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.

Family history of premature cardiovascular disease: blood pressure control and long-term mortality outcomes in hypertensive patients.

AIMS: Current guidelines recommend early referral and initiation of intensive cardiovascular (CV) risk reduction in individuals with a positive family history of coronary heart disease (CHD). We hypothesized that a family history of premature CHD and stroke [CV disease (CVD)] would lead to earlier referral of hypertensive patients to secondary care clinic, leading to better control of risk factors, mitigating the excess risk seen in these individuals. METHODS AND RESULTS: We studied the association of a positive family history of CVD in 10 787 individuals with longitudinal changes in risk factors and long-term cause-specific mortality in the Glasgow Blood Pressure Clinic using generalized estimating equations and the Cox proportional hazard models, respectively. The total time at risk was 193 756 person-years with a median survival time of 29.2 years. A positive family history of CVD was associated with an earlier presentation to the clinic, a lower burden of traditional CV risk factors, and similar longitudinal blood pressure reduction and drug adherence compared with those without. But despite these positive features, all-cause [hazard ratio (HR) = 1.12, 95% confidence interval 1.01-1.25] and CV (HR = 1.20, 1.04-1.38) mortality independent of baseline risk factors were worse. Consistent results were observed in propensity score-matched analysis. Inclusion of family history of CVD did not improve mortality risk discrimination over and above traditional risk factors. CONCLUSION: Our study suggests that despite earlier referral and treatment of individuals with a positive family history of premature CVD, excess risk persists, indicating the need for continued and sustained efforts to reduce risk factors and drug adherence in these individuals.

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.

Headwaters are critical reservoirs of microbial diversity for fluvial networks.

Streams and rivers form conspicuous networks on the Earth and are among nature's most effective integrators. Their dendritic structure reaches into the terrestrial landscape and accumulates water and sediment en route from abundant headwater streams to a single river mouth. The prevailing view over the last decades has been that biological diversity also accumulates downstream. Here, we show that this pattern does not hold for fluvial biofilms, which are the dominant mode of microbial life in streams and rivers and which fulfil critical ecosystem functions therein. Using 454 pyrosequencing on benthic biofilms from 114 streams, we found that microbial diversity decreased from headwaters downstream and especially at confluences. We suggest that the local environment and biotic interactions may modify the influence of metacommunity connectivity on local biofilm biodiversity throughout the network. In addition, there was a high degree of variability in species composition among headwater streams that could not be explained by geographical distance between catchments. This suggests that the dendritic nature of fluvial networks constrains the distributional patterns of microbial diversity similar to that of animals. Our observations highlight the contributions that headwaters make in the maintenance of microbial biodiversity in fluvial networks.

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.

The Role of Chlorine in the Formation and Development of Tap Water Biofilms under Different Flow Regimes.

Water companies make efforts to reduce the risk of microbial contamination in drinking water. A widely used strategy is to introduce chlorine into the drinking water distribution system (DWDS). A subtle potential risk is that non-lethal chlorine residuals may select for chlorine resistant species in the biofilms that reside in DWDS. Here, we quantify the thickness, density, and coverage of naturally occurring multi-species biofilms grown on slides in tap water with and without chlorine, using fluorescence microscopy. We then place the slides in an annular rotating reactor and expose them to fluid-wall shears, which are redolent of those on pipe walls in DWDS. We found that biofilms in chlorine experiment were thicker, denser and with higher coverage than in non-chlorine conditions under all flow regimes and during incubation. This suggests that the formation and development of biofilms was promoted by chlorine. Surprisingly, for both chlorinated and non-chlorinated conditions, biofilm thickness, density and coverage were all positively correlated with shear stress. More differences were detected in biofilms under the different flow regimes in non-chlorine than in chlorine experiments. This suggests a more robust biofilm under chlorine conditions. While this might imply less mobilization of biofilms in high shear events in pipe networks, it might also provide refuge from chlorine residuals for pathogens.

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.