intI1 gene abundance from septic tanks in Thailand using validated intI1 primers.

IMPORTANCE: Antimicrobial resistance is a global crisis, and wastewater treatment, including septic tanks, remains an important source of antimicrobial resistance (AMR) genes. The role of septic tanks in disseminating class 1 integron, and by extension AMR genes, in Thailand, where antibiotic use is unregulated remains understudied. We aimed to monitor gene abundance as a proxy to infer potential AMR from septic tanks in Thailand. We evaluated published intI1 primers due to the lack of consensus on optimal Q-PCR primers and the absence of standardization. Our findings confirmed septic tanks are a source of class 1 integron to the environment. We highlighted the significance of intI1 primer choice, in the context of interpretation of risk associated with AMR spread from septic tanks. We recommend the validated set (F3-R3) for optimal intI1 quantification toward the goal of achieving standardization across studies.

Environmental and ecological controls of the spatial distribution of microbial populations in aggregates.

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.

Biochemistry shapes growth kinetics of nitrifiers and defines their activity under specific environmental conditions.

Is it possible to find trends between the parameters that define microbial growth to help us explain the vast microbial diversity? Through an extensive database of kinetic parameters of nitrifiers, we analyzed if the dominance of specific populations of nitrifiers could be predicted and explained. We concluded that, in general, higher growth yield (YXS ) and ammonia affinity (a0NH3 ) and lower growth rate (µmax ) are observed for ammonia-oxidizing archaea (AOA) than bacteria (AOB), which would explain their considered dominance in oligotrophic environments. However, comammox (CMX), with the maximum energy harvest per mole of ammonia, and some AOB, have higher a0NH3 and lower µmax than some AOA. Although we were able to correlate the presence of specific terminal oxidases with observed oxygen affinities (a0O2 ) for nitrite-oxidizing bacteria (NOB), that correlation was not observed for AOB. Moreover, the presumed dominance of AOB over NOB in O2 -limiting environments is discussed. Additionally, lower statistical variance of a0O2 values than for ammonia and nitrite affinities was observed, suggesting nitrogen limitation as a stronger selective pressure. Overall, specific growth strategies within nitrifying groups were not identified through the reported kinetic parameters, which might suggest that mostly, fundamental differences in biochemistry are responsible for underlying kinetic parameters.

Drift dynamics in microbial communities and the effective community size.

The structure and diversity of all open microbial communities are shaped by individual births, deaths, speciation and immigration events; the precise timings of these events are unknowable and unpredictable. This randomness is manifest as ecological drift in the population dynamics, the importance of which has been a source of debate for decades. There are theoretical reasons to suppose that drift would be imperceptible in large microbial communities, but this is at odds with circumstantial evidence that effects can be seen even in huge, complex communities. To resolve this dichotomy we need to observe dynamics in simple systems where key parameters, like migration, birth and death rates can be directly measured. We monitored the dynamics in the abundance of two genetically modified strains of Escherichia coli, with tuneable growth characteristics, that were mixed and continually fed into 10 identical chemostats. We demonstrated that the effects of demographic (non-environmental) stochasticity are very apparent in the dynamics. However, they do not conform to the most parsimonious and commonly applied mathematical models, where each stochastic event is independent. For these simple models to reproduce the observed dynamics we need to invoke an 'effective community size', which is smaller than the census community size.

Neutral mechanisms and niche differentiation in steady-state insular microbial communities revealed by single cell analysis.

In completely insular microbial communities, evolution of community structure cannot be shaped by the immigration of new members. In addition, when those communities are run in steady state, the influence of environmental factors on their assembly is reduced. Therefore, one would expect similar community structures under steady-state conditions. Yet, in parallel setups, variability does occur. To reveal ecological mechanisms behind this phenomenon, five parallel reactors were studied at the single-cell level for about 100 generations and community structure variations were quantified by ecological measures. Whether community variability can be controlled was tested by implementing soft temperature stressors as potential synchronizers. The low slope of the lognormal rank-order abundance curves indicated a predominance of neutral mechanisms, i.e., where species identity plays no role. Variations in abundance ranks of subcommunities and increase in inter-community pairwise ß-diversity over time support this. Niche differentiation was also observed, as indicated by steeper geometric-like rank-order abundance curves and increased numbers of correlations between abiotic and biotic parameters during initial adaptation and after disturbances. Still, neutral forces dominated community assembly. Our findings suggest that complex microbial communities in insular steady-state environments can be difficult to synchronize and maintained in their original or desired structure, as they are non-equilibrium systems.

Herbicide-tolerant endophytic bacteria of rice plants as the biopriming agents for fertility recovery and disease suppression of unhealthy rice seeds.

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.

The effect of metabolic stress on genome stability of a synthetic biology chassis Escherichia coli K12 strain.

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.

Biofilm community succession: a neutral perspective.

Although biofilms represent one of the dominant forms of life in aqueous environments, our understanding of the assembly and development of their microbial communities remains relatively poor. In recent years, several studies have addressed this and have extended the concepts of succession theory in classical ecology into microbial systems. From these datasets, niche-based conceptual models have been developed explaining observed biodiversity patterns and their dynamics. These models have not, however, been formulated mathematically and so remain untested. Here, we further develop spatially resolved neutral community models and demonstrate that these can also explain these patterns and offer alternative explanations of microbial succession. The success of neutral models suggests that stochastic effects alone may have a much greater influence on microbial community succession than previously acknowledged. Furthermore, such models are much more readily parameterised and can be used as the foundation of more complex and realistic models of microbial community succession.

Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform.

With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%.

Fluvial network organization imprints on microbial co-occurrence networks.

Recent studies highlight linkages among the architecture of ecological networks, their persistence facing environmental disturbance, and the related patterns of biodiversity. A hitherto unresolved question is whether the structure of the landscape inhabited by organisms leaves an imprint on their ecological networks. We analyzed, based on pyrosequencing profiling of the biofilm communities in 114 streams, how features inherent to fluvial networks affect the co-occurrence networks that the microorganisms form in these biofilms. Our findings suggest that hydrology and metacommunity dynamics, both changing predictably across fluvial networks, affect the fragmentation of the microbial co-occurrence networks throughout the fluvial network. The loss of taxa from co-occurrence networks demonstrates that the removal of gatekeepers disproportionately contributed to network fragmentation, which has potential implications for the functions biofilms fulfill in stream ecosystems. Our findings are critical because of increased anthropogenic pressures deteriorating stream ecosystem integrity and biodiversity.

Benchmarking of viral haplotype reconstruction programmes: an overview of the capacities and limitations of currently available programmes.

Viral haplotype reconstruction from a set of observed reads is one of the most challenging problems in bioinformatics today. Next-generation sequencing technologies enable us to detect single-nucleotide polymorphisms (SNPs) of haplotypes-even if the haplotypes appear at low frequencies. However, there are two major problems. First, we need to distinguish real SNPs from sequencing errors. Second, we need to determine which SNPs occur on the same haplotype, which cannot be inferred from the reads if the distance between SNPs on a haplotype exceeds the read length. We conducted an independent benchmarking study that directly compares the currently available viral haplotype reconstruction programmes. We also present nine in silico data sets that we generated to reflect biologically plausible populations. For these data sets, we simulated 454 and Illumina reads and applied the programmes to test their capacity to reconstruct whole genomes and individual genes. We developed a novel statistical framework to demonstrate the strengths and limitations of the programmes. Our benchmarking demonstrated that all the programmes we tested performed poorly when sequence divergence was low and failed to recover haplotype populations with rare haplotypes.

Metagenomic Sequencing Unravels Gene Fragments with Phylogenetic Signatures of O2-Tolerant NiFe Membrane-Bound Hydrogenases in Lacustrine Sediment.

Many promising hydrogen technologies utilising hydrogenase enzymes have been slowed by the fact that most hydrogenases are extremely sensitive to O2. Within the group 1 membrane-bound NiFe hydrogenase, naturally occurring tolerant enzymes do exist, and O2 tolerance has been largely attributed to changes in iron-sulphur clusters coordinated by different numbers of cysteine residues in the enzyme's small subunit. Indeed, previous work has provided a robust phylogenetic signature of O2 tolerance [1], which when combined with new sequencing technologies makes bio prospecting in nature a far more viable endeavour. However, making sense of such a vast diversity is still challenging and could be simplified if known species with O2-tolerant enzymes were annotated with information on metabolism and natural environments. Here, we utilised a bioinformatics approach to compare O2-tolerant and sensitive membrane-bound NiFe hydrogenases from 177 bacterial species with fully sequenced genomes for differences in their taxonomy, O2 requirements, and natural environment. Following this, we interrogated a metagenome from lacustrine surface sediment for novel hydrogenases via high-throughput shotgun DNA sequencing using the Illumina™ MiSeq platform. We found 44 new NiFe group 1 membrane-bound hydrogenase sequence fragments, five of which segregated with the tolerant group on the phylogenetic tree of the enzyme's small subunit, and four with the large subunit, indicating de novo O2-tolerant protein sequences that could help engineer more efficient hydrogenases.

Microbial stratification and DOM removal in drinking water biofilters: Implications for enhanced performance.

Biofiltration is a low-cost, low-energy technology that employs a biologically activated bed of porous medium to reduce the biodegradable fraction of the dissolved organic matter (DOM) pool in source water, resulting in the production of drinking water. Microbial communities at different bed depths within the biofilter play crucial roles in the degradation and removal of dissolved organic carbon (DOC), ultimately impacting its performance. However, the relationships between the composition of microbial communities inhabiting different biofilter depths and their utilisation of various DOC fractions remain poorly understood. To address this knowledge gap, we conducted an experimental study where microbial communities from the upper (i.e., top 10 cm) and lower (i.e., bottom 10 cm) sections of a 30-cm long laboratory-scale biofilter were recovered. These communities were then individually incubated for 10 days using the same source water as the biofilter influent. Our study revealed that the bottom microbial community exhibited lower diversity yet had a co-occurrence network with a higher degree of interconnections among its members compared to the top microbial community. Moreover, we established a direct correlation between the composition and network structure of the microbial communities and their ability to utilise various DOM compounds within a DOM pool. Interestingly, although the bottom microbial community had only 20 % of the total cell abundance compared to the top community at the beginning of the incubation, it utilised and hence removed approximately 60 % more total DOC from the DOM pool than the top community. While both communities rapidly utilised labile carbon fractions, such as low-molecular-weight neutrals, the utilisation of more refractory carbon fractions, like high-molecular-weight humic substances with an average molecular weight of more than ca. 1451 g/mol, was exclusive to the bottom microbial community. By employing techniques that capture microbial diversity (i.e., flow cytometry and 16S rRNA amplicon sequencing) and considering the complexities of DOM (i.e., LCOCD), our study provides novel insights into how microbial community structure could influence the microbial-mediated processes of engineering significance in drinking water production. Finally, our findings could offer the opportunity to improve biofilter performances via engineering interventions that shape the compositions of biofilter microbial communities and enhance their utilisation and removal of DOM, most notably the more classically humified and refractory DOM compound groups.

Modelling the effects of dispersal mechanisms and hydrodynamic regimes upon the structure of microbial communities within fluvial biofilms.

The spatial distribution of microbial taxa is determined primarily by physical and chemical environments and by dispersal. In a homogeneous landscape with limited dispersal, the similarity in abundance of taxa in samples declines with separation distance. We present a one-dimensional model for the spatial autocorrelation in abundances arising from immigration from some remote community and dispersal between environmentally similar landscape patches. Spatial correlation in taxa abundances were calculated from biofilms from the beds of two flumes which differed only in their bedform profiles; one flat and the other a periodic sawtooth shape. The hydraulic regime is approximately uniform over the flat bed, whereas the sawtooth induces fast flow over the peaks and recirculation in the troughs. On the flat bed, the correlation decline between samples was reproduced by a model using one biologically reasonable parameter. A decline was apparent in the other flume; however, a better fit was achieved when dispersal was not assumed constant everywhere. However, analysis of finer-resolution data for the heterogeneous flume suggested even this model did not adequately capture the community's complexity. We conclude that hydrodynamics are a strong driver of taxa-abundance patterns in stream biofilms. However, local adaptability must also be considered to build up a complete mechanistic model.

Magnetic resonance imaging of mass transport and structure inside a phototrophic biofilm.

The aim of this study was to utilize magnetic resonance imaging (MRI) to image structural heterogeneity and mass transport inside a biofilm which was too thick for photon based imaging. MRI was used to map water diffusion and image the transport of the paramagnetically tagged macromolecule, Gd-DTPA, inside a 2.5 mm thick cyanobacterial biofilm. The structural heterogeneity of the biofilm was imaged at resolutions down to 22 × 22 µm, enabling the impact of biofilm architecture on the mass transport of both water and Gd-DTPA to be investigated. Higher density areas of the biofilm correlated with areas exhibiting lower relative water diffusion coefficients and slower transport of Gd-DTPA, highlighting the impact of biofilm structure on mass transport phenomena. This approach has potential for shedding light on heterogeneous mass transport of a range of molecular mass molecules in biofilms.

Combined niche and neutral effects in a microbial wastewater treatment community.

It has long been assumed that differences in the relative abundance of taxa in microbial communities reflect differences in environmental conditions. Here we show that in the economically and environmentally important microbial communities in a wastewater treatment plant, the population dynamics are consistent with neutral community assembly, where chance and random immigration play an important and predictable role in shaping the communities. Using dynamic observations, we demonstrate a straightforward calibration of a purely neutral model and a parsimonious method to incorporate environmental influence on the reproduction (or birth) rate of individual taxa. The calibrated model parameters are biologically plausible, with the population turnover and diversity in the heterotrophic community being higher than for the ammonia oxidizing bacteria (AOB) and immigration into AOB community being relatively higher. When environmental factors were incorporated more of the variance in the observations could be explained but immigration and random reproduction and deaths remained the dominant driver in determining the relative abundance of the common taxa. Consequently we suggest that neutral community models should be the foundation of any description of an open biological system.

Engineering biology in the face of uncertainty.

Combining engineering and biology surely must be a route to delivering solutions to the world's most pressing problems in depleting resources, energy and the environment. Engineers and biologists have long recognized the power in coupling their disciplines and have evolved a healthy variety of approaches to realizing technologies. Yet recently, there has been a movement to narrow the remit of engineering biology. Its definition as 'the application of engineering principles to the design of biological systems' ought to encompass a broad church. However, the emphasis is firmly on construction '…of novel biological devices and systems from standardized artificial parts' within cells. Thus, engineering biology has become synonymous with synthetic biology, despite the many longstanding technologies that use natural microbial communities. The focus on the nuts and bolts of synthetic organisms may be deflecting attention from the significant challenge of delivering solutions at scale, which cuts across all engineering biology, synthetic and natural. Understanding, let alone controlling, every component of an engineered system is an unrealistic goal. To realize workable solutions in a timely manner we must develop systematic ways of engineering biology in the face of the uncertainties that are inherent in biological systems and that arise through lack of knowledge.

Multiscale models driving hypothesis and theory-based research in microbial ecology.

Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the improvement of current environmental biotechnologies. We propose that a multiscale modelling bottom-up approach (piecing together sub-systems to give rise to more complex systems) can be used as a framework to generate mechanistic hypotheses and theories (in-silico bottom-up methodology). To accomplish this, formal comprehension of the mathematical model design is required together with a systematic procedure for the application of the in-silico bottom-up methodology. Ruling out the belief that experimentation before modelling is indispensable, we propose that mathematical modelling can be used as a tool to direct experimentation by validating theoretical principles of microbial ecology. Our goal is to develop methodologies that effectively integrate experimentation and modelling efforts to achieve superior levels of predictive capacity.

Competitive and substrate limited environments drive metabolic heterogeneity for comammox Nitrospira.

Nitrospira has been revealed as a high versatile genus. Although previously considered only responsible for the conversion of nitrite to nitrate, now we know that Nitrospira can perform complete ammonia oxidation to nitrate too (comammox). Comammox activity was firstly reported as dominant in extremely limited oxygen environments, where anaerobic ammonia oxidation was also occurring (anammox). To explain the comammox selection, we developed an Individual-based Model able to describe Nitrospira and anammox growth in suspended flocs assembled in a dynamic nitrogen and oxygen-limiting environment. All known and hypothesized nitrogen transformations of Nitrospira were considered: ammonia and nitrite oxidation, comammox, nitrate-reducing ammonia oxidation, and anaerobic nitrite-reducing ammonia oxidation. Through bioenergetics analysis, the growth yield associated to each activity was estimated. The other kinetic parameters necessary to describe growth were calibrated according to the reported literature values. Our modeling results suggest that even extremely low oxygen concentrations (~1.0 µM) allow for a proportional growth of anammox versus Nitrospira similar to the one experimentally observed. The strong oxygen limitation was followed by a limitation of ammonia and nitrite, because anammox, without strong competitors, were able to grow faster than Nitrospira depleting the environment in nitrogen. These substrate limitations created an extremely competitive environment that proved to be decisive in the community assembly of Nitrospira and anammox. Additionally, a diversity of metabolic activities for Nitrospira was observed in all tested conditions, which in turn, explained the transient nitrite accumulation observed in aerobic environments with higher ammonia availability.

Temporal stability and community assembly mechanisms in healthy broiler cecum.

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.