Simple Microbial Communities Research Articles

Evaluation of the quality of products from multiple industrial-scale composting treatment facilities for kitchen waste and exploration of influencing factors

The aerobic composting process is extensively utilized to manage kitchen waste. Nonetheless, the variability in the quality of compost derived from engineering practices which significantly hinders its broader industrial application. This work investigated the final products of kitchen waste compost at multiple industrial-scale treatment facilities utilizing three distinct aerobic composting processes in a bid to explore key factors affecting compost quality. The quality evaluation was based on technical parameters like seed germination index (GI), and limiting factors such as heavy metal content. The results showed that most of the compost products failed to meet the established standards, with GI being the primary limiting indicator. Furthermore, maturity assessments suggested that compost with low GI exhibited reduced humification could not be recommended for agricultural use. The investigation delved into the primary determinants of GI, focusing on risk factors such as the oil and salt of kitchen waste, and the microbial community of the humification driving forces. The results indicated that products with low GI had higher oil and salt content and a relatively simple microbial community. A thorough analysis suggested that excessive levels oil and salt were potential influencing factors on GI, as they stimulated the activity of acid-producing bacteria like Lactobacillus, suppressed the activity of humification-promoting bacteria such as Actinomarinales, and influenced the decomposition and humification processes of organic matter and total nitrogen, thereby affecting product quality. The findings provide valuable insights for improving kitchen waste compost products for agricultural applications.

A review on recent taxonomic updates of gut bacteria associated with social bees, with a curated genomic reference database.

Honeybees and bumblebees play a crucial role as essential pollinators. The special gut microbiome of social bees is a key factor in determining the overall fitness and health of the host. Although bees harbor relatively simple microbial communities at the genus level, recent studies have unveiled significant genetic divergence and variations in gene content within each bacterial genus. However, a comprehensive and refined genomics-based taxonomic database specific to social bee gut microbiomes remains lacking. Here, we first provided an overview of the current knowledge on the distribution and function of social bee gut bacteria, as well as the factors that influence the gut population dynamics. We then consolidated all available genomes of the gut bacteria of social bees and refined the species-level taxonomy, by constructing a maximum-likelihood core genome phylogeny and calculating genome-wide pairwise average nucleotide identity. On the basis of the refined species taxonomy, we constructed a curated genomic reference database, named the bee gut microbe genome sequence database (BGM-GDb). To evaluate the species-profiling performance of the curated BGM-GDb, we retrieved a series of bee gut metagenomic data and inferred the species-level composition using metagenomic intra-species diversity analysis system (MIDAS), and then compared the results with those obtained from a prebuilt MIDAS database. We found that compared with the default database, the BGM-GDb excelled in aligned read counts and bacterial richness. Overall, this high-resolution and precise genomic reference database will facilitate research in understanding the gut community structure of social bees.

Proteome allocation and the evolution of metabolic cross-feeding.

In a common instance of metabolic cross-feeding (MCF), an organism incompletely metabolizes nutrients and releases metabolites that are used by another to produce energy or building blocks. Why would the former waste edible food, and why does this preferentially occur at specific locations in a metabolic pathway have challenged evolutionary theory for decades. To address these questions, we combine adaptive dynamics with an explicit model of cell metabolism, including enzyme-driven catalysis of metabolic reactions and the cellular constraints acting on the proteome that may incur a cost to expressing all enzymes along a pathway. After pointing out that cells should in principle prioritize upstream reactions when metabolites are restrained inside the cell, we show that the occurrence of permeability-driven MCF is rare and requires that an intermediate metabolite be extremely diffusive. Indeed, only at very high levels of membrane permeability (consistent with those of acetate and glycerol, for instance) and under distinctive sets of parameters should the population diversify and MCF evolve. These results help understand the origins of simple microbial communities, such as those that readily evolve in short-term evolutionary experiments, and may later be extended to investigate how evolution has progressively built up today's extremely diverse ecosystems.

Evaluation of multiple displacement amplification for metagenomic analysis of low biomass samples.

Combining multiple displacement amplification (MDA) with metagenomics enables the analysis of samples with extremely low DNA concentrations, making them suitable for high-throughput sequencing. Although amplification bias and nonspecific amplification have been reported from MDA-amplified samples, the impact of MDA on metagenomic datasets is not well understood. We compared three MDA methods (i.e. bulk MDA, emulsion MDA, and primase MDA) for metagenomic analysis of two DNA template concentrations (approx. 1 and 100pg) derived from a microbial community standard "mock community" and two low biomass environmental samples (i.e. borehole fluid and groundwater). We assessed the impact of MDA on metagenome-based community composition, assembly quality, functional profiles, and binning. We found amplification bias against high GC content genomes but relatively low nonspecific amplification such as chimeras, artifacts, or contamination for all MDA methods. We observed MDA-associated representational bias for microbial community profiles, especially for low-input DNA and with the primase MDA method. Nevertheless, similar taxa were represented in MDA-amplified libraries to those of unamplified samples. The MDA libraries were highly fragmented, but similar functional profiles to the unamplified libraries were obtained for bulk MDA and emulsion MDA at higher DNA input and across these MDA libraries for the groundwater sample. Medium to low-quality bins were possible for the high input bulk MDA metagenomes for the most simple microbial communities, borehole fluid, and mock community. Although MDA-based amplification should be avoided, it can still reveal meaningful taxonomic and functional information from samples with extremely low DNA concentration where direct metagenomics is otherwise impossible.

On the De Novo Emergence of Ecological Interactions during Evolutionary Diversification: A Conceptual Framework and Experimental Test.

AbstractEcological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities.

Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity.

Cross feeding between microbes is ubiquitous, but its impact on the diversity and productivity of microbial communities is incompletely understood. A reductionist approach using simple microbial communities has the potential to detect cross feeding interactions and their impact on ecosystem properties. However, quantifying abundance of more than two microbes in a community in a high throughput fashion requires rapid, inexpensive assays. Here, we show that multicolor flow cytometry combined with a machine learning-based classifier can rapidly quantify species abundances in simple, synthetic microbial communities. Our approach measures community structure over time and detects the exchange of metabolites in a four-member community of fluorescent Bacteroides species. Notably, we quantified species abundances in co-cultures and detected evidence of cooperation in polysaccharide processing and competition for monosaccharide utilization. We also observed that co-culturing on simple sugars, but not complex sugars, reduced microbial productivity, although less productive communities maintained higher community diversity. In summary, our multicolor flow cytometric approach presents an economical, tractable model system for microbial ecology using well-studied human bacteria. It can be extended to include additional species, evaluate more complex environments, and assay response of communities to a variety of disturbances.

Anthropogenic land uses drive shifts in denitrification‐related microbiota in freshwater river ecosystems

AbstractMicrobiota play essential roles in nitrogen (N) cycling in freshwater river ecosystems. However, our understanding of microbial functional groups associated with N cycling (especially denitrification) in freshwater rivers under anthropogenic disturbance is still poor. Here, we studied the impacts of different land‐use types on denitrification‐related microbiota in the Weihe River, Hanjiang River, and their tributaries, in the Qinling Mountains, China. The major land‐use types in the three river areas were divided into natural (forest, shrub, grassland, and open water) and anthropogenic (agricultural and urbanized land) types. A landscape survey of microbiota in the river water and sediment was carried out with extensive sample sources based on deep 16S rRNA gene sequencing, which yielded operational taxonomic units for predicting functional groups. With increases in proportions of agricultural and urbanized land areas, electrical conductivity, total N, ammonium‐N, and nitrate‐N all increased in water samples. Conversely, microbial diversity exhibited a decreasing trend in water samples, whereas the relative abundance of denitrification‐related functional groups increased, with increases in the proportions of agricultural and urbanized land areas. The relative abundances of denitrification‐ and human‐related microbial functional groups in sediment samples were distinctively higher in Weihe River (mainly under agriculture and urbanization), when compared with those of Hanjiang River and Qinling tributaries (dominated by forests). The results indicate that anthropogenic land‐use types, such as agricultural and urbanized land, result in simple microbial community structure and stimulate microbe‐mediated denitrification in freshwater rivers.

Sequencing introduced false positive rare taxa lead to biased microbial community diversity, assembly, and interaction interpretation in amplicon studies

BackgroundIncreasing studies have demonstrated potential disproportionate functional and ecological contributions of rare taxa in a microbial community. However, the study of the microbial rare biosphere is hampered by their inherent scarcity and the deficiency of currently available techniques. Sample-wise cross contaminations might be introduced by sample index misassignment in the most widely used metabarcoding amplicon sequencing approach. Although downstream bioinformatic quality control and clustering or denoising algorithms could remove sequencing errors and non-biological artifact reads, no algorithm could eliminate high quality reads from sample-wise cross contaminations introduced by index misassignment, making it difficult to distinguish between bona fide rare taxa and potential false positives in metabarcoding studies.ResultsWe thoroughly evaluated the rate of index misassignment of the widely used NovaSeq 6000 and DNBSEQ-G400 sequencing platforms using both commercial and customized mock communities, and observed significant lower (0.08% vs. 5.68%) fraction of potential false positive reads for DNBSEQ-G400 as compared to NovaSeq 6000. Significant batch effects could be caused by stochastically introduced false positive or false negative rare taxa. These false detections could also lead to inflated alpha diversity of relatively simple microbial communities and underestimated that of complex ones. Further test using a set of cow rumen samples reported differential rare taxa by different sequencing platforms. Correlation analysis of the rare taxa detected by each sequencing platform demonstrated that the rare taxa identified by DNBSEQ-G400 platform had a much higher possibility to be correlated with the physiochemical properties of rumen fluid as compared to NovaSeq 6000 platform. Community assembly mechanism and microbial network correlation analysis indicated that false positive or negative rare taxa detection could lead to biased community assembly mechanism and identification of fake keystone species of the community.ConclusionsWe highly suggest proper positive/negative/blank controls, technical replicate settings, and proper sequencing platform selection in future amplicon studies, especially when the microbial rare biosphere would be focused.

Rice washing drainage (RWD) embedded in poly(vinyl alcohol)/sodium alginate as denitrification inoculum for high nitrate removal rate with low biodiversity

Immobilization technology with low maintenance is a promising alternative to enhance nitrate removal from water. In this study, washing rice drainage (RWD) was immobilized by poly(vinyl alcohol)/sodium alginate (PVA/SA) to obtain RWD-PVA/SA gel beads as inoculum for denitrification. When initial nitrate concentration was 50 mg N/L, nitrate was effectively removed at rates of 50–600 mg/(L∙d) using acetate as carbon source (C/N = 1.25). Arrhenius activation energy (Ea) of nitrate oxidoreductase was 28.64 kJ/mol for the RWD-PVA/SA gel beads. Temporal and spatial variation in microbial community structures were revealed along with RWD storage and in the reactors by Illumina high-throughput sequencing technology. RWD-PVA/SA gel beads has a simple (operational taxonomic units (OTUs) 〈100). Dechloromonas, Pseudomonas, Flavobacterium and Acidovorax were the most four dominant genera in the denitrification reactors inoculated with RWD-PVA/SA gel beads. This study provides an inoculum for denitrification with high nitrate removal performance and simple microbial community structures.

Market forces determine the distribution of a leaky function in a simple microbial community

Many biological functions are leaky, and organisms that perform them contribute some of their products to a community "marketplace" in which nonperforming individuals may compete for them. Leaky functions are partitioned unequally in microbial communities, and the evolutionary forces determining which species perform them and which become beneficiaries are poorly understood. Here, we demonstrate that the market principle of comparative advantage determines the distribution of a leaky antibiotic resistance gene in an environment occupied by two "species"-strains of Escherichia coli growing on mutually exclusive resources and thus occupying separate niches. Communities comprised of antibiotic-resistant cells were rapidly invaded by sensitive cells of both types. While the two phenotypes coexisted stably for 500 generations, in 15/18 replicates, antibiotic sensitivity became fixed in one species. Fixation always occurred in the same species despite both species being genetically identical except for their niche-defining mutation. In the absence of antibiotic, the fitness cost of resistance was identical in both species. However, the intrinsic resistance of the species that ultimately became the sole helper was significantly lower, and thus its reward for expressing the resistance gene was higher. Opportunity cost of resistance, not absolute cost or efficiency of antibiotic removal, determined which species became the helper, consistent with the economic theory of comparative advantage. We present a model that suggests that this market-like dynamic is a general property of Black Queen systems and, in communities dependent on multiple leaky functions, could lead to the spontaneous development of an equitable and efficient division of labor.

An automated multiplexed turbidometric and data collection system for measuring growth kinetics of anaerobes dependent on gaseous substrates

Standard methods of monitoring the growth kinetics of anaerobic microorganisms are generally impractical when there is a protracted or indeterminate period of active growth, and when high numbers of samples or replications are required. As part of our studies of the adaptive evolution of a simple anaerobic syntrophic mutualism, requiring the characterization of many isolates and alternative syntrophic pairings, we developed a multiplexed growth monitoring system using a combination of commercially available electronics and custom designed circuitry and materials. This system automatically monitors up to 64 sealed, and as needed pressurized, culture tubes and reports the growth data in real-time through integration with a customized relational database. The utility of this system was demonstrated by resolving minor differences in growth kinetics associated with the adaptive evolution of a simple microbial community comprised of a sulfate reducing bacterium, Desulfovibrio vulgaris, grown in syntrophic association with Methanococcus maripaludis, a hydrogenotrophic methanogen.

Complex yeast\u2013bacteria interactions affect the yield of industrial ethanol fermentation

Sugarcane ethanol fermentation represents a simple microbial community dominated by S. cerevisiae and co-occurring bacteria with a clearly defined functionality. In this study, we dissect the microbial interactions in sugarcane ethanol fermentation by combinatorically reconstituting every possible combination of species, comprising approximately 80% of the biodiversity in terms of relative abundance. Functional landscape analysis shows that higher-order interactions counterbalance the negative effect of pairwise interactions on ethanol yield. In addition, we find that Lactobacillus amylovorus improves the yeast growth rate and ethanol yield by cross-feeding acetaldehyde, as shown by flux balance analysis and laboratory experiments. Our results suggest that Lactobacillus amylovorus could be considered a beneficial bacterium with the potential to improve sugarcane ethanol fermentation yields by almost 3%. These data highlight the biotechnological importance of comprehensively studying microbial communities and could be extended to other microbial systems with relevance to human health and the environment.

Historical Contingency in Microbial Resilience to Hydrologic Perturbations

Development of reliable biogeochemical models requires a mechanistic consideration of microbial interactions with hydrology. Microbial response to and its recovery after hydrologic perturbations (i.e., resilience) is a critical component to understand in this regard, but generally difficult to predict because the impacts of future events can be dependent on the history of perturbations (i.e., historical contingency). Fundamental issues underlying this phenomenon include how microbial resilience to hydrologic perturbations is influenced by historical contingency and how their relationships vary depending on the characteristics of microbial functions. To answer these questions, we considered a simple microbial community composed of two species that redundantly consume a common substrate but specialize in producing distinct products and developed a continuous flow reactor model where the two species grow with trade-offs along the flow rate. Simulations of this model revealed that (1) the history of hydrologic perturbations can lead to the shifts in microbial populations, which consequently affect the community's functional dynamics, and (2) while historical contingency in resilience was consistently predicted for all microbial functions, it was more pronounced for specialized functions, compared to the redundant function. As a signature of historical contingency, our model also predicted the emergence of hysteresis in the transitions across conditions, a critical aspect that can affect transient formation of intermediate compounds in biogeochemistry. This work presents microbial growth traits and their functional redundancy or specialization as fundamental factors that control historical contingencies in resilience.

Fungal diversity and functionality are driven by soil texture in Taylor Valley, Antarctica

The McMurdo Dry Valleys surface is mainly constituted from unconsolidated permafrost. Despite the combination of cold and dry conditions, transiently wetted soils close to lake edges are hotspots of intense biological activity, that can support the surrounding soil ecosystems in such extreme environments. These soils host simple microbial communities that allow easy characterization of the parameters determining microbial establishment and diversification. Soil samples were collected close to three different glacial lakes (Lake Fryxell, Lake Hoare and Lake Joyce) located along a longitudinal gradient from the lower to the upper Taylor Valley. Fungal diversity and functionality of sampled soils were studied through ITS1 metabarcoding sequencing. The correlation between the parameters describing fungal diversity (i.e. total richness, relative richness of dominant taxonomic and functional groups, and community composition) and the edaphic physicochemical parameters (i.e. pH, moisture, C, N, P, Na + , K + , Mg 2+ and Ca 2+ , cation exchange capacity, and soil granulometry) was assessed. The fungal communities showed low richness (48 ± 32 OTUs per sample). Their composition was highly diversified even within different sites close to the same lake. The main parameters affecting the diversity and composition of fungal communities were soil texture, in turn influencing the retention of water and nutrients, and physicochemical properties. This is of particular concern for the survival of these communities, given the expected environmental changes due to global warming.

Survival of the weakest in non-transitive asymmetric interactions among strains of E. coli

Hierarchical organization in ecology, whereby interactions are nested in a manner that leads to a dominant species, naturally result in the exclusion of all but the dominant competitor. Alternatively, non-hierarchical competitive dynamics, such as cyclical interactions, can sustain biodiversity. Here, we designed a simple microbial community with three strains of E. coli that cyclically interact through (i) the inhibition of protein production, (ii) the digestion of genomic DNA, and (iii) the disruption of the cell membrane. We find that intrinsic differences in these three major mechanisms of bacterial warfare lead to an unbalanced community that is dominated by the weakest strain. We also use a computational model to describe how the relative toxin strengths, initial fractional occupancies, and spatial patterns affect the maintenance of biodiversity. The engineering of active warfare between microbial species establishes a framework for exploration of the underlying principles that drive complex ecological interactions.

Interactions between Kazachstania humilis Yeast Species and Lactic Acid Bacteria in Sourdough.

Sourdoughs harbor simple microbial communities usually composed of a few prevailing lactic acid bacteria species (LAB) and yeast species. However, yeast and LAB found in sourdough have been described as highly diverse. Even if LAB and yeast associations have been widely documented, the nature of the interactions between them has been poorly described. These interactions define the composition and structure of sourdough communities, and therefore, the characteristics of the final bread product. In this study, the nature of the interactions between strains of two commonly found sourdough yeast species, Kazachstania humilis and Saccharomyces cerevisiae, and lactic acid bacteria isolated from sourdoughs has been analyzed. Population density analysis showed no evidence of positive interactions, but instead revealed neutral or negative asymmetric interaction outcomes. When in coculture, the yeasts´ population size decreased in the presence of LAB regardless of the strain, while the LAB´s population size was rarely influenced by the presence of yeasts. However, a higher maltose depletion was shown in maltose-negative K. humilis and maltose-positive obligately heterofermentative LAB cocultures compared to monocultures. In addition, tested pairs of obligately heterofermentative LAB and K. humilis strains leavened dough as much as couples of LAB and S. cerevisiae strains, while K. humilis strains never leavened dough as much as S. cerevisiae when in monoculture. Taken together, our results demonstrate that even if higher fermentation levels with increased maltose depletion were detected for K. humilis and obligately heterofermentative LAB pairs, these interactions cannot be ecologically classified as positive, leading us to rethink the established hypothesis of coexistence by facilitation in sourdoughs.

Mortality causes universal changes in microbial community composition

All organisms are sensitive to the abiotic environment, and a deteriorating environment can cause extinction. However, survival in a multispecies community depends upon interactions, and some species may even be favored by a harsh environment that impairs others, leading to potentially surprising community transitions as environments deteriorate. Here we combine theory and laboratory microcosms to predict how simple microbial communities will change under added mortality, controlled by varying dilution. We find that in a two-species coculture, increasing mortality favors the faster grower, confirming a theoretical prediction. Furthermore, if the slower grower dominates under low mortality, the outcome can reverse as mortality increases. We find that this tradeoff between growth and competitive ability is prevalent at low dilution, causing outcomes to shift dramatically as dilution increases, and that these two-species shifts propagate to simple multispecies communities. Our results argue that a bottom-up approach can provide insight into how communities change under stress.

Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community

Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2–4), high-temperature (> 65 °C) springs of Yellowstone National Park contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from the studied Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.

Life at extreme elevations on Atacama volcanoes: the closest thing to Mars on Earth?

Here we describe recent breakthroughs in our understanding of microbial life in dry volcanic tephra ("soil") that covers much of the surface area of the highest elevation volcanoes on Earth. Dry tephra above 6000m.a.s.l. is perhaps the best Earth analog for the surface of Mars because these "soils" are acidic, extremely oligotrophic, exposed to a thin atmosphere, high UV fluxes, and extreme temperature fluctuations across the freezing point. The simple microbial communities found in these extreme sites have among the lowest alpha diversity of any known earthly ecosystem and contain bacteria and eukaryotes that are uniquely adapted to these extreme conditions. The most abundant eukaryotic organism across the highest elevation sites is a Naganishia species that is metabolically versatile, can withstand high levels of UV radiation and can grow at sub-zero temperatures, and during extreme diurnal freeze-thaw cycles (e.g. - 10 to + 30°C). The most abundant bacterial phylotype at the highest dry sites sampled (6330m.a.s.l. on Volcán Llullaillaco) belongs to the enigmatic B12-WMSP1 clade which is related to the Ktedonobacter/Thermosporothrix clade that includes versatile organisms with the largest known bacterial genomes. Close relatives of B12-WMSP1 are also found in fumarolic soils on Volcán Socompa and in oligotrophic, fumarolic caves on Mt. Erebus in Antarctica. In contrast to the extremely low diversity of dry tephra, fumaroles found at over 6000m.a.s.l. on Volcán Socompa support very diverse microbial communities with alpha diversity levels rivalling those of low elevation temperate soils. Overall, the high-elevation biome of the Atacama region provides perhaps the best "natural experiment" in which to study microbial life in both its most extreme setting (dry tephra) and in one of its least extreme settings (fumarolic soils).

Comparative Analysis of Drosophila melanogaster Gut Microbiota with Respect to Host Strain, Sex, and Age.

Microbiota has a significant impact on the health of the host individual. The complexity of the interactions between mammalian hosts and their microbiota highlights the value of using Drosophila melanogaster as a model organism, because of its relatively simple microbial community and ease of physiological and genetic manipulation. However, highly variable and sometimes inconsistent results regarding the microbiota of D. melanogaster have been reported for host samples collected from different geographical locations; discrepancies that may be because of the inherent physiological conditions of the D. melanogaster host. Here, we conducted a comparative analysis of the gut microbiota of two D. melanogaster laboratory strains, w 1118 and Canton S, with respect to the sex and age of the host, by pyrosequencing of the 16S rRNA gene. In addition to the widespread and abundant commensal bacterial genera Lactobacillus and Acetobacter, we identified Enterococcus and Leuconostoc as major host-strain-specific bacterial genera. The relative proportions of these bacterial genera, and those of the species within each, were found to differ markedly with respect to strain, sex, and age of the host, even though host individuals were reared under the same nutritional conditions. By using various bioinformatic tools, we uncovered several characteristic features of microbiota corresponding to specific categories of the flies: host-sex-bias association of specific bacteria, age-dependent alteration of microbiota across host species and sex, and uniqueness of the microbiota of female w 1118 flies. Our results, thus, help to further our understanding of host-microbe interactions in the D. melanogaster model.