Ecological and evolutionary forces shaping microbial diversity in the human intestine.

Summary
Soil is a complex and dynamic biological system, and still in 2003 it is difficult to determine the composition of microbial communities in soil. We are also limited in the determination of microbially mediated reactions because present assays for determining the overall rate of entire metabolic processes (such as respiration) or specific enzyme activities (such as urease, protease and phosphomonoesterase activity) do not allow any identification of the microbial species directly involved in the measured processes. The central problem posed by the link between microbial diversity and soil function is to understand the relations between genetic diversity and community structure and between community structure and function. A better understanding of the relations between microbial diversity and soil functions requires not only the use of more accurate assays for taxonomically and functionally characterizing DNA and RNA extracted from soil, but also high-resolution techniques with which to detect inactive and active microbial cells in the soil matrix.

Soil seems to be characterized by a redundancy of functions; for example, no relationship has been shown to exist between microbial diversity and decomposition of organic matter. Generally, a reduction in any group of species has little effect on overall processes in soil because other microorganisms can take on its function.

The determination of the composition of microbial communities in soil is not necessary for a better quantification of nutrient transformations. The holistic approach, based on the division of the systems in pools and the measurement of fluxes linking these pools, is the most efficient. The determination of microbial C, N, P and S contents by fumigation techniques has allowed a better quantification of nutrient dynamics in soil. However, further advances require determining new pools, such as active microbial biomass, also with molecular techniques. Recently investigators have separated 13C- and 12C-DNA, both extracted from soil treated with a 13C source, by density-gradient centrifugation. This technique should allow us to calculate the active microbial C pool by multiplying the ratio between labelled and total DNA by the microbial biomass C content of soil. In addition, the taxonomic and functional characterization of 13C-DNA allows us to understand more precisely the changes in the composition of microbial communities affected by the C-substrate added to soil.

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Microbial diversity and soil functions

Microbial metabolism powers biogeochemical cycling in Earth’s ecosystems. The taxonomic composition of microbial communities varies substantially between environments, but the ecological causes of this variation remain largely unknown. We analyzed taxonomic and functional community profiles to determine the factors that shape marine bacterial and archaeal communities across the global ocean. By classifying >30,000 marine microorganisms into metabolic functional groups, we were able to disentangle functional from taxonomic community variation. We find that environmental conditions strongly influence the distribution of functional groups in marine microbial communities by shaping metabolic niches, but only weakly influence taxonomic composition within individual functional groups. Hence, functional structure and composition within functional groups constitute complementary and roughly independent “axes of variation” shaped by markedly different processes.

http://science.sciencemag.org/content/sci/353/6305/1272.full.pdf

Decoupling function and taxonomy in the global ocean microbiome

Microbial fuel cells hold great promise as a sustainable biotechnological solution to future energy needs. Current efforts to improve the efficiency of such fuel cells are limited by the lack of knowledge about the microbial ecology of these systems. The purposes of this study were (i) to elucidate whether a bacterial community, either suspended or attached to an electrode, can evolve in a microbial fuel cell to bring about higher power output, and (ii) to identify species responsible for the electricity generation. Enrichment by repeated transfer of a bacterial consortium harvested from the anode compartment of a biofuel cell in which glucose was used increased the output from an initial level of 0.6 W m−2 of electrode surface to a maximal level of 4.31 W m−2 (664 mV, 30.9 mA) when plain graphite electrodes were used. This result was obtained with an average loading rate of 1 g of glucose liter−1 day−1 and corresponded to 81% efficiency for electron transfer from glucose to electricity. Cyclic voltammetry indicated that the enhanced microbial consortium had either membrane-bound or excreted redox components that were not initially detected in the community. Dominant species of the enhanced culture were identified by denaturing gradient gel electrophoresis and culturing. The community consisted mainly of facultative anaerobic bacteria, such as Alcaligenes faecalis and Enterococcus gallinarum, which are capable of hydrogen production. Pseudomonas aeruginosa and other Pseudomonas species were also isolated. For several isolates, electrochemical activity was mainly due to excreted redox mediators, and one of these mediators, pyocyanin produced by P. aeruginosa, could be characterized. Overall, the enrichment procedure, irrespective of whether only attached or suspended bacteria were examined, selected for organisms capable of mediating the electron transfer either by direct bacterial transfer or by excretion of redox components.

https://espace.library.uq.edu.au/view/UQ:164735/UQ164735_OA.pdf

Biofuel Cells Select for Microbial Consortia That Self-Mediate Electron Transfer

Freshwater bacteria are at the hub of biogeochemical cycles and control water quality in lakes. Despite this, little is known about the identity and ecology of functionally significant lake bacteria. Molecular studies have identified many abundant lake bacteria, but there is a large variation in the taxonomic or phylogenetic breadths among the methods used for this exploration. Because of this, an inconsistent and overlapping naming structure has developed for freshwater bacteria, creating a significant obstacle to identifying coherent ecological traits among these groups. A discourse that unites the field is sorely needed. Here we present a new freshwater lake phylogeny constructed from all published 16S rRNA gene sequences from lake epilimnia and propose a unifying vocabulary to discuss freshwater taxa. With this new vocabulary in place, we review the current information on the ecology, ecophysiology, and distribution of lake bacteria and highlight newly identified phylotypes. In the second part of our review, we conduct meta-analyses on the compiled data, identifying distribution patterns for bacterial phylotypes among biomes and across environmental gradients in lakes. We conclude by emphasizing the role that this review can play in providing a coherent framework for future studies.

A Guide to the Natural History of Freshwater Lake Bacteria

The microbial community dynamics of a functionally stable, well-mixed, methanogenic reactor fed with glucose were analyzed over a 605-day period. The reactor maintained constant pH and chemical oxygen demand removal during this period. Thirty-six rrn clones from each of seven sampling events were analyzed by amplified ribosomal DNA restriction analysis (ARDRA) for the Bacteria and Archaea domains and by sequence analysis of dominant members of the community. Operational taxonomic units (OTUs), distinguished as unique ARDRA patterns, showed reproducible distribution for three sample replicates. The highest diversity was observed in the Bacteria domain. The 16S ribosomal DNA Bacteria clone library contained 75 OTUs, with the dominant OTU accounting for 13% of the total clones, but just 21 Archaea OTUs were found, and the most prominent OTU represented 50% of the clones from the respective library. Succession in methanogenic populations was observed, and two periods were distinguished: in the first, Methanobacterium formicicum was dominant, and in the second, Methanosarcina mazei and a Methanobacterium bryantii-related organism were dominant. Higher variability in Bacteria populations was detected, and the temporal OTU distribution suggested a chaotic pattern. Although dominant OTUs were constantly replaced from one sampling point to the next, phylogenetic analysis indicated that inferred physiologic changes in the community were not as dramatic as were genetic changes. Seven of eight dominant OTUs during the first period clustered with the spirochete group, although a cyclic pattern of substitution occurred among members within this order. A more flexible community structure characterized the second period, since a sequential replacement of a Eubacterium-related organism by an unrelated deep-branched organism and finally by a Propionibacterium-like species was observed. Metabolic differences among the dominant fermenters detected suggest that changes in carbon and electron flow occurred during the stable performance and indicate that an extremely dynamic community can maintain a stable ecosystem function.

How stable is stable? Function versus community composition.

Objective: A CGM sensor that is disposable and requires no calibration may make glucose management easier for people living with diabetes. The present study reports on the interim analysis of a new disposable zero-calibration sensor in adults and youth with type 1 (T1D) or type 2 diabetes (T2D) .
 Methods: A prospective study enrolled individuals (N=123 adults, aged 18-80 years and N=120 youth, aged 2-17 years) with diabetes at 13 sites in the United States. Raw sensor data were compared with a YSI (Yellow Springs Instruments) or blood glucose (BG) reference and involved N=15388 paired points (pps) from the arm of adults, and N=8627pps from the arm and 7781pps from the buttock of youth. Data were processed using a new zero-calibration algorithm. The primary endpoint was agreement within 20%/20mg/dL (sensor glucose [SG] ≥80mg/dL/<80mg/dL) . Multiple secondary and descriptive endpoints included agreement within 15%/15mg/dL (SG ≥70mg/dL/<70mg/dL) and the mean absolute relative difference (MARD) for the adult arm location and youth arm and buttock locations.
 Results: The overall 20%/20mg/dL agreement rate was 90.6% for adults, and 87.8% and 88.5% for youth arm and buttock, respectively. For adults, the 15%/15mg/dL agreement rates were 90.1% and 87.6% (SG <70 mg/dL and SG >180 mg/dL, respectively) . For youth, the 15%/15mg/dL rates were 93.2% and 86.5% for the arm (SG <70 mg/dL and SG >180 mg/dL, respectively) and 90.3% and 89.5% for the buttock (SG <70 mg/dL and SG>180 mg/dL, respectively) . The MARDs were 10.2% for adults, and 10.7% and 10.1% for youth arm and buttock, respectively.
 Conclusion: These interim findings on the clinical performance of the new disposable and calibration-free sensor are good and may support non-adjunctive insulin dosing in standalone CGM and automated insulin delivery systems.
 
 
 B.W.Bode: Advisory Panel; CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Zealand Pharma A/S, Consultant; Bigfoot Biomedical, Inc., Research Support; Abbott, Beta Bionics, Inc., Dexcom, Inc., Diasome, Dompé, Eli Lilly and Company, Insulet Corporation, IQVIA Inc., Jaeb Center for Health Research, Medtronic, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanvita Medical, Senseonics, ViaCyte, Inc., Speaker’s Bureau; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Insulet Corporation, MannKind Corporation, Novo Nordisk, Sanofi, Xeris Pharmaceuticals, Inc., Stock/Shareholder; AgaMatrix, Glytec, LLC. J.Shin: Employee; Medtronic. F.Peng: None. S.Huang: n/a. A.S.Rhinehart: Employee; Medtronic, Stock/Shareholder; Medtronic. R.A.Vigersky: Employee; Medtronic. T.S.Bailey: Advisory Panel; Abbott Diabetes, CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Consultant; LifeScan, Sanofi, Research Support; Abbott Diabetes, Abbott Diagnostics, Biolinq, Capillary Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Kowa Research Institute, Inc., Livongo, MannKind Corporation, Medtronic, Novo Nordisk, REMD Biotherapeutics, Sanofi, Sanvita Medical, Senseonics, ViaCyte, Inc., vTv Therapeutics, Zealand Pharma A/S, Speaker’s Bureau; Becton, Dickinson and Company, Medtronic, Sanofi. K.N.Castorino: Consultant; Lilly Diabetes, Research Support; Abbott Diabetes, Dexcom, Inc., Drawbridge Health, Inc., Eyenuk, Inc., Laxmi Therapeutic Devices, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Speaker’s Bureau; Dexcom, Inc. M.P.Christiansen: Research Support; Abbott Diabetes, Ascensia Diabetes Care, AstraZeneca, Biolinq, Dexcom, Inc., Eli Lilly and Company, Helixmith, MannKind Corporation, Medtronic, Merck Sharp & Dohme Corp. S.K.Garg: Advisory Panel; Bayer AG, Medtronic, Zealand Pharma A/S, Consultant; Novo Nordisk, Research Support; Dexcom, Inc., Medtronic. K.B.Kaiserman: Advisory Panel; Medtronic, Consultant; Medtronic, Employee; MannKind Corporation, Research Support; Medtronic, Speaker’s Bureau; Medtronic, Stock/Shareholder; MannKind Corporation. D.R.Liljenquist: None. D.I.Shulman: Advisory Panel; Medtronic. R.H.Slover: None.


Suiying Huang

Papers

How stable is stable? Function versus community composition.

672-P: Performance of a New Disposable Zero-Calibration Continuous Glucose Monitoring (CGM) Sensor