Shifts in Microbial Community Composition Following Surface Application of Dredged River Sediments

Sediment input to the Illinois River has drastically decreased river depth and reduced habitats for aquatic organisms. Dredging is being used to remove sediment from the Illinois River, and the dredged sediment is being applied to the surface of a brownfield site in Chicago with the goal of revegetating the site. In order to determine the effects of this drastic habitat change on sediment microbial communities, we examined sediment physical, chemical, and microbial characteristics at the time of sediment application to the soil surface as well as 1 and 2 years after application. Microbial community biomass was determined by measurement of lipid phosphate. Microbial community composition was assessed using phospholipid fatty acid (PLFA) analysis, terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes, and clone library sequencing of 16S rRNA genes. Results indicated that the moisture content, organic carbon, and total nitrogen content of the sediment all decreased over time. Total microbial biomass did not change over the course of the study, but there were significant changes in the composition of the microbial communities. PLFA analysis revealed relative increases in fungi, actinomycetes, and Gram positive bacteria. T-RFLP analysis indicated a significant shift in bacterial community composition within 1 year of application, and clone library analysis revealed relative increases in Proteobacteria, Gemmatimonadetes, and Bacteriodetes and relative decreases in Acidobacteria, Spirochaetes, and Planctomycetes. These results provide insight into microbial community shifts following land application of dredged sediment.     

Seasonal Fluctuations of Bacterial Community Diversity in Agricultural Soil and Experimental Validation by Laboratory Disturbance Experiments

Natural fluctuations in soil microbial communities are poorly documented because of the inherent difficulty to perform a simultaneous analysis of the relative abundances of multiple populations over a long time period. Yet, it is important to understand the magnitudes of community composition variability as a function of natural influences (e.g., temperature, plant growth, or rainfall) because this forms the reference or baseline against which external disturbances (e.g., anthropogenic emissions) can be judged. Second, definition of baseline fluctuations in complex microbial communities may help to understand at which point the systems become unbalanced and cannot return to their original composition. In this paper, we examined the seasonal fluctuations in the bacterial community of an agricultural soil used for regular plant crop production by using terminal restriction fragment length polymorphism profiling (T-RFLP) of the amplified 16S ribosomal ribonucleic acid (rRNA) gene diversity. Cluster and statistical analysis of T-RFLP data showed that soil bacterial communities fluctuated very little during the seasons (similarity indices between 0.835 and 0.997) with insignificant variations in 16S rRNA gene richness and diversity indices. Despite overall insignificant fluctuations, between 8 and 30% of all terminal restriction fragments changed their relative intensity in a significant manner among consecutive time samples. To determine the magnitude of community variations induced by external factors, soil samples were subjected to either inoculation with a pure bacterial culture, addition of the herbicide mecoprop, or addition of nutrients. All treatments resulted in statistically measurable changes of T-RFLP profiles of the communities. Addition of nutrients or bacteria plus mecoprop resulted in bacteria composition, which did not return to the original profile within 14 days. We propose that at less than 70% similarity in T-RFLP, the bacterial communities risk to drift apart to inherently different states.     

Effect of long‐term mineral fertilisation on soil microbial abundance,community structure and diversity in a Typic Hapludoll under intensive farming systems

Fertiliser application can not only influence plant communities, but also the soil microbial community dynamics, and consequently soil quality. Specifically, mineral fertilisation can directly or indirectly affect soil chemical properties, microbial abundance and, the structure and diversity of soil microbial communities. We investigated the impact of six different mineral fertiliser regimes in a maize/soybean rotation system: control (CK, without fertilisation), PS (application of phosphorus plus sulphur), NS (application of nitrogen plus S), NP (application of N plus P), NPS (application of N, P plus S) and NPSm (application of N, P, S plus micronutrients). Soil samples were collected at the physiological maturity stage of maize and soybean in March of 2013 and 2014, respectively. Overall, mineral fertilisation resulted in significantly decreased soil pH and increased total organic carbon compared with the control (CK). The analysis of terminal restriction fragment length polymorphism (T‐RFLP) revealed that mineral fertilisers caused a shift in the composition of both bacterial and fungal communities. In 2013, the highest value of Shannon diversity of bacterial terminal restriction fragments (TRFs) was found in control soils. In 2014, NPSm treated soils showed the lowest values of diversity for both bacterial and fungal TRFs. In both crop growing seasons, the analysis of phospholipid fatty acid (PLFA) detected the lowest value of total microbial biomass under CK. As PLFA analysis can be used to evaluate total microbial community, this result suggests that fertilisation increased total microbial biomass. When the bacterial and fungal abundance were examined using real time polymerase chain reaction, the results revealed that mineral fertilisation led to decreased bacterial abundance (16S rRNA), while fungal abundance (18S rRNA) was found to be increased in both crop growing seasons. Our results show that mineral fertiliser application has a significant impact on soil properties, bacterial and fungal abundance and microbial diversity. However, further studies are needed to better understand the mechanisms involved in the changes to microbial communities as a consequence of mineral fertilisation.     

Soil microbial properties under different vegetation types on Mountain Han

This study investigated the influence of broadleaf and conifer vegetation on soil microbial communities in a distinct vertical distribution belt in Northeast China.Soil samples were taken at 0-5,5-10 and 10-20 cm depths from four vegetation types at different altitudes,which were characterized by poplar(Populus davidiana)(1250-1300 m),poplar(P.davidiana) mixed with birch(Betula platyphylla)(1370-1550 m),birch(B.platyphylla)(1550-1720 m),and larch(Larix principis-rupprechtii)(1840-1890 m).Microbial biomass and community structure were determined using the fumigation-extraction method and phospholipid fatty acid(PLFA) analysis,and soil fungal community level physiological profiles(CLPP) were characterized using Biolog FF Microplates.It was found that soil properties,especially soil organic carbon and water content,contributed significantly to the variations in soil microbes.With increasing soil depth,the soil microbial biomass,fungal biomass,and fungal catabolic ability diminished;however,the ratio of fungi to bacteria increased.The fungal ratio was higher under larch forests compared to that under poplar,birch,and their mixed forests,although the soil microbial biomass was lower.The direct contribution of vegetation types to the soil microbial community variation was 12%.If the indirect contribution through soil organic carbon was included,variations in the vegetation type had substantial influences on soil microbial composition and diversity.     

罕山土壤微生物群落组成对植被类型的响应

选取分布在中国东北部地区的阔叶林-针叶林-亚高山草甸这一明显的植被垂直带谱来研究植被类型对土壤微生物群落组成的影响。选取5种植被类型-山杨(Populus davidiana)(1250—1300 m),山杨(P.davidiana)与白桦(Betula platyphylla)的混交林(1370—1550 m),白桦(B.platyphylla)(1550—1720 m),落叶松(Larix principis-rupprechtii)(1840—1890 m),亚高山草甸(1900—1951 m),采用磷脂脂肪酸(Phopholipid Fatty Acids,PLFAs)分析方法测定不同植被类型下的土壤微生物群落组成。分别采用主成分分析(Principal Components Analysis,PCA)以及冗余分析(Redundancy Analysis,RDA)来解释单种特征PLFAs的分异以及土壤理化指标与微生物PLFAs指标间的相关性。结果表明不同植被类型下土壤有机碳(SOC)对土壤微生物PLFAs总量,各类群(真菌(f)、细菌(b)、革兰氏阳性菌(G+)、革兰氏阴性菌(G-))生物量以及群落结构影响显著;土壤微生物PLFAs总量及各类群的生物量随土层加深总体上表现降低趋势,G+/G-和f/b分别随土层加深总体上表现升高趋势。不同植被类型下,阔叶混交林土壤PLFAs总量及各类群生物量总体上最高;针叶林比阔叶林下的f/b和G+/G-高;亚高山草甸下低的p H值对有机碳的可利用性有一定的抑制作用,导致f/b和G+/G-的值相对较高。总之,不同植被类型下SOC对土壤微生物群落组成的影响最为显著,而较低的p H对有机碳的可利用性有一定的抑制作用;真菌对植被类型的变化比细菌更敏感,而细菌更易受可利用性养分和p H变异的影响,这对预测不同林型下的土壤微生物群落组成有重要的启示作用。     

Interpreting 16S rDNA T-RFLP Data: Application of Self-Organizing Maps and Principal Component Analysis to Describe Community Dynamics and Convergence

Interpreting the large amount of data generated by rapid profiling techniques, such as T-RFLP, DGGE, and DNA arrays, is a difficult problem facing microbial ecologists. This study compares the ability of two very different ordination methods, principal component analysis (PCA) and self-organizing map neural networks (SOMs), to analyze 16S-DNA terminal restriction-fragment length polymorphism (T-RFLP) profiles from microbial communities in glucose-fed methanogenic bioreactors during startup and changes in operational parameters. Our goal was not only to identify which samples were similar, but also to decipher community dynamics and describe specific phylotypes, i.e., phylogenetically similar organisms, that behaved similarly in different reactors. Fifteen samples were taken over 56 volume changes from each of two bioreactors inoculated from river sediment (S2) and anaerobic digester sludge (M3) and from a well-established control reactor (R1). PCA of bacterial T-RFLP profiles indicated that both the S2 and M3 communities changed rapidly during the first nine volume changes, and then became relatively stable. PCA also showed that an HRT of 8 or 6 days had no effect on either reactor communtity, while an HRT of 2 days changed community structure significantly in both reactors. The SOM clustered the terminal restriction fragments according to when each fragment was most abundant in a reactor community, resulting in four clearly discernible groups. Thirteen fragments behaved similarly in both reactors, eight of which composed a significant proportion of the microbial community as judged by the relative abundance of the fragment in the T-RFLP profiles. Six Bacteria terminal restriction fragments shared between the two communities matched cloned 16S rDNA sequences from the reactors related to Spirochaeta, Aminobacterium, Thermotoga, and Clostridium species. Convergence also occurred within the acetoclastic methanogen community, resulting in a predominance of Methanosarcina siciliae-related organisms. The results demonstrate that both PCA and SOM analysis are useful in the analysis of T-RFLP data; however, the SOM was better at resolving patterns in more complex and variable data than PCA ordination.     

Use of the T-RFLP technique to assess spatial and temporal changes in the bacterial community structure within an agricultural soil planted with transgenic and non-transgenic potato plants

The aim of this study was to examine whether the terminal restriction fragment length polymorphism (T-RFLP) analysis represents an appropriate technique for monitoring highly diverse soil bacterial communities, i.e. to assess spatial and/or temporal effects on bacterial community structure. The T-RFLP method, a recently described fingerprinting technique, is based on terminal restriction fragment length polymorphisms between distinct small-subunit rRNA gene sequence types. This technique permits an automated quantification of the fluorescence signal intensities of the individual terminal restriction fragments (T-RFs) in a given community fingerprint pattern. The indigenous bacterial communities of three soil plots located within an agricultural field of 110 m(2) were compared. The first site was planted with non-transgenic potato plants, while the other two were planted with transgenic GUS and Barnase/Barstar potato plants, respectively. Once prior to planting and three times after planting, seven parallel samples were taken from each of the three soil plots. The T-RFLP analysis resulted in very complex but highly reproducible community fingerprint patterns. The percentage abundance values of defined T-RFs were calculated for the seven parallel samples of the respective soil plot. A multivariate analysis of variance was used to test T-RFLP data sets for significant differences. The statistical treatments clearly revealed spatial and temporal effects, as well as spacextime interaction effects, on the structural composition of the bacterial communities. T-RFs which showed the highest correlations to the discriminant factors were not those T-RFs which showed the largest single variations between the seven-sample means of individual plots. In summary, the T-RFLP technique, although a polymerase chain reaction-based method, proved to be a suitable technique for monitoring highly diverse soil microbial communities for changes over space and/or time.     

Influences of space, soil, nematodes and plants on microbial community composition of chalk grassland soils

Microbial communities respond to a variety of environmental factors related to resources (e.g. plant and soil organic matter), habitat (e.g. soil characteristics) and predation (e.g. nematodes, protozoa and viruses). However, the relative contribution of these factors on microbial community composition is poorly understood. Here, we sampled soils from 30 chalk grassland fields located in three different chalk hill ridges of Southern England, using a spatially explicit sampling scheme. We assessed microbial communities via phospholipid fatty acid (PLFA) analyses and PCR-denaturing gradient gel electrophoresis (DGGE) and measured soil characteristics, as well as nematode and plant community composition. The relative influences of space, soil, vegetation and nematodes on soil microorganisms were contrasted using variation partitioning and path analysis. Results indicate that soil characteristics and plant community composition, representing habitat and resources, shape soil microbial community composition, whereas the influence of nematodes, a potential predation factor, appears to be relatively small. Spatial variation in microbial community structure was detected at broad (between fields) and fine (within fields) scales, suggesting that microbial communities exhibit biogeographic patterns at different scales. Although our analysis included several relevant explanatory data sets, a large part of the variation in microbial communities remained unexplained (up to 92% in some analyses). However, in several analyses, significant parts of the variation in microbial community structure could be explained. The results of this study contribute to our understanding of the relative importance of different environmental and spatial factors in driving the composition of soil-borne microbial communities.     

Microbial communities show parallels at sites with distinct litter and soil characteristics

Plant and microbial community composition in connection with soil chemistry determines soil nutrient cycling. The study aimed at demonstrating links between plant and microbial communities and soil chemistry occurring among and within four sites: two pine forests with contrasting soil pH and two grasslands of dissimilar soil chemistry and vegetation. Soil was characterized by C and N content, particle size, and profiles of low-molecular-weight compounds determined by high-performance liquid chromatography (HPLC) of soil extracts. Bacterial and actinobacterial community composition was assessed by terminal restriction fragment length polymorphism (T-RFLP) and cloning followed by sequencing. Abundances of bacteria, fungi, and actinobacteria were determined by quantitative PCR. In addition, a pool of secondary metabolites was estimated by erm resistance genes coding for rRNA methyltransferases. The sites were characterized by a stable proportion of C/N within each site, while on a larger scale, the grasslands had a significantly lower C/N ratio than the forests. A Spearman's test showed that soil pH was correlated with bacterial community composition not only among sites but also within each site. Bacterial, actinobacterial, and fungal abundances were related to carbon sources while T-RFLP-assessed microbial community composition was correlated with the chemical environment represented by HPLC profiles. Actinobacteria community composition was the only studied microbial characteristic correlated to all measured factors. It was concluded that the microbial communities of our sites were influenced primarily not only by soil abiotic characteristics but also by dominant litter quality, particularly, by percentage of recalcitrant compounds.     

Variations in Soil Microbial Communities and Residues Along an Altitude Gradient on the Northern Slope of Changbai Mountain,China

Altitudinally-defined climate conditions provide specific vegetation types and soil environments that could influence soil microbial communities, which in turn may affect microbial residues. However, the knowledge is limited in terms of the degree to which microbial communities and residues present and differ along altitude. In this study, we examined the soil microbial communities and residues along the northern slope of Changbai Mountain, China using phospholipid fatty acid (PLFA) and amino sugar analysis, respectively. Soil samples were taken from five different vegetation belts defined by climates. Principal component analysis (PCA) revealed substantial differences in soil microbial community composition among study sites, appeared to be driven primarily by soil pH and C/N ratio on the first principal component (PC1) which accounted for 50.7% of the total sample variance. The alpine tundra was separated from forest sites on the second principal component (PC2) by a signifiscantly higher amount of fungal PLFA (18:2ω6,9). Soil pH and C/N ratio were also correlated with the ratios of Gram-positive to Gram-negative bacteria (Gm⁺/Gm⁻), glucosamine to galactosamine (GluN/GalN), and glucosamine to muramic acid (GluN/MurA). Both total PLFAs and amino sugars were positively correlated with soil organic carbon, inorganic nitrogen, available phosphorus and potassium. We concluded that soil pH and C/N ratio were the most important drivers for microbial community structure and amino sugar pattern, while substrate availability was of great importance in determining the concentrations of microbial communities and residues. These findings could be used to facilitate interpretation of soil microbial community and amino sugar data derived from measurements in latitude or managed forests.     

Community Structure of Actively Growing Bacterial Populations in Plant Pathogen Suppressive Soil

The bacterial community in soil was screened by using various molecular approaches for bacterial populations that were activated upon addition of different supplements. Plasmodiophora brassicae spores, chitin, sodium acetate, and cabbage plants were added to activate specific bacterial populations as an aid in screening for novel antagonists to plant pathogens. DNA from growing bacteria was specifically extracted from the soil by bromodeoxyuridine immunocapture. The captured DNA was fingerprinted by terminal restriction fragment length polymorphism (T-RFLP). The composition of the dominant bacterial community was also analyzed directly by T-RFLP and by denaturing gradient gel electrophoresis (DGGE). After chitin addition to the soil, some bacterial populations increased dramatically and became dominant both in the total and in the actively growing community. Some of the emerging bands on DGGE gels from chitin-amended soil were sequenced and found to be similar to known chitin-degrading genera such as Oerskovia, Kitasatospora, and Streptomyces species. Some of these sequences could be matched to specific terminal restriction fragments on the T-RFLP output. After addition of Plasmodiophora spores, an increase in specific Pseudomonads could be observed with Pseudomonas-specific primers for DGGE. These results demonstrate the utility of microbiomics, or a combination of molecular approaches, for investigating the composition of complex microbial communities in soil.     

A novel strategy to extract specific phylogenetic sequence information from community T-RFLP

Cultivation-independent analyses of soil microbial community structures are frequently used to describe microbiological soil characteristics. Semi-automated terminal restriction fragment length polymorphism (T-RFLP) analyses yield high-resolution genetic profiles of highly diverse soil microbial communities and hold great potential for use in routine soil quality monitoring. A serious limitation of T-RFLP analyses has been the inability to reliably affiliate observed terminal restriction fragments (T-RF) to phylogenetic groups. In the study presented here, we were able to overcome this limitation of T-RFLP. With a combination of adapter ligation, fragment size selection, and re-amplification with adapter site specific PCR, we were able to isolate a T-RF-fraction of a narrow size-range containing a T-RF that was significantly more abundant in heavy metal amended soils. Cloning the size-selected T-RF fraction allowed for the efficient isolation of clones containing this specific T-RF. Sequence determination and phylogenetic inference in RDP-II affiliated the sequence to unclassified cyanobacteria. Specific primer design and PCR amplification from bulk soil DNA allowed for independent confirmation of the results from bacterial T-RFLP and T-RF cloning. Our results show that specific T-RFs can be efficiently isolated and identified, and that the adapter ligation approach holds great potential for genetic profiling and for identification of community components of interest.     

非培养方法在土壤微生物生态学研究中的应用

由于有相当数量的土壤微生物是目前不可培养的,因此利用传统培养技术来研究土壤微生物,不仅费时费力,所得到的结果可能和真实的情况相差甚远。近年来发展了三类不需培养的方法来研究土壤微生物的种类和数量,这些方法大体上分为生物化学、生理学和分子生物学三类。生物化学方法主要根据细胞膜磷脂酸(PLFA)的种类和数量来判定微生物的多样性;BIOLOG微量板分析系统是生理学方法的代表,它主要是根据土样细胞悬液对95种单一碳源的利用模式来说明群落结构的变化;分子生物学方法是发展应用最广的方法。基本步骤是提取土壤的总DNA,然后用通用引物或选择性高的引物来扩增16SrRNA基因。由于对扩增产物分析方法的不同,该方法又可分为PCR-DGGE,PCR-RFLP等。最近在PCR-RFLP基础上发展起来的T—RFLP分析方法,将微生物的多样性分析工作同RDP(ribosomal database project)数据库结合,充分利用了Internet的数据资源共享的优势,具有分辨率高,可实现自动化等优点。是未来土壤微生物生态学研究的有力工具。     

Diversity, Composition, and Geographical Distribution of Microbial Communities in California Salt Marsh Sediments

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes.     

Effects of long term CO2 enrichment on microbial community structure in calcareous grassland

Elevated CO₂ generally increases plant productivity, and has been found to alter plant community composition in many ecosystems. Because soil microbes depend on plant-derived C and are often associated with specific plant species, elevated CO₂ has the potential to alter structure and functioning of soil microbial communities. We investigated soil microbial community structure of a species-rich semi-natural calcareous grassland that had been exposed to elevated CO₂ (600 μL L^?1) for 6 growing seasons. We analysed microbial community structure using phospholipid fatty acid (PLFA) profiles and DNA fingerprints obtained by Denaturing Gradient Gel Electrophoresis (DGGE) of 16S rDNA fragments amplified by the Polymerase Chain Reaction (PCR). PLFA profiles were not affected by CO₂ enrichment and the ratio of fungal and bacterial PLFA did not change. Ordination analysis of DNA fingerprints revealed a significant relation between CO₂ enrichment and variation in DNA fingerprints in summer (P=0.01), but not in spring. This variation was due to changes in low-intensity bands, while dominant bands did not differ between CO₂ treatments. Diversity of the bacterial community, as assessed by number of bands in DNA fingerprints and calculation of Shannon diversity indices, was not affected by elevated CO₂. Overall, only minor effects on microbial community structure were detected, corroborating earlier findings that soil carbon inputs did probably change much less than suggested by plant photosynthetic responses.     

Application of ARDRA and PLFA analysis in characterizing the bacterial communities of the food,gut and excrement of saprophagous larvae of<Emphasis Type="Italic">Penthetria holosericea</Emphasis> (<Emphasis Type="Italic">Diptera: Bibionidae</Emphasis>): a pilot study

Amplified ribosomal DNA restriction analysis (ARDRA) was used to compare the bacterial communities of the food, the gut sections (ceca, anterior and posterior midgut, hindgut) and the excrement of the litter feeding bibionid larvae of Penthetria holosericea. For universal eubacterial primers ARDRA patterns were complex with only minor differences among samples. Taxon specific primers were also applied to characterize the samples. Fragment composition was transformed to presence/absence binary data and further analyzed. Cluster analysis revealed that bacterial communities of gut highly resembled each other with the exception of the ceca. ARDRA patterns of consumed leaves clustered together with the intact leaves but differed from those of the excrement. ARDRA results were compared with microbial community structure based on phospholipid fatty acid (PLFA) fingerprints. The cluster analysis of PLFA (presence/absence binary) data resulted in a pattern similar to the ARDRA data. The PCA analysis of PLFA relative content separated microbial communities into five groups: (1) anterior and posterior midgut, (2) hindgut, (3) ceca, (4) consumed and intact litter, (5) excrement. Both methods indicated that conditions in the larval gut result in formation of a specific microbial community which differs from both the food and excrement ones. Particularly ceca--(blind appendages, harbor very specific microbial community) are divided from the rest of the gut by perithropic membrane.     

内蒙古草原典型植物对土壤微生物群落的影响

为了分析内蒙古草原不同植物物种对土壤微生物群落的影响, 采用实时荧光定量PCR (real-time PCR)以及末端限制性片段长度多态性分析(terminal restriction fragment length polymorphism, T-RFLP)等分子生物学技术, 测定了退化-恢复样地上几种典型植物的根际土壤和非根际土壤中细菌和真菌的数量及群落结构。结果表明, 不同植物物种对根际和非根际细菌及根际真菌数量均有显著影响。根际土壤中的细菌和真菌数量普遍高于非根际土壤, 尤其以真菌更为明显。对T-RFLP数据进行多响应置换过程(multi-response permutation procedures, MRPP)分析和主成分分析(principal component analysis, PCA), 结果表明, 大多数物种的根际细菌及真菌的群落结构与非根际有明显差异, 并且所有物种的真菌群落可以按根际和非根际明显分为两大类群。此外, 细菌和真菌群落结构在一定程度上存在按物种聚类的现象, 以细菌较为明显。这些结果揭示了不同植物对土壤微生物群落的影响特征, 对理解内蒙古草原地区退化及恢复过程中植被演替引起的土壤性质和功能的变化有一定的帮助。     

Diversity, composition, and geographical distribution of microbial communities in California salt marsh sediments

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes.     

Development of a fluorophore-ribosomal DNA restriction typing method for monitoring structural shifts of microbial communities

DNA restriction fragment polymorphism technologies such as amplified ribosomal DNA restriction analysis (ARDRA) and terminal restriction fragment length polymorphism (T-RFLP) have been widely used in investigating microbial community structures. However, these methods are limited due to either the low resolution or sensitivity. In this study, a fluorophore-ribosomal DNA restriction typing (f-DRT) approach is developed for structural profiling of microbial communities. 16S rRNA genes are amplified from the community DNA and digested by a single restriction enzyme Msp I. All restriction fragments are end-labeled with a fluorescent nucleotide Cy5-dCTP via a one-step extension reaction and detected with an automated DNA sequencer. All 50 predicted restriction fragments between 100 and 600 bp were detected when twelve single 16S rRNA gene sequences were analyzed using f-DRT approach; 92% of these fragments were determined with accuracy of ±2 bp. In the defined model communities containing five components with different ratios, relative abundance of each component was correctly revealed by this method. The f-DRT analysis also showed structural shifts of intestinal microbiota in carcinogen-treated rats during the formation of precancerous lesions in the colon, as sensitive as multiple digestion-based T-RFLP analysis. This study provides a labor and cost-saving new method for monitoring structural shifts of microbial communities.     

Successional and seasonal variations in soil and litter microbial community structure and function during tropical postagricultural forest regeneration: a multiyear study

Soil microorganisms regulate fundamental biochemical processes in plant litter decomposition and soil organic matter (SOM) transformations. Understanding how microbial communities respond to changes in vegetation is critical for improving predictions of how land‐cover change affects belowground carbon storage and nutrient availability. We measured intra‐ and interannual variability in soil and forest litter microbial community composition and activity via phospholipid fatty acid analysis (PLFA) and extracellular enzyme activity across a well‐replicated, long‐term chronosequence of secondary forests growing on abandoned pastures in the wet subtropical forest life zone of Puerto Rico. Microbial community PLFA structure differed between young secondary forests and older secondary and primary forests, following successional shifts in tree species composition. These successional patterns held across seasons, but the microbial groups driving these patterns differed over time. Microbial community composition from the forest litter differed greatly from those in the soil, but did not show the same successional trends. Extracellular enzyme activity did not differ with forest succession, but varied by season with greater rates of potential activity in the dry seasons. We found few robust significant relationships among microbial community parameters and soil pH, moisture, carbon, and nitrogen concentrations. Observed inter‐ and intrannual variability in microbial community structure and activity reveal the importance of a multiple, temporal sampling strategy when investigating microbial community dynamics with land‐use change. Successional control over microbial composition with forest recovery suggests strong links between above and belowground communities.