Characterization of the fecal bacteria communities of forage-fed horses by pyrosequencing of 16S rRNA V4 gene amplicons

The diversity of the equine fecal bacterial community was evaluated using pyrosequencing of 16S rRNA gene amplicons. Fecal samples were obtained from horses fed cool-season grass hay. Fecal bacteria were characterized by amplifying the V4 region of bacterial 16S rRNA gene. Of 5898 mean unique sequences, a mean of 1510 operational taxonomic units were identified in the four fecal samples. Equine fecal bacterial richness was higher than that reported in humans, but lower than that reported in either cattle feces or soil. Bacterial classified sequences were assigned to 16 phyla, of which 10 were present in all samples. The largest number of reads belonged to Firmicutes (43.7% of total bacterial sequences), Verrucomicrobia (4.1%), Proteobacteria (3.8%), and Bacteroidetes (3.7%). The less abundant Actinobacteria, Cyanobacteria, and TM7 phyla presented here have not been previously described in the gut contents or feces of horses. Unclassified sequences represented 38.1% of total bacterial sequences; therefore, the equine fecal microbiome diversity is likely greater than that described. This is the first study to characterize the fecal bacterial community in horses by the use of 16S rRNA gene amplicon pyrosequencing, expanding our knowledge of the fecal microbiota of forage-fed horses.     

Changes in the Rumen Epimural Bacterial Diversity of Beef Cattle as Affected by Diet and Induced Ruminal Acidosis

Little is known about the nature of the rumen epithelial adherent (epimural) microbiome in cattle fed different diets. Using denaturing gradient gel electrophoresis (DGGE), quantitative real-time PCR (qPCR), and pyrosequencing of the V3 hypervariable coding region of 16S rRNA, epimural bacterial communities of 8 cattle were profiled during the transition from a forage to a high-concentrate diet, during acidosis, and after recovery. A total of 153,621 high-quality gene sequences were obtained, with populations exhibiting less taxonomic variability among individuals than across diets. The bacterial community composition exhibited clustering (P < 0.03) by diet, with only 14 genera, representing >1% of the rumen epimural population, differing (P ≤ 0.05) among diets. During acidosis, levels of Atopobium, Desulfocurvus, Fervidicola, Lactobacillus, and Olsenella increased, while during the recovery, Desulfocurvus, Lactobacillus, and Olsenella reverted to levels similar to those with the high-grain diet and Sharpea and Succinivibrio reverted to levels similar to those with the forage diet. The relative abundances of bacterial populations changed during diet transition for all qPCR targets except Streptococcus spp. Less than 5% of total operational taxonomic units (OTUs) identified exhibited significant variability across diets. Based on DGGE, the community structures of epithelial populations differed (P ≤ 0.10); segregation was most prominent for the mixed forage diet versus the grain, acidotic challenge, and recovery diets. Atopobium, cc142, Lactobacillus, Olsenella, RC39, Sharpea, Solobacterium, Succiniclasticum, and Syntrophococcus were particularly prevalent during acidosis. Determining the metabolic roles of these key genera in the rumens of cattle fed high-grain diets could define a clinical microbial profile associated with ruminal acidosis.     

Metagenomic Analysis of the Pygmy Loris Fecal Microbiome Reveals Unique Functional Capacity Related to Metabolism of Aromatic Compounds

The animal gastrointestinal tract contains a complex community of microbes, whose composition ultimately reflects the co-evolution of microorganisms with their animal host. An analysis of 78,619 pyrosequencing reads generated from pygmy loris fecal DNA extracts was performed to help better understand the microbial diversity and functional capacity of the pygmy loris gut microbiome. The taxonomic analysis of the metagenomic reads indicated that pygmy loris fecal microbiomes were dominated by Bacteroidetes and Proteobacteria phyla. The hierarchical clustering of several gastrointestinal metagenomes demonstrated the similarities of the microbial community structures of pygmy loris and mouse gut systems despite their differences in functional capacity. The comparative analysis of function classification revealed that the metagenome of the pygmy loris was characterized by an overrepresentation of those sequences involved in aromatic compound metabolism compared with humans and other animals. The key enzymes related to the benzoate degradation pathway were identified based on the Kyoto Encyclopedia of Genes and Genomes pathway assignment. These results would contribute to the limited body of primate metagenome studies and provide a framework for comparative metagenomic analysis between human and non-human primates, as well as a comparative understanding of the evolution of humans and their microbiome. However, future studies on the metagenome sequencing of pygmy loris and other prosimians regarding the effects of age, genetics, and environment on the composition and activity of the metagenomes are required.     

Escherichia coli O157:H7 Super-Shedder and Non-Shedder Feedlot Steers Harbour Distinct Fecal Bacterial Communities

Escherichia coli O157:H7 is a major foodborne human pathogen causing disease worldwide. Cattle are a major reservoir for this pathogen and those that shed E. coli O157:H7 at >10⁴ CFU/g feces have been termed “super-shedders”. A rich microbial community inhabits the mammalian intestinal tract, but it is not known if the structure of this community differs between super-shedder cattle and their non-shedding pen mates. We hypothesized that the super-shedder state is a result of an intestinal dysbiosis of the microbial community and that a “normal” microbiota prevents E. coli O157:H7 from reaching super-shedding levels. To address this question, we applied 454 pyrosequencing of bacterial 16S rRNA genes to characterize fecal bacterial communities from 11 super-shedders and 11 contemporary pen mates negative for E. coli O157:H7. The dataset was analyzed by using five independent clustering methods to minimize potential biases and to increase confidence in the results. Our analyses collectively indicated significant variations in microbiome composition between super-shedding and non-shedding cattle. Super-shedders exhibited higher bacterial richness and diversity than non-shedders. Furthermore, seventy-two operational taxonomic units, mostly belonging to Firmicutes and Bacteroidetes phyla, were identified showing differential abundance between these two groups of cattle. The operational taxonomic unit affiliation provides new insight into bacterial populations that are present in feces arising from super-shedders of E. coli O157:H7.     

The importance of scale in comparative microbiome research: New insights from the gut and glands of captive and wild lemurs

Research on animal microbiomes is increasingly aimed at determining the evolutionary and ecological factors that govern host–microbiome dynamics, which are invariably intertwined and potentially synergistic. We present three empirical studies related to this topic, each of which relies on the diversity of Malagasy lemurs (representing a total of 19 species) and the comparative approach applied across scales of analysis. In Study 1, we compare gut microbial membership across 14 species in the wild to test the relative importance of host phylogeny and feeding strategy in mediating microbiome structure. Whereas host phylogeny strongly predicted community composition, the same feeding strategies shared by distant relatives did not produce convergent microbial consortia, but rather shaped microbiomes in host lineage‐specific ways, particularly in folivores. In Study 2, we compare 14 species of wild and captive folivores, frugivores, and omnivores, to highlight the importance of captive populations for advancing gut microbiome research. We show that the perturbational effect of captivity is mediated by host feeding strategy and can be mitigated, in part, by modified animal management. In Study 3, we examine various scent‐gland microbiomes across three species in the wild or captivity and show them to vary by host species, sex, body site, and a proxy of social status. These rare data provide support for the bacterial fermentation hypothesis in olfactory signal production and implicate steroid hormones as mediators of microbial community structure. We conclude by discussing the role of scale in comparative microbial studies, the links between feeding strategy and host–microbiome coadaptation, the underappreciated benefits of captive populations for advancing conservation research, and the need to consider the entirety of an animal's microbiota. Ultimately, these studies will help move the field from exploratory to hypothesis‐driven research.     

Potential of fecal microbiota for early-stage detection of colorectal cancer

Several bacterial species have been implicated in the development of colorectal carcinoma (CRC), but CRC-associated changes of fecal microbiota and their potential for cancer screening remain to be explored. Here, we used metagenomic sequencing of fecal samples to identify taxonomic markers that distinguished CRC patients from tumor-free controls in a study population of 156 participants. Accuracy of metagenomic CRC detection was similar to the standard fecal occult blood test (FOBT) and when both approaches were combined, sensitivity improved > 45% relative to the FOBT, while maintaining its specificity. Accuracy of metagenomic CRC detection did not differ significantly between early- and late-stage cancer and could be validated in independent patient and control populations (N = 335) from different countries. CRC-associated changes in the fecal microbiome at least partially reflected microbial community composition at the tumor itself, indicating that observed gene pool differences may reveal tumor-related host–microbe interactions. Indeed, we deduced a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by an increase of lipopolysaccharide metabolism.     

Improving the standards for gut microbiome analysis of fecal samples: insights from the field biology of Japanese macaques on Yakushima Island

Fecal DNA-based 16S ribosomal RNA (rRNA) gene sequencing using next-generation sequencers allows us to understand the dynamic gut microbiome adaptation of animals to their specific habitats. Conventional techniques of fecal microbiome analysis have been developed within the broad contexts defined by human biology; hence, many of these techniques are not immediately applicable to wild nonhuman primates. In order to establish a standard experimental protocol for the analysis of the gut microbiomes of wild animals, we selected the Japanese macaques (Macaca fuscata yakui) on Yakushima Island. We tested different protocols for each stage of fecal sample processing: storage, DNA extraction, and choice of the sequencing region in the bacterial 16S rRNA gene. We also analyzed the gut microbiome of captive Japanese macaques as the control. The comparison of samples obtained from identical macaques but subjected to different protocols showed that the tested storage methods (RNAlater and lysis buffer) produced effectively the same composition of bacterial operational taxonomic units (OTUs) as the standard frozen storage method, although the relative abundance of each OTU was quantitatively affected. Taxonomic assignment of the detected bacterial groups was also significantly affected by the region being sequenced, indicating that sequencing regions and the corresponding polymerase chain reaction (PCR) primer pairs for the 16S rRNA gene should be carefully selected. This study improves the current standard methods for microbiome analysis in wild nonhuman primates. Japanese macaques were shown to be a suitable model for understanding microbiome adaptation to various environments.     

Identification of bacterial DNA markers for the detection of human fecal pollution in water

We used genome fragment enrichment and bioinformatics to identify several microbial DNA sequences with high potential for use as markers in PCR assays for detection of human fecal contamination in water. Following competitive solution-phase hybridization of total DNA from human and pig fecal samples, 351 plasmid clones were sequenced and were determined to define 289 different genomic DNA regions. These putative human-specific fecal bacterial DNA sequences were then analyzed by dot blot hybridization, which confirmed that 98% were present in the source human fecal microbial community and absent from the original pig fecal DNA extract. Comparative sequence analyses of these sequences suggested that a large number (43.5%) were predicted to encode bacterial secreted or surface-associated proteins. Deoxyoligonucleotide primers capable of annealing to a subset of 26 of the candidate sequences predicted to encode factors involved in interactions with host cells were then used in the PCR and did not amplify markers in DNA from any additional pig fecal specimens. These 26 PCR assays exhibited a range of specificity in tests with 11 other animal sources, with more than half amplifying markers only in specimens from dogs or cats. Four assays were more specific, detecting markers only in specimens from humans, including those from 18 different human populations examined. We then demonstrated the potential utility of these assays by using them to detect human fecal contamination in several impacted watersheds.     

Identification of Bacterial DNA Markers for the Detection of Human Fecal Pollution in Water

We used genome fragment enrichment and bioinformatics to identify several microbial DNA sequences with high potential for use as markers in PCR assays for detection of human fecal contamination in water. Following competitive solution-phase hybridization of total DNA from human and pig fecal samples, 351 plasmid clones were sequenced and were determined to define 289 different genomic DNA regions. These putative human-specific fecal bacterial DNA sequences were then analyzed by dot blot hybridization, which confirmed that 98% were present in the source human fecal microbial community and absent from the original pig fecal DNA extract. Comparative sequence analyses of these sequences suggested that a large number (43.5%) were predicted to encode bacterial secreted or surface-associated proteins. Deoxyoligonucleotide primers capable of annealing to a subset of 26 of the candidate sequences predicted to encode factors involved in interactions with host cells were then used in the PCR and did not amplify markers in DNA from any additional pig fecal specimens. These 26 PCR assays exhibited a range of specificity in tests with 11 other animal sources, with more than half amplifying markers only in specimens from dogs or cats. Four assays were more specific, detecting markers only in specimens from humans, including those from 18 different human populations examined. We then demonstrated the potential utility of these assays by using them to detect human fecal contamination in several impacted watersheds.     

Potential Human Pathogenic Bacteria in a Mixed Urban Watershed as Revealed by Pyrosequencing

Current microbial source tracking (MST) methods for water depend on testing for fecal indicator bacterial counts or specific marker gene sequences to identify fecal contamination where potential human pathogenic bacteria could be present. In this study, we applied 454 high-throughput pyrosequencing to identify bacterial pathogen DNA sequences, including those not traditionally monitored by MST and correlated their abundances to specific sources of contamination such as urban runoff and agricultural runoff from concentrated animal feeding operations (CAFOs), recreation park area, waste-water treatment plants, and natural sites with little or no human activities. Samples for pyrosequencing were surface water, and sediment collected from 19 sites. A total of 12,959 16S rRNA gene sequences with average length of ≤400 bp were obtained, and were assigned to corresponding taxonomic ranks using ribosomal database project (RDP), Classifier and Greengenes databases. The percent of total potential pathogens were highest in urban runoff water (7.94%), agricultural runoff sediment (6.52%), and Prado Park sediment (6.00%), respectively. Although the numbers of DNA sequence tags from pyrosequencing were very high for the natural site, corresponding percent potential pathogens were very low (3.78–4.08%). Most of the potential pathogenic bacterial sequences identified were from three major phyla, namely, Proteobacteria, Bacteroidetes, and Firmicutes. The use of deep sequencing may provide improved and faster methods for the identification of pathogen sources in most watersheds so that better risk assessment methods may be developed to enhance public health.     

Comparative Analysis of Microbial Profiles in Cow Rumen Fed with Different Dietary Fiber by Tagged 16S rRNA Gene Pyrosequencing

The ruminal microbiome of cattle plays an important role not only in animal health and productivity but also in food safety and environment. Microbial profiles of rumen fluid obtained from dairy cows fed on three different fiber/starch diet compositions were characterized. Tagged 16S rRNA gene pyrosequencing and statistical analysis revealed that the dominant ruminal bacteria shared by all three sample groups belonged to phyla Bacteroidetes, Firmicutes, and Proteobacteria. However, the relative abundance of these bacterial groups was markedly affected by diet composition. In animals fed with a high fiber diet, the fibrolytic and cellulolytic bacteria Lachnospiraceae, Ruminococcaceae, and Fibrobacteraceae were found in highest abundance compared with animals fed other diets with lower fiber content. The polysaccharide-degrading Prevotellaceae and Flavobacteriaceae bacteria were most abundant in the rumen of cows fed on diet with the highest starch content. These data highlight the ruminal microbiome’s ability to adapt to feed composition and also provide a basis for the development of feed formulation systems designed to improve livestock productivity.     

Virulence-associated and antibiotic resistance genes of microbial populations in cattle feces analyzed using a metagenomic approach

The bovine fecal microbiota impacts human food safety as well as animal health. Although the bacteria of cattle feces have been well characterized using culture-based and culture-independent methods, techniques have been lacking to correlate total community composition with community function. We used high throughput sequencing of total DNA extracted from fecal material to characterize general community composition and examine the repertoire of microbial genes present in beef cattle feces, including genes associated with antibiotic resistance and bacterial virulence. Results suggest that traditional 16S sequencing using “universal” primers to generate full-length sequence may under represent Acitinobacteria and Proteobacteria. Over eight percent (8.4%) of the sequences from our beef cattle fecal pool sample could be categorized as virulence genes, including a suite of genes associated with resistance to antibiotic and toxic compounds (RATC). This is a higher proportion of virulence genes found in Sargasso sea, chicken cecum, and cow rumen samples, but comparable to the proportion found in Antarctic marine derived lake, human fecal, and farm soil samples. The quantitative nature of metagenomic data, combined with the large number of RATC classes represented in samples from widely different habitats indicates that metagenomic data can be used to track relative amounts of antibiotic resistance genes in individual animals over time. Consequently, these data can be used to generate sample-specific and temporal antibiotic resistance gene profiles to facilitate an understanding of the ecology of the microbial communities in each habitat as well as the epidemiology of antibiotic resistant gene transport between and among habitats.     

Consumption of lysozyme-rich milk can alter microbial fecal populations

Human milk contains antimicrobial factors such as lysozyme and lactoferrin that are thought to contribute to the development of an intestinal microbiota beneficial to host health. However, these factors are lacking in the milk of dairy animals. Here we report the establishment of an animal model to allow the dissection of the role of milk components in gut microbiota modulation and subsequent changes in overall and intestinal health. Using milk from transgenic goats expressing human lysozyme at 68%, the level found in human milk and young pigs as feeding subjects, the fecal microbiota was analyzed over time using 16S rRNA gene sequencing and the G2 Phylochip. The two methods yielded similar results, with the G2 Phylochip giving more comprehensive information by detecting more OTUs. Total community populations remained similar within the feeding groups, and community member diversity was changed significantly upon consumption of lysozyme milk. Levels of Firmicutes (Clostridia) declined whereas those of Bacteroidetes increased over time in response to the consumption of lysozyme-rich milk. The proportions of these major phyla were significantly different (P < 0.05) from the proportions seen with control-fed animals after 14 days of feeding. Within phyla, the abundance of bacteria associated with gut health (Bifidobacteriaceae and Lactobacillaceae) increased and the abundance of those associated with disease (Mycobacteriaceae, Streptococcaceae, Campylobacterales) decreased with consumption of lysozyme milk. This study demonstrated that a single component of the diet with bioactivity changed the gut microbiome composition. Additionally, this model enabled the direct examination of the impact of lysozyme on beneficial microbe enrichment versus detrimental microbe reduction in the gut microbiome community.     

Similarity of the ruminal bacteria across individual lactating cows

Dairy cattle hold enormous significance for man as a source of milk and meat. Their remarkable ability to convert indigestible plant mass into these digestible food products resides in the rumen - an anaerobic chambered compartment - in the bovine digestive system. The rumen houses a complex microbiota which is responsible for the degradation of plant material, consequently enabling the conversion of plant fibers into milk and meat and determining their quality and quantity. Hence, an understanding of this complex ecosystem has major economic implications. One important question that is yet to be addressed is the degree of conservation of rumen microbial composition across individual animals. Here we quantified the degree of similarity between rumen bacterial populations of 16 individual cows. We used real-time PCR to determine the variance of specific ruminal bacterial species with different metabolic functions, revealing that while some bacterial strains vary greatly across animals, others show only very low variability. This variance could not be linked to the metabolic traits of these bacteria. We examined the degree of similarity in the dominant bacterial populations across all animals using automated ribosomal intergenic spacer analysis (ARISA), and identified a bacterial community consisting of 32% operational taxonomic units (OTUs) shared by at least 90% of the animals and 19% OTUs shared by 100% of the animals. Looking only at the presence or absence of each OTU gave an average similarity of 75% between each cow pair. When abundance of each OTU was added to the analysis, this similarity decreased to an average of less than 60%. Thus, as suggested in similar recent studies of the human gut, a bovine rumen core microbiome does exist, but taxa abundance may vary greatly across animals.     

Characterization of the human DNA gut virome across populations with different subsistence strategies and geographical origin

It is a matter of fact that the human gut microbiome also includes a non‐bacterial fraction represented by eukaryotic cells and viruses. To further explore the gut microbiome variation in human populations, here we characterized the human DNA viral community from publicly available gut metagenome data sets from human populations with different geographical origin and lifestyle. In particular, such data sets encompass microbiome information from two western urban societies (USA and Italy), as well as two traditional hunter‐gatherer communities (the Hadza from Tanzania and Matses from Peru) and one pre‐agricultural tribe (Tunapuco from Peru). Our results allowed for the first taxonomic reconstruction of the complex viral metacommunities within the human gut. The core virome structure included herpesviruses, papillomaviruses, polyomaviruses, adenoviruses and anelloviruses. Using Random Forests and a co‐occurrence analysis approach, we identified the viruses that distinguished populations according to their geographical origin and/or lifestyle. This paves the way for new research aimed at investigating the biological role of the gut virome in human physiology, and the importance of our viral counterpart in the microbiome‐host co‐evolutionary process.     

An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection

Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.     

Benchmarking of 16S rRNA gene databases using known strain sequences

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.     

Bacterial Community and Diversity from the Watermelon Cultivated Soils through Next Generation Sequencing Approach

Knowledge and better understanding of functions of the microbial community are pivotal for crop management. This study was conducted to study bacterial structures including Acidovorax species community structures and diversity from the watermelon cultivated soils in different regions of South Korea. In this study, soil samples were collected from watermelon cultivation areas from various places of South Korea and microbiome analysis was performed to analyze bacterial communities including Acidovorax species community. Next generation sequencing (NGS) was performed by extracting genomic DNA from 92 soil samples from 8 different provinces using a fast genomic DNA extraction kit. NGS data analysis results revealed that, total, 39,367 operational taxonomic unit (OTU), were obtained. NGS data results revealed that, most dominant phylum in all the soil samples was Proteobacteria (37.3%). In addition, most abundant genus was Acidobacterium (1.8%) in all the samples. In order to analyze species diversity among the collected soil samples, OTUs, community diversity, and Shannon index were measured. Shannon (9.297) and inverse Simpson (0.996) were found to have the highest diversity scores in the greenhouse soil sample of Gyeonggi-do province (GG4). Results from NGS sequencing suggest that, most of the soil samples consists of similar trend of bacterial community and diversity. Environmental factors play a key role in shaping the bacterial community and diversity. In order to address this statement, further correlation analysis between soil physical and chemical parameters with dominant bacterial community will be carried out to observe their interactions.