment on anaerobic digestion of corn stalk
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2022
Zhiqiang Wang, Jinming Liu, Feng Tan
Alpha diversity reflects the species diversity of a single sample. The ACE and Chao1 index are used to estimate the total number of species in the sample, and the higher the value, the more species. Shannon and Simpson indexes are commonly used to reflect the diversity of alpha. The higher the Shannon value is, the higher the community diversity is, while the Simpson value is the opposite. From Table 6, the sequence numbers of CK were 45221–72453 for bacteria and 48967–55216 for archaea, with a total of 1143–1782 and 532–631 OTUs detected for bacteria and archaea at day 5, 15, and 25, respectively. Whereas the sequence numbers of MAFC were 48346−72950 for bacteria and 56085−58822 for archaea, with a total of 1031−2113 and 597–683 OTUs detected for bacteria and archaea, respectively. Higher Alpha diversity reflects better ecological stability and higher toxicity resistance during anaerobic digestion (Lu, Xing, and Ren 2012). Therefore, the application of MAFC pretreatment improved the stability of the anaerobic digestion system. In addition, the changes in ACE, Chao1, Shannon, and Simpson indexes also confirmed that MAFC was beneficial to the stability of anaerobic digestion.
Quinoline’s influence on nitrogen removal performance and microbial community composition of the anammox process
Published in Environmental Technology, 2019
Ting Yang, Qi-feng Liu, Qian Hao, Zhimin Fu
Shannon and Simpson diversity index were used to determine the alpha diversity which focuses on the number of species under local uniform habitat. Usually, the higher Shannon index infers the greater alpha diversity, while the Simpson diversity index reverses. Table 1 shows that the original sample (B0) had the highest diversity. The relative abundances were not homogeneous as Pielou’s evenness was 0.59, due to that ohtaekwangia and anammox microorganisms were selected and become dominant (Figure 6). There were remarkable changes in the relative abundance under quinoline stress and in the final recovery phase (B3). From B0 to B1, three indexes of the microbial community (richness, diversity and evenness) decreased, indicating that the consortia selected by quinoline matured gradually. In the recovery phase (from B2 to B3), the diversity and evenness of the microbial community first increase then decrease, except the richness, which kept increasing. Finally, the alpha diversity and evenness indices of B3 showed an obvious decrease, compared with B0 (before quinoline addition). However, Pereira et al. [13] reported that the taxa diversity in the reactor did not change by phenol addition. It was speculated due to different reactor configuration and different chemicals.
Elucidation of molecular diversity and functional characterization of phenanthrene degrading consortium NS-PAH-2015-PNP-5
Published in Bioremediation Journal, 2022
Suryakant Panchal, Arpita Ghosh, Prerana Koti, Namita Singh
Alpha diversity measures average species diversity in ecological and microorganism communities. Bioinformatics analysis for identification and assigning OTUs is a convenient method to measure species richness in metagenome samples. Therefore, the 273 OTUs identified in NS-PAH-2015-PNP-5 represent its alpha or species-level diversity. The Shannon–Wiener index (H') and Pielou's Evenness Index (J') in NS-PAH-2015-PNP-5 were calculated at 2.43 and 0.43, respectively. Table 1 shows data statistics of diversity analysis in NS-PAH-2015-PNP-5.