Microbial Population and Fermentation Characteristic in Response to Sapindus Rarak Mineral Block Supplementation

This experiment was conducted to evaluate the effect of supplementation with lerak extract combined with mineral block on protozoal and bacterial population, and fermentation characteristic in vitro. The experimental design was completely randomized block design with 3 treatments and 4 replications. Control diet was a substrate that consisted of concentrate, forage and feed block with ratio 50 : 48 : 2, respectively. The treatments as a substrate were: control diet (C), C + 0.09% lerak extract, and C + 0.18% lerak extract from the total ration. Variables observed were protozoal and bacterial population, dry matter and organic matter degradability, N-NH3 and total volatile fatty acid (VFA) concentration. Data were analyzed using analysis of variance (ANOVA). The result showed that there were no significant effect (P>0.05) for all parameter measured with lerak extract supplementation up to 0.18% in the presence of mineral block. However, supplementation of lerak extract 0.18% only slightly reduced protozoal numbers but tended to increase bacterial numbers. Dry matter and organic matter degradability and concentration of N-NH3 were similar among treatments. Volatile fatty acids profile changed which propionate tended to increase and acetate tended to decrease and ratio of acetate to propionate tended to decrease. In conclusion, addition of lerak extract up to 0.18% from total ration in the presence of mineral block was not yet effective to depress protozoal population, but could modify fermentation characteristic in vitro

Population–reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population–reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population–reaction model. We also show that population–reaction models can be applied to various ecological concepts, such as predator–prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms

A population-based microbial oscillator

Genetic oscillators are a major theme of interest in the emerging field of synthetic biology. Until recently, most work has been carried out using intra-cellular oscillators, but this approach restricts the broader applicability of such systems. Motivated by a desire to develop large-scale, spatially-distributed cell-based computational systems, we present an initial design for a population-level oscillator which uses three different bacterial strains. Our system is based on the client-server model familiar to computer science, and uses quorum sensing for communication between nodes. We present the results of extensive in silico simulation tests, which confirm that our design is both feasible and robust.Comment: Submitte

Microbial population dynamics in rubber coagula from Hevea brasiliensis

Natural rubber produced from the tree Hevea brasiliensis is a material of first importance for the tyre industry and for many other sectors such as the vibration isolation and the general rubber good industries. To produce TSR10 or 20 block rubber, trees are tapped, and the produced latex coagulates a few hours later in the collection cup. The fresh coagulate of natural rubber is then subjected to a maturation process that involves complex microbial populations. These microorganisms were shown to influence the biochemical composition and the properties of the final material [1]. This study intends to better understand the dynamics of microbial populations during the maturation process through culture-dependent and high-throughput culture-independent methods (454 pyrosequencing). (Résumé d'auteur

Interconnectivity of habitats in soil:combining X-ray micro tomography and thin sectioning to reveal fungal-soil structure interactions

The extreme heterogeneity and interconnectivity of the 3-dimensional pore space within soil makes it a unique habitat for the diverse microbial population and has a pivotal role in microbial interactions. Manipulation and quantification of the 3-dimensional pore space and the spatial distribution of micro-organisms is therefore essential if we are to fully understand microbial interactions. Here we pack soil microcosms at different bulk-densities to manipulate soil structure and use x-ray micro tomography and soil thin sections to analyse the effect on the connectivity of the pore volume and on fungal exploration

Microbial metabolism: optimal control of uptake versus synthesis

Microbes require several complex organic molecules for growth. A species may obtain a required factor by taking up molecules released by other species or by synthesizing the molecule. The patterns of uptake and synthesis set a flow of resources through the multiple species that create a microbial community. This article analyzes a simple mathematical model of the tradeoff between uptake and synthesis. Key factors include the influx rate from external sources relative to the outflux rate, the rate of internal decay within cells, and the cost of synthesis. Aspects of demography also matter, such as cellular birth and death rates, the expected time course of a local resource flow, and the associated lifespan of the local population. Spatial patterns of genetic variability and differentiation between populations may also strongly influence the evolution of metabolic regulatory controls of individual species and thus the structuring of microbial communities. The widespread use of optimality approaches in recent work on microbial metabolism has ignored demography and genetic structure

Microbial community changes induced by Managed Aquifer Recharge activities: linking hydrogeological and biological processes

Managed Aquifer Recharge (MAR) is a technique used worldwide to increase the availability of water resources. We study how MAR modifies microbial ecosystems and its implications for enhancing biodegradation processes to eventually improve groundwater quality. We compare soil and groundwater samples taken from a MAR facility located in NE Spain during recharge (with the facility operating continuously for several months) and after 4 months of no recharge. The study demonstrates a strong correlation between soil and water microbial prints with respect to sampling location along the mapped infiltration path. In particular, managed recharge practices disrupt groundwater ecosystems by modifying diversity indices and the composition of microbial communities, indicating that infiltration favors the growth of certain populations. Analysis of the genetic profiles showed the presence of nine different bacterial phyla in the facility, revealing high biological diversity at the highest taxonomic range. In fact, the microbial population patterns under recharge conditions agree with the intermediate disturbance hypothesis (IDH). Moreover, DNA sequence analysis of excised denaturing gradient gel electrophoresis (DGGE) band patterns revealed the existence of indicator species linked to MAR, most notably Dehalogenimonas sp., Nitrospira sp. and Vogesella sp.. Our real facility multidisciplinary study (hydrological, geochemical and microbial), involving soil and groundwater samples, indicates that MAR is a naturally based, passive and efficient technique with broad implications for the biodegradation of pollutants dissolved in water.Peer ReviewedPostprint (published version

Overcoming organic and nitrogen overload in thermophilic anaerobic digestion of pig slurry by coupling a microbial electrolysis cell

The combination of the anaerobic digestion (AD) process with a microbial electrolysis cell (MEC) coupled to an ammonia stripping unit as a post-treatment was assessed both in series operation, to improve the quality of the effluent, and in loop configuration recirculating the effluent, to increase the AD robustness. The MEC allowed maintaining the chemical oxygen demand removal of the whole system of 46 ± 5% despite the AD destabilization after doubling the organic and nitrogen loads, while recovering 40 ± 3% of ammonia. The AD-MEC system, in loop configuration, helped to recover the AD (55% increase in methane productivity) and attained a more stable and robust operation. The microbial population assessment revealed an enhancement of AD methanogenic archaea numbers and a shift in eubacterial population. The AD-MEC combined system is a promising strategy for stabilizing AD against organic and nitrogen overloads, while improving the quality of the effluent and recovering nutrients for their reutilization.Postprint (author's final draft

The Community Simulator: A Python package for microbial ecology

Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproducible, transparent and scalable way. The Community Simulator includes five major elements: tools for preparing the initial states and environmental conditions for a set of samples, automatic generation of dynamical equations based on a dictionary of modeling assumptions, random parameter sampling with tunable levels of metabolic and taxonomic structure, parallel integration of the dynamical equations, and support for metacommunity dynamics with migration between samples. To significantly speed up simulations using Community Simulator, our Python package implements a new Expectation-Maximization (EM) algorithm for finding equilibrium states of community dynamics that exploits a recently discovered duality between ecological dynamics and convex optimization. We present data showing that this EM algorithm improves performance by between one and two orders compared to direct numerical integration of the corresponding ordinary differential equations. We conclude by listing several recent applications of the Community Simulator to problems in microbial ecology, and discussing possible extensions of the package for directly analyzing microbiome compositional data.Comment: 14 pages, 6 figure

Thermodynamic modelling of synthetic communities predicts minimum free energy requirements for sulfate reduction and methanogenesis

Microbial communities are complex dynamical systems harbouring many species interacting together to implement higher-level functions. Among these higher-level functions, conversion of organic matter into simpler building blocks by microbial communities underpins biogeochemical cycles and animal and plant nutrition, and is exploited in biotechnology. A prerequisite to predicting the dynamics and stability of community-mediated metabolic conversions is the development and calibration of appropriate mathematical models. Here, we present a generic, extendable thermodynamic model for community dynamics and calibrate a key parameter of this thermodynamic model, the minimum energy requirement associated with growth-supporting metabolic pathways, using experimental population dynamics data from synthetic communities composed of a sulfate reducer and two methanogens. Our findings show that accounting for thermodynamics is necessary in capturing the experimental population dynamics of these synthetic communities that feature relevant species using low energy growth pathways. Furthermore, they provide the first estimates for minimum energy requirements of methanogenesis (in the range of −30 kJ mol−1) and elaborate on previous estimates of lactate fermentation by sulfate reducers (in the range of −30 to −17 kJ mol−1 depending on the culture conditions). The open-source nature of the developed model and demonstration of its use for estimating a key thermodynamic parameter should facilitate further thermodynamic modelling of microbial communities