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The research was carried out to determine the potential effect of microbiota, organic carbon, percentage of moisture content, and microbial biomass concentration as an evaluator of variation in basal soil respiration rate. Relative distribution and composition of the microbial population were estimated from six different chronosequence manganese mine spoil (MBO0, MBO2, MBO4, MBO6, MBO8, MBO10) and forest soil (FS). The variation was seen in moisture content (6.494±0.210-11.535±0.072)%, organic carbon (0.126±0.001- 3.469± 0.099)%, MB-C (5.519±1.371- 646.969± 11.428) μg.g-1 of soil. A positive correlation was shown between OC with MB-C (r = 0.938; p< 0.01) and moisture content (MC) (r = 0.962; p< 0.01). Variation in the basal soil respiration (BSR) and microbial metabolic quotients (MMQ) was shown to range between 0.352 ± 0.007- 0.958 ±0.014μg CO2-C.g-1 and 6.5× 10-3 - 1.481×10-3 μg CO2-C.g-1 microbial-C.h-1 with BSR: OC from (2.793-0.276)% respectively. This result shows that there is a gradual increase in OC, MC, MB-C, and BSR across seven different sites due to progressive enhancement in soil fertility that leads to the initialization of succession. Stepwise multiple regression analysis further confirms the degree of variability added by microbial biomass C, moisture content, organic carbon, and microbial population on basal soil respiration in microbes. Principal component analysis enables the differentiation of seven different soil profiles into independent clusters based on cumulative variance given by physico-chemical and microbial attributes that indicate the level of degradation of land and act as an index to restore soil fertility.

This study was carried out to evaluate the effects of herbal mixture on the growth performance, intestinal microbial population, and immune responses of broiler chickens. In all, 600 day-old as-hatched Ross 308 broiler chickens were assigned in a completely randomized design with four treatments, five replicates, and 30 birds in each replicate. The four treatments were: the control group (not treated) and, the second group received 1 mL L-1 herbal solutions (Bioherbal®), and two other groups were received 16.6, and 33.3 mL L-1 commercial herbal solutions (Orex®), respectively. Results showed that while water supplementation of the herbal mixture had no significant effect on feed intake (FI), body weight (BW), and feed conversion ratio (FCR) of broiler chickens (p > 0.05), the productive efficiency index (PEI) improved by dietary inclusion of herbal blend at 33.3 mL L-1 (p < 0.05). Furthermore, the lactobacilli population increased and E. coli population was reduced by both herbal mixture addition (p < 0.05). The application of both Herbal growth promoters (Orex® and Bioherbal®) boosted cellular and humoral immunity and decreased the heterophil-to-lymphocyte ratio (p < 0.05). The present study indicated the positive effect of Orex® addition to water at both concentrations (16.6 or 33.3 mL L-1) on livability, PEI, ileal microbial populations, and immune system function.

Past studies of plant-microbe interactions in the alpine nitrogen cycle have revealed a seasonal separation of N use, with plants absorbing N primarily during the summer months and microbes immobilizing N primarily during the autumn months. On the basis of these studies, it has been concluded that competition for N between plants and microbes is minimized along this seasonal gradient. In this study, we examined more deeply the links between microbial population dynamics and plant N availability in an alpine dry meadow. We conducted a year-round field study and performed experiments on isolated soil microorganisms. Based on previous work in this ecosystem, we hypothesized that microbial biomass would decline before the plant growing season and would release N that would become available to plants. Microbial biomass was highest when soils were cold, in autumn, winter, and early spring. During this time, N was immobilized in microbial biomass. After snow melt in spring, microbial biomass decreased. A peak in the soil protein concentration was seen at this time, followed by peaks in soil amino acid and ammonium concentrations in late June. Soil protease rates were initially high after snow melt, decreased to below detection limits by midsummer, and partially recovered by late summer. Proteolytic activity in soil was saturated early in the growing season and became protein limited later in the summer. We concluded that the key event controlling N availability to alpine plants occurs after snow melt, when protein is released from the winter microbial biomass. This protein pulse provides substrate for soil proteases, which supply plants with amino acids during the growing season. On average, microbial biomass was lower in the summer than at other times, although the biomass fluctuated widely during the summer. Within the summer months, maximum numbers of amino-acid-degrading microorganisms and the maximum amount of microbial biomass coincided with the peak in soil amino acids, when plants are most active. All bacterial strains isolated from this summer community had the ability to grow rapidly on low concentrations of amino acids and to degrade protein. This explains the previously observed result that the soil microbial biomass can compete strongly with plants for organic N, despite the seasonal offset of maximum plant and microbial N uptake.

The spectrophotometer has been used for decades to measure the density of bacterial populations as the turbidity expressed as optical density–OD. However, the OD alone is an unreliable metric and is only proportionately accurate to cell titers to about an OD of 0.1. The relationship between OD and cell titer depends on the configuration of the spectrophotometer, the length of the light path through the culture, the size of the bacterial cells, and the cell culture density. We demonstrate the importance of plate reader calibration to identify the exact relationship between OD and cells/mL. We use four bacterial genera and two sizes of micro-titer plates (96-well and 384-well) to show that the cell/ml per unit OD depends heavily on the bacterial cell size and plate size. We applied our calibration curve to real growth curve data and conclude the cells/mL–rather than OD–is a metric that can be used to directly compare results across experiments, labs, instruments, and species.

Plant-associated microorganisms have been shown to critically affect host physiology and performance, suggesting that evolution and ecology of plants and animals can only be understood in a holobiont (host and its associated organisms) context. Host-associated microbial community structures are affected by abiotic and host factors, and increased attention is given to the role of the microbiome in interactions such as pathogen inhibition. However, little is known about how these factors act on the microbial community, and especially what role microbe-microbe interaction dynamics play. We have begun to address this knowledge gap for phyllosphere microbiomes of plants by simultaneously studying three major groups of Arabidopsis thaliana symbionts (bacteria, fungi and oomycetes) using a systems biology approach. We evaluated multiple potential factors of microbial community control: we sampled various wild A. thaliana populations at different times, performed field plantings with different host genotypes, and implemented successive host colonization experiments under lab conditions where abiotic factors, host genotype, and pathogen colonization was manipulated. Our results indicate that both abiotic factors and host genotype interact to affect plant colonization by all three groups of microbes. Considering microbe-microbe interactions, however, uncovered a network of interkingdom interactions with significant contributions to community structure. As in other scale-free networks, a small number of taxa, which we call microbial \"hubs,\" are strongly interconnected and have a severe effect on communities. By documenting these microbe-microbe interactions, we uncover an important mechanism explaining how abiotic factors and host genotypic signatures control microbial communities. In short, they act directly on \"hub\" microbes, which, via microbe-microbe interactions, transmit the effects to the microbial community. We analyzed two \"hub\" microbes (the obligate biotrophic oomycete pathogen Albugo and the basidiomycete yeast fungus Dioszegia) more closely. Albugo had strong effects on epiphytic and endophytic bacterial colonization. Specifically, alpha diversity decreased and beta diversity stabilized in the presence of Albugo infection, whereas they otherwise varied between plants. Dioszegia, on the other hand, provided evidence for direct hub interaction with phyllosphere bacteria. The identification of microbial \"hubs\" and their importance in phyllosphere microbiome structuring has crucial implications for plant-pathogen and microbe-microbe research and opens new entry points for ecosystem management and future targeted biocontrol. The revelation that effects can cascade through communities via \"hub\" microbes is important to understand community structure perturbations in parallel fields including human microbiomes and bioprocesses. In particular, parallels to human microbiome \"keystone\" pathogens and microbes open new avenues of interdisciplinary research that promise to better our understanding of functions of host-associated microbiomes.

Marine microbial communities are engines of globally important processes, such as the marine carbon, nitrogen and sulphur cycles. Recent data on the structures of these communities show that they adhere to universal biological rules. Co-occurrence patterns can help define species identities, and systems-biology tools are revealing networks of interacting microorganisms. Some microbial systems are found to change predictably, helping us to anticipate how microbial communities and their activities will shift in a changing world.

Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomal RNA gene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.

Granular activated sludge has gained increasing interest due to its potential in treating wastewater in a compact and efficient way. It is well-established that activated sludge can form granules under certain environmental conditions such as batch-wise operation with feast-famine feeding, high hydrodynamic shear forces, and short settling time which select for dense microbial aggregates. Aerobic granules with stable structure and functionality have been obtained with a range of different wastewaters seeded with different sources of sludge at different operational conditions, but the microbial communities developed differed substantially. In spite of this, granule instability occurs. In this review, the available literature on the mechanisms involved in granulation and how it affects the effluent quality is assessed with special attention given to the microbial interactions involved. To be able to optimize the process further, more knowledge is needed regarding the influence of microbial communities and their metabolism on granule stability and functionality. Studies performed at conditions similar to full-scale such as fluctuation in organic loading rate, hydrodynamic conditions, temperature, incoming particles, and feed water microorganisms need further investigations.

Populations of millions of colloidal rolling particles are shown to self-organize to achieve coherent motion; comparison between experiment and theory based on the microscopic interactions between these ‘rollers’ suggests that hydrodynamic interactions promote the emergence of the collective motion. Microrobots with self-organizing potential Collective motion can be observed in the natural world at all scales, from flocking birds to schooling fish and swarming bacteria, but it is difficult to capture such behaviour in simple physical models. Artificial 'active matter' systems that show collective behaviour usually rely on collisions, making the description of interactions complex. Denis Bartolo and colleagues have now developed a unique experimental system consisting of self-propelled rolling spheres that self-organize and move in one direction in a crowd of millions. The spheres 'sense' each other via straightforward hydrodynamic interactions so that all parameters can be easily calculated and tuned. This work demonstrates that genuine physical interactions at the individual level are sufficient to set homogeneous active populations into stable directed motion. The system could be used to model natural collective motion and to design new self-organized materials and swarming microrobots. From the formation of animal flocks to the emergence of coordinated motion in bacterial swarms, populations of motile organisms at all scales display coherent collective motion. This consistent behaviour strongly contrasts with the difference in communication abilities between the individuals. On the basis of this universal feature, it has been proposed that alignment rules at the individual level could solely account for the emergence of unidirectional motion at the group level 1 , 2 , 3 , 4 . This hypothesis has been supported by agent-based simulations 1 , 5 , 6 . However, more complex collective behaviours have been systematically found in experiments, including the formation of vortices 7 , 8 , 9 , fluctuating swarms 7 , 10 , clustering 11 , 12 and swirling 13 , 14 , 15 , 16 . All these (living and man-made) model systems (bacteria 9 , 10 , 16 , biofilaments and molecular motors 7 , 8 , 13 , shaken grains 14 , 15 and reactive colloids 11 , 12 ) predominantly rely on actual collisions to generate collective motion. As a result, the potential local alignment rules are entangled with more complex, and often unknown, interactions. The large-scale behaviour of the populations therefore strongly depends on these uncontrolled microscopic couplings, which are extremely challenging to measure and describe theoretically. Here we report that dilute populations of millions of colloidal rolling particles self-organize to achieve coherent motion in a unique direction, with very few density and velocity fluctuations. Quantitatively identifying the microscopic interactions between the rollers allows a theoretical description of this polar-liquid state. Comparison of the theory with experiment suggests that hydrodynamic interactions promote the emergence of collective motion either in the form of a single macroscopic ‘flock’, at low densities, or in that of a homogenous polar phase, at higher densities. Furthermore, hydrodynamics protects the polar-liquid state from the giant density fluctuations that were hitherto considered the hallmark of populations of self-propelled particles 2 , 3 , 17 . Our experiments demonstrate that genuine physical interactions at the individual level are sufficient to set homogeneous active populations into stable directed motion.

Advances in the analysis of amplicon sequence datasets have introduced a methodological shift in how research teams investigate microbial biodiversity, away from sequence identity-based clustering (producing Operational Taxonomic Units, OTUs) to denoising methods (producing amplicon sequence variants, ASVs). While denoising methods have several inherent properties that make them desirable compared to clustering-based methods, questions remain as to the influence that these pipelines have on the ecological patterns being assessed, especially when compared to other methodological choices made when processing data (e.g. rarefaction) and computing diversity indices. We compared the respective influences of two widely used methods, namely DADA2 (a denoising method) vs. Mothur (a clustering method) on 16S rRNA gene amplicon datasets (hypervariable region v4), and compared such effects to the rarefaction of the community table and OTU identity threshold (97% vs. 99%) on the ecological signals detected. We used a dataset comprising freshwater invertebrate (three Unionidae species) gut and environmental (sediment, seston) communities sampled in six rivers in the southeastern USA. We ranked the respective effects of each methodological choice on alpha and beta diversity, and taxonomic composition. The choice of the pipeline significantly influenced alpha and beta diversities and changed the ecological signal detected, especially on presence/absence indices such as the richness index and unweighted Unifrac. Interestingly, the discrepancy between OTU and ASV-based diversity metrics could be attenuated by the use of rarefaction. The identification of major classes and genera also revealed significant discrepancies across pipelines. Compared to the pipeline’s effect, OTU threshold and rarefaction had a minimal impact on all measurements.