Search

A search has been carried out for Magnetized Quark Nuggets (MQNs) accumulating in iron ore over geologic time. MQNs, which are theoretically consistent with the Standard Models of Physics and of Cosmology, have been suggested as dark-matter candidates. Indirect evidence of MQNs has been previously inferred from observations of magnetars and of non-meteorite impact craters. It is shown in this paper that MQNs can accumulate in taconite (iron ore) and be transferred into ferromagnetic rod-mill liners during processing of the ore. When the liners are recycled to make fresh steel, they are heated to higher than the Curie temperature so that their ferromagnetic properties are destroyed. The MQNs would then be released and fall into the ferromagnetic furnace bottom where they would be trapped. Three such furnace bottoms have been magnetically scanned to search for the magnetic anomalies consistent with trapped MQNs. The observed magnetic anomalies are equivalent to an accumulation rate of ~1 kg of MQNs per 1.2 × 108 kg of taconite ore processed. The results are consistent with MQNs but there could be other, unknown explanations. We propose an experiment and calculations to definitively test the MQN hypothesis for dark matter.

Abstract A search for magnetised quark nuggets (MQN) is reported using acoustic signals from hydrophones placed in the Great Salt Lake (GSL) in the USA. No events satisfying the expected signature were seen. This observation allows limits to be set on the flux of MQNs penetrating the Earth’s atmosphere and depositing energy in the GSL. The expected signature of the events was ​derived from pressure pulses caused by high-explosive cords between the lake surface and bottom at various locations in the GSL. The limits obtained from this search are compared with those obtained from previous searches and are compared to models for the formation of MQNs.

Abstract Quark nuggets are theoretical objects composed of approximately equal numbers of up, down, and strange quarks and are also called strangelets and nuclearites. They have been proposed as a candidate for dark matter, which constitutes ~85% of the universe’s mass and which has been a mystery for decades. Previous efforts to detect quark nuggets assumed that the nuclear-density core interacts directly with the surrounding matter so the stopping power is minimal. Tatsumi found that quark nuggets could well exist as a ferromagnetic liquid with a ~1012-T magnetic field. We find that the magnetic field produces a magnetopause with surrounding plasma, as the earth’s magnetic field produces a magnetopause with the solar wind, and substantially increases their energy deposition rate in matter. We use the magnetopause model to compute the energy deposition as a function of quark-nugget mass and to analyze testing the quark-nugget hypothesis for dark matter by observations in air, water, and land. We conclude the water option is most promising.

Abstract The inclusive photoproduction of D ∗ mesons and of D ∗-tagged dijets is investigated with the H1 detector at the ep collider HERA. The kinematic region covers small photon virtualities Q 21.8 GeV. The heavy quark production process is further investigated in events with at least two jets with transverse momentum p T(jet)>3.5 GeV each, one containing the D ∗ meson. Differential cross sections for D ∗-tagged dijet production and for correlations between the jets are measured in the range |η(D ∗)|2.1 GeV. The results are compared with predictions from Monte Carlo simulations and next-to-leading order perturbative QCD calculations.

Abstract A measurement of the inclusive ep scattering cross section is presented in the region of low momentum transfers, 0.2 GeV2 ≤Q 2≤12 GeV2, and low Bjorken x, 5⋅10−6≤x≤0.02. The result is based on two data sets collected in dedicated runs by the H1 Collaboration at HERA at beam energies of 27.6 GeV and 920 GeV for positrons and protons, respectively. A combination with data previously published by H1 leads to a cross section measurement of a few percent accuracy. A kinematic reconstruction method exploiting radiative ep events extends the measurement to lower Q 2 and larger x. The data are compared with theoretical models which apply to the transition region from photoproduction to deep inelastic scattering.

ABSTRACT Alpha mannose-oligosaccharide (MOS) prebiotics are widely deployed in animal agriculture as immunomodulators as well as to enhance growth and gut health. Their mode of action is thought to be mediated through their impact on host microbial communities and their associated metabolism. Bio-Mos is a commercially available prebiotic currently used in the agri-feed industry, but studies show contrasting results of its effect on fish performance and feed efficiency. Thus, detailed studies are needed to investigate the effect of MOS supplements on the fish microbiome to enhance our understanding of the link between MOS and gut health. To assess Bio-Mos for potential use as a prebiotic growth promoter in salmonid aquaculture, we have modified an established Atlantic salmon in vitro gut model, SalmoSim, to evaluate its impact on the host microbial communities. The microbial communities obtained from ceca compartments from four adult farmed salmon were inoculated in biological triplicate reactors in SalmoSim. Prebiotic treatment was supplemented for 20 days, followed by a 6-day washout period. Inclusion of Bio-Mos in the media resulted in a significant increase in formate (P = 0.001), propionate (P = 0.037) and 3-methyl butanoic acid (P = 0.024) levels, correlated with increased abundances of several, principally, anaerobic microbial genera (Fusobacterium, Agarivorans, Pseudoalteromonas). DNA metabarcoding with the 16S rDNA marker confirmed a significant shift in microbial community composition in response to Bio-Mos supplementation with observed increase in lactic acid producing Carnobacterium. In conjunction with previous in vivo studies linking enhanced volatile fatty acid production alongside MOS supplementation to host growth and performance, our data suggest that Bio-Mos may be of value in salmonid production. Furthermore, our data highlights the potential role of in vitro gut models to complementin vivo trials of microbiome modulators. IMPORTANCE In this paper we report the results of the impact of a prebiotic (alpha-MOS supplementation) on microbial communities, using an in vitro simulator of the gut microbial environment of the Atlantic salmon. Our data suggest that Bio-Mos may be of value in salmonid production as it enhances volatile fatty acid production by the microbiota from salmon pyloric ceca and correlates with a significant shift in microbial community composition with observed increase in lactic acid producing Carnobacterium. In conjunction with previous in vivo studies linking enhanced volatile fatty acid production alongside MOS supplementation to host growth and performance, our data suggest that Bio-Mos may be of value in salmonid production. Furthermore, our data highlights the potential role of in vitro gut models to augment in vivo trials of microbiome modulators.

Abstract Background The factors affecting host-pathogen ecology in terms of the microbiome remain poorly studied. Chickens are a key source of protein with gut health heavily dependent on the complex microbiome which has key roles in nutrient assimilation and vitamin and amino acid biosynthesis. The chicken gut microbiome may be influenced by extrinsic production system parameters such as Placement Birds/m 2 (stocking density), feed type and additives. Such parameters, in addition to on-farm biosecurity may influence performance and also pathogenic bacterial numbers such as Campylobacter. In this study, three different production systems ‘Normal’ (N), ‘Higher Welfare’ (HW) and ‘Omega-3 Higher Welfare’ (O) were investigated in an industrial farm environment at day 7 and day 30 with a range of extrinsic parameters correlating performance with microbial dynamics and Campylobacter presence. Results Our data identified production system N as significantly dissimilar from production systems HW and O when comparing the prevalence of genera. An increase in Placement Birds/m 2 density led to a decrease in environmental pressure influencing the microbial community structure. Prevalence of genera, such as Eisenbergiella within HW and O, and likewise Alistipes within N were representative. These genera have roles directly relating to energy metabolism, amino acid, nucleotide and short chain fatty acid (SCFA) utilisation. Thus, an association exists between consistent and differentiating parameters of the production systems that affect feed utilisation, leading to competitive exclusion of genera based on competition for nutrients and other factors. Campylobacter was identified within specific production system and presence was linked with the increased diversity and increased environmental pressure on microbial community structure. Addition of Omega-3 though did alter prevalence of specific genera, in our analysis did not differentiate itself from HW production system. However, Omega-3 was linked with a positive impact on weight gain. Conclusions Overall, our results show that microbial communities in different industrial production systems are deterministic in elucidating the underlying biological confounders, and these recommendations are transferable to farm practices and diet manipulation leading to improved performance and better intervention strategies against Campylobacter within the food chain. Video Abstract

Abstract Background Amplicon sequencing methods targeting the 16S rRNA gene have been used extensively to investigate microbial community composition and dynamics in anaerobic digestion. These methods successfully characterize amplicons but do not distinguish micro-organisms that are actually responsible for the process. In this research, the archaeal and bacterial community of 48 full-scale anaerobic digestion plants were evaluated on DNA (total community) and RNA (active community) level via 16S rRNA (gene) amplicon sequencing. Results A significantly higher diversity on DNA compared with the RNA level was observed for archaea, but not for bacteria. Beta diversity analysis showed a significant difference in community composition between the DNA and RNA of both bacteria and archaea. This related with 25.5 and 42.3% of total OTUs for bacteria and archaea, respectively, that showed a significant difference in their DNA and RNA profiles. Similar operational parameters affected the bacterial and archaeal community, yet the differentiating effect between DNA and RNA was much stronger for archaea. Co-occurrence networks and functional prediction profiling confirmed the clear differentiation between DNA and RNA profiles. Conclusions In conclusion, a clear difference in active (RNA) and total (DNA) community profiles was observed, implying the need for a combined approach to estimate community stability in anaerobic digestion.

Abstract Background Synthetic organism-based biotechnologies are increasingly being proposed for environmental applications, such as in situ sensing. Typically, the novel function of these organisms is delivered by compiling genetic fragments in the genome of a chassis organism. To behave predictably, these chassis are designed with reduced genomes that minimize biological complexity. However, in these proposed applications it is expected that even when contained within a device, organisms will be exposed to fluctuating, often stressful, conditions and it is not clear whether their genomes will retain stability. Results Here we employed a chemostat design which enabled us to maintained two strains of E. coli K12 under sustained starvation stress: first the reduced genome synthetic biology chassis MDS42 and then, the control parent strain MG1655. We estimated mutation rates and utilised them as indicators of an increase in genome instability. We show that within 24 h the spontaneous mutation rate had increased similarly in both strains, destabilizing the genomes. High rates were maintained for the duration of the experiment. Growth rates of a cohort of randomly sampled mutants from both strains were utilized as a proxy for emerging phenotypic, and by association genetic variation. Mutant growth rates were consistently less than rates in non-mutants, an indicator of reduced fitness and the presence of mildly deleterious mutations in both the strains. In addition, the effect of these mutations on the populations as a whole varied by strain. Conclusions Overall, this study shows that genome reductions in the MDS42 did not stabilize the chassis under metabolic stress. Over time, this could compromise the effectiveness of synthetic organisms built on chassis in environmental applications.

Abstract A way to defeat antimicrobial resistance (AMR) crisis is to supply novel drugs to the pharmaceutical industry. This effort leads to a global call for seeking the beneficial microbes from underexplored habitats. To support this call, we isolated Streptomyces sp. TM32 from the rhizosphere soil of a medicinal plant, turmeric (Curcuma longa L.). TM32 exhibited strong antimicrobial activities against both human and plant pathogens, including an AMR pathogen, Staphylococcus haemolyticus MR‐CoNS. Surprisingly, such antimicrobial results of TM32's autoclaved crude extract remained the same. Based on the genome data analysis, TM32 belongs to the same genomic species with Streptomyces sioyaensis DSM 40032T, supported by the relatively high‐average nucleotide identity values (ANIb: 96.80% and OrthoANIu: 97.14%) and in silico DNA–DNA relatedness value of 75.40%. Importantly, the gene annotation analyses revealed that TM32's genome contains various genes encoding the biosynthesis of either known or unknown antibiotics and some metabolites involved in plant growth‐promoting traits. However, bioactivities and genome data comparison of TM32 and DSM 40032T showed a set of apparent differences, for example, antimicrobial potentials, genome size, number, and occurrence of coding DNA sequences in the chromosomes. These findings suggest that TM32 is a new strain of S. sioyaensis and serves as an emerging source for further discovery of valuable and novel bioactive compounds.

Studies investigating the feasibility of new, or improved, biotechnologies, such as wastewater treatment digesters, inevitably start with laboratory-scale trials. However, it is rarely determined whether laboratory-scale results reflect full-scale performance or microbial ecology. The Expanded Granular Sludge Bed (EGSB) bioreactor, which is a high-rate anaerobic digester configuration, was used as a model to address that knowledge gap in this study. Two laboratory-scale idealizations of the EGSB—a one-dimensional and a three- dimensional scale-down of a full-scale design—were built and operated in triplicate under near-identical conditions to a full-scale EGSB. The laboratory-scale bioreactors were seeded using biomass obtained from the full-scale bioreactor, and, spent water from the distillation of whisky from maize was applied as substrate at both scales. Over 70 days, bioreactor performance, microbial ecology, and microbial community physiology were monitored at various depths in the sludge-beds using 16S rRNA gene sequencing (V4 region), specific methanogenic activity (SMA) assays, and a range of physical and chemical monitoring methods. SMA assays indicated dominance of the hydrogenotrophic pathway at full-scale whilst a more balanced activity profile developed during the laboratory-scale trials. At each scale, Methanobacterium was the dominant methanogenic genus present. Bioreactor performance overall was better at laboratory-scale than full-scale. We observed that bioreactor design at laboratory-scale significantly influenced spatial distribution of microbial community physiology and taxonomy in the bioreactor sludge-bed, with 1-D bioreactor types promoting stratification of each. In the 1-D laboratory bioreactors, increased abundance of Firmicutes was associated with both granule position in the sludge bed and increased activity against acetate and ethanol as substrates. We further observed that stratification in the sludge-bed in 1-D laboratory-scale bioreactors was associated with increased richness in the underlying microbial community at species (OTU) level and improved overall performance.

Bacterial motility is one important factor that affects biofilm formation. In drinking water there are key bacteria in aggregation, whose biology acts to enhance the formation of biofilms. However, it is unclear whether the motility of these key bacteria is an important factor for the interactions between bacteria in drinking water, and, subsequently, in the formation of aggregates, which are precursors to biofilms. Thus, the role of the motility of one of these key bacteria, the Methylobacterium strain DSM 18358, was investigated in the interactions between bacteria in drinking water. The motility of pure Methylobacterium colonies was initially explored; if it was affected by the viscosity of substrate, the temperature, the available energy and the type of substrate. Furthermore, the role of Methylobacterium in the interactions between mixed drinking water bacteria was investigated under the mostly favourable conditions for the motility of Methylobacterium identified before. Overall, the motility of Methylobacterium was found to play a key role in the communication and interactions between bacteria in drinking water. Understanding the role of the motility of key bacteria in drinking water might be useful for the water industry as a potential tool to control the formation of biofilms in drinking water pipes.

In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete) model simulates absolute numbers of individual cells, whereas the other (continuous) model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.

The structure of biofilms in drinking water systems is influenced by the interplay between biological and physical processes. Bacterial aggregates in bulk fluid are important in seeding biofilm formation on surfaces. In simple pure and co-cultures, certain bacteria, including Methylobacterium, are implicated in the formation of aggregates. However, it is unclear whether they help to form aggregates in complex mixed bacterial communities. Furthermore, different flow regimes could affect the formation and destination of aggregates. In this study, real drinking water mixed microbial communities were inoculated with the Methylobacterium strain DSM 18358. The propensity of Methylobacterium to promote aggregation was monitored under both stagnant and flow conditions. Under stagnant conditions, Methylobacterium enhanced bacterial aggregation even when it was inoculated in drinking water at 1% relative abundance. Laminar and turbulent flows were developed in a rotating annular reactor. Methylobacterium was found to promote a higher degree of aggregation in turbulent than laminar flow. Finally, fluorescence in situ hybridisation images revealed that Methylobacterium aggregates had distinct spatial structures under the different flow conditions. Overall, Methylobacterium was found to be a key strain in the formation of aggregates in bulk water and subsequently in the formation of biofilms on surfaces.

The UP modelling system has been applied to the 570,000 km2 Arkansas-Red River Basin (ARRB) as part of the UK NERC Terrestrial initiative in Global Environmental Research (TIGER). The model can be run as a stand-alone basin hydrology model or be linked to existing climate and weather forecasting models. It runs on a grid comprising 1923 UP elements, each 17km by 17km in area, and each containing five water storage compartments: one each for the snowpack, vegetation canopy, surface water, root zone and groundwater. All the main transfers and processes of the terrestrial phase of the hydrological cycle are represented, including river network routing of the runoff from the UP elements. The parameters of the ARRB model are physically-based, being derived either from fine-scale, sub-grid, data on the topography and physical properties of the soils, aquifers and vegetation of the basin, or from the results of fine-scale physically-based simulations. With the approach, the parameters account for the effects of sub-grid variations in moisture status and spatial distribution and are sensitive to changes in the fine-scale property data. This sensitivity is either absent or less directly represented in existing large-scale hydrology models, yet it plays a central role in studies of the impact of changes in climate and land-use. The ARRB model, as described here and in Kilsby et al. (1999), is a first attempt at large-scale physically-based hydrological modelling of the type outlined in the 'blueprint' for the UP system (Ewen, 1997), and gives a clear, positive, indication of the nature and quality of what is currently practical with the approach.

The UP (Upscaled Physically-based) hydrological modelling system to the Arkansas-Red River basin (USA) is designed for macro-scale simulations of land surface processes, and aims for a physical basis and, avoids the use of discharge records in the direct calibration of parameters. This is achieved in a two stage process: in the first stage parametrizations are derived from detailed modelling of selected representative small and then used in a second stage in which a simple distributed model is used to simulate the dynamic behaviour of the whole basin. The first stage of the process is described in a companion paper (Ewen et al., this issue), and the second stage of this process is described here. The model operated at an hourly time-step on 17-km grid squares for a two year simulation period, and represents all the important hydrological processes including regional aquifer recharge, groundwater discharge, infiltration- and saturation-excess runoff, evapotranspiration, snowmelt, overland and channel flow. Outputs from the model are discussed, and include river discharge at gauging stations and space-time fields of evaporation and soil moisture. Whilst the model efficiency assessed by comparison of simulated and observed discharge records is not as good as could be achieved with a model calibrated against discharge, there are considerable advantages in retaining a physical basis in applications to ungauged river basins and assessments of impacts of land use or climate change.

Abstract  In this talk the current status of our knowledge of the structure of the nucleon will be reviewed as revealed in deep inelastic scattering. The current data on the structure functions of the nucleon both diffractive and non-diffractive will be discussed. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs), or stand‐alone models that are forced by the output from GCMs, are increasingly being used to simulate the interactions between snow cover, snowmelt, climate and water resources. The variation in snowpack extent, and hence albedo, through time in a cell is likely to be substantial, especially in mid‐latitude mountainous regions. As a consequence, the energy budget simulation by a GCM relies on a realistic representation of snowpack extent. Similarly, from a water resource perspective, the spatial extent of the pack is key in predicting meltwater discharges into rivers. In this paper a simple computationally efficient regional snow model has been developed, which is based on a degree‐day approach and simulates the fraction of the model domain covered by snow, the spatially averaged melt rate and the mean snowpack depth. Computational efficiency is achieved through a novel spatial averaging procedure, which relies on the assumptions that precipitation and temperature scale linearly with elevation and that the distribution of elevations in the domain can be modelled by a continuous function. The resulting spatially averaged model is compared with both observations of the duration of snow cover throughout Austria and with results from a distributed model based on the same underlying assumptions but applied at a fine spatial resolution. The new spatially averaged model successfully simulated the seasonal snow duration observations and reproduced the daily dynamics of snow cover extent, the spatially averaged melt rate and mean pack depth simulated by the distributed model. It, therefore, offers a computationally efficient and easily applied alternative to the current crop of regional snow models. Copyright © 2004 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Septic tanks are widely deployed for off-grid sewage management but are typified by poor treatment performance, discharge of polluting effluents and the requirement for frequent de-sludging. The Solar Septic Tank (SST) is a novel septic tank design that uses passive heat from the sun to raise in-tank temperatures and improves solids degradation, resulting in a cleaner effluent. Treatment has been shown to exceed conventional systems, however, the underlying biology driving treatment in the system is poorly understood. We used next generation sequencing (Illumina Miseq (San Diego, CA, USA), V4 region 16S DNA) to monitor the microbiology in the sludge and effluent of two mature systems, a conventional septic tank and an SST, during four months of routine operation in Bangkok, Thailand, and evaluated the ecology against a suite of operating and performance data collected during the same time period. Significant differences were observed between the microbiome of the sludge and effluent in each system and the dominant taxa in each appeared persistent over time. Furthermore, variation in the microbial community composition in the system effluents correlated with effluent water quality and treatment performance parameters, including the removal of chemical and biochemical oxygen demand and the concentration of fecal and total coliforms in the effluent. Thus, we propose that a wide-scale survey of the biology underlying decentralised biotechnologies for sewage treatment such as the SST could be conducted by sampling system effluent rather than sampling sludge. This is advantageous as accessing sludge during sampling is both hazardous and potentially disruptive to the anaerobic methanogenic consortia underlying treatment in the systems. [ABSTRACT FROM AUTHOR]

Abstract A recent experiment probed how purposeful action emerges in early life by manipulating infants’ functional connection to an object in the environment (i.e., tethering an infant’s foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

The paradigm of centralised water and wastewater services is coming under significant pressure from multiple global factors. Therefore, there is a need to consider the challenges and opportunities for decentralised water and wastewater technologies and systems. This search is particularly relevant within the context of Scotland, where a proportion of the population uses existing decentralised technologies. The Scottish context shows that those using decentralised services struggle to manage their water and wastewater services without appropriate support. However, the global goals of universal access to safe water and adequate sanitation, a just transition to net-zero and community empowerment, provide opportunities and policy pathways towards the implementation and improvement of decentralised technologies and systems. HIGHLIGHTS Decentralised water and wastewater systems provide an alternative to traditional carbon-intensive centralised infrastructure.; Challenges with existing decentralised systems in Scotland are a rural issue due to historical factors.; Opportunities for improvements to the management of decentralised systems are universal access to water and sanitation, a just transition to net-zero and community empowerment.;

Dissolved organic matter (DOM) is a complex mixture of carbon-based compounds present in natural aquatic systems, which significantly affects drinking water treatment processes. Biofiltration, utilising biologically active beds of porous medium, offers a low-energy and low-chemical solution for controlling bioavailable DOM. However, the impact of microbial community composition on DOM degradation in biofilters remains poorly understood. This study aimed to explore the abilities of microbial communities from the top, middle, and bottom (TOP, MID, and BOT) of a biofilter to process DOM. We showed varying growth rates on the DOM, with bottom community exhibiting the highest cell abundance at the end of the experiment (1.83 × 106 ± 9 × 103; 2.06 × 106 ± 1 × 104; 2.15 × 106 ± 7 × 103 cells/mL for the TOP, MID, and BOT, respectively). The three communities showed different preferences for utilising specific DOM fractions, with the bottom community targeting more complex ones. The microbial communities from the bottom of the biofilter had a higher relative abundance of the Curvibacter genus, suggesting it could play a crucial role in degrading complex DOM fractions. These findings highlight the influence of microbial community composition on DOM degradation in biofilters, providing valuable insights for optimising their performance. HIGHLIGHTS Communities were extracted from three different depths of a biofilter (TOP, MID, and BOT).; Communities differed in growth kinetics, with BOT showing the greatest growth.; The TOP and MID communities preferentially used the smaller fractions of DOM.; The BOT community used the more complex DOM fraction of humic substances.; Microbial communities from different depths of a biofilter exhibit distinct abilities to degrade DOM.;

In recent years, there has been an unprecedented advancement in in situ analytical approaches that contribute to the mechanistic understanding of microbial communities by explicitly incorporating ecology and studying their assembly. In this study, we have analyzed the temporal profiles of the healthy broiler cecal microbiome from day 3 to day 35 to recover the stable and varying components of microbial communities. During this period, the broilers were fed three different diets chronologically, and therefore, we have recovered signature microbial species that dominate during each dietary regime. Since broilers were raised in multiple pens, we have also parameterized these as an environmental condition to explore microbial niches and their overlap. All of these analyses were performed in view of different parameters such as body weight (BW-mean), feed intake (FI), feed conversion ratio (FCR), and age (days) to link them to a subset of microbes that these parameters have a bearing upon. We found that gut microbial communities exhibited strong and statistically significant specificity for several environmental variables. Through regression models, genera that positively/negatively correlate with the bird’s age were identified. Some short-chain fatty acids (SCFAs)-producing bacteria, including Izemoplasmatales, Gastranaerophilales, and Roseburia, have a positive correlation with age. Certain pathogens, such as Escherichia-Shigella, Sporomusa, Campylobacter, and Enterococcus, negatively correlated with the bird’s age, which indicated a high disease risk in the initial days. Moreover, the majority of pathways involved in amino acid biosynthesis were also positively correlated with the bird’s age. Some probiotic genera associated with improved performance included Oscillospirales; UCG-010, Shuttleworthia, Bifidobacterium, and Butyricicoccaceae; UCG-009. In general, predicted antimicrobial resistance genes (piARGs) contributed at a stable level, but there was a slight increase in abundance when the diet was changed. To the best of the authors’ knowledge, this is one of the first studies looking at the stability, complexity, and ecology of natural broiler microbiota development in a temporal setting.

Abstract A meta-analysis approach was used, to study the microbiomes of biofilms and planktonic communities underpinning microbial electrosynthesis (MES) cells. High-throughput DNA sequencing of 16S rRNA gene amplicons has been increasingly applied to understand MES systems. In this meta-analysis of 22 studies, we find that acetogenic and methanogenic MES cells share 80% of a cathodic core microbiome, and that different inoculum pre-treatments strongly affect community composition. Oxygen scavengers were more abundant in planktonic communities, and several key organisms were associated with operating parameters and good cell performance. We suggest Desulfovibrio sp. play a role in initiating early biofilm development and shaping microbial communities by catalysing H2 production, to sustain either Acetobacterium sp. or Methanobacterium sp. Microbial community assembly became more stochastic over time, causing diversification of the biofilm (cathodic) community in acetogenic cells and leading to re-establishment of methanogens, despite inoculum pre-treatments. This suggests that repeated interventions may be required to suppress methanogenesis.

Abstract There is growing evidence that individual bacteria sense and respond to changes in mechanical loading. However, the subtle responses of multispecies biofilms to dynamic fluid shear stress are not well documented because experiments often fail to disentangle any beneficial effects of shear stress from those delivered by convective transport of vital nutrients. We observed the development of biofilms with lognormally distributed microcolony sizes in drinking water on the walls of flow channels underflow regimes of increasing complexity. First, where regular vortices induced oscillating wall shear and simultaneously enhanced mass transport, which produced the thickest most extensive biofilms. Second, where unsteady uniform flow imposed an oscillating wall shear, with no enhanced transport, and where the biomass and coverage were only 20% smaller. Finally, for uniform steady flows with constant wall shear where the extent, thickness, and density of the biofilms were on average 60% smaller. Thus, the dynamics of shear stress played a significant role in promoting biofilm development, over and above its magnitude or mass transfer effects, and therefore, mechanosensing may prevail in complex multispecies biofilms which could open up new ways of controlling biofilm structure.

In microbial communities, the ecological interactions between species of different populations are responsible for the spatial distributions observed in aggregates (granules, biofilms or flocs). To explore the underlying mechanisms that control these processes, we have developed a mathematical modelling framework able to describe, label and quantify defined spatial structures that arise from microbial and environmental interactions in communities. An artificial system of three populations collaborating or competing in an aggregate is simulated using individual-based modelling under different environmental conditions. In this study, neutralism, competition, commensalism and concurrence of commensalism and competition have been considered. We were able to identify interspecific segregation of communities that appears in competitive environments (columned stratification), and a layered distribution of populations that emerges in commensal (layered stratification). When different ecological interactions were considered in the same aggregate, the resultant spatial distribution was identified as the one controlled by the most limiting substrate. A theoretical modulus was defined, with which we were able to quantify the effect of environmental conditions and ecological interactions to predict the most probable spatial distribution. The specific microbial patterns observed in our results allowed us to identify the optimal spatial organizations for bacteria to thrive when building a microbial community and how this permitted co-existence of populations at different growth rates. Our model reveals that although ecological relationships between different species dictate the distribution of bacteria, the environment controls the final spatial distribution of the community.

ABSTRACT Bdellovibrio bacteriovorus is a predatory, Gram-negative bacteria that feeds on many pathogenic bacteria and has been investigated as a possible solution for mitigating biofilms in different fields. The application depends on more fundamental ecological studies into the dynamics between Bdellovibrio and their prey. To do so requires an accurate, reliable, and, preferably rapid, way of enumerating the cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated in the enumeration of Bdellovibrio. In this study, we developed a protocol to measure the number of Bdellovibrio in samples of various densities using FCM and compared the results with those of other methods: optical density (OD), PFU assay (PFU), and quantitative PCR (qPCR). We observed a strong correlation between values obtained using FCM and PFU (ρ = 0.923) and FCM and qPCR (ρ = 0.987). Compared to optical density there was a much weaker correlation (ρ = 0.784), which was to be expected given the well-documented uncertainty in converting optical density (OD) to cell numbers. The FCM protocol was further validated by demonstrating its ability to distinguish and count mixed populations of Bdellovibrio and the prey Pseudomonas. Thus, the accuracy of FCM as well as its speed and reproducibility make it a suitable alternative for measuring Bdellovibrio cell numbers, especially where many samples are required to capture the dynamics of predator-prey interactions. IMPORTANCE The rise of antibiotic resistance and the unwanted growth of bacteria is a universally growing problem. Predatory bacteria can be used as a biological alternative to antibiotics because they grow by feeding on other bacteria. To apply this effectively requires further study and a deeper understanding of the forces that drive a prey population to elimination. Initially, such studies require more reliable methods to count these cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated for predatory bacteria. This study develops a protocol to count the predatory bacteria Bdellovibrio bacteriovorus and its Pseudomonas prey using FCM and compare the results with those of other methods, demonstrating its ability for studies into B. bacteriovorus predation dynamics. This could lead to the use of B. bacteriovorus for killing bacterial biofilms in fields, such as drinking water and agriculture.

Abstract Background Dirty panicle disease (DPD) caused by several fungal phytopathogens results in damage and depreciation of rice seeds. Unhealthy rice seeds with DPD are potent reservoirs of pathogens and unable to be used as seed stock as they can spread the disease in the paddy fields leading to the severe loss of rice yield and quality. In this study, we aim to search for beneficial endophytes of commercially cultivated rice plants and utilize them as biostimulants in seed biopriming for fertility recovery and disease suppression of unhealthy rice seeds. Results Forty-three bacterial endophytes were isolated from rice plants grown in the herbicide-treated paddy fields. Five isolates of these endophytes belonging to the genus Bacillus show excellent antifungal activity against fungal pathogens of DPD. Based on germination tests, biopriming unhealthy rice seeds by soaking in bacterial suspensions for 9 or 12 h was optimal as evidenced by the lowest disease incidence and longer shoot and root lengths of seedlings germinated, compared with controls made of non-treated or hydroprimed healthy and unhealthy seeds. Pot experiments were carried out to evaluate the impact of seed biopriming, in which the percentage of healthy rice yield produced by rice plants emerging from bioprimed seeds was not significantly different, compared to the controls originating respectively from non-treated healthy seeds and chemical fungicide-treated unhealthy seeds. Conclusion Biopriming of unhealthy rice seeds with herbicide-tolerant endophytic bacteria could recover seed fertility and protect the full life cycle of emerging rice plants from fungal pests. With our findings, seed biopriming is a straightforward approach that farmers can apply to recover unhealthy rice seed stock, which enables them to reduce the cost and use of agrochemicals in the commercial production of rice and to promote green technology in sustainable agriculture.

In recent years a wealth of studies have examined the relationships between a host and its microbiome across diverse taxa. Many studies characterise the host microbiome without considering the ecological processes that underpin microbiome assembly. In this study, the intestinal microbiota of Atlantic salmon, Salmo salar, sampled from farmed and wild environments was first characterised using 16s rDNA MiSeq sequencing analysis. We used neutral community models to determine the balance of stochastic and deterministic processes that underpin microbial community assembly and transfer across lifecycle stage and between gut compartments. Across gut compartments in farmed fish, neutral models suggest that most microbes are transient with no evidence of adaptation to their environment. In wild fish, we find declining taxonomic and functional microbial community richness as fish mature through different lifecycle stages. Alongside neutral community models applied to wild fish, we suggest declining richness demonstrates an increasing role for the host in filtering microbial communities that is correlated with age. We find a limited subset of gut microflora adapted to the farmed and wild host environment among which Mycoplasma sp. are prominent. Our study reveals the ecological drivers underpinning community assembly in both farmed and wild Atlantic salmon and underlines the importance of understanding the role of stochastic processes such as random drift and small migration rates in microbial community assembly, before considering any functional role of the gut microbes encountered. [ABSTRACT FROM AUTHOR]

Although it is generally believed that the increase in the mean global surface temperature since industrialization is caused by the increase in green house gases in the atmosphere, some people cite solar activity, either directly or through its effect on cosmic rays, as an underestimated contributor to such global warming. In this letter a simplified version of the standard picture of the role of greenhouse gases in causing the global warming since industrialization is described. The conditions necessary for this picture to be wholly or partially wrong are then introduced. Evidence is presented from which the contributions of either cosmic rays or solar activity to this warming is deduced. The contribution is shown to be less than 10% of the warming seen in the twentieth century.