Spatial Distribution Of Microbes Research Articles

Temporal and spatial variation of microbial communities in stored rice grains from two major depots in China

Microbial activity in stored rice grains could cause quality deterioration and mycotoxin accumulation that may lead to serious economic losses and food safety risks. However, limited studies have examined the spatial and temporal variation of microbial communities associated with stored rice grains. Here, we performed amplicon sequence analysis to investigate the temporal and spatial distribution of microbes in stored rice grains from Chongqing grain depot (Southern China) and Liaoning grain depot (Northern China). Bacterial and fungal diversities, in addition to community structures of rice grains in Chongqing were significantly different from those in Liaoning in terms of α diversity (Chongqing > Liaoning, p <001) and β diversity (p < 0.001, bacterial communities: R = 0.9293, fungal communities: R = 1.0). The core bacterial taxa among stored rice grains comprised Pantoea, Pseudomonas, Rhizobium, and Methylobacterium, while the core fungal taxa comprised Alternaria, Aspergillus, and Cladosporium. In addition, different microbial communities were observed at different stored time points (i.e., post-harvest period, storage for one year, and storage for two years), and along different stored vertical depths (upper, middle, and lower layers) within the Chinese horizontal warehouse. The relative abundances of Aspergillus increased over storage time, but decreased with the increase of stored vertical depth within the warehouse. Temperature was the most important factor associated with differences in microbial communities across storage periods. The potential mycotoxin producing fungal species A. flavus and A. niger exhibited significantly higher abundances in rice grains of Chongqing compared to those of Liaoning. These data could be useful for evaluating potential risks of toxigenic fungi and mycotoxin contamination of stored rice grains. Further, these insights can help grain depot managers optimize storage conditions and reduce risks of deleterious fungi during rice grains storage.

Mucus

Mucus is a slimy hydrogel that lines the mucosal surfaces in our body, including the intestines, stomach, eyes, lungs and urogenital tract. This glycoprotein-rich network is truly the jack of all trades. As a barrier, it lubricates surfaces, protects our cells from physical stress, and selectively allows the passage of nutrients while clearing out pathogens and debris. As a home to our microbiota, it supports a level of microbial diversity that is unattainable with most culture methods. As a reservoir of complex carbohydrate structures called glycans, it plays critical roles in controlling cell adhesion and signaling, and it alters the behavior and spatial distribution of microbes. On top of all this, mucus regulates the passage of sperm during fertilization, heals wounds, helps us smell, and prevents the stomach from digesting itself, to name just a few of its functions. Given these impressive features, it is no wonder that mucus crosses boundaries of species and kingdoms - mucus gels are made by organisms ranging from the simplest metazoans to corals, snails, fish, and frogs. It is also no surprise that mucus is exploited in everyday applications, including foods, cosmetics, and other products relevant to medicine and industry.

Humus microhabitat affects distributions of soil fungi and bacteria in a temperate mountain forest

AbstractHumus layer has an important effect on the diversity and spatial distribution of microbes. However, the role of partitioning of humus layer microhabitats for soil microbial diversity has been poorly documented. In this study, 120 soil samples were collected from a 5‐ha forest dynamic monitoring sample plot in a deciduous broad‐leaved forest. Clustering analysis was used to delineate microhabitats by humus layer. We explored diversity and community composition of soil fungi and bacteria using Illumina sequencing of the ITS rRNA gene and 16S rRNA gene region on the MiSeq platform. We investigated the diversity, species composition, and the microhabitat preferences of fungi and bacteria and then analyzed the effects of environmental factors on soil fungi and bacteria. Our results showed that the diversity, species composition, and the indicator species of the fungal and bacterial community varied among different humus layer microhabitats. In network analysis, the specialization indexes showed that 16.20%/22.30% of the fungal/bacterial operational taxonomic units (OTUs) had the characteristics of distribution specialization for humus layer microhabitats. Mantel test showed that the main environmental drivers of fungi and bacteria were not consistent among the four microhabitats. Our findings indicated that the distribution of soil microbes among humus layer microhabitats is not random, but specialized. We furthermore found that there were differences in the relationship between soil microbes and environment among microhabitats defined by humus layer. Together, these findings suggest the importance of partitioning of humus layer microhabitats in maintaining local diversity in a soil microbial community.

Distinct microbial communities among different tissues of citrus tree Citrus reticulata cv. Chachiensis

Plant microbiota colonize all organs of a plant and play crucial roles including supplying nutrients to plants, stimulating seed germination, promoting plant growth, and defending plants against biotic and abiotic stress. Because of the economic importance, interactions between citrus and microbes have been studied relatively extensively, especially citrus-pathogen interactions. However, the spatial distribution of microbial taxa in citrus trees remains under-studied. In this study, Citrus reticulata cv. Chachiensis was examined for the spatial distribution of microbes by sequencing 16S rRNA genes. More than 2.5 million sequences were obtained from 60 samples collected from soil, roots, leaves, and phloem. The dominant microbial phyla from all samples were Proteobacteria, Actinobacteria and Acidobacteria. The composition and structure of microbial communities in different samples were analyzed by PCoA, CAP, Anosim and MRPP methods. Variation in microbial species between samples were analyzed and the indicator microbes of each sample group were identified. Our results suggested that the microbial communities from different tissues varied significantly and the microenvironments of tree tissues could affect the composition of its microbial community.

Correlations Between Substrate Structure and Microbial Community in Subsurface Flow Constructed Wetlands

To identify the microbial factors that cause the differences in the purification performance of constructed wetlands with different substrate structures, the relationship between the substrate structure and the microbial community composition in horizontal subsurface flow constructed wetlands (HSSFCWs) was studied by high throughput sequencing. The results revealed that the purification performance of a six-layer constructed wetland (CW6), of which the permeability coefficient gradually increased from the surface layer to the bottom layer, was the highest among the three constructed wetland systems. The average concentrations of COD, TN, NO3--N, and NH4+-N in the effluent were 39, 11, 0.35, and 4 mg·L-1, respectively. The monolayer structure constructed wetland (CW1) had the worst purifying efficiency, with average effluent concentrations of 95, 21, 0.60 and 12 mg·L-1 for COD, TN, NO3--N, and NH4+-N, respectively. The results of the high-throughput sequencing showed that the number of microbial OTUs in multilayer structure wetlands was slightly lower than that in the monolayer structure wetland, but the relative abundance of the dominant phylum Proteobacteria and the nitrifying and denitrifying bacteria in the genus was significantly higher than the monolayer structure wetland. The results of PCA and heatmap indicated that there were significant differences in the spatial distribution of microbes in the genus of Proteobacteria in CW3 and CW6, which facilitated the degradation of pollutants. No significant differences were found in the community structure of CW1.

A 3-dimensional mathematical model of microbial proliferation that generates the characteristic cumulative relative abundance distributions in gut microbiomes.

The gut microbiome is highly variable among individuals, largely due to differences in host lifestyle and physiology. However, little is known about the underlying processes or rules that shape the complex microbial community. In this paper, we show that the cumulative relative abundance distribution (CRAD) of microbial species can be approximated by a power law function, and found that the power exponent of CRADs generated from 16S rRNA gene and metagenomic data for normal gut microbiomes of humans and mice was similar consistently with ∼0.9. A similarly robust power exponent was observed in CRADs of gut microbiomes during dietary interventions and several diseases. However, the power exponent was found to be ∼0.6 in CRADs from gut microbiomes characterized by lower species richness, such as those of human infants and the small intestine of mice. In addition, the CRAD of gut microbiomes of mice treated with antibiotics differed slightly from those of infants and the small intestines of mice. Based on these observations, in addition to data on the spatial distribution of microbes in the digestive tract, we developed a 3-dimensional mathematical model of microbial proliferation that reproduced the experimentally observed CRAD patterns. Our model indicated that the CRAD may be determined by the ratio of emerging to pre-existing species during non-uniform spatially competitive proliferation, independent of species composition.

"Every Gene Is Everywhere but the Environment Selects": Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis.

The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as “everything is everywhere but the environment selects.” While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge.

Spatio-Temporal Dynamics of Quorum Sensing Signals

Microbes communicate with each other using chemical signals in order to cooperate or compete with neighboring microbes. Acyl-homoserine lactones (AHLs) are one type of signal used by many species of microbes to regulate gene expression. AHLs activates the process of quorum sensing which is involved in biofilm formation, antibiotic resistance, and virulence. An individual microbe that activates quorum sensing upregulates the production of AHLs, and this signal can diffuse to nearby cells to either activate or sometimes inhibit quorum sensing.In this way, quorum sensing activation spreads through networks of microbes that are distributed in space. Our study is focused on understanding how the activation of quorum sensing depends on the species composition and spatial distribution of microbes in multispecies microbial networks.We developed an assay to quantify the ability of microbial networks to use signals to coordinate gene expression over long distances. In the assay a receiver strain, which responds to but does not produce the signal, is distributed homogenously on an agar plate. Activation of quorum sensing in this receiver strain is monitor by fluorescence. Upon addition of a signal producing strain to the center of the plate, we monitor quorum sensing activation in the lawn of receiver strains. The activation time of quorum sensing is measured as a function of position on the plate. This assay is used to quantify potential signal inference from a secondary strain added to the system to examine crosstalk between different species of microbes. A mathematical model is used to compare experimental observations to reaction diffusion models and to extend these results to more complex geometric arrangements of cells.

Temporal and spatial differences in microbial composition during the manufacture of a continental-type cheese.

We sought to determine if the time, within a production day, that a cheese is manufactured has an influence on the microbial community present within that cheese. To facilitate this, 16S rRNA amplicon sequencing was used to elucidate the microbial community dynamics of brine-salted continental-type cheese in cheeses produced early and late in the production day. Differences in the microbial composition of the core and rind of the cheese were also investigated. Throughout ripening, it was apparent that cheeses produced late in the day had a more diverse microbial population than their early equivalents. Spatial variation between the cheese core and rind was also noted in that cheese rinds were initially found to have a more diverse microbial population but thereafter the opposite was the case. Interestingly, the genera Thermus, Pseudoalteromonas, and Bifidobacterium, not routinely associated with a continental-type cheese produced from pasteurized milk, were detected. The significance, if any, of the presence of these genera will require further attention. Ultimately, the use of high-throughput sequencing has facilitated a novel and detailed analysis of the temporal and spatial distribution of microbes in this complex cheese system and established that the period during a production cycle at which a cheese is manufactured can influence its microbial composition.

Spatial distribution of prokaryotic symbionts and ammoxidation, denitrifier bacteria in marine sponge Astrosclera willeyana

The present knowledge of microbial community mainly focus on total sponge, the spatial distribution of microbes in sponges is rarely known, especially those with potential ecological functions. In this study, based on gene library and ∫-LIBSHUFF analysis, the spatial distribution of prokaryotic symbionts and nitrogen cycling genes in the cortex and endosome sections of sponge Astrosclera willeyana were investigated. A significance difference of bacterial phylotypes between the cortex and endosome was revealed. For example Bacteroidetes, Frankineae and Propionibacterineae were detected only in the endosome, whereas Cyanobacteria, Planctomycetacia and Micrococcineae were only associated with the cortex. Some branches of α-Proteobacteria, γ-Proteobacteria, Corynebacterineae, Acidimicobidae, Crenarchaeota and Euryarchaeota also showed distribution difference. Bacterial denitrifiers and ammonia oxidizing bacteria (AOB) were observed using nirS and amoA genes as markers. Particularly, AOB were only associated with the endosome. This study highlighted the spatial distribution of bacterial symbionts especially those with ammonia oxidization function.

In situ spatial patterns of soil bacterial populations, mapped at multiple scales, in an arable soil.

Very little is known about the spatial organization of soil microbes across scales that are relevant both to microbial function and to field-based processes. The spatial distributions of microbes and microbially mediated activity have a high intrinsic variability. This can present problems when trying to quantify the effects of disturbance, management practices, or climate change on soil microbial systems and attendant function. A spatial sampling regime was implemented in an arable field. Cores of undisturbed soil were sampled from a 3 x 3 x 0.9 m volume of soil (topsoil and subsoil) and a biological thin section, in which the in situ distribution of bacteria could be quantified, prepared from each core. Geostatistical analysis was used to quantify the nature of spatial structure from micrometers to meters and spatial point pattern analysis to test for deviations from complete spatial randomness of mapped bacteria. Spatial structure in the topsoil was only found at the microscale (micrometers), whereas evidence for nested scales of spatial structure was found in the subsoil (at the microscale, and at the centimeter to meter scale). Geostatistical ranges of spatial structure at the micro scale were greater in the topsoil and tended to decrease with depth in the subsoil. Evidence for spatial aggregation in bacteria was stronger in the topsoil and also decreased with depth in the subsoil, though extremely high degrees of aggregation were found at very short distances in the deep subsoil. The data suggest that factors that regulate the distribution of bacteria in the subsoil operate at two scales, in contrast to one scale in the topsoil, and that bacterial patches are larger and more prevalent in the topsoil.

New Environmental Scanning Electron Microscopic (ESEM) Observations of Bacteria on Simulated Soil Substrates

Abstract Conventional scanning and transmission electron microscopy (SEM and TEM) of the rhizosphere (soil around plant roots) has been used to describe the spatial organization of biotic (microorganisms including bacteria and fungi) and abiotic (organomineral complexes and clay platelets) constituents in soil.1 However, soil is deeper than plant rootS2 and the spatial distribution of microbes, the morphology of the microbial growth habit, and the spatial association of microbes with mineral substrates in the deeper vadose zone are little known. That subsurface terrestrial microbes catalyze most major nutrient-cycling reactions in the terrestrial biosphere3 punctuates the need to observe the true morphology of bacteria in association with mineral surfaces and microbemicrobe associations. Here, we present our use of environmental scanning electron microscopy (ESEM) to image bacteria on unsaturated sand, a simple surrogate for heterogeneous soil. ESEM is a choice tool for high resolution imaging of combined soft and hard matter, where delicate hydrated expolymer matrices bind microbes to each other and to soil particles as biofilm.4