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Testing 21 different fecal DNA extraction protocols in multiple laboratories results in a standardized protocol with the potential to improve comparability across human gut microbiome studies. Technical variation in metagenomic analysis must be minimized to confidently assess the contributions of microbiota to human health. Here we tested 21 representative DNA extraction protocols on the same fecal samples and quantified differences in observed microbial community composition. We compared them with differences due to library preparation and sample storage, which we contrasted with observed biological variation within the same specimen or within an individual over time. We found that DNA extraction had the largest effect on the outcome of metagenomic analysis. To rank DNA extraction protocols, we considered resulting DNA quantity and quality, and we ascertained biases in estimates of community diversity and the ratio between Gram-positive and Gram-negative bacteria. We recommend a standardized DNA extraction method for human fecal samples, for which transferability across labs was established and which was further benchmarked using a mock community of known composition. Its adoption will improve comparability of human gut microbiome studies and facilitate meta-analyses.

Background Diverse microbial communities colonizing the intestine of fish contribute to their growth, digestion, nutrition, and immune function. We hypothesized that fecal samples representing the gut microbiota of rainbow trout could be associated with differential growth rates observed in fish breeding programs. If true, harnessing the functionality of this microbiota can improve the profitability of aquaculture. The first objective of this study was to test this hypothesis if gut microbiota is associated with fish growth rate (body weight). Four full-sibling families were stocked in the same tank and fed an identical diet. Two fast-growing and two slow-growing fish were selected from each family for 16S rRNA microbiota profiling. Microbiota diversity varies with different DNA extraction methods. The second objective of this study was to compare the effects of five commonly used DNA extraction methods on the microbiota profiling and to determine the most appropriate extraction method for this study. These methods were Promega-Maxwell, Phenol-chloroform, MO-BIO, Qiagen-Blood/Tissue, and Qiagen-Stool. Methods were compared according to DNA integrity, cost, feasibility and inter-sample variation based on non-metric multidimensional scaling ordination (nMDS) clusters. Results Differences in DNA extraction methods resulted in significant variation in the identification of bacteria that compose the gut microbiota. Promega-Maxwell had the lowest inter-sample variation and was therefore used for the subsequent analyses. Beta diversity of the bacterial communities showed significant variation between breeding families but not between the fast- and slow-growing fish. However, an indicator analysis determined that cellulose, amylose degrading and amino acid fermenting bacteria ( Clostridium , Leptotrichia, and Peptostreptococcus ) are indicator taxa of the fast-growing fish. In contrary, pathogenic bacteria ( Corynebacterium and Paeniclostridium ) were identified as indicator taxa for the slow-growing fish. Conclusion DNA extraction methodology should be carefully considered for accurate profiling of the gut microbiota. Although the microbiota was not significantly different between the fast- and slow-growing fish groups, some bacterial taxa with functional implications were indicative of fish growth rate. Further studies are warranted to explore how bacteria are transmitted and potential usage of the indicator bacteria of fast-growing fish for development of probiotics that may improve fish health and growth.

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.

Background Growing evidence has shown that the gut-renal connection and gut microbiota dysbiosis play a critical role in immunoglobulin A nephropathy (IgAN). However, the fecal microbiome profile in Chinese patients with IgAN remains unknown. A cross-sectional study was designed for the first time to investigate the fecal microbiota compositions in patients with primary IgAN in China and to evaluate the relationship between the fecal microbiome and IgAN clinical presentation. Methods Fecal samples were collected from 17 IgAN patients and 18 age-, sex-, and body mass index-matched healthy controls, and bacterial DNA was extracted for 16S ribosomal RNA gene sequencing targeting the V3-V4 region. Results Fecal samples from the IgAN patients and healthy controls showed differences in gut microbiota community richness and compositions. Compared to the healthy controls, IgAN patients at the phylum level had an increased abundance of Fusobacteria , but a decreased abundance of Synergistetes . The significantly increased genera in the IgAN group were Escherichia-Shigella, Hungatella, and Eggerthella, all of which possess pathogenic potential. Furthermore, the genus Escherichia-Shigella was negatively associated with the estimated glomerular filtration rate (eGFR) but was positively associated with the urinary albumin-to-creatinine ratio (uACR). However, the genus rectale_group was present in the IgAN group with a low abundance and was negatively associated with the uACR. Functional analysis disclosed that infection-related pathways were enriched in the IgAN group. Conclusions We demonstrate that gut microbiota dysbiosis occurs in patients with IgAN, and that changes in gut bacterial populations are closely related to IgAN clinical features, suggesting that certain specific gut microbiota may be a potential therapeutic target for IgAN.

A large number of tumor-related methylated genes have been suggested to be of diagnostic and prognostic values for CRC when analyzed in patients' stool samples; however, reported sensitivities and specificities have been inconsistent and widely varied. This meta-analysis was conducted to assess the detection accuracy of stool DNA methylation assay in CRC, early stages of CRC (advanced adenoma, non-advanced adenomas) and hyperplastic polyps, separately. We searched MEDLINE, Web of Science, Scopus and Google Scholar databases until May 1, 2016. From 469 publications obtained in the initial literature search, 38 studies were included in the final analysis involving 4867 individuals. The true positive, false positive, true negative and false negative of a stool-based DNA methylation biomarker using all single-gene tests considering a certain gene; regardless of a specific gene were pooled and studied in different categories. The sensitivity of different genes in detecting different stages of CRC ranged from 0% to 100% and the specificities ranged from 73% to 100%. Our results elucidated that SFRP1 and SFRP2 methylation possessed promising accuracy for detection of not only CRC (DOR: 31.67; 95%CI, 12.31-81.49 and DOR: 35.36; 95%CI, 18.71-66.84, respectively) but also the early stages of cancer, adenoma (DOR: 19.72; 95%CI, 6.68-58.25 and DOR: 13.20; 95%CI, 6.01-28.00, respectively). Besides, NDRG4 could be also considered as a significant diagnostic marker gene in CRC (DOR: 24.37; 95%CI, 10.11-58.73) and VIM in adenoma (DOR: 15.21; 95%CI, 2.72-85.10). In conclusion, stool DNA hypermethylation assay based on the candidate genes SFRP1, SFRP2, NDRG4 and VIM could offer potential diagnostic value for CRC based on the findings of this meta-analysis.

Tuberculosis (TB) is difficult to diagnose in children using molecular tests, because children have difficulty providing respiratory samples. Stool could replace sputum for diagnostic TB testing if adequate sample processing techniques were available. We developed a rapid method to process large volumes of stool for downstream testing by the Xpert MTB/RIF (Xpert) TB-detection assay. The method was tested and optimized on stool samples spiked with known numbers of M. tuberculosis colony forming units (CFU), and stools from M. tuberculosis-infected cynomolgus macaques (Macaca fascicularis). Performance was scored on number of positive Xpert tests, the cycle thresholds (Cts) of the Xpert sample-processing control (SPC), and the Cts of the M. tuberculosis-specific rpoB probes. The method was then validated on 20 confirmed TB cases and 20 controls in Durban, South Africa. The assay's analytical limit of detection was 1,000 CFU/g of stool. As much as one gram of spiked stool could be tested without showing increased PCR inhibition. In analytical spiking experiments using human stool, 1g samples provided the best sensitivity compared to smaller amounts of sample. However, in Macaques with TB, 0.6g stool samples performed better than either 0.2g or 1.2g samples. Testing the stool of pediatric TB suspects and controls suggested an assay sensitivity of 85% (95% CI 0.6-0.9) and 84% (95% CI 0.6-0.96) for 0.6g and 1.2g stool samples, respectively, and a specificity of 100% (95% CI 0.77-1) and 94% (95% CI 0.7-0.99), respectively. This novel approach may permit simple and rapid detection of TB using pediatric stool samples.

The results of coproscopical examinations in domestic animals and hedgehogs carried out as routine diagnostics in the years 2003 to 2012 at the Institute for Parasitology, University of Veterinary Medicine Hannover, Germany, are presented. Of 3475 horse faecal samples, 30.1% contained stages of strongyles and 1.3% eggs of Strongyloides westeri and Parascaris equorum , respectively. The most frequently observed parasite stages in 1416 cattle faecal samples were Eimeria oocysts (21.3%) and strongyle eggs or larvae (15.9%). Dictyocaulus viviparus larvae and Fasciola hepatica eggs were identified in 0.9 and 1.3% of samples. Of 574 bovine faecal samples analysed by carbol-fuchsin staining, 39.9% were positive for Cryptosporidium oocysts. Stages of strongyles were found in 52.4% of sheep ( n  = 374) and 44.9% of goat faeces ( n  = 98) and Eimeria oocysts in 41.4 and 32.7% of their faeces, respectively. Of 1848 pig faecal samples, 3.0% contained stages of strongyles, 1.6% eggs of Ascaris suum and 3.3% coccidian ( Eimeria or Cystoisospora spp.) oocysts. The most frequently detected helminth eggs in faecal samples of dogs ( n  = 2731) and cats ( n  = 903) were Toxocara spp. (2.8 and 3.9%, respectively). Cystoisospora oocysts were identified in 5.6% of dog and 2.4% of cat faeces. Furthermore, 0.7% of the cat samples were positive for small Toxoplasma gondii -like oocysts. The faecal samples of rabbits ( n  = 434) contained eggs of Passalurus ambiguus (3.0%), strongyles (1.8%) and Trichuris leporis (0.2%) as well as Eimeria oocysts (21.2%). The most abundant nematodes in the samples of hedgehogs ( n  = 205) were Capillaria spp. (39.5%) and Crenosoma striatum (26.8%); coccidian oocysts were found in 14.2% of the samples.

Background Here we investigated the influence of different stabilization and storage strategies on the quality and composition of the fecal microbial community. Namely, same-day isolated murine DNA was compared to samples stored for 1 month in air at ambient temperature, with or without preservative buffers (i.e. EDTA and lysis buffer), different temperatures (i.e. 4 °C, − 20 °C, and − 80 °C), and hypoxic conditions. Results Only storage in lysis buffer significantly reduced DNA content, yet without integrity loss. Storage in EDTA affected alpha diversity the most, which was also reflected in cluster separation. Distinct changes were also seen in the phyla and bacterial species abundance per storage strategy. Metabolic function analysis showed 22 pathways not significantly affected by storage conditions, whereas the tyrosine metabolism pathway was significantly changed in all strategies except by EDTA. Conclusion Each long-term storage strategy introduced a unique post-collection bias, which is important to take into account when interpreting data.

Much work has been dedicated to identifying members of the microbial gut community that have potential to augment the growth rate of agricultural animals including chickens. Here, we assessed any correlations between the fecal microbiome, a proxy for the gut microbiome, and feed efficiency or weight gain at the pedigree chicken level, the highest tier of the production process. Because selective breeding is conducted at the pedigree level, our aim was to determine if microbiome profiles could be used to predict feed conversion or weight gain in order to improve selective breeding. Using 16s rRNA amplicon sequencing, we profiled the microbiomes of high and low weight gain (WG) birds and good and poor feed efficient (FE) birds in two pedigree lineages of broiler chickens. We also aimed to understand the dynamics of the microbiome with respect to maturation. A time series experiment was conducted, where fecal samples of chickens were collected at 6 points of the rearing process and the microbiome of these samples profiled. We identified OTUs differences at different taxonomic levels in the fecal community between high and low performing birds within each genetic line, indicating a specificity of the microbial community profiles correlated to performance factors. Using machine-learning methods, we built a classification model that could predict feed conversion performance from the fecal microbial community. With respect to maturation, we found that the fecal microbiome is dynamic in early life but stabilizes after 3 weeks of age independent of lineage. Our results indicate that the fecal microbiome profile can be used to predict feed conversion, but not weight gain in these pedigree lines. From the time series experiments, it appears that these predictions can be evaluated as early as 20 days of age. Our data also indicates that there is a genetic factor for the microbiome profile.