Spatial distribution of prokaryotic communities in hypersaline soils

Increasing salinization in wetland systems is a major threat to ecosystem services carried out by microbial communities. Thus, it is paramount to understand how salinity drives both microbial community structures and their diversity. Here we evaluated the structure and diversity of the prokaryotic communities from a range of highly saline soils (EC1:5 from 5.96 to 61.02 dS/m) from the Odiel Saltmarshes and determined their association with salinity and other soil physicochemical features by analyzing 16S rRNA gene amplicon data through minimum entropy decomposition (MED). We found that these soils harbored unique communities mainly composed of halophilic and halotolerant taxa from the phyla Euryarchaeota, Proteobacteria, Balneolaeota, Bacteroidetes and Rhodothermaeota. In the studied soils, several site-specific properties were correlated with community structure and individual abundances of particular sequence variants. Salinity had a secondary role in shaping prokaryotic communities in these highly saline samples since the dominant organisms residing in them were already well-adapted to a wide range of salinities. We also compared ESV-based results with OTU-clustering derived ones, showing that, in this dataset, no major differences in ecological outcomes were obtained by the employment of one or the other method.España, Ministerio de Economía, Industria y Competitividad CGL2013-46941-P and CGL2017-83385-PJunta de Andalucía BIO-21

Aligning the Measurement of Microbial Diversity with Macroecological Theory

The number of microbial operational taxonomic units (OTUs) within a community is akin to species richness within plant/animal (“macrobial”) systems. A large literature documents OTU richness patterns, drawing comparisons to macrobial theory. There is, however, an unrecognized fundamental disconnect between OTU richness and macrobial theory: OTU richness is commonly estimated on a per-individual basis, while macrobial richness is estimated per-area. Furthermore, the range or extent of sampled environmental conditions can strongly influence a study's outcomes and conclusions, but this is not commonly addressed when studying OTU richness. Here we (i) propose a new sampling approach that estimates OTU richness per-mass of soil, which results in strong support for species energy theory, (ii) use data reduction to show how support for niche conservatism emerges when sampling across a restricted range of environmental conditions, and (iii) show how additional insights into drivers of OTU richness can be generated by combining different sampling methods while simultaneously considering patterns that emerge by restricting the range of environmental conditions. We propose that a more rigorous connection between microbial ecology and macrobial theory can be facilitated by exploring how changes in OTU richness units and environmental extent influence outcomes of data analysis. While fundamental differences between microbial and macrobial systems persist (e.g., species concepts), we suggest that closer attention to units and scale provide tangible and immediate improvements to our understanding of the processes governing OTU richness and how those processes relate to drivers of macrobial species richness

Genetic and metabolic links between the murine microbiome and memory.

BackgroundRecent evidence has linked the gut microbiome to host behavior via the gut-brain axis [1-3]; however, the underlying mechanisms remain unexplored. Here, we determined the links between host genetics, the gut microbiome and memory using the genetically defined Collaborative Cross (CC) mouse cohort, complemented with microbiome and metabolomic analyses in conventional and germ-free (GF) mice.ResultsA genome-wide association analysis (GWAS) identified 715 of 76,080 single-nucleotide polymorphisms (SNPs) that were significantly associated with short-term memory using the passive avoidance model. The identified SNPs were enriched in genes known to be involved in learning and memory functions. By 16S rRNA gene sequencing of the gut microbial community in the same CC cohort, we identified specific microorganisms that were significantly correlated with longer latencies in our retention test, including a positive correlation with Lactobacillus. Inoculation of GF mice with individual species of Lactobacillus (L. reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6) resulted in significantly improved memory compared to uninoculated or E. coli DH10B inoculated controls. Untargeted metabolomics analysis revealed significantly higher levels of several metabolites, including lactate, in the stools of Lactobacillus-colonized mice, when compared to GF control mice. Moreover, we demonstrate that dietary lactate treatment alone boosted memory in conventional mice. Mechanistically, we show that both inoculation with Lactobacillus or lactate treatment significantly increased the levels of the neurotransmitter, gamma-aminobutyric acid (GABA), in the hippocampus of the mice.ConclusionTogether, this study provides new evidence for a link between Lactobacillus and memory and our results open possible new avenues for treating memory impairment disorders using specific gut microbial inoculants and/or metabolites. Video Abstract

Identifying Low pH Active and Lactate-Utilizing Taxa within Oral Microbiome Communities from Healthy Children Using Stable Isotope Probing Techniques

<div><h3>Background</h3><p>Many human microbial infectious diseases including dental caries are polymicrobial in nature. How these complex multi-species communities evolve from a healthy to a diseased state is not well understood. Although many health- or disease-associated oral bacteria have been characterized <em>in vitro</em>, their physiology within the complex oral microbiome is difficult to determine with current approaches. In addition, about half of these species remain uncultivated to date with little known besides their 16S rRNA sequence. Lacking culture-based physiological analyses, the functional roles of uncultivated species will remain enigmatic despite their apparent disease correlation. To start addressing these knowledge gaps, we applied a combination of Magnetic Resonance Spectroscopy (MRS) with RNA and DNA based Stable Isotope Probing (SIP) to oral plaque communities from healthy children for <em>in vitro</em> temporal monitoring of metabolites and identification of metabolically active and inactive bacterial species.</p> <h3>Methodology/Principal Findings</h3><p>Supragingival plaque samples from caries-free children incubated with ¹³C-substrates under imposed healthy (buffered, pH 7) and diseased states (pH 5.5 and pH 4.5) produced lactate as the dominant organic acid from glucose metabolism. Rapid lactate utilization upon glucose depletion was observed under pH 7 conditions. SIP analyses revealed a number of genera containing cultured and uncultivated taxa with metabolic capabilities at pH 5.5. The diversity of active species decreased significantly at pH 4.5 and was dominated by <em>Lactobacillus</em> and <em>Propionibacterium</em> species, both of which have been previously found within carious lesions from children.</p> <h3>Conclusions/Significance</h3><p>Our approach allowed for identification of species that metabolize carbohydrates under different pH conditions and supports the importance of Lactobacilli and Propionibacterium in the development of childhood caries. Identification of species within healthy subjects that are active at low pH can lead to a better understanding of oral caries onset and generate appropriate targets for preventative measures in the early stages.</p> </div

Using enzymes to link soil structure and microbial community function in a prairie chronosequence

Thesis (M.S.), Soil Science, Washington State UniversityDepartment of Crop and Soil Sciences, Washington State Universit

A broad-host-range event detector: expanding and quantifying performance between Escherichia coli and Pseudomonas species

Modern microbial biodesign relies on the principle that well-characterized genetic parts can be reused and reconfigured for different functions. However, this paradigm has only been successful in a limited set of hosts, mostly comprised from common lab strains of Escherichia coli. It is clear that new applications such as chemical sensing and event logging in complex environments will benefit from new host chassis. This study quantitatively compared how the same chemical event logger performed across four strains and three different microbial species. An integrase-based sensor and memory device was operated by two representative soil Pseudomonads - Pseudomonas fluorescens SBW25 and Pseudomonas putida DSM 291. Quantitative comparisons were made between these two non-traditional hosts and two benchmark E. coli chassis including the probiotic Nissle 1917 and common cloning strain DH5α. The performance of sensor and memory components changed according to each host, such that a clear chassis effect was observed and quantified. These results were obtained via fluorescence from reporter proteins that were transcriptionally fused to the integrase and downstream recombinant region and via data-driven kinetic models. The Pseudomonads proved to be acceptable chassis for the operation of this event logger, which outperformed the common E. coli DH5α in many ways. This study advances an emerging frontier in synthetic biology that aims to build broad-host-range devices and understand the context by which different species can execute programmable genetic operations

Disturbance triggers non-linear microbe–environment feedbacks

Conceptual frameworks linking microbial community membership, properties, and processes with the environment and emergent function have been proposed but remain untested. Here we refine and test a recent conceptual framework using hyporheic zone sediments exposed to wetting–drying transitions. Our refined framework includes relationships between cumulative properties of a microbial community (e.g., microbial membership, community assembly properties, and biogeochemical rates), environmental features (e.g., organic matter thermodynamics), and emergent ecosystem function. Our primary aim was to evaluate the hypothesized relationships that comprise the conceptual framework and contrast outcomes from the whole and putatively active bacterial and archaeal communities. Throughout the system we found threshold-like responses to the duration of desiccation. Membership of the putatively active community – but not the whole bacterial and archaeal community – responded due to enhanced deterministic selection (an emergent community property). Concurrently, the thermodynamic properties of organic matter (OM) became less favorable for oxidation (an environmental component), and respiration decreased (a microbial process). While these responses were step functions of desiccation, we found that in deterministically assembled active communities, respiration was lower and thermodynamic properties of OM were less favorable. Placing the results in context of our conceptual framework points to previously unrecognized internal feedbacks that are initiated by disturbance and mediated by thermodynamics and that cause the impacts of disturbance to be dependent on the history of disturbance

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The taxonomic and functional diversity inherent to the soil microbiome complicate assessments of the metabolic potential carried out by the community members. An alternative approach is to break down the soil microbiome into reduced-complexity subsets based on metabolic capacities (functional modules) prior to sequencing and analysis. Here, we demonstrate that this approach successfully identified specific phylogenetic and biochemical traits of the soil microbiome that otherwise remained hidden from a more top-down analysis.The soil microbiome represents one of the most complex microbial communities on the planet, encompassing thousands of taxa and metabolic pathways, rendering holistic analyses computationally intensive and difficult. Here, we developed an alternative approach in which the complex soil microbiome was broken into components (“functional modules”), based on metabolic capacities, for individual characterization. We hypothesized that reproducible, low-complexity communities that represent functional modules could be obtained through targeted enrichments and that, in combination, they would encompass a large extent of the soil microbiome diversity. Enrichments were performed on a starting soil inoculum with defined media based on specific carbon substrates, antibiotics, alternative electron acceptors under anaerobic conditions, or alternative growing conditions reflective of common field stresses. The resultant communities were evaluated through 16S rRNA amplicon sequencing. Less permissive modules (anaerobic conditions, complex polysaccharides, and certain stresses) resulted in more distinct community profiles with higher richness and more variability between replicates, whereas modules with simple substrates were dominated by fewer species and were more reproducible. Collectively, approximately 27% of unique taxa present in the liquid soil extract control were found across functional modules. Taxa that were underrepresented or undetected in the source soil were also enriched across the modules. Metatranscriptomic analyses were carried out on a subset of the modules to investigate differences in functional gene expression. These results demonstrate that by dissecting the soil microbiome into discrete components it is possible to obtain a more comprehensive view of the soil microbiome and its biochemical potential than would be possible using more holistic analyses