Adjusting microbiome profiles for differences in microbial load by spike-in bacteria

Microbial liberation of N-methylserotonin from orange fiber in gnotobiotic mice and humans

Plant fibers in byproduct streams produced by non-harsh food processing methods represent biorepositories of diverse, naturally occurring, and physiologically active biomolecules. To demonstrate one approach for their characterization, mass spectrometry of intestinal contents from gnotobiotic mice, plus in vitro studies, revealed liberation of N-methylserotonin from orange fibers by human gut microbiota members including Bacteroides ovatus. Functional genomic analyses of B. ovatus strains grown under permissive and non-permissive N-methylserotonin "mining" conditions revealed polysaccharide utilization loci that target pectins whose expression correlate with strain-specific liberation of this compound. N-methylserotonin, orally administered to germ-free mice, reduced adiposity, altered liver glycogenesis, shortened gut transit time, and changed expression of genes that regulate circadian rhythm in the liver and colon. In human studies, dose-dependent, orange-fiber-specific fecal accumulation of N-methylserotonin positively correlated with levels of microbiome genes encoding enzymes that digest pectic glycans. Identifying this type of microbial mining activity has potential therapeutic implications.

Inoculation with the pH Lowering Plant Growth Promoting Bacterium Bacillus sp. ZV6 Enhances Ni Phytoextraction by Salix alba from a Ni-Polluted Soil Receiving Effluents from Ni Electroplating Industry

Soil contamination with Ni poses serious ecological risks to the environment. Several members of the Salix genus have the ability to accumulate high concentrations of Ni in their aerial parts, and thus can be used for the remediation of Ni-contaminated soils. Interestingly, the efficacy of Ni phytoextraction by Salix may be improved by the acidification of rhizosphere with rhizosphere acidifying bacterial strains. Therefore, the aim of this study was to assess the efficacy of bacterial strain Bacillus sp. ZV6 in the presence of animal manure (AM) and leaf manure (LM) for enhancing the bioavailability of Ni in the rhizosphere of Salix alba via reducing the pH of rhizosphere and resultantly, enhanced phytoextraction of Ni. Inoculation of Ni-contaminated soil with strain ZV6 significantly increased plant growth as well as Ni uptake by alba. It was found that the addition of AM and LM resulted into a significant increase in plant growth and Ni uptake by alba in Ni-contaminated soil inoculated with ZV6 stain. However, the highest improvements in diethylene triamine penta-acetic acid (DTPA) extractable Ni (10%), Ni removal from soil (54%), Ni bioconcentration factor (26%) and Ni translocation factor (13%) were detected in the soil inoculated with ZV6 along with the addition of LM, compared to control. Similarly, the enhancements in microbial biomass (92%), bacterial count (348%), organic carbon (organic C) (57%) and various enzymatic activities such as urease (56%), dehydrogenase (32%), β-glucosidase (53%), peroxidase (26%) and acid phosphatase (38%) were also significantly higher in the soil inoculated with ZV6 along with the addition of LM. The findings of this study suggest that the inoculation of Ni-contaminated soils with rhizosphere acidifying bacteria can effectively improve Ni phytoextraction and, in parallel, enhance soil health.

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.

The Pre-Analytical CEN/TS Standard for Microbiome Diagnostics-How Can Research and Development Benefit?

Recently, CEN/TS 17626:2021, the European pre-analytical standard for human specimens intended for microbiome DNA analysis, was published. Although this standard relates to diagnostic procedures for microbiome analysis and is relevant for in vitro diagnostic (IVD) manufacturers and diagnostic laboratories, it also has implications for research and development (R&D). We present here why standards are needed in biomedical research, what pre-analytical standards can accomplish, and which elements of the pre-analytical workflow they cover. The benefits of standardization for the generation of FAIR (findable, accessible, interoperable, reusable) data and to support innovation are briefly discussed.

Aerosolization Behaviour of Fungi and Its Potential Health Effects during the Composting of Animal Manure

Compost is an important source of airborne fungi that can adversely affect occupational health. However, the aerosol behavior of fungi and their underlying factors in composting facilities are poorly understood. We collected samples from compost piles and the surrounding air during the composting of animal manure and analyzed the aerosolization behavior of fungi and its potential health effects based on the fungal composition and abundance in two media using high-throughput sequencing and ddPCR. There were differences in fungal diversity and richness between the air and composting piles. Ascomycota and Basidiomycota were the two primary fungal phyla in both media. The dominant fungal genera in composting piles were Aspergillus, Thermomyces, and Alternaria, while the dominant airborne fungal genes were Alternaria, Cladosporium, and Sporobolomyces. Although the communities of total fungal genera and pathogenic/allergenic genera were different in the two media, fungal abundance in composting piles was significantly correlated with abundance in air. According to the analysis on fungal composition, a total of 69.10% of the fungal genera and 91.30% of pathogenic/allergenic genera might escape from composting pile into the air. A total of 77 (26.64%) of the fungal genera and six (20%) of pathogenic/allergenic genera were likely to aerosolize. The influence of physicochemical parameters and heavy metals on the aerosol behavior of fungal genera, including pathogenic/allergenic genera, varied among the fungal genera. These results increase our understanding of fungal escape during composting and highlight the importance of aerosolization behavior for predicting the airborne fungal composition and corresponding human health risks in compost facilities.

Products of gut microbial Toll/interleukin-1 receptor domain NADase activities in gnotobiotic mice and Bangladeshi children with malnutrition

Perturbed gut microbiome development has been linked to childhood malnutrition. Here, we characterize bacterial Toll/interleukin-1 receptor (TIR) protein domains that metabolize nicotinamide adenine dinucleotide (NAD), a co-enzyme with far-reaching effects on human physiology. A consortium of 26 human gut bacterial strains, representing the diversity of TIRs observed in the microbiome and the NAD hydrolase (NADase) activities of a subset of 152 bacterial TIRs assayed in vitro, was introduced into germ-free mice. Integrating mass spectrometry and microbial RNA sequencing (RNA-seq) with consortium membership manipulation disclosed that a variant of cyclic-ADPR (v-cADPR-x) is a specific product of TIR NADase activity and a prominent, colonization-discriminatory, taxon-specific metabolite. Guided by bioinformatic analyses of biochemically validated TIRs, we find that acute malnutrition is associated with decreased fecal levels of genes encoding TIRs known or predicted to generate v-cADPR-x, as well as decreased levels of the metabolite itself. These results underscore the need to consider microbiome TIR NADases when evaluating NAD metabolism in the human holobiont.

Contribution of Clinical Metagenomics to the Diagnosis of Bone and Joint Infections

Bone and joint infections (BJIs) are complex infections that require precise microbiological documentation to optimize antibiotic therapy. Currently, diagnosis is based on microbiological culture, sometimes complemented by amplification and sequencing of the 16S rDNA gene. Clinical metagenomics (CMg), that is, the sequencing of the entire nucleic acids in a sample, was previously shown to identify bacteria not detected by conventional methods, but its actual contribution to the diagnosis remains to be assessed, especially with regard to 16S rDNA sequencing. In the present study, we tested the performance of CMg in 34 patients (94 samples) with suspected BJIs, as compared to culture and 16S rDNA sequencing. A total of 94 samples from 34 patients with suspicion of BJIs, recruited from two sites, were analyzed by (i) conventional culture, (ii) 16S rDNA sequencing (Sanger method), and (iii) CMg (Illumina Technology). Two negative controls were also sequenced by CMg for contamination assessment. Based on the sequencing results of negative controls, 414 out of 539 (76.7%) bacterial species detected by CMg were considered as contaminants and 125 (23.2%) as truly present. For monomicrobial infections (13 patients), the sensitivity of CMg was 83.3% as compared to culture, and 100% as compared to 16S rDNA. For polymicrobial infections (13 patients), the sensitivity of CMg was 50% compared to culture, and 100% compared to 16S rDNA. For samples negative in culture (8 patients, 21 samples), CMg detected 11 bacteria in 10 samples from 5 different patients. In 5/34 patients, CMg brought a microbiological diagnosis where conventional methods failed, and in 16/34 patients, CMg provided additional information. Finally, 99 antibiotic resistance genes were detected in 24 patients (56 samples). Provided sufficient genome coverage (87.5%), a correct inference of antibiotic susceptibility was achieved in 8/8 bacteria (100%). In conclusion, our study demonstrated that the CMg provides complementary and potentially valuable data to conventional methods of BJIs diagnosis.

Bifidobacterium infantis treatment promotes weight gain in Bangladeshi infants with severe acute malnutrition

Disrupted development of the gut microbiota is a contributing cause of childhood malnutrition. Bifidobacterium longum subspecies infantis is a prominent early colonizer of the infant gut that consumes human milk oligosaccharides (HMOs). We found that the absolute abundance of Bifidobacterium infantis is lower in 3- to 24-month-old Bangladeshi infants with severe acute malnutrition (SAM) compared to their healthy age-matched counterparts. A single-blind, placebo-controlled trial (SYNERGIE) was conducted in 2- to 6-month-old Bangladeshi infants with SAM. A commercial U.S. donor-derived B. infantis strain (EVC001) was administered daily with or without the HMO lacto-N-neotetraose for 28 days. This intervention increased fecal B. infantis abundance in infants with SAM, although to levels still 10- to 100-fold lower than in untreated healthy controls. EVC001 treatment promoted weight gain that was associated with reduced intestinal inflammation markers in infants with SAM. We cultured fecal B. infantis strains from Bangladeshi infants and colonized gnotobiotic mice with these cultured strains. The gnotobiotic mice were fed a diet representative of that consumed by 6-month-old Bangladeshi infants, with or without HMO supplementation. One B. infantis strain, Bg_2D9, expressing two gene clusters involved in uptake and utilization of N-glycans and plant-derived polysaccharides, exhibited superior fitness over EVC001. The fitness advantage of Bg_2D9 was confirmed in a gnotobiotic mouse model of mother-to-infant gut microbiota transmission where dams received a pretreatment fecal community from a SAM infant in the SYNERGIE trial. Whether Bg_2D9 is superior to EVC001 for treating malnourished infants who consume a diet with limited breastmilk requires further clinical testing.

Early Identification of Fungal and Mycobacterium Infections in Pulmonary Granulomas Using Metagenomic Next-Generation Sequencing on Formalin fixation and paraffin embedding tissue

BACKGROUND

The purpose of the study is to assess the etiology detection ability of Metagenomic Next-Generation Sequencing (mNGS) on formalin fixation and paraffin embedding (FFPE) tissue from postoperative biopsy specimen.

METHODS

We prospectively enrolled specimens from patients undergone surgery biopsy due to undefinite diagnosis and pathologically indicated granulomatous lesions. FFPE tissues were tested by mNGS and histopathology. The etiology detection rate of mNGS was calculated and compared with histopathology, using the clinical diagnosis as the reference criteria.

RESULTS

Among the 69 cases eventually included, 41 (59.42%) were diagnosed as infectious granuloma. The overall fungi and mycobacteria etiology detection rate of mNGS in granuloma lesions was 87.80 % (36/41) . The mNGS increased detection rate by 68.29 % (28/41) compared with histopathology, the difference was statistically significant (χ2= 28.97, P 0.00).The detection rates of mNGS in fungal infections (12/12,100%) and in mycobacterium infections (22/27, 81.48%) were significant higher than those of histopathology (8/12, 66.67% and 0/27,0.00 %;both P 0.00). 2 (2/2.100%) cases of co-infection were detected at one time by mNGS. All mNGS-based clinical decisions were made within 2 days.

CONCLUSIONS

The mNGS could accurately and quickly detect fungi and mycobacteria on FFPE specimens from postoperative granuloma specimens and identify the pathogens to the species level.

CLINICAL TRIALS REGISTRATION

China Clinical Trial Registry ChiCTR2000035464.

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.

Relative and Quantitative Rhizosphere Microbiome Profiling Results in Distinct Abundance Patterns

Next-generation sequencing is one of the most popular and cost-effective ways of characterizing microbiome in multiple samples. However, most of the currently available amplicon sequencing approaches are limited, as they result in relative abundance profiles of microbial taxa, which does not represent actual abundance in the environment. Here, we combined amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) with real-time quantitative PCR (qPCR) to characterize the rhizosphere microbiome of wheat. We show that changes in the relative abundance of major microbial phyla do not necessarily follow the same pattern as the estimated quantitative abundance. Most of the bacterial phyla linked with the rhizosphere of plants grown in soil with no history of water stress showed enrichment patterns in their estimated absolute abundance, which was in contradiction with the trends observed in the relative abundance data. However, in the case of the fungal groups (except for Basidiomycota), such an enrichment pattern was not observed and the abundance of fungi remained relatively unchanged under different soil water stress history when estimated absolute abundance was considered. Comparing relative and estimated absolute abundances of dominant bacterial and fungal phyla, as well as their correlation with the functional processes in the rhizosphere, our results suggest that the estimated absolute abundance approach gives a different and more realistic perspective than the relative abundance approach. Such a quantification approach provides complementary information that helps to better understand the rhizosphere microbiomes and their associated ecological functional processes.

Gut Microbiome Composition in Obese and Non-Obese Persons: A Systematic Review and Meta-Analysis

Whether the gut microbiome in obesity is characterized by lower diversity and altered composition at the phylum or genus level may be more accurately investigated using high-throughput sequencing technologies. We conducted a systematic review in PubMed and Embase including 32 cross-sectional studies assessing the gut microbiome composition by high-throughput sequencing in obese and non-obese adults. A significantly lower alpha diversity (Shannon index) in obese versus non-obese adults was observed in nine out of 22 studies, and meta-analysis of seven studies revealed a non-significant mean difference (−0.06, 95% CI −0.24, 0.12, I² = 81%). At the phylum level, significantly more Firmicutes and fewer Bacteroidetes in obese versus non-obese adults were observed in six out of seventeen, and in four out of eighteen studies, respectively. Meta-analyses of six studies revealed significantly higher Firmicutes (5.50, 95% 0.27, 10.73, I² = 81%) and non-significantly lower Bacteroidetes (−4.79, 95% CI −10.77, 1.20, I² = 86%). At the genus level, lower relative proportions of Bifidobacterium and Eggerthella and higher Acidaminococcus, Anaerococcus, Catenibacterium, Dialister, Dorea, Escherichia-Shigella, Eubacterium, Fusobacterium, Megasphera, Prevotella, Roseburia, Streptococcus, and Sutterella were found in obese versus non-obese adults. Although a proportion of studies found lower diversity and differences in gut microbiome composition in obese versus non-obese adults, the observed heterogeneity across studies precludes clear answers.

Grazing weakens competitive interactions between active methanotrophs and nitrifiers modulating greenhouse-gas emissions in grassland soils

Grassland soils serve as a biological sink and source of the potent greenhouse gases (GHG) methane (CH4) and nitrous oxide (N2O). The underlying mechanisms responsible for those GHG emissions, specifically, the relationships between methane- and ammonia-oxidizing microorganisms in grazed grassland soils are still poorly understood. Here, we characterized the effects of grazing on in situ GHG emissions and elucidated the putative relations between the active microbes involving in methane oxidation and nitrification activity in grassland soils. Grazing significantly decreases CH4 uptake while it increases N2O emissions basing on 14-month in situ measurement. DNA-based stable isotope probing (SIP) incubation experiment shows that grazing decreases both methane oxidation and nitrification processes and decreases the diversity of active methanotrophs and nitrifiers, and subsequently weakens the putative competition between active methanotrophs and nitrifiers in grassland soils. These results constitute a major advance in our understanding of putative relationships between methane- and ammonia-oxidizing microorganisms and subsequent effects on nitrification and methane oxidation, which contribute to a better prediction and modeling of future balance of GHG emissions and active microbial communities in grazed grassland ecosystems.

Diurnal oscillations in gut bacterial load and composition eclipse seasonal and lifetime dynamics in wild meerkats

Circadian rhythms in gut microbiota composition are crucial for metabolic function, yet the extent to which they govern microbial dynamics compared to seasonal and lifetime processes remains unknown. Here, we investigate gut bacterial dynamics in wild meerkats (Suricata suricatta) over a 20-year period to compare diurnal, seasonal, and lifetime processes in concert, applying ratios of absolute abundance. We found that diurnal oscillations in bacterial load and composition eclipsed seasonal and lifetime dynamics. Diurnal oscillations were characterised by a peak in Clostridium abundance at dawn, were associated with temperature-constrained foraging schedules, and did not decay with age. Some genera exhibited seasonal fluctuations, whilst others developed with age, although we found little support for microbial senescence in very old meerkats. Strong microbial circadian rhythms in this species may reflect the extreme daily temperature fluctuations typical of arid-zone climates. Our findings demonstrate that accounting for circadian rhythms is essential for future gut microbiome research.

High-resolution sweep metagenomics using fast probabilistic inference

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

Untangling Microbiota Diversity and Assembly Patterns in the World's Largest Water Diversion Canal

Large water diversion projects are important constructions for reallocation of human-essential water resources. Deciphering microbiota dynamics and assembly mechanisms underlying canal water ecosystem services especially during long-distance diversion is a prerequisite for water quality monitoring, biohazard warning and sustainable management. Using a 1432-km canal of the South-to-North Water Diversion Projects as a model system, we answer three central questions: how bacterial and micro-eukaryotic communities spatio-temporally develop, how much ecological stochasticity contributes to microbiota assembly, and which immigrating populations better survive and navigate across the canal. We applied quantitative ribosomal RNA gene sequence analyses to investigate canal water microbial communities sampled over a year, as well as null model- and neutral model-based approaches to disentangle the microbiota assembly processes. Our results showed clear microbiota dynamics in community composition driven by seasonality more than geographic location, and seasonally dependent influence of environmental parameters. Overall, bacterial community was largely shaped by deterministic processes, whereas stochasticity dominated micro-eukaryotic community assembly. We defined a local growth factor (LGF) and demonstrated its innovative use to quantitatively infer microbial proliferation, unraveling taxonomically dependent population response to local environmental selection across canal sections. Using LGF as a quantitative indicator of immigrating capacities, we also found that most micro-eukaryotic populations (82%) from the source water sustained growth in the canal and better acclimated to the hydrodynamical water environment than bacteria (67%). Taxa inferred to largely propagate include Limnohabitans sp. and Cryptophyceae, potentially contributing to water auto-purification. Combined, our work poses first and unique insights into the microbiota assembly patterns and dynamics in the world's largest water diversion canal, providing important ecological knowledge for long-term sustainable water quality maintenance in such a giant engineered system.

Current Applications of Absolute Bacterial Quantification in Microbiome Studies and Decision-Making Regarding Different Biological Questions

High throughput sequencing has emerged as one of the most important techniques for characterizing microbial dynamics and revealing bacteria and host interactions. However, data interpretation using this technique is mainly based on relative abundance and ignores total bacteria load. In certain cases, absolute abundance is more important than compositional relative data, and interpretation of microbiota data based solely on relative abundance can be misleading. The available approaches for absolute quantification are highly diverse and challenging, especially for quantification in differing biological situations, such as distinguishing between live and dead cells, quantification of specific taxa, enumeration of low biomass samples, large sample size feasibility, and the detection of various other cellular features. In this review, we first illustrate the importance of integrating absolute abundance into microbiome data interpretation. Second, we briefly discuss the most widely used cell-based and molecular-based bacterial load quantification methods, including fluorescence spectroscopy, flow cytometry, 16S qPCR, 16S qRT-PCR, ddPCR, and reference spike-in. Last, we present a specific decision-making scheme for absolute quantification methods based on different biological questions and some of the latest quantitative methods and procedure modifications.

Measuring the absolute abundance of the microbiome by adding yeast containing 16S rRNA gene from a hyperthermophile

High-throughput sequencing (HTS) of 16S rRNA gene amplicons provides compositional information regarding the microbial community, but not the absolute abundance of the bacteria. We aimed to develop a standardized method for quantifying the absolute abundance of bacteria in microbiome studies. To demonstrate the utility of our approach, we quantified the number of bacteria from the compositional data of the fecal and cecal microbiomes. The 16S rRNA gene of a hyperthermophile, Thermus aquaticus, was cloned into Pichia pastoris (yeast) genome, and an equivalent amount of the yeast was added to the stool and cecal samples of mice before DNA extraction. 16S rRNA gene library construction and HTS were performed after DNA extraction. The absolute abundances of bacteria were calculated using T. aquaticus reads. The average relative abundances of T. aquaticus in the five stool and five cecal samples were 0.95% and 0.33%, respectively, indicating that the number of bacteria in a cecum sample is 2.9 times higher than that in a stool sample. The method proposed for quantifying the absolute abundance of the bacterial population in this study is expected to overcome the limitation of showing only compositional data in most microbiome studies.

Merging Fungal and Bacterial Community Profiles via an Internal Control

Integrated measurements of fungi and bacteria are critical to understand how interactions between these taxa drive key processes in ecosystems ranging from soils to animal guts. High-throughput amplicon sequencing is commonly used to census microbiomes, but the genetic markers targeted for fungi and bacteria (typically ribosomal regions) are domain-specific so profiling must be performed separately, obscuring relationships between these groups. To solve this problem, we developed a spike-in method with an internal control (IC) construct containing primer sites commonly used for bacterial and fungal taxonomic profiling. The internal control offers several advantages: estimation of absolute abundances, estimation of fungal to bacterial ratios (F:B), integration of bacterial and fungal profiles for holistic community analysis, and lower costs compared to other quantitation methods. To validate the IC as a scaling method, we compared IC-derived measures of F:B to measures from quantitative PCR (qPCR) using a commercial mock community (the ZymoBiomic Microbial Community DNA Standard II, containing two fungi and eight bacteria) and complex environmental samples. For both the mock community and the environmental samples, the IC produced F:B values that were statistically consistent with qPCR. Merging the environmental fungal and bacterial profiles based on the IC-derived F:B values revealed new relationships among samples in terms of community similarity. This IC method is the first spike-in method to employ a single construct for cross-domain amplicon sequencing, offering more reliable measurements.

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.

Characterizing Microbiomes via Sequencing of Marker Loci: Techniques To Improve Throughput, Account for Cross-Contamination, and Reduce Cost

New approaches to characterizing microbiomes via high-throughput sequencing provide impressive gains in efficiency and cost reduction compared to approaches that were standard just a few years ago. However, the speed of method development has been such that staying abreast of the latest technological advances is challenging. Moreover, shifting laboratory protocols to include new methods can be expensive and time consuming. To facilitate adoption of new techniques, we provide a guide and review of recent advances that are relevant for single-locus sequence-based study of microbiomes—from extraction to library preparation—including a primer regarding the use of liquid-handling automation in small-scale academic settings. Additionally, we describe several amendments to published techniques to improve throughput, track contamination, and reduce cost. Notably, we suggest adding synthetic DNA molecules to each sample during nucleic acid extraction, thus providing a method of documenting incidences of cross-contamination. We also describe a dual-indexing scheme for Illumina sequencers that allows multiplexing of many thousands of samples with minimal PhiX input. Collectively, the techniques that we describe demonstrate that laboratory technology need not impose strict limitations on the scale of molecular microbial ecology studies.

IMPORTANCE New methods to characterize microbiomes reduce technology-imposed limitations to study design, but many new approaches have not been widely adopted. Here, we present techniques to increase throughput and reduce contamination alongside a thorough review of current best practices.

Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

While metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

Here, the authors use simulated quantitative gut microbial communities to benchmark the performance of 13 common data transformations in determining diversity as well as microbe-microbe and microbe-metadata associations, finding that quantitative approaches incorporating microbial load variation outperform computational strategies in downstream analyses, urging for a widespread adoption of quantitative approaches, or recommending specific computational transformations whenever determination of microbial load of samples is not feasible.

Microbiota functional activity biosensors for characterizing nutrient metabolism in vivo

Methods for measuring gut microbiota biochemical activities in vivo are needed to characterize its functional states in health and disease. To illustrate one approach, an arabinan-containing polysaccharide was isolated from pea fiber, its structure defined, and forward genetic and proteomic analyses used to compare its effects, versus unfractionated pea fiber and sugar beet arabinan, on a human gut bacterial strain consortium in gnotobiotic mice. We produced 'Microbiota Functional Activity Biosensors' (MFABs) consisting of glycans covalently linked to the surface of fluorescent paramagnetic microscopic glass beads. Three MFABs, each containing a unique glycan/fluorophore combination, were simultaneously orally gavaged into gnotobiotic mice, recovered from their intestines, and analyzed to directly quantify bacterial metabolism of structurally distinct arabinans in different human diet contexts. Colocalizing pea-fiber arabinan and another polysaccharide (glucomannan) on the bead surface enhanced in vivo degradation of glucomannan. MFABs represent a potentially versatile platform for developing new prebiotics and more nutritious foods.

Mining microbes for mental health: Determining the role of microbial metabolic pathways in human brain health and disease

There is increasing knowledge regarding the role of the microbiome in modulating the brain and behaviour. Indeed, the actions of microbial metabolites are key for appropriate gut-brain communication in humans. Among these metabolites, short-chain fatty acids, tryptophan, and bile acid metabolites/pathways show strong preclinical evidence for involvement in various aspects of brain function and behaviour. With the identification of neuroactive gut-brain modules, new predictive tools can be applied to existing datasets. We identified 278 studies relating to the human microbiota-gut-brain axis which included sequencing data. This spanned across psychiatric and neurological disorders with a small number also focused on normal behavioural development. With a consistent bioinformatics pipeline, thirty-five of these datasets were reanalysed from publicly available raw sequencing files and the remainder summarised and collated. Among the reanalysed studies, we uncovered evidence of disease-related alterations in microbial metabolic pathways in Alzheimer's Disease, schizophrenia, anxiety and depression. Amongst studies that could not be reanalysed, many sequencing and technical limitations hindered the discovery of specific biomarkers of microbes or metabolites conserved across studies. Future studies are warranted to confirm our findings. We also propose guidelines for future human microbiome analysis to increase reproducibility and consistency within the field.

Multi-kingdom ecological drivers of microbiota assembly in preterm infants

The gut microbiota of preterm infants develops predictably1-7, with pioneer species colonizing the gut after birth, followed by an ordered succession of microorganisms. The gut microbiota is vital to the health of preterm infants8,9, but the forces that shape these predictable dynamics of microbiome assembly are unknown. The environment, the host and interactions between microorganisms all potentially shape the dynamics of the microbiota, but in such a complex ecosystem, identifying the specific role of any individual factor is challenging10-14. Here we use multi-kingdom absolute abundance quantification, ecological modelling and experimental validation to address this challenge. We quantify the absolute dynamics of bacteria, fungi and archaea in a longitudinal cohort of 178 preterm infants. We uncover microbial blooms and extinctions, and show that there is an inverse correlation between bacterial and fungal loads in the infant gut. We infer computationally and demonstrate experimentally in vitro and in vivo that predictable assembly dynamics may be driven by directed, context-dependent interactions between specific microorganisms. Mirroring the dynamics of macroscopic ecosystems15-17, a late-arriving member of the microbiome, Klebsiella, exploits the pioneer microorganism, Staphylococcus, to gain a foothold within the gut. Notably, we find that interactions between different kingdoms can influence assembly, with a single fungal species-Candida albicans-inhibiting multiple dominant genera of gut bacteria. Our work reveals the centrality of simple microbe-microbe interactions in shaping host-associated microbiota, which is critical both for our understanding of microbiota ecology and for targeted microbiota interventions.

Conducting research on diet-microbiome interactions: A review of current challenges, essential methodological principles, and recommendations for best practice in study design

Diet is one of the strongest modulators of the gut microbiome. However, the complexity of the interactions between diet and the microbial community emphasises the need for a robust study design and continued methodological development. This review aims to summarise considerations for conducting high-quality diet-microbiome research, outline key challenges unique to the field, and provide advice for addressing these in a practical manner useful to dietitians, microbiologists, gastroenterologists and other diet-microbiome researchers. Searches of databases and references from relevant articles were conducted using the primary search terms 'diet', 'diet intervention', 'dietary analysis', 'microbiome' and 'microbiota', alone or in combination. Publications were considered relevant if they addressed methods for diet and/or microbiome research, or were a human study relevant to diet-microbiome interactions. Best-practice design in diet-microbiome research requires appropriate consideration of the study population and careful choice of trial design and data collection methodology. Ongoing challenges include the collection of dietary data that accurately reflects intake at a timescale relevant to microbial community structure and metabolism, measurement of nutrients in foods pertinent to microbes, improving ability to measure and understand microbial metabolic and functional properties, adequately powering studies, and the considered analysis of multivariate compositional datasets. Collaboration across the disciplines of nutrition science and microbiology is crucial for high-quality diet-microbiome research. Improvements in our understanding of the interaction between nutrient intake and microbial metabolism, as well as continued methodological innovation, will facilitate development of effective evidence-based personalised dietary treatments.

Metagenomic Quantification of Genes with Internal Standards

qPCR and metagenomics are central molecular techniques that have offered insights into biological processes for decades, from monitoring spatial and temporal gene dynamics to tracking ARGs or pathogens. Still needed is a tool that can quantify thousands of relevant genes in a sample as gene copies per sample mass or volume.

We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families.

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.

Zinc Supplementation Forms Influenced Zinc Absorption and Accumulation in Piglets

The study aimed at determining the effect of different zinc (Zn) supplementation forms on Zn accumulation, activities of Zn-containing enzymes, gene expression of metallothionein (MT), and Zn transporters in piglets. Eighteen piglets were randomly divided into three groups: (a) a basal diet supplemented with 150 mg/kg Zn from Zn methionine (Zn-Met) in the feed (Zn-Met group), (b) a basal diet supplemented with 150 mg/kg Zn from Zn sulfate (ZnSO₄) in the feed (ZnSO₄, _feed group), and (c) a basal diet supplemented with the same dose of Zn as in ZnSO4,_feed group but in water (ZnSO₄, _water group). The results showed that Zn-Met added in feed and ZnSO₄ dissolved in drinking water significantly improved (p < 0.05) the Zn concentration in liver and jejunum and the apparent digestibility of Zn in comparison with the ZnSO₄ added in feed. In addition, dietary Zn supplementation as Zn-Met significantly increased (p < 0.05) the activity of alkaline phosphatase (AKP) in the jejunum of piglets in comparison with the ZnSO₄, _feed group. Furthermore, the Zn-Met and ZnSO₄, _water groups showed an improved total superoxide dismutase activity (T-SOD) in the ileum as compared to the ZnSO₄, _feed group. Meanwhile, the qPCR and western blot results showed that Zn-Met and ZnSO₄ dissolved in drinking water increased the expression of MT in the jejunum in comparison with the ZnSO₄ added in the piglets' feed. However, different Zn supplementation forms had no effect on the mRNA expressions of Zip4 and ZnT1 transporters. In conclusion, Zn-Met added in feed and ZnSO₄ dissolved in drinking water had higher bioavailability in piglets.

Cyanobacterial blooms in wastewater treatment facilities: Significance and emerging monitoring strategies

Municipal wastewater treatment facilities (WWTFs) are prone to the proliferation of cyanobacterial species which thrive in stable, nutrient-rich environments. Dense cyanobacterial blooms frequently disrupt treatment processes and the supply of recycled water due to their production of extracellular polymeric substances, which hinder microfiltration, and toxins, which pose a health risk to end-users. A variety of methods are employed by water utilities for the identification and monitoring of cyanobacteria and their toxins in WWTFs, including microscopy, flow cytometry, ELISA, chemoanalytical methods, and more recently, molecular methods. Here we review the literature on the occurrence and significance of cyanobacterial blooms in WWTFs and discuss the pros and cons of the various strategies for monitoring these potentially hazardous events. Particular focus is directed towards next-generation metagenomic sequencing technologies for the development of site-specific cyanobacterial bloom management strategies. Long-term multi-omic observations will enable the identification of indicator species and the development of site-specific bloom dynamics models for the mitigation and management of cyanobacterial blooms in WWTFs. While emerging metagenomic tools could potentially provide deep insight into the diversity and flux of problematic cyanobacterial species in these systems, they should be considered a complement to, rather than a replacement of, quantitative chemoanalytical approaches.

Shrinkage improves estimation of microbial associations under different normalization methods

Estimation of statistical associations in microbial genomic survey count data is fundamental to microbiome research. Experimental limitations, including count compositionality, low sample sizes and technical variability, obstruct standard application of association measures and require data normalization prior to statistical estimation. Here, we investigate the interplay between data normalization, microbial association estimation and available sample size by leveraging the large-scale American Gut Project (AGP) survey data. We analyze the statistical properties of two prominent linear association estimators, correlation and proportionality, under different sample scenarios and data normalization schemes, including RNA-seq analysis workflows and log-ratio transformations. We show that shrinkage estimation, a standard statistical regularization technique, can universally improve the quality of taxon-taxon association estimates for microbiome data. We find that large-scale association patterns in the AGP data can be grouped into five normalization-dependent classes. Using microbial association network construction and clustering as downstream data analysis examples, we show that variance-stabilizing and log-ratio approaches enable the most taxonomically and structurally coherent estimates. Taken together, the findings from our reproducible analysis workflow have important implications for microbiome studies in multiple stages of analysis, particularly when only small sample sizes are available.

Effects of Low and High FODMAP Diets on Human Gastrointestinal Microbiota Composition in Adults with Intestinal Diseases: A Systematic Review

A diet high in non-digestible carbohydrates is known to promote health, in part through its effect on the gut microbiome. While substantially proven for healthy individuals, these effects are more ambiguous in subjects with intestinal diseases. At the same time, a diet low in these fermentable carbohydrates, the low FODMAP (acronym for Fermentable Oligo-, Di-, Mono-saccharides, And Polyols) diet, is gaining popularity as a treatment option for symptom relief in irritable bowel syndrome and inflammatory bowel disease. There are, however, several indications that this diet induces effects opposite to those of prebiotic supplementation, resulting in gut microbiome changes that might be detrimental. Here, we provide a systematic review of the effects of low and high FODMAP diets on human gastrointestinal microbiota composition in adults with intestinal diseases, through literature screening using the databases PubMed, Embase, and Web of Science. We summarize study findings on dietary impact in patients, including the effect on bacterial taxa and diversity. In general, similar to healthy subjects, restricting non-digestible carbohydrate intake in patients with intestinal diseases has opposite effects compared to prebiotic supplementation, causing a reduction in bifidobacteria and an increase in bacteria associated with dysbiosis. Future studies should focus on assessing whether the induced microbial changes persist over time and have adverse effects on long-term colonic health.

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.

Pathogenic Detection by Metagenomic Next-Generation Sequencing in Osteoarticular Infections

Objectives: To evaluate metagenomic next-generation sequencing (mNGS) as a diagnostic tool in detecting pathogens from osteoarticular infection (OAI) samples. Methods: 130 samples of joint fluid, sonicate fluid, and tissue were prospectively collected from 92 patients with OAI. The performance of mNGS and microbiology culture was compared pairwise. Results: The overall sensitivity of mNGS was 88.5% (115/130), significantly higher than that of microbiological culture, which had a sensitivity of 69.2% (90/130, p < 0.01). Sensitivity was significantly higher for joint fluid (mNGS: 86.7% vs. microbiology culture: 68.7%, p < 0.01) and sonicate fluid (mNGS: 100% vs. microbiology culture: 66.7%, p < 0.05) samples. mNGS detected 12 pathogenic strains undetected by microbiological culture. Additional pathogens detected by mNGS were Coagulase-negative Staphylococci, Gram-negative Bacillus, Streptococci, Anaerobe, non-tuberculosis mycobacterium, MTCP (p > 0.05), and Mycoplasma (OR = ∞, 95% confidence interval, 5.12-∞, p < 0.001). Additionally, sensitivity by mNGS was higher in antibiotic-treated samples compared to microbiological culture (89.7 vs. 61.5%, p < 0.01). Conclusions: mNGS is a robust diagnostic tool for pathogenic detection in samples from OAI patients, compared to routine cultures. The mNGS technique is particularly valuable to diagnose pathogens that are difficult to be cultured, or to test samples from patients previously treated with antibiotics.

Shining Light on Human Gut Bacteriophages

The human gut is a complex environment that contains a multitude of microorganisms that are collectively termed the microbiome. Multiple factors have a role to play in driving the composition of human gut bacterial communities either toward homeostasis or the instability that is associated with many disease states. One of the most important forces are likely to be bacteriophages, bacteria-infecting viruses that constitute by far the largest portion of the human gut virome. Despite this, bacteriophages (phages) are the one of the least studied residents of the gut. This is largely due to the challenges associated with studying these difficult to culture entities. Modern high throughput sequencing technologies have played an important role in improving our understanding of the human gut phageome but much of the generated sequencing data remains uncharacterised. Overcoming this requires database-independent bioinformatic pipelines and even those phages that are successfully characterized only provide limited insight into their associated biological properties, and thus most viral sequences have been characterized as “viral dark matter.” Fundamental to understanding the role of phages in shaping the human gut microbiome, and in turn perhaps influencing human health, is how they interact with their bacterial hosts. An essential aspect is the isolation of novel phage-bacteria host pairs by direct isolation through various screening methods, which can transform in silico phages into a biological reality. However, this is also beset with multiple challenges including culturing difficulties and the use of traditional methods, such as plaquing, which may bias which phage-host pairs that can be successfully isolated. Phage-bacteria interactions may be influenced by many aspects of complex human gut biology which can be difficult to reproduce under laboratory conditions. Here we discuss some of the main findings associated with the human gut phageome to date including composition, our understanding of phage-host interactions, particularly the observed persistence of virulent phages and their hosts, as well as factors that may influence these highly intricate relationships. We also discuss current methodologies and bottlenecks hindering progression in this field and identify potential steps that may be useful in overcoming these hurdles.

Combining whole-genome shotgun sequencing and rRNA gene amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, support the acquisition of nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of the 16S rRNA gene and/or the internal transcribed spacer (ITS) of rRNA genomic loci, which show the relative abundance of the microbes to each other. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S and eukaryotic ITS1 rRNA amplicon data from 176 of these samples. Shotgun data, which unlike the amplicon data capture the ratio of microbe to plant DNA, enable scaling of microbial read abundances to reflect the microbial load on the host. In a more cost-effective hybrid strategy, we show they also allow a similar scaling of amplicon data to overcome compositionality problems. Our wild plants were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. Microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. Critically, considering absolute microbial load led to fundamentally different conclusions about microbiome assembly and the interaction networks among major taxa.

Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on human milk microbiota at three months post-partum

BACKGROUND

Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, we systematically investigated the associations between these maternal factors in women ≥20 years and milk microbial composition and predicted functionality by V4-16S ribosomal RNA gene sequencing (NCT01405547;  https://clinicaltrials.gov/ct2/show/NCT01405547 ). Demographic data, weight, height, and a 3-h oral glucose tolerance test were gathered at 30 (95% CI: 25-33) weeks gestation, and milk samples were collected at 3 months post-partum (n = 113).

RESULTS

Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and milk microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk microbiota beta-diversity (Bray-Curtis R² = 0.037). Women with a pre-pregnancy BMI > 30 kg/m² (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61-8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43-0.90]) in their milk, compared to women with an overweight BMI (25.0-29.9 kg/m²) as assessed by multivariable Poisson regression. An increased incidence of Gemella was observed among mothers with gestational diabetes who had an overweight BMI versus healthy range BMI (5.96 [1.85-19.21]). An increased incidence of Gemella was also observed among mothers with impaired glucose tolerance with an obese BMI versus mothers with a healthy range BMI (4.04 [1.63-10.01]). An increased incidence of Brevundimonas (16.70 [5.99-46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that pre-pregnancy obesity was associated with an increased abundance of genes encoding for the biosynthesis of secondary metabolites pathway in milk (coefficient = 0.0024, P_FDR < 0.1).

CONCLUSIONS

Human milk has a diverse microbiota of which its diversity and differential abundance appear associated with maternal BMI, glucose tolerance status, mode of delivery, and ethnicity. Further research is warranted to determine whether this variability in the milk microbiota impacts colonization of the infant gut.

Thermus thermophilus DNA can be used as internal control for process monitoring of clinical metagenomic next-generation sequencing of urine samples

INTRODUCTION

Metagenomics is increasingly considered for clinical diagnostics. In order for this technology to become integrated in the clinical microbiology laboratory, process controls are required. Molecular diagnostic tests typically integrate an internal control (IC) to detect potential sources of variation and technical failure. However, few studies report on the integration of an IC in metagenomics.

AIM

We aimed to develop an easy-to-use IC method for the process control of library preparation and sequencing applied to metagenomics in clinical microbiology diagnostics using Thermus thermophilus DNA.

METHODOLOGY

DNA was extracted from urine samples and sequenced on the Ion Torrent Proton in the absence and presence of incremental concentrations (0.5-2-5%) of IC. Between aliquots of each sample, we compared the IC relative abundance (RA), and after in silico subtraction of IC reads, analysed microbial composition and the RA of pathogens. The optimal IC concentration was defined as the lowest concentration still detectable in all samples with the smallest impact on the microbial composition.

RESULTS

The RA of IC correlated linearly with the spiked IC concentration (r² = 0.99). IC added in a concentration of 0.5% of the total DNA concentration was detectable in all sample aliquots, regardless of human-bacterial DNA proportion, and after in silico removal gave the smallest difference in RA of pathogens compared to the sample aliquot sequenced in the absence of IC. The microbial composition in the presence and absence of IC was highly similar after in silico removal of IC reads (median BC-dissimilarity per sample: 0.059), provided samples had a mean of >10,000 bacterial reads.

CONCLUSION

T. thermophilus DNA at a percentage of 0.5% of the total DNA concentration was successfully applied for the process control of metagenomics of urine samples. We demonstrated negligible alterations in sample microbial composition after in silico subtraction of IC reads. This approach contributes toward implementation of metagenomics in the clinical microbiology laboratory.

Chinese Liquor Fermentation: Identification of Key Flavor-Producing Lactobacillus spp. by Quantitative Profiling with Indigenous Internal Standards

Identifying the functional microbes in spontaneous food fermentation is important for improving food quality. To identify the key flavor producers in Chinese liquor fermentation, we propose a novel quantitative microbiome profiling method that uses indigenous internal standards to normalize high-throughput amplicon sequencing results. We screened Lactobacillus acetotolerans and Lactobacillus jinshani as indigenous internal standards based on their high distribution frequencies and relative abundances. After determining the absolute abundance of indigenous internal standards using quantitative PCR with species-specific primers, the liquor-fermented bacterial community and its dynamics were better characterized by internal standards normalization. Based on quantitative microbiome profiling, we identified that Lactobacillus was a key flavor producer correlated with eight flavor compounds. Metatranscriptomic analysis indicated that Lactobacillus was active in transcribing genes involving the biosynthesis of flavor compounds and their precursors. This work has developed a novel and extensible absolute quantification method for microbiota that will alleviate concerns in the statistical analyses based on relative microbiome profiling, and shed insights into the function of Lactobacillus in food fermentation. It can potentially be applied to other microbial ecology studies.IMPORTANCE In this study, we developed a novel strategy using indigenous internal standards to normalize the high-throughput amplicon sequencing results. We chose two Lactobacillus species as indigenous internal standards and characterized the absolute abundance of the bacterial community. Further, we identified Lactobacillus as the key flavor producer using quantitative microbiome profiling combined with multivariate statistics and metatranscriptomic analysis. This work developed a novel strategy for absolute quantitative abundance analysis of microbiota and expanded our understanding of the role of Lactobacillus in food fermentation.

Protein Level and Infantile Diarrhea in a Postweaning Piglet Model

Infantile diarrhea is a serious public health problem around worldwide and results in millions of deaths each year. The levels and sources of dietary protein are potential sources of diarrhea, but the relationship between the pathogenesis causes of infantile diarrhea and protein intake remains poorly understood. Many studies have indicated that the key to understanding the relationship between the protein in the diet and the postweaning diarrhea of piglets is to explore the influences of protein sources and levels on the mammalian digestion system. The current study was designed to control diarrhea control by choosing different protein levels in the diet and aimed at providing efficient regulatory measures for infantile diarrhea by controlling the protein levels in diets using a postweaning piglets model. To avoid influences from other protein sources, casein was used as the only protein source in this study. Fourteen piglets (7.98 ± 0.14 kg, weaned at 28 d) were randomly allotted to two dietary treatments: a control group (Cont, containing 17% casein) and a high protein group (HP, containing 30% casein). The experiment lasted for two weeks and all animals were free to eat and drink water ad libitum. The diarrhea score (1 = normal; 3 = watery diarrhea) and growth performance were recorded daily. The results showed that the piglets in HP group had persistent diarrhea during the whole study, while no diarrhea was noticed in the control groups. Also, the feed intake and body weights were reduced in the HP groups compared with the other group (P < 0.05). The diarrhea-related mRNA abundances were analyzed by real-time PCR; the results showed that HP treatment markedly decreased the expression of aquaporin (AQP, P < 0.05) and the tight junction protein (P<0.05), but increased inflammatory cytokines (P < 0.01) than those in control group. In addition, the Adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway (P < 0.01) was inhibited in the HP group. Intestinal microbiota was tested by 16S sequencing, and we found that the HP group had a low diversity compared the other group. In conclusion, despite being highly digestible, a high casein diet induced postweaning diarrhea and reduced the growth performance of the postweaning piglets. Meanwhile, AQP, tight junction protein, and intestinal immune were compromised. Thus, the mechanism of how a highly digestible protein diet induces diarrhea might be associated with the AMPK signaling pathway and intestinal microbiome.

A quantitative sequencing framework for absolute abundance measurements of mucosal and lumenal microbial communities

A fundamental goal in microbiome studies is determining which microbes affect host physiology. Standard methods for determining changes in microbial taxa measure relative, rather than absolute abundances. Moreover, studies often analyze only stool, despite microbial diversity differing substantially among gastrointestinal (GI) locations. Here, we develop a quantitative framework to measure absolute abundances of individual bacterial taxa by combining the precision of digital PCR with the high-throughput nature of 16S rRNA gene amplicon sequencing. In a murine ketogenic-diet study, we compare microbial loads in lumenal and mucosal samples along the GI tract. Quantitative measurements of absolute (but not relative) abundances reveal decreases in total microbial loads on the ketogenic diet and enable us to determine the differential effects of diet on each taxon in stool and small-intestine mucosa samples. This rigorous quantitative microbial analysis framework, appropriate for diverse GI locations enables mapping microbial biogeography of the mammalian GI tract and more accurate analyses of changes in microbial taxa in microbiome studies.

Profiling of Oral Bacterial Communities

The profiling of bacterial communities by the sequencing of housekeeping genes such as that encoding the small subunit ribosomal RNA has revealed the extensive diversity of bacterial life on earth. Standard protocols have been developed and are widely used for this application, but individual habitats may require modification of methods. This review discusses the sequencing and analysis methods most appropriate for the study of the bacterial component of the human oral microbiota. If possible, DNA should be extracted from samples soon after collection. If samples have to be stored for practical reasons, precautions to avoid DNA degradation on freezing should be taken. A critical aspect of profiling oral bacterial communities is the choice of region of the 16S rRNA gene for sequencing. The V1-V2 region provides the best discrimination between species of the genus Streptococcus, the most common genus in the mouth and important in health and disease. The MiSeq platform is most commonly used for sequencing, but long-read technologies are now becoming available that should improve the resolution of analyses. There are a variety of well-established data analysis pipelines available, including mothur and QIIME, which identify sequence reads as phylotypes by comparing them to reference data sets or grouping them into operational taxonomic units. DADA2 has improved sequence error correction capabilities and resolves reads to unique variants. Two curated oral 16S rRNA databases are available: HOMD and CORE. Expert interpretation of community profiles is required, both to detect the presence of contaminating DNA, which is commonly present in the reagents used in analysis, and to differentiate oral and nonoral bacteria and determine the significance of findings. Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling via 16S rRNA sequence analysis remains a valuable technique for the characterization of oral bacterial populations.

A bird's-eye view of phylosymbiosis: weak signatures of phylosymbiosis among all 15 species of cranes

In numerous animal clades, the evolutionary history of host species drives patterns of gut microbial community structure, resulting in more divergent microbiota with increasing phylogenetic distance between hosts. This phenomenon, termed phylosymbiosis, has been observed in diverse evolutionary lineages, but has been difficult to detect in birds. Previous tests of phylosymbiosis among birds have been conducted using wild individuals, and thus interspecific differences in diet and environment may have masked a phylogenetic signal. Therefore, we tested for phylosymbiosis among all 15 species of cranes (family Gruidae) housed in the same captive environment and maintained on identical diets. 16S rRNA sequencing revealed that crane species harbour distinct gut microbiota. Overall, we detected marginally significant patterns of phylosymbiosis, the strength of which was increased when including the estimates of absolute microbial abundance (rather than relative abundance) derived from microbial densities determined by flow cytometry. Using this approach, we detected the statistically significant signatures of phylosymbiosis only after removing male cranes from our analysis, suggesting that using mixed-sex animal cohorts may prevent the detection of phylosymbiosis. Though weak compared with mammals (and especially insects), these results provide evidence of phylosymbiosis in birds. We discuss the potential differences between birds and mammals, such as transmission routes and host filtering, that may underlie the differences in the strength of phylosymbiosis.

A framework for assessing 16S rRNA marker-gene survey data analysis methods using mixtures

BACKGROUND

There are a variety of bioinformatic pipelines and downstream analysis methods for analyzing 16S rRNA marker-gene surveys. However, appropriate assessment datasets and metrics are needed as there is limited guidance to decide between available analysis methods. Mixtures of environmental samples are useful for assessing analysis methods as one can evaluate methods based on calculated expected values using unmixed sample measurements and the mixture design. Previous studies have used mixtures of environmental samples to assess other sequencing methods such as RNAseq. But no studies have used mixtures of environmental to assess 16S rRNA sequencing.

RESULTS

We developed a framework for assessing 16S rRNA sequencing analysis methods which utilizes a novel two-sample titration mixture dataset and metrics to evaluate qualitative and quantitative characteristics of count tables. Our qualitative assessment evaluates feature presence/absence exploiting features only present in unmixed samples or titrations by testing if random sampling can account for their observed relative abundance. Our quantitative assessment evaluates feature relative and differential abundance by comparing observed and expected values. We demonstrated the framework by evaluating count tables generated with three commonly used bioinformatic pipelines: (i) DADA2 a sequence inference method, (ii) Mothur a de novo clustering method, and (iii) QIIME an open-reference clustering method. The qualitative assessment results indicated that the majority of Mothur and QIIME features only present in unmixed samples or titrations were accounted for by random sampling alone, but this was not the case for DADA2 features. Combined with count table sparsity (proportion of zero-valued cells in a count table), these results indicate DADA2 has a higher false-negative rate whereas Mothur and QIIME have higher false-positive rates. The quantitative assessment results indicated the observed relative abundance and differential abundance values were consistent with expected values for all three pipelines.

CONCLUSIONS

We developed a novel framework for assessing 16S rRNA marker-gene survey methods and demonstrated the framework by evaluating count tables generated with three bioinformatic pipelines. This framework is a valuable community resource for assessing 16S rRNA marker-gene survey bioinformatic methods and will help scientists identify appropriate analysis methods for their marker-gene surveys.

Occurrence of leaf litter inhabiting myxomycetes from lowland forest patches of Northern and Central Vietnam

During the last years, much of the diversity studies of myxomycetes (plasmodial slime molds) have been concentrated mostly in the Southern region of Vietnam. Moreover, information on leaf litter inhabiting myxomycetes for the country is still in scarcity. Hence, this study aims to assess the occurrence and distribution of leaf litter inhabiting myxomycetes in different forest types in the subtropical northern and coastal tropical monsoon central part of the country. Samples of aerial and ground leaf litter that were used to prepare moist chamber cultures in the laboratory were collected in (1) Ba Vi National Park, Ha Noi, (2) Ho Nui Coc, Thai Nguyen, and (3) coastal forest patches in Da Nang. A total of 24 species belonging to 10 genera, wherein the majority of these myxomycete species appeared abundantly (11 species) is reported for this study. Based on species richness, Ha Noi harbored the highest number of myxomycete species. Leaf litter inhabiting myxomycete communities between aerial and ground substrates shared a high level of similarity based on their species composition and relative abundance. Highest level of similarity of leaf litter inhabiting myxomycete asssemblages is also reported between Ha Noi and Da Nang (CC = 0.78, PS = 0.56). This research study is the first step in understanding the complex myxomycete ecology of leaf inhabiting myxomycetes and would help filling now the large gap in one of the unexplored tropical areas of the world.

High-resolution sweep metagenomics using fast probabilistic inference

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

Insect herbivory reshapes a native leaf microbiome

Insect herbivory is pervasive in plant communities, but its impact on microbial plant colonizers is not well-studied in natural systems. By calibrating sequencing-based bacterial detection to absolute bacterial load, we find that the within-host abundance of most leaf microbiome (phyllosphere) taxa colonizing a native forb is amplified within leaves affected by insect herbivory. Herbivore-associated bacterial amplification reflects community-wide compositional shifts towards lower ecological diversity, but the extent and direction of such compositional shifts can be interpreted only by quantifying absolute abundance. Experimentally eliciting anti-herbivore defences reshaped within-host fitness ranks among Pseudomonas spp. field isolates and amplified a subset of putatively phytopathogenic P. syringae in a manner causally consistent with observed field-scale patterns. Herbivore damage was inversely correlated with plant reproductive success and was highly clustered across plants, which predicts tight co-clustering with putative phytopathogens across hosts. Insect herbivory may thus drive the epidemiology of plant-infecting bacteria as well as the structure of a native plant microbiome by generating variation in within-host bacterial fitness at multiple phylogenetic and spatial scales. This study emphasizes that 'non-focal' biotic interactions between hosts and other organisms in their ecological settings can be crucial drivers of the population and community dynamics of host-associated microbiomes.

Influences of a Prolific Gut Fungus (Zancudomyces culisetae) on Larval and Adult Mosquito (Aedes aegypti)-Associated Microbiota

Adult mosquitoes inherit a bacterial community from larvae via transstadial transmission, an understudied process that may influence host-microbe interactions. Microbes contribute to important host life history traits, and analyzing transmitted microbial communities, the interrelationship between larval and adult-associated microbiota, and factors influencing host-microbe relationships provides targets for research. During its larval stage, the yellow fever mosquito (Aedes aegypti) hosts the trichomycete gut fungus Zancudomyces culisetae, and fungal colonization coincides with environmental perturbations in the digestive tract microecosystem. Natural populations are differentially exposed to fungi, thereby potentially harboring distinct microbiota and experiencing disparate host-microbe interactions. This study's objectives were to characterize larval and initial adult microbiomes, investigate variation in diversity and distribution of microbial communities across individuals, and assess whether larval fungal colonization impacted microbiomes at these developmental stages. Laboratory-based fungal infestation assays, sequencing of 16S rRNA gene amplicons, and bacterial load quantification protocols revealed that initial adult microbiomes varied in diversity and distribution. Larval fungal colonization had downstream effects on initial adult microbiomes, significantly reducing microbial community variation, shifting relative abundances of certain bacterial families, and influencing transstadial transmission outcomes of particular genera. Further, abundances of several families consistently decreased in adults relative to levels in larvae, possibly reflecting impacts of host development on specific bacterial taxa. These findings demonstrated that a prolific gut fungus impacted mosquito-associated microbiota at two developmental stages in an insect connected with global human health.IMPORTANCE Mosquitoes are widespread vectors of numerous human pathogens and harbor microbiota known to affect host phenotypic traits. However, little research has directly investigated how bacterial communities associated with larvae and adults are connected. We characterized whole-body bacterial communities in mosquito larvae preceding pupation and in newly emerged adults, and investigated whether a significant biotic factor, fungal colonization of the larval hindgut, impacted these microbiomes. Results showed that fungal colonization reduced microbial community variation across individuals and differentially impacted the outcomes of transstadial transmission for certain bacterial genera, revealing downstream effects of the fungus on initial adult microbiomes. The importance of our research is in providing a thorough comparative analysis of whole-body microbiota harbored in larvae and adults of the yellow fever mosquito (Aedes aegypti) and in demonstrating the important role a widespread gut fungus played in a host-associated microbiome.