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

Synthetic microbe communities provide internal reference standards for metagenome sequencing and analysis

The complexity of microbial communities, combined with technical biases in next-generation sequencing, pose a challenge to metagenomic analysis. Here, we develop a set of internal DNA standards, termed “sequins” (sequencing spike-ins), that together constitute a synthetic community of artificial microbial genomes. Sequins are added to environmental DNA samples prior to library preparation, and undergo concurrent sequencing with the accompanying sample. We validate the performance of sequins by comparison to mock microbial communities, and demonstrate their use in the analysis of real metagenome samples. We show how sequins can be used to measure fold change differences in the size and structure of accompanying microbial communities, and perform quantitative normalization between samples. We further illustrate how sequins can be used to benchmark and optimize new methods, including nanopore long-read sequencing technology. We provide metagenome sequins, along with associated data sets, protocols, and an accompanying software toolkit, as reference standards to aid in metagenomic studies.

Complex microbial communities pose a challenge to metagenomic analysis. Here the authors develop ‘sequins’, internal DNA standards that represent a synthetic community of artificial genomes.

Absolute quantitation of microbiota abundance in environmental samples

BACKGROUND

Microbial communities (microbiota) influence human and animal disease and immunity, geochemical nutrient cycling and plant productivity. Specific groups, including bacteria, archaea, eukaryotes or fungi, are amplified by PCR to assess the relative abundance of sub-groups (e.g. genera). However, neither the absolute abundance of sub-groups is revealed, nor can different amplicon families (i.e. OTUs derived from a specific pair of PCR primers such as bacterial 16S, eukaryotic 18S or fungi ITS) be compared. This prevents determination of the absolute abundance of a particular group and domain-level shifts in microbiota abundance can remain undetected.

RESULTS

We have developed absolute quantitation of amplicon families using synthetic chimeric DNA spikes. Synthetic spikes were added directly to environmental samples, co-isolated and PCR-amplified, allowing calculation of the absolute abundance of amplicon families (e.g. prokaryotic 16S, eukaryotic 18S and fungal ITS per unit mass of sample).

CONCLUSIONS

Spikes can be adapted to any amplicon-specific group including rhizobia from soils, Firmicutes and Bifidobacteria from human gut or Enterobacteriaceae from food samples. Crucially, using highly complex soil samples, we show that the absolute abundance of specific groups can remain steady or increase, even when their relative abundance decreases. Thus, without absolute quantitation, the underlying pathology, physiology and ecology of microbial groups may be masked by their relative abundance.

Reproducible protocols for metagenomic analysis of human faecal phageomes

BACKGROUND

Recent studies have demonstrated that the human gut is populated by complex, highly individual and stable communities of viruses, the majority of which are bacteriophages. While disease-specific alterations in the gut phageome have been observed in IBD, AIDS and acute malnutrition, the human gut phageome remains poorly characterised. One important obstacle in metagenomic studies of the human gut phageome is a high level of discrepancy between results obtained by different research groups. This is often due to the use of different protocols for enriching virus-like particles, nucleic acid purification and sequencing. The goal of the present study is to develop a relatively simple, reproducible and cost-efficient protocol for the extraction of viral nucleic acids from human faecal samples, suitable for high-throughput studies. We also analyse the effect of certain potential confounding factors, such as storage conditions, repeated freeze-thaw cycles, and operator bias on the resultant phageome profile. Additionally, spiking of faecal samples with an exogenous phage standard was employed to quantitatively analyse phageomes following metagenomic sequencing. Comparative analysis of phageome profiles to bacteriome profiles was also performed following 16S rRNA amplicon sequencing.

RESULTS

Faecal phageome profiles exhibit an overall greater individual specificity when compared to bacteriome profiles. The phageome and bacteriome both exhibited moderate change when stored at + 4 °C or room temperature. Phageome profiles were less impacted by multiple freeze-thaw cycles than bacteriome profiles, but there was a greater chance for operator effect in phageome processing. The successful spiking of faecal samples with exogenous bacteriophage demonstrated large variations in the total viral load between individual samples.

CONCLUSIONS

The faecal phageome sequencing protocol developed in this study provides a valuable additional view of the human gut microbiota that is complementary to 16S amplicon sequencing and/or metagenomic sequencing of total faecal DNA. The protocol was optimised for several confounding factors that are encountered while processing faecal samples, to reduce discrepancies observed within and between research groups studying the human gut phageome. Rapid storage, limited freeze-thaw cycling and spiking of faecal samples with an exogenous phage standard are recommended for optimum results.

The Madness of Microbiome: Attempting To Find Consensus "Best Practice" for 16S Microbiome Studies

The development and continuous improvement of high-throughput sequencing platforms have stimulated interest in the study of complex microbial communities. Currently, the most popular sequencing approach to study microbial community composition and dynamics is targeted 16S rRNA gene metabarcoding. To prepare samples for sequencing, there are a variety of processing steps, each with the potential to introduce bias at the data analysis stage. In this short review, key information from the literature pertaining to each processing step is described, and consequently, general recommendations for future 16S rRNA gene metabarcoding experiments are made.

Future Technologies

Microbiome analysis of environmental samples may represent the next frontier in environmental microbial forensics. Next-generation sequencing technologies significantly increased the available genetic data that could be used as evidentiary material. It is not clear, however, whether the microbiome can scale across institutions using forensic-based evidence due to the data resource requirements and the associated costs of maintaining these databases. A successful microbiome study is impacted by the quality of the information gathered and the steps in sample processing and data analysis. To ascertain the validity of methods and the results obtained, there needs to be a stringent procedure to validate the methods and ensure that the results are comparable and reproducible, not only within the laboratory but also between laboratories conducting similar research. Of primary importance for meaningful microbiome studies is an experimental design that leads to carefully executed, controlled, and reproducible studies. The microbiome literature contains a fair share of anecdotal descriptions of microbial community composition and "diagnostic" relative abundance of the taxa therein. These studies are now being supplemented by experimental designs that feature repeated measurements, error estimates, correlations of microbiota with covariates, and increasingly sophisticated statistical tests that enhance the robustness of data analysis and study conclusions. It is imperative to be careful, especially when carrying out attribution studies, to be fully aware of the possible biases included in a specific sample being analyzed.

Definitions and Historical Perspectives in Environmental Forensics

Environmental forensics is a tool that uses chemical, physical, and statistical techniques to investigate contaminants in the environment as a means to determine attribution for legal purposes. Environmental microbiology is a branch of science that has benefited from the use of metagenomics. The term microbial forensics, which includes nucleic acid sequencing methods, is now used to investigate the sources of microorganisms for attribution purposes as well. Environmental microbial forensics can fully address the questions that must be answered for attribution of causation and subsequent remedial actions within a reasonably short time frame. Although sensu stricto forensics refers to obtaining scientific evidence to be presented during legal proceedings, the term sensu lato is used as a description of the procedures used to reconstruct previous events, such as contamination. The term microbial forensics was first used to describe a forensic science approach for attribution purposes, specifically for bioterror as a purposeful release of pathogen microorganisms, but it also especially refers to investigations on the inadvertent or accidental release of pathogenic agents. However, microbial forensics can be used to determine the source of a microorganism or a group of microorganisms, regardless of whether they are pathogenic or not. Microbial forensics has limitations, but it should be used as part of a toolbox of methods to be relied upon when doing forensic studies. Environmental microbial forensics can only benefit from the development of new methods, and we already are experiencing a paradigm change in terms of approaches to the forensic sciences.

Genome watch: Keeping tally in the microbiome

This month's Genome Watch highlights how the development of new approaches for quantifying the human microbiome may pave the way for a better understanding of microbial shifts in the context of human health and disease.

'TIME': A Web Application for Obtaining Insights into Microbial Ecology Using Longitudinal Microbiome Data

Realization of the importance of microbiome studies, coupled with the decreasing sequencing cost, has led to the exponential growth of microbiome data. A number of these microbiome studies have focused on understanding changes in the microbial community over time. Such longitudinal microbiome studies have the potential to offer unique insights pertaining to the microbial social networks as well as their responses to perturbations. In this communication, we introduce a web based framework called 'TIME' (Temporal Insights into Microbial Ecology'), developed specifically to obtain meaningful insights from microbiome time series data. The TIME web-server is designed to accept a wide range of popular formats as input with options to preprocess and filter the data. Multiple samples, defined by a series of longitudinal time points along with their metadata information, can be compared in order to interactively visualize the temporal variations. In addition to standard microbiome data analytics, the web server implements popular time series analysis methods like Dynamic time warping, Granger causality and Dickey Fuller test to generate interactive layouts for facilitating easy biological inferences. Apart from this, a new metric for comparing metagenomic time series data has been introduced to effectively visualize the similarities/differences in the trends of the resident microbial groups. Augmenting the visualizations with the stationarity information pertaining to the microbial groups is utilized to predict the microbial competition as well as community structure. Additionally, the 'causality graph analysis' module incorporated in TIME allows predicting taxa that might have a higher influence on community structure in different conditions. TIME also allows users to easily identify potential taxonomic markers from a longitudinal microbiome analysis. We illustrate the utility of the web-server features on a few published time series microbiome data and demonstrate the ease with which it can be used to perform complex analysis.

Maintenance of Distal Intestinal Structure in the Face of Prolonged Fasting: A Comparative Examination of Species From Five Vertebrate Classes

It was recently shown that fasting alters the composition of microbial communities residing in the distal intestinal tract of animals representing five classes of vertebrates [i.e., fishes (tilapia), amphibians (toads), reptiles (leopard geckos), birds (quail), and mammals (mice)]. In this study, we tested the hypothesis that the extent of tissue reorganization in the fasted distal intestine was correlated with the observed changes in enteric microbial diversity. Segments of intestine adjacent to those used for the microbiota study were examined histologically to quantify cross-sectional and mucosal surface areas and thicknesses of mucosa, submucosa, and tunica muscularis. We found no fasting-induced differences in the morphology of distal intestines of the mice (3 days), quail (7 days), or geckos (28 days). The toads, which exhibited a general increase in phylogenetic diversity of their enteric microbiota with fasting, also exhibited reduced mucosal circumference at 14 and 21 days of fasting. Tilapia showed increased phylogenetic diversity of their enteric microbiota, and showed a thickened tunica muscularis at 21 days of fasting; but this morphological change was not related to microbial diversity or absorptive surface area, and thus, is unlikely to functionally match the changes in their microbiome. Given that fasting caused significant increases and reductions in the enteric microbial diversity of mice and quail, respectively, but no detectable changes in distal intestine morphology, we conclude that reorganization is not the primary factor shaping changes in microbial diversity within the fasted colon, and the observed modest structural changes are more related to the fasted state. Anat Rec, 300:2208-2219, 2017. © 2017 Wiley Periodicals, Inc.

Quantitative microbiome profiling links gut community variation to microbial load

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host-microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn's disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling).

Maternal microbiomes in preterm birth: Recent progress and analytical pipelines

Worldwide, 10% of babies are born preterm, defined as birth before 37 weeks' gestation. We have had little success in developing strategies to prevent preterm births, the majority of which are due to infection or are idiopathic. An emerging hypothesis is that the maternal microbiome-the bacteria that inhabit the mother's body and play vital functions in normal health-contributes to the etiology of preterm birth. Here, we highlight the latest data revealing correlations between preterm birth and maternal intestinal, vaginal, cervical, and placental microbiomes. Additionally, we describe the most commonly used comparative microbiome analysis methods and highlight important issues to consider when conducting such studies.

Resolving Species Level Changes in a Representative Soil Bacterial Community Using Microfluidic Quantitative PCR

Rapid advances in genome sequencing technologies enable determination of relative bacterial abundances and community composition, yet, changes at the species level remain difficult to detect despite importance for certain ecological inferences. We present a method for extraction and direct quantification of species composition of a predefined multispecies bacterial community using microfluidic-based quantitative real-time PCR (qPCR). We employ a nested PCR approach based on universal 16S rRNA gene pre-amplification followed by detection and quantification of absolute abundance of bacterial species using microfluidic array of parallel singleplex qPCR reactions. Present microfluidic qPCR supports 2,304 simultaneous reactions on a single chip, while automatic distribution of samples and reactants minimizes pipetting errors and technical variations. The utility of the method is illustrated using a synthetic soil bacterial community grown in two contrasting environments – sand microcosms and batch cultures. The protocol entails extraction of total nucleic acid, preparation of genomic DNA, and steps for qPCR assessment of bacterial community composition. This method provides specific and sensitive quantification of bacterial species requiring only 2 ng of community DNA. Optimized extraction protocol and preamplification step allow for rapid, quantitative, and simultaneous detection of candidate species with high throughput. The proposed method offers a simple and accurate alternative to present sequencing methods especially when absolute values of species abundance are required. Quantification of changes at the species level contributes to the mechanistic understanding of the roles of particular species in a bacterial community functioning.

Effects of Long-Term Protein Restriction on Meat Quality, Muscle Amino Acids, and Amino Acid Transporters in Pigs

This study aimed to investigate the long-term effects of protein restriction from piglets to finishing pigs for 16 weeks on meat quality, muscle amino acids, and amino acid transporters. Thirty-nine piglets were randomly divided into three groups: a control (20-18-16% crude protein, CP) and two protein restricted groups (17-15-13% CP and 14-12-10% CP). The results showed that severe protein restriction (14-12-10% CP) inhibited feed intake and body weight, while moderate protein restriction (17-15-13% CP) had little effect on growth performance in pigs. Meat quality (i.e., pH, color traits, marbling, water-holding capacity, and shearing force) were tested, and the results exhibited that 14-12-10% CP treatment markedly improved muscle marbling score and increased yellowness (b*). pH value (45 min) was significantly higher in 17-15-13% CP group than that in other groups. In addition, protein restriction reduced muscle histone, arginine, valine, and isoleucine abundances and enhanced glycine and lysine concentrations compared with the control group, while the RT-PCR results showed that protein restriction downregulated amino acids transporters. Mechanistic target of rapamycin (mTOR) signaling pathway was inactivated in the moderate protein restricted group (17-15-13% CP), while severe protein restriction with dietary 14-12-10% CP markedly enhanced mTOR phosphorylation. In conclusion, long-term protein restriction affected meat quality and muscle amino acid metabolism in pigs, which might be associated with mTOR signaling pathway.

Soil bacterial quantification approaches coupling with relative abundances reflecting the changes of taxa

Understanding the abundance change of certain bacterial taxa is quite important for the study of soil microbiology. However, the observed differences of relative abundances by high-throughput techniques may not accurately reflect those of the actual taxon abundances. This study investigated whether soil microbial abundances coupling with microbial quantities can be more informative in describing the microbial population distribution under different locations. We analyzed relative abundances of the major species in soil microbial communities from Beijing and Tibet grasslands by using 16 S rRNA high-throughput sequencing technique, and quantified the absolute bacterial cell numbers directly or indirectly by multiple culture-independent measurements, including adenosine tri-phosphate (ATP), flow cytometry (FCM), quantitative real-time PCR (qPCR), phospholipid fatty acids (PLFA) and microbial biomass Carbon (MBC). By comparison of the relative abundance and the estimated absolute abundances (EAA) of the major components in soil microbial communities, several dominant phyla, including Actinobacteria, Bacteroidetes, Verrucomicrobia, Chloroflexi, Gemmatimonates and Planctomycetes, showed significantly different trends. These results indicated that the change in EAA might be more informative in describing the dynamics of a population in a community. Further studies of soil microbes should combine the quantification and relative abundances of the microbial communities for the comparisons among various locations.

Novel micelle PCR-based method for accurate, sensitive and quantitative microbiota profiling

In the last decade, many researchers have embraced 16S rRNA gene sequencing techniques, which has led to a wealth of publications and documented differences in the composition of microbial communities derived from many different ecosystems. However, comparison between different microbiota studies is currently very difficult due to the lack of a standardized 16S rRNA gene sequencing protocol. Here we report on a novel approach employing micelle PCR (micPCR) in combination with an internal calibrator that allows for standardization of microbiota profiles via their absolute abundances. The addition of an internal calibrator allows the researcher to express the resulting operational taxonomic units (OTUs) as a measure of 16S rRNA gene copies by correcting the number of sequences of each individual OTU in a sample for efficiency differences in the NGS process. Additionally, accurate quantification of OTUs obtained from negative extraction control samples allows for the subtraction of contaminating bacterial DNA derived from the laboratory environment or chemicals/reagents used. Using equimolar synthetic microbial community samples and low biomass clinical samples, we demonstrate that the calibrated micPCR/NGS methodology possess a much higher precision and a lower limit of detection compared with traditional PCR/NGS, resulting in more accurate microbiota profiles suitable for multi-study comparison.

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing

High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible identity to known nucleotide sequences, permitting unambiguous identification of spike-in sequences in 16S-seq read data from any microbiome sample. Using defined mock communities and environmental microbiota, we characterized the performance of the spike-in standards and demonstrated their utility for evaluating data quality on a per-sample basis. Further, we showed that staggered spike-in mixtures added at the point of DNA extraction enable concurrent estimation of absolute microbial abundances suitable for comparative analysis. Results also underscored that template-specific Illumina sequencing artifacts may lead to biases in the perceived abundance of certain taxa. Taken together, the spike-in standards represent a novel bioanalytical tool that can substantially improve 16S-seq-based microbiome studies by enabling comprehensive quality control along with absolute quantification.