Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium.

Microbiome research has experienced a surge of interest in recent years due to the advances and reduced cost of next-generation sequencing technology. The production of high quality and comparable data is dependent on proper sample collection and storage and should be standardized as far as possible. However, this becomes challenging when samples are collected in the field, especially in resource-limited settings. We investigated the impact of different stool storage methods common to the TB-CHAMP clinical trial on the microbial communities in stool. Ten stool samples were subjected to DNA extraction after 48-hour storage at -80°C, room temperature and in a cooler-box, as well as immediate DNA extraction. Three stool DNA extraction kits were evaluated based on DNA yield and quality. Quantitative PCR was performed to determine the relative abundance of the two major gut phyla Bacteroidetes and Firmicutes, and other representative microbial groups. The bacterial populations in the frozen group closely resembled the immediate extraction group, supporting previous findings that storage at -80°C is equivalent to the gold standard of immediate DNA extraction. More variation was seen in the room temperature and cooler-box groups, which may be due to the growth temperature preferences of certain bacterial populations. However, for most bacterial populations, no significant differences were found between the storage groups. As seen in other microbiome studies, the variation between participant samples was greater than that related to differences in storage. We determined that the risk of introducing bias to microbial community profiling through differences in storage will likely be minimal in our setting.

Microbiome research has experienced a surge of interest in recent years due to the advances and reduced cost of next-generation sequencing technology. The production of high quality and comparable data is dependent on proper sample collection and storage and should be standardized as far as possible. However, this becomes challenging when samples are collected in the field, especially in resource-limited settings. We investigated the impact of different stool storage methods common to the TB-CHAMP clinical trial on the microbial communities in stool. Ten stool samples were subjected to DNA extraction after 48-hour storage at -80°C, room temperature and in a cooler-box, as well as immediate DNA extraction. Three stool DNA extraction kits were evaluated based on DNA yield and quality. Quantitative PCR was performed to determine the relative abundance of the two major gut phyla Bacteroidetes and Firmicutes, and other representative microbial groups. The bacterial populations in the frozen group closely resembled the immediate extraction group, supporting previous findings that storage at -80°C is equivalent to the gold standard of immediate DNA extraction. More variation was seen in the room temperature and cooler-box groups, which may be due to the growth temperature preferences of certain bacterial populations. However, for most bacterial populations, no significant differences were found between the storage groups. As seen in other microbiome studies, the variation between participant samples was greater than that related to differences in storage. We determined that the risk of introducing bias to microbial community profiling through differences in storage will likely be minimal in our setting.

The human microbial communities are associated with many human diseases such as obesity, diabetes and inflammatory bowel disease. High-throughput sequencing technology has been widely used to quantify the microbial composition in order to understand its impacts on human health. Longitudinal measurements of microbial communities are commonly obtained in many microbiome studies. A key question in such microbiome studies is to identify the microbes that are associated with clinical outcomes or environmental factors. However, microbiome compositional data are highly skewed, bounded in [0,1), and often sparse with many zeros. In addition, the observations from repeated measures in longitudinal studies are correlated. A method that takes into account these features is needed for association analysis in longitudinal microbiome data. In this paper, we propose a two-part zero-inflated Beta regression model with random effects (ZIBR) for testing the association between microbial abundance and clinical covariates for longitudinal microbiome data. The model includes a logistic regression component to model presence/absence of a microbe in the samples and a Beta regression component to model non-zero microbial abundance, where each component includes a random effect to account for the correlations among the repeated measurements on the same subject. Both simulation studies and the application to real microbiome data have shown that ZIBR model outperformed the previously used methods. The method provides a useful tool for identifying the relevant taxa based on longitudinal or repeated measures in microbiome research. https://github.com/chvlyl/ZIBR CONTACT: hongzhe@upenn.edu.

Research on the human microbiome has become one of the most frequently published and highly cited areas in science. In parallel, environmental DNA (eDNA) and RNA (eRNA) microbiome studies have expanded rapidly, often using similar technical workflows. Numerous studies optimizing these workflows have demonstrated that nucleic acid purification can significantly influence bacterial metagenomic outcomes. Although this issue is widely acknowledged and efforts are often made to ensure workflow consistency, such protocol standardization may obscure a deeper problem. Specifically, even when protocols are consistent, the resulting data is unlikely to reflect the true microbial community. This systemic bias, herein described as The Great Microbiome Extraction Anomaly , refers to the widespread distortion of observed microbial community composition caused by variation in nucleic acid extraction efficiencies across microbial nucleic acid states, species biology, and specimen composition. The term draws inspiration from The Great Plate Count Anomaly , a long‐recognized discrepancy between observable and cultivable microbial diversity. The Great Microbiome Extraction Anomaly presents a parallel methodological challenge which, like the original, will likely require novel technological innovation to resolve, as to date, no current protocol has achieved truly unbiased microbial DNA recovery. Currently, this limitation can only be addressed with carefully considered analytical controls that enable transparent reporting of microbial DNA recovery biases. However, the rate of control use in microbiome research remains very low. This review examines the evidence for nucleic acid state, microbe biology, and specimen‐specific nucleic acid extraction efficiency biases specifically within eDNA and eRNA microbiome workflows, while citing evidence of extraction bias from human microbiome and molecular diagnostic research to demonstrate the broader constraints underlying differential microbial nucleic acid recovery. In addition, this review evaluates the extent to which controls are implemented in microbiome research, outlines explicit examples of analytical controls that are essential for inclusion in microbiome research, and argues that implementing these robust analytical control strategies, especially the use of positive controls, is essential to detect and mitigate the biases of The Great Microbiome Extraction Anomaly .

Development and application of functional gene arrays for microbial community analysis

Exploring efficient methods to enhance leaching efficiency is critical for bioleaching technology to deal with sulfide concentrate. In our study, a novel artificial microbial community was established to augment the bioleaching efficiency and recovery of copper (Cu) and zinc (Zn). The optimum parameters in bioleaching experiments were explored according to compare a series of conditions from gradient experiments: the pH value was 1.2, temperature was 45 °C, and rotation speed was 160 r/min, which were different with pure microorganism growth conditions. Under optimal conditions, the result of recovery for Cu and Zn indicated that the average leaching rate reached to 80% and 100% respectively, which almost increased 1.8 times and 1.2 times more than control (aseptic condition) group. Therefore, this method of Cu and Zn recovery using a new-type artificial microbial community is expected to be an environmentally-friendly and efficient bioleaching technology solution, which has the potential of large-field engineering application in the future.

Both the host microbiome and the microbiome of the built environment can have profound impacts on human health. While prior studies have suggested that the variability introduced by DNA extraction method is less than typical biologic variation, most studies have focused on 16S rRNA amplicon sequencing or on high biomass fecal samples. Shotgun metagenomic sequencing provides advantages over amplicon sequencing for surveying the microbiome, but is a challenge to perform in lower microbial biomass samples with high human DNA content such as sputum or vacuumed dust. Here we systematically evaluate the impact of four different extraction methods (phenol:choloroform, and three high-throughput kit-based approaches, the Promega Maxwell gDNA, Qiagen MagAttract PowerSoil DNA, and ZymoBIOMICS 96 MagBead). We report the variation in microbial community structure and predicted microbial function assessed by shotgun metagenomics sequencing in human stool, sputum, and vacuumed dust obtained from ongoing cohort studies or clinical trials. The same beadbeating protocol was used for all samples to focus our evaluation on the impact of kit chemistries on sequencing results. DNA yield was overall highest in the phenol:choloroform and Promega approaches. Only the phenol:choloroform approach showed evidence of contamination in negative controls. Bias was evaluated using mock community controls, and was noted across all extraction methods, although Promega exhibited the least amount of bias. The extraction method did not impact the proportion of human reads, although stool had the lowest proportion of human reads (0.1%) as compared to dust (44.1%) and sputum (80%). We calculated Bray-Curtis dissimilarity and Aitchison distances to evaluate the impact of extraction method on microbial community structure by sample type. Extraction method had the lowest impact in stool (extraction method responsible for 3.0–3.9% of the variability), the most impact in vacuumed dust (12–16% of the variability) and intermediate values for sputum (9.2–12% variability). Similar differences were noted when evaluating microbial community function. Our results will inform investigators planning microbiome studies using diverse sample types in large clinical studies. A consistent DNA extraction approach across all sample types is recommended, particularly with lower microbial biomass samples that are more heavily influenced by extraction method.

Succession mechanism of microbial community with high species diversity in nutrient-deficient environments with low-dose ionizing radiation

This study used an artificial microbial community with four known moderately thermophilic acidophiles (three bacteria including Acidithiobacillus caldus S1, Sulfobacillus thermosulfidooxidans ST and Leptospirillum ferriphilum YSK, and one archaea, Ferroplasma thermophilum L1) to explore the variation of microbial community structure, composition, dynamics and function (e.g., copper extraction efficiency) in chalcopyrite bioleaching (C) systems with additions of pyrite (CP) or sphalerite (CS). The community compositions and dynamics in the solution and on the ore surface were investigated by real-time quantitative PCR (qPCR). The results showed that the addition of pyrite or sphalerite changed the microbial community composition and dynamics dramatically during the chalcopyrite bioleaching process. For example, A. caldus (above 60%) was the dominant species at the initial stage in three groups, and at the middle stage, still dominated C group (above 70%), but it was replaced by L. ferriphilum (above 60%) in CP and CS groups; at the final stage, L. ferriphilum dominated C group, while F. thermophilum dominated CP group on the ore surface. Furthermore, the additions of pyrite or sphalerite both made the increase of redox potential (ORP) and the concentrations of Fe3+ and H+, which would affect the microbial community compositions and copper extraction efficiency. Additionally, pyrite could enhance copper extraction efficiency (e.g., improving around 13.2% on day 6) during chalcopyrite bioleaching; on the contrary, sphalerite restrained it.

Extraction of zinc from sphalerite using bio-hydrometallurgical technologies has become more and more popular. This study used an artificial microbial community with five known microorganisms to examine the relationship among microbial diversity, composition, and function (e.g., zinc extraction rates) in sphalerite bioleaching systems with additional pyrite (SP), chalcopyrite (SC), or both (SPC). Real-time quantitative PCR (qPCR) analysis showed that additional pyrite or chalcopyrite changed the microbial community composition dramatically during the sphalerite bioleaching process. Shannon diversity index, compared with Sphalerite (0.109), showed an increase in SP (0.508), SC (0.536) and SPC (0.289) on day 30, and zinc extraction rates were enhanced by about 12.1%, 4.3% and 9.47%, respectively. Also, additional pyrite or chalcopyrite made ORP and the concentrations of Fe3+, Zn2+ and H+ increased, which were the main factors on shaping the microbial community composition by Mantel test analysis. We developed a unitary model, showing that additional pyrite or chalcopyrite increased the microbial community diversity.

Effect of diurnal temperature range on bioleaching of sulfide ore by an artificial microbial consortium

An artificial microbial community consisted of Ketogulonicigenium vulgare and Bacillus megaterium has been used in industry to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. During the mix culture fermentation process, sporulation and cell lysis of B. megaterium can be observed. In order to investigate how these phenomena correlate with 2-KGA production, and to explore how two species interact with each other during the fermentation process, an integrated time-series proteomic and metabolomic analysis was applied to the system. The study quantitatively identified approximate 100 metabolites and 258 proteins. Principal Component Analysis of all the metabolites identified showed that glutamic acid, 5-oxo-proline, L-sorbose, 2-KGA, 2, 6-dipicolinic acid and tyrosine were potential biomarkers to distinguish the different time-series samples. Interestingly, most of these metabolites were closely correlated with the sporulation process of B. megaterium. Together with several sporulation-relevant proteins identified, the results pointed to the possibility that Bacillus sporulation process might be important part of the microbial interaction. After sporulation, cell lysis of B. megaterium was observed in the co-culture system. The proteomic results showed that proteins combating against intracellular reactive oxygen stress (ROS), and proteins involved in pentose phosphate pathway, L-sorbose pathway, tricarboxylic acid cycle and amino acids metabolism were up-regulated when the cell lysis of B. megaterium occurred. The cell lysis might supply purine substrates needed for K. vulgare growth. These discoveries showed B. megaterium provided key elements necessary for K. vulgare to grow better and produce more 2-KGA. The study represents the first attempt to decipher 2-KGA-producing microbial communities using quantitative systems biology analysis.

This study was completed on an artificial microbial community (consortium) including three microorganisms of dairy interest, two mesophilic (Lactococcus lactis subsp. cremoris and Geotrichum candidum) and one thermophilic (Lactobacillus delbrueckii subsp. bulgaricus). The aim of this work was to study the stress responses of the food microbial consortium subjected to a freeze–thaw challenge (–20°C, 10 min / +25°C, 3 min) combined with physiological cryoadaptation (cryotolerance). Our results show that induction of cryotolerance by near-freezing temperature pretreatment of G. candidum and L. cremoris within the microbial community is similar to the one obtained with pure cultures. However, cryotolerance of L. bulgaricus was only induced within the consortium in milk. An interspecies cryoprotection was thus identified. This acquisition is correlated with the cell envelope extracts of G. candidum and/or the extracellular fractions of the two adapted mesophilic microorganisms. Therefore, in our experimental c...

Microbial diversity formation and maintenance due to temporal niche differentiation caused by low-dose ionizing radiation in oligotrophic environments

This paper shows that for microbial communities, "fences make good neighbors." Communities of soil microorganisms perform critical functions: controlling climate, enhancing crop production, and remediation of environmental contamination. Microbial communities in the oral cavity and the gut are of high biomedical interest. Understanding and harnessing the function of these communities is difficult: artificial microbial communities in the laboratory become unstable because of "winner-takes-all" competition among species. We constructed a community of three different species of wild-type soil bacteria with syntrophic interactions using a microfluidic device to control spatial structure and chemical communication. We found that defined microscale spatial structure is both necessary and sufficient for the stable coexistence of interacting bacterial species in the synthetic community. A mathematical model describes how spatial structure can balance the competition and positive interactions within the community, even when the rates of production and consumption of nutrients by species are mismatched, by exploiting nonlinearities of these processes. These findings provide experimental and modeling evidence for a class of communities that require microscale spatial structure for stability, and these results predict that controlling spatial structure may enable harnessing the function of natural and synthetic multispecies communities in the laboratory.