Host-Associated Quantitative Abundance Profiling Reveals the Microbial Load Variation of Root Microbiome

Chromosomal barcodes for simultaneous tracking of near-isogenic bacterial strains in plant microbiota

DNA-amplicon-based microbiota profiling can estimate species diversity and abundance but cannot resolve genetic differences within individuals of the same species. Here we report the development of modular bacterial tags (MoBacTags) encoding DNA barcodes that enable tracking of near-isogenic bacterial commensals in an array of complex microbiome communities. Chromosomally integrated DNA barcodes are then co-amplified with endogenous marker genes of the community by integrating corresponding primer binding sites into the barcode. We use this approach to assess the contributions of individual bacterial genes to Arabidopsis thaliana root microbiota establishment with synthetic communities that include MoBacTag-labelled strains of Pseudomonas capeferrum. Results show reduced root colonization for certain mutant strains with defects in gluconic-acid-mediated host immunosuppression, which would not be detected with traditional amplicon sequencing. Our work illustrates how MoBacTags can be applied to assess scaling of individual bacterial genetic determinants in the plant microbiota.

Dynamic root microbiome sustains soybean productivity under unbalanced fertilization

Root-associated microbiomes contribute to plant growth and health, and are dynamically affected by plant development and changes in the soil environment. However, how different fertilizer regimes affect quantitative changes in microbial assembly to effect plant growth remains obscure. Here, we explore the temporal dynamics of the root-associated bacteria of soybean using quantitative microbiome profiling (QMP) to examine its response to unbalanced fertilizer treatments (i.e., lacking either N, P or K) and its role in sustaining plant growth after four decades of unbalanced fertilization. We show that the root-associated bacteria exhibit strong succession during plant development, and bacterial loads largely increase at later stages, particularly for Bacteroidetes. Unbalanced fertilization has a significant effect on the assembly of the soybean rhizosphere bacteria, and in the absence of N fertilizer the bacterial community diverges from that of fertilized plants, while lacking P fertilizer impedes the total load and turnover of rhizosphere bacteria. Importantly, a SynCom derived from the low-nitrogen-enriched cluster is capable of stimulating plant growth, corresponding with the stabilized soybean productivity in the absence of N fertilizer. These findings provide new insights in the quantitative dynamics of the root-associated microbiome and highlight a key ecological cluster with prospects for sustainable agricultural management.

Exogenously applied Casuarina equisetifolia leaf extracts act as an osmoprotectant on proline accumulation under drought stress in local rice from Indonesia

The effects of exogenously supplied osmoprotectants in crops have not yet been extensively studied. In this study, an osmoprotectant containing a high concentration of proline (2.5 g mol-1 FW) was obtained from a Casuarina equisetifolia leaf extract. The effect of the extract was evaluated in local Indonesian rice cultivars Boawae Seratus Malam (BSM), Gogo Jak (GJ), Situ Bagendit (SB) (drought-tolerant), Kisol Manggarai (KM) and Ciherang (drought-susceptible) cultivars under drought at the morphological, physiological, and genetic levels. Under drought, the KM showed an increased level of OsWRKY, OsNAC, OsDREB1A, and OsDREB2A expression after application of the osmoprotectant, leading to the activation of proline synthesis genes including OsP5CS1, OsP5CR, and OsProDH, while the tolerant cultivars (BSM, GJ, and SB) showed no difference. The content of chlorophyll, carotenoids, anthocyanins, ascorbate peroxidase, catalase, and superoxide dismutase activities also increased in GJ and KM, during drought stress and applied osmoprotectants, but remained low in the BSM. We conclude that the foliar application of osmoprotectants derived from C.equisetifolia caused an accumulation of proline in susceptible plants. The existence of these extracts stabilizes leaf cells and supports photosynthetic compartments and carbon assimilation in plants, leading to growth.

A Synthetic Microbial Community of Plant Core Microbiome Can Be a Potential Biocontrol Tool

Microbes are accepted as the foremost drivers of the rhizosphere ecology that influences plant health in direct or indirect ways. In recent years, the rapid development of gene sequencing technology has greatly facilitated the study of plant microbiome structure and function, and various plant-associated microbiomes have been categorized. Additionally, there is growing research interest in plant-disease-related microbes, and some specific microflora beneficial to plant health have been identified. This Review discusses the plant-associated microbiome's biological control pathways and functions to modulate plant defense against pathogens. How do plant microbiomes enhance plant resistance? How does the plant core microbiome-associated synthetic microbial community (SynCom) improve plant health? This Review further points out the primary need to develop smart agriculture practices using SynComs against plant diseases. Finally, this Review provides ideas for future opportunities in plant disease control and mining new microbial resources.

Optimization of Molecular Methods for Detecting Duckweed-Associated Bacteria

The bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains and in the context of complex bacterial communities. Quantitative methods that can resolve closely related bacteria within complex communities can lead to a better understanding of plant-microbe interactions. However, current methods often lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study duckweed-associated bacteria. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed-bacterium associations, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed-bacterium associations present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root-frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe associations within plant-microbial communities.

Metagenomic sequencing combined with flow cytometry facilitated a novel microbial risk assessment framework for bacterial pathogens in municipal wastewater without cultivation

A workflow that combined metagenomic sequencing with flow cytometry was developed. The absolute abundance of pathogens was accurately estimated in mock communities and real samples. Metagenome-assembled genomes binned from metagenomic data set is robust in phylogenetic analysis and virulence profiling.

High throughput method of 16S rRNA gene sequencing library preparation for plant root microbial community profiling

Microbiota are a major component of agroecosystems. Root microbiota, which inhabit the inside and surface of plant roots, play a significant role in plant growth and health. As next-generation sequencing technology allows the capture of microbial profiles without culturing the microbes, profiling of plant microbiota has become a staple tool in plant science and agriculture. Here, we have increased sample handling efficiency in a two-step PCR amplification protocol for 16S rRNA gene sequencing of plant root microbiota, improving DNA extraction using AMPure XP magnetic beads and PCR purification using exonuclease. These modifications reduce sample handling and capture microbial diversity comparable to that obtained by the manual method. We found a buffer with AMPure XP magnetic beads enabled efficient extraction of microbial DNA directly from plant roots. We also demonstrated that purification using exonuclease before the second PCR step enabled the capture of higher degrees of microbial diversity, thus allowing for the detection of minor bacteria compared with the purification using magnetic beads in this step. In addition, our method generated comparable microbiome profile data in plant roots and soils to that of using common commercially available DNA extraction kits, such as DNeasy PowerSoil Pro Kit and FastDNA SPIN Kit for Soil. Our method offers a simple and high-throughput option for maintaining the quality of plant root microbial community profiling.

Nodulation and nitrogen fixation in Medicago truncatula strongly alters the abundance of its root microbiota and subtly affects its structure

The plant common symbiosis signalling (SYM) pathway has shared function between interactions with rhizobia and arbuscular mycorrhizal fungi, the two most important symbiotic interactions between plants and microorganisms that are crucial in plant and agricultural yields. Here, we determine the role of the plant SYM pathway in the structure and abundance of the microbiota in the model legume Medicago truncatula and whether this is controlled by the nitrogen or phosphorus status of the plant. We show that SYM mutants (dmi3) differ substantially from the wild type (WT) in the absolute abundance of the root microbiota, especially under nitrogen limitation. Changes in the structure of the microbiota were less pronounced and depended on both plant genotype and nutrient status. Thus, the SYM pathway has a major impact on microbial abundance in M. truncatula and also subtly alters the composition of the microbiota.

Investigating plant-microbe interactions within the root

A diverse lineage of microorganisms inhabits plant roots and interacts with plants in various ways. Further, these microbes communicate and interact with each other within the root microbial community. These symbioses add an array of influences, such as plant growth promotion or indirect protection to the host plant. Omics technology and genetic manipulation have been applied to unravel these interactions. Recent studies probed plants' control over microbes. However, the activity of the root microbial community under host influence has not been elucidated enough. In this mini-review, we discussed the recent advances and limits of omics technology and genetics for dissecting the activity of the root-associated microbial community. These materials may help us formulate the correct experimental plans to capture the entire molecular mechanisms of the plant-microbe interaction.

Impacts of combined water-saving irrigation and controlled-release urea on CH4 emission and its associated microbial communities and function

Water-saving irrigation and controlled-release nitrogen fertilizer are used in rice farming. The aim of this study was to understand the effects of water-saving irrigation and controlled-release urea on methane (CH₄) emission and its associated microbial communities and function. A field experiment was conducted with two nitrogen treatments (NU 100% normal urea, CU 60% normal urea and 40% controlled-release urea, total N amount was the same) and three irrigation modes (CI continuous flooding irrigation, AI alternate wetting and drying irrigation, RI ridge irrigation). CH₄ fluxes, organic acid contents and enzyme activities were measured, and soil microbial communities and function were investigated by whole-genome shotgun sequencing analysis, and then their relationships were analyzed by Spearman correlation analysis, redundancy analysis and mantel test. Compared to CI, AI and RI decreased cumulative CH₄ emissions by 43.5% and 25.8% in NU, and 64.9% and 13.3% in CU, respectively. Among all treatments, AICU had the lowest CH₄ emission and reduced it by 72.2% compared to CINU. AI and RI had higher contents of some organic acids than CI. Compared to CINU, AICU decreased the relative abundance of Methanosarcina barkeri and associated genes in the CO₂-reduction methanogenesis pathway by 83.4% and 91.0%. Both abundance of methanogens and associated genes in the CO₂-reduction methanogenesis pathway were positively correlated with cumulative CH₄ emission, but negatively correlated with most soil organic acids. Thus AICU can mitigate CH₄ emission by decreasing the abundance of methanogens and associated genes in the CO₂-reduction methanogenesis pathway.

Accurate 16S Absolute Quantification Sequencing Revealed Vaginal Microecological Composition and Dynamics During Mixed Vaginitis Treatment With Fufang FuRong Effervescent Suppository

Background

The diagnosis and treatment of mixed vaginitis are more complicated than single pathogenic infections, and there may be adverse reactions and several contraindications to conventional antibiotic therapy. Therefore, this study aimed to evaluate the preliminary effects of Fufang Furong Effervescent Suppository for the management of aerobic vaginitis (AV) mixed with bacterial vaginosis (BV) using Accurate 16S absolute quantification sequencing (Accu16S).

Methods

In the present randomized, blind, multi-center clinical trial, women (20 to 55 years) who had received a diagnosis of AV+BV were randomly assigned into clindamycin positive control (n = 41) and Fufang Furong Effervescent Suppository (n = 39) groups. The follow-up occurred in three time periods (V1: -2~0 days; V2: 15-17 days; V3: 40 ± 3 days). At each visit, two vaginal swabs, one for clinical evaluation and one for laboratory examination, were taken from each patient. The Nugent score, Donders’ score, drug-related complications, recurrence rates, and microecological changes of vaginal swabs were assessed in the time three periods.

Results

At baseline, the two groups were similar in frequency of presentation with vaginal burning, odor, abnormal discharge, and itching. No meaningful differences in Nugent and Donders’ scores were detected between the two groups at stage V2 (Nugent: p = 0.67; Donders’: p = 0.85) and V3 (Nugent: p = 0.97; Donders: p = 0.55). The Furong group presented fewer complications compared to the Clindamycin group. However, this difference was not statistically significant (p = 0.15). Additionally, Accu16S indicated that the total abundance of bacteria in both groups sharply decreased in stage V2, but slightly increased in V3. In stage V3, the absolute abundance of Lactobacillus in the Furong group was considerably higher compared to untreated samples (p < 0.05). On the other hand, no momentous increase was detected in the Clindamycin group (p > 0.05).

Conclusion

Fufang Furong Effervescent Suppository can be as effective as clindamycin cream in the management of AV+BV while may restore the vagina microecosystem better.

Rapid absolute quantification of pathogens and ARGs by nanopore sequencing

Compositional nature of relative abundance data in the current standard microbiome studies limits microbial dynamics interpretations and cross-sample comparisons. Here, we demonstrate the first rapid (1-h sequencing) method coupling Nanopore metagenomic sequencing with cellular spike-in to facilitate the absolute quantification and removal assessment of pathogens and antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs). Nanopore sequencing-based quantification results for both simple mock community and complex real environmental samples showed a high consistency with those from the widely-used Illumina and culture-based approaches. Implementing such method, we quantified 46 predominant putative pathogenic species, and 361 ARGs in three WWTP sample sets. Though high log removals of dominant pathogens (2.23 logs) and ARGs (1.98 logs) were achieved, complete removal of all pathogens and ARGs were not achieved. Noticeably, Mycobacterium spp., Clostridium_P perfringens, and Borrelia hermsii exhibited low removal, and 13 ARGs even increased in absolute abundance after the treatment. Our proposed approach manifested its profound ability in providing absolute quantitation information guiding wastewater-based epidemiological surveillance and quantitative risk assessment facilitating microbial hazards management.

Characterization of bacterial communities isolated from municipal waste compost and screening of their plant-interactive phenotypes

Four batches of commercial compost obtained from the organic fraction of municipal solid waste were analyzed from chemical and microbiological standpoints. The working hypothesis was that, being this type of compost derived partly from plant waste, it could contain plant-growth promoting bacterial endophytes, prone to be active again upon its usual delivery as fertilizer. Culturable bacteria were isolated at different temperatures, quantified by colony morphology, identified taxonomically by 16S sequencing and screened for plant-growth promoting phenotypes including auxin and siderophore production, phosphate solubilization and peptide mineralization to ammonia. In parallel, the total community was assessed by culture independent DNA metabarcoding. The capability of plants to select, uptake and internally multiply bacteria from these compost samples was analyzed using grapevine in-vitro rooting cuttings from which acquired bacteria were reisolated, quantified and their identities determined as above. Major differences in compost bacterial composition were observed as function of the season, with the winter sample being rather distinct from the summer ones. Bacillales and Actinomycetales dominated the culturable communities while Alteromonadales, Oceanospirillales and Flavobacteriales prevailed in the total community. In spite of the challenging composting cycle conditions, the plant nature of the main input substrates appeared determinant in guaranteeing that 82% of the culturable bacteria were found endowed with one or more of the plant growth-promoting phenotypes tested. Beside its fertilization role, compost proved to be also a potential inoculant carrier for the in-soil delivery of plant beneficial microorganisms. Furthermore, upon an in vitro passage through grapevine plants under axenic conditions, the subsequently recoverable endophyte community yielded also members of the Rhizobiales order which had not been detectable when culturing directly from compost. This observation further suggests that compost-borne plant-interacting taxa could be also rescued from non-culturable states and/or enriched above detectability levels by a contact with their potential host plants.

High-Throughput Profiling of Root-Associated Microbial Communities

Roots of healthy plants are colonized by a great diversity of bacteria and fungi but also other microorganisms that are collectively referred to as the root microbiota. Root microbiota composition is shaped by environmental cues, by host genetics, but also by microbe-microbe interactions, and recent evidence indicates that a direct link exists between root microbiota assembly and host health. In order to characterize the root microbiota or to study the complex interplay between plants and their associated microbes, the assessment of microbial community structure via marker gene amplicon sequencing has become a key tool. Herein, we present detailed methods for the preparation of 16S rRNA gene and internal transcribed spacer (ITS) amplicon libraries to characterize Arabidopsis thaliana-associated bacterial and fungal communities along the soil-root continuum. The protocols can be easily adapted for different host organs or plant species.

Improved quantitative microbiome profiling for environmental antibiotic resistance surveillance

BACKGROUND

Understanding environmental microbiomes and antibiotic resistance (AR) is hindered by over reliance on relative abundance data from next-generation sequencing. Relative data limits our ability to quantify changes in microbiomes and resistomes over space and time because sequencing depth is not considered and makes data less suitable for Quantitative Microbial Risk Assessments (QMRA), critical in quantifying environmental AR exposure and transmission risks.

RESULTS

Here we combine quantitative microbiome profiling (QMP; parallelization of amplicon sequencing and 16S rRNA qPCR to estimate cell counts) and absolute resistome profiling (based on high-throughput qPCR) to quantify AR along an anthropogenically impacted river. We show QMP overcomes biases caused by relative taxa abundance data and show the benefits of using unified Hill number diversities to describe environmental microbial communities. Our approach overcomes weaknesses in previous methods and shows Hill numbers are better for QMP in diversity characterisation.

CONCLUSIONS

Methods here can be adapted for any microbiome and resistome research question, but especially providing more quantitative data for QMRA and other environmental applications.

Prolonged drought imparts lasting compositional changes to the rice root microbiome

Microbial symbioses can mitigate drought stress in crops but harnessing these beneficial interactions will require an in-depth understanding of root microbiome responses to drought cycles. Here, by detailed temporal characterization of root-associated microbiomes of rice plants during drought stress and recovery, we find that endosphere communities remained compositionally altered after rewatering, with prolonged droughts leading to decreased resilience. Several endospheric Actinobacteria were significantly enriched during drought and for weeks after rewatering. Notably, the most abundant endosphere taxon during this period was a Streptomyces, and a corresponding isolate promoted root growth. Additionally, drought stress disrupted the temporal dynamics of late-colonizing microorganisms, permanently altering the normal successional trends of root microbiota. These findings reveal that severe drought results in enduring impacts on rice root microbiomes, including enrichment of taxonomic groups that could shape the recovery response of the host, and have implications relevant to drought protection strategies using root microbiota.

Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition

The ratio of microbial population size relative to the amount of host tissue, or 'microbial load', is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because existing methods to determine load, such as serial dilution plating, quantitative PCR, and whole metagenome sequencing add substantial cost and/or experimental burden, they are only rarely paired with amplicon sequencing. We introduce host-associated microbe PCR (hamPCR), a robust strategy to both quantify microbial load and describe interkingdom microbial community composition in a single amplicon library. We demonstrate its accuracy across multiple study systems, including nematodes and major crops, and further present a cost-saving technique to reduce host overrepresentation in the library prior to sequencing. Because hamPCR provides an accessible experimental solution to the well-known limitations and statistical challenges of compositional data, it has far-reaching potential in culture-independent microbiology.

Progress and Prospects of Mycorrhizal Fungal Diversity in Orchids

Orchids form mycorrhizal symbioses with fungi in natural habitats that affect their seed germination, protocorm growth, and adult nutrition. An increasing number of studies indicates how orchids gain mineral nutrients and sometime even organic compounds from interactions with orchid mycorrhizal fungi (OMF). Thus, OMF exhibit a high diversity and play a key role in the life cycle of orchids. In recent years, the high-throughput molecular identification of fungi has broadly extended our understanding of OMF diversity, revealing it to be a dynamic outcome co-regulated by environmental filtering, dispersal restrictions, spatiotemporal scales, biogeographic history, as well as the distribution, selection, and phylogenetic spectrum width of host orchids. Most of the results show congruent emerging patterns. Although it is still difficult to extend them to all orchid species or geographical areas, to a certain extent they follow the "everything is everywhere, but the environment selects" rule. This review provides an extensive understanding of the diversity and ecological dynamics of orchid-fungal association. Moreover, it promotes the conservation of resources and the regeneration of rare or endangered orchids. We provide a comprehensive overview, systematically describing six fields of research on orchid-fungal diversity: the research methods of orchid-fungal interactions, the primer selection in high-throughput sequencing, the fungal diversity and specificity in orchids, the difference and adaptability of OMF in different habitats, the comparison of OMF in orchid roots and soil, and the spatiotemporal variation patterns of OMF. Further, we highlight certain shortcomings of current research methodologies and propose perspectives for future studies. This review emphasizes the need for more information on the four main ecological processes: dispersal, selection, ecological drift, and diversification, as well as their interactions, in the study of orchid-fungal interactions and OMF community structure.

A practical guide to amplicon and metagenomic analysis of microbiome data

Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.

Mycorrhizal symbiosis modulates the rhizosphere microbiota to promote rhizobia-legume symbiosis

Plants establish symbioses with mutualistic fungi, such as arbuscular mycorrhizal (AM) fungi, and bacteria, such as rhizobia, to exchange key nutrients and thrive. Plants and symbionts have coevolved and represent vital components of terrestrial ecosystems. Plants employ an ancestral AM signaling pathway to establish intracellular symbioses, including the legume-rhizobia symbiosis, in their roots. Nevertheless, the relationship between the AM and rhizobial symbioses in native soil is poorly understood. Here, we examined how these distinct symbioses affect root-associated bacterial communities in Medicago truncatula by performing quantitative microbiota profiling (QMP) of 16S rRNA genes. We found that M. truncatula mutants that cannot establish AM or rhizobia symbiosis have an altered microbial load (quantitative abundance) in the rhizosphere and roots, and in particular that AM symbiosis is required to assemble a normal quantitative root-associated microbiota in native soil. Moreover, quantitative microbial co-abundance network analyses revealed that AM symbiosis affects Rhizobiales hubs among plant microbiota and benefits the plant holobiont. Through QMP of rhizobial rpoB and AM fungal SSU rRNA genes, we revealed a new layer of interaction whereby AM symbiosis promotes rhizobia accumulation in the rhizosphere of M. truncatula. We further showed that AM symbiosis-conditioned microbial communities within the M. truncatula rhizosphere could promote nodulation in different legume plants in native soil. Given that the AM and rhizobial symbioses are critical for crop growth, our findings might inform strategies to improve agricultural management. Moreover, our work sheds light on the co-evolution of these intracellular symbioses during plant adaptation to native soil conditions.

Metagenomic tools in microbial ecology research

Ability to directly sequence DNA from the environment permanently changed microbial ecology. Here, we review the new insights to microbial life gleaned from the applications of metagenomics, as well as the extensive set of analytical tools that facilitate exploration of diversity and function of complex microbial communities. While metagenomics is shaping our understanding of microbial functions in ecosystems via gene-centric and genome-centric methods, annotating functions, metagenome assembly and binning in heterogeneous samples remains challenging. Development of new analysis and sequencing platforms generating high-throughput long-read sequences and functional screening opportunities will aid in harnessing metagenomes to increase our understanding of microbial taxonomy, function, ecology, and evolution in the environment.

Gradient Internal Standard Method for Absolute Quantification of Microbial Amplicon Sequencing Data

High-throughput amplicon sequencing is a critical tool for studying microbiota; however, it results only in relative abundance data. Thus, changes in absolute abundance of microbiota cannot be determined, which hinders further microbiology research. We have therefore established a gradient internal standard absolute quantification (GIS-AQ) method to overcome this issue, which can simultaneously obtain the absolute abundances of bacteria and fungi. Deviations from the quantitative equations of microbes and internal standards were eliminated through calibration. Compared with traditional quantitative real-time PCR and microscopy quantifications, this method is reliable (R 2 average = 0.998; P < 0.001) and accurate (P internals versus microscopy > 0.05). The GIS-AQ method can be adapted to any amplicon primer choice (e.g., 336F/806R and ITS3/ITS4), rendering it applicable to ecosystem studies including food, soil, and water samples. Crucially, when using solid-state fermentation samples from various temporal dimensions, the results obtained from the relative and absolute abundance are different. The absolute abundance can be used to study the difference in communities between different samples, and the GIS-AQ method allows this to be done rapidly. Therefore, combining the absolute abundance with relative abundance can accurately reflect the microbiota composition.IMPORTANCE To solve the problem of amplicon sequencing cannot discern the microbiota absolute abundance, we proposed a gradient internal standard absolute quantification method. We used Chinese liquor fermentation as a model system to demonstrate the reliability and accuracy of the method. By comparing the relative and absolute abundances of microbiota in various temporal dimensions, we found dynamic changes in the absolute abundance of communities under various temporal dimensions from the relative abundance. Based on its design principle, this method can be widely applied to different ecosystems. Therefore, we believe that the GIS-AQ method can play an immeasurably useful role in microbiological research.

The quest for absolute abundance: The use of internal standards for DNA-based community ecology

To characterize microbiomes and other ecological assemblages, ecologists routinely sequence and compare loci that differ among focal taxa. Counts of these sequences convey information regarding the occurrence and relative abundances of taxa, but provide no direct measure of their absolute abundances, due to the technical limitations of the sequencing process. The relative abundances in compositional data are inherently constrained and difficult to interpret. The incorporation of internal standards (ISDs; colloquially referred to as 'spike-ins') into DNA pools can ameliorate the problems posed by relative abundance data and allow absolute abundances to be approximated. Unfortunately, many laboratory and sampling biases cause ISDs to underperform or fail. Here, we discuss how careful deployment of ISDs can avoid these complications and be an integral component of well-designed studies seeking to characterize ecological assemblages via sequencing of DNA.

Water management and phenology influence the root-associated rice field microbiota

Microbial communities associated with plants are greatly influenced by water availability in soil. In flooded crops, such as rice, the impact of water management on microbial dynamics is not fully understood. Here, we present a comprehensive study of the rice microbiota investigated in an experimental field located in one of the most productive areas of northern Italy. The microbiota associated with paddy soil and root was investigated using 454 pyrosequencing of 16S, ITS and 18S rRNA gene amplicons under two different water managements, upland (non-flooded, aerobic) and lowland (traditional flooding, anaerobic), at three plant development stages. Results highlighted a major role of the soil water status in shaping microbial communities, while phenological stage had low impacts. Compositional shifts in prokaryotic and fungal communities upon water management consisted in significant abundance changes of Firmicutes, Methanobacteria, Chloroflexi, Sordariomycetes, Dothideomycetes and Glomeromycotina. A vicariance in plant beneficial microbes and between saprotrophs and pathotrophs was observed between lowland and upland. Moreover, through network analysis, we demonstrated different co-abundance dynamics between lowland and upland conditions with a major impact on microbial hubs (strongly interconnected microbes) that fully shifted to aerobic microbes in the absence of flooding.

Host Genotype and Colonist Arrival Order Jointly Govern Plant Microbiome Composition and Function

The composition of host-associated microbiomes can have important consequences for host health and fitness [1-3]. Yet we still lack understanding of many fundamental processes that determine microbiome composition [4, 5]. There is mounting evidence that historical contingency during microbiome assembly may overshadow more deterministic processes, such as the selective filters imposed by host traits [6-8]. More specifically, species arrival order has been frequently shown to affect microbiome composition [9-12], a phenomenon known as priority effects [13-15]. However, it is less clear whether priority effects during microbiome assembly are consequential for the host [16] or whether intraspecific variation in host traits can alter the trajectory of microbiome assembly under priority effects. In a greenhouse inoculation experiment using the black cottonwood (Populus trichocarpa) foliar microbiome, we manipulated host genotype and the colonization order of common foliar fungi. We quantified microbiome assembly outcomes using fungal marker gene sequencing and measured susceptibility of the colonized host to a leaf rust pathogen, Melampsora × columbiana. We found that the effect of species arrival order on microbiome composition, and subsequent disease susceptibility, depended on the host genotype. Additionally, we found that microbiome assembly history can affect host disease susceptibility independent of microbiome composition at the time of pathogen exposure, suggesting that the interactive effects of species arrival order and host genotype can decouple community composition and function. Overall, these results highlight the importance of a key process underlying stochasticity in microbiome assembly while also revealing which hosts are most likely to experience these effects.

Rhizosphere bacterial and fungal communities during the growth of Angelica sinensis seedlings cultivated in an Alpine uncultivated meadow soil

BACKGROUND

Angelica sinensis seedlings are grown in alpine uncultivated meadow soil with rainfed agroecosystems to ensure the quality of A. sinensis after seedling transplantation. The aim was to investigate the rhizosphere bacterial and fungal communities during the growth stages of A. sinensis seedlings.

METHODS

The bacterial and fungal communities were investigated by HiSeq sequencing of 16S and 18S rDNA, respectively.

RESULTS

Proteobacteria and Bacteroidetes were bacterial dominant phyla throughout growth stages. Fungal dominant phyla varied with growth stages, dominant phyla Ascomycota and Chytridiomycota in AM5, dominant phyla Basidiomycota, Ascomycota and Zygomycota in BM5, and dominant phyla Basidiomycota and Ascomycota in CM5. There was no significant variation in the alpha-diversity of the bacterial and fungal communities, but significant variation was in the beta-diversity. We found that the variation of microbial community composition was accompanied by the changes in community function. The relative abundance of fungal pathogens increased with plant growth. We also identified the core microbes, significant-changing microbes, stage-specific microbes, and host-specific microbes. Plant weight, root length, root diameter, soil pH, rainfall, and climate temperature were the key divers to microbial community composition.

CONCLUSIONS

Our findings reported the variation and environmental drivers of rhizosphere bacterial and fungal communities during the growth of A. sinensis seedlings, which enhance the understanding of the rhizosphere microbial community in this habitat.