Patricio Jeraldo

Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls.

Multiple sclerosis (MS) is an immune-mediated disease, the etiology of which involves both genetic and environmental factors. The exact nature of the environmental factors responsible for predisposition to MS remains elusive; however, it’s hypothesized that gastrointestinal microbiota might play an important role in pathogenesis of MS. Therefore, this study was designed to investigate whether gut microbiota are altered in MS by comparing the fecal microbiota in relapsing remitting MS (RRMS) (n = 31) patients to that of age- and gender-matched healthy controls (n = 36). Phylotype profiles of the gut microbial populations were generated using hypervariable tag sequencing of the V3–V5 region of the 16S ribosomal RNA gene. Detailed fecal microbiome analyses revealed that MS patients had distinct microbial community profile compared to healthy controls. We observed an increased abundance of Psuedomonas, Mycoplana, Haemophilus, Blautia, and Dorea genera in MS patients, whereas control group showed increased abundance of Parabacteroides, Adlercreutzia and Prevotella genera. Thus our study is consistent with the hypothesis that MS patients have gut microbial dysbiosis and further study is needed to better understand their role in the etiopathogenesis of MS.

An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis.

BackgroundThe adaptive immune response in rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. Association of the gut microbiota with various diseases has been reported, though the specific components of the microbiota that affect the host response leading to disease remain unknown. However, there is limited information on the role of gut microbiota in RA. In this study we aimed to define a microbial and metabolite profile that could predict disease status. In addition, we aimed to generate a humanized model of arthritis to confirm the RA-associated microbe.MethodsTo identify an RA biomarker profile, the 16S ribosomal DNA of fecal samples from RA patients, first-degree relatives (to rule out environment/background as confounding factors), and random healthy non-RA controls were sequenced. Analysis of metabolites and their association with specific taxa was performed to investigate a potential mechanistic link. The role of an RA-associated microbe was confirmed using a human epithelial cell line and a humanized mouse model of arthritis.ResultsPatients with RA exhibited decreased gut microbial diversity compared with controls, which correlated with disease duration and autoantibody levels. A taxon-level analysis suggested an expansion of rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared with controls. Prediction models based on the random forests algorithm suggested that three genera, Collinsella, Eggerthella, and Faecalibacterium, segregated with RA. The abundance of Collinsella correlated strongly with high levels of alpha-aminoadipic acid and asparagine as well as production of the proinflammatory cytokine IL-17A. A role for Collinsella in altering gut permeability and disease severity was confirmed in experimental arthritis.ConclusionsThese observations suggest dysbiosis in RA patients resulting from the abundance of certain rare bacterial lineages. A correlation between the intestinal microbiota and metabolic signatures could determine a predictive profile for disease causation and progression.

Diet and exercise orthogonally alter the gut microbiome and reveal independent associations with anxiety and cognition

BackgroundThe ingestion of a high-fat diet (HFD) and the resulting obese state can exert a multitude of stressors on the individual including anxiety and cognitive dysfunction. Though many studies have shown that exercise can alleviate the negative consequences of a HFD using metabolic readouts such as insulin and glucose, a paucity of well-controlled rodent studies have been published on HFD and exercise interactions with regard to behavioral outcomes. This is a critical issue since some individuals assume that HFD-induced behavioral problems such as anxiety and cognitive dysfunction can simply be exercised away. To investigate this, we analyzed mice fed a normal diet (ND), ND with exercise, HFD diet, or HFD with exercise.ResultsWe found that mice on a HFD had robust anxiety phenotypes but this was not rescued by exercise. Conversely, exercise increased cognitive abilities but this was not impacted by the HFD. Given the importance of the gut microbiome in shaping the host state, we used 16S rRNA hypervariable tag sequencing to profile our cohorts and found that HFD massively reshaped the gut microbial community in agreement with numerous published studies. However, exercise alone also caused massive shifts in the gut microbiome at nearly the same magnitude as diet but these changes were surprisingly orthogonal. Additionally, specific bacterial abundances were directly proportional to measures of anxiety or cognition.ConclusionsThus, behavioral domains and the gut microbiome are both impacted by diet and exercise but in unrelated ways. These data have important implications for obesity research aimed at modifications of the gut microbiome and suggest that specific gut microbes could be used as a biomarker for anxiety or cognition or perhaps even targeted for therapy.

The microbiome of the chicken gastrointestinal tract.

Abstract The modern molecular biology movement was developed in the 1960s with the conglomeration of biology, chemistry, and physics. Today, molecular biology is an integral part of studies aimed at understanding the evolution and ecology of gastrointestinal microbial communities. Molecular techniques have led to significant gains in our understanding of the chicken gastrointestinal microbiome. New advances, primarily in DNA sequencing technologies, have equipped researchers with the ability to explore these communities at an unprecedented level. A reinvigorated movement in systems biology offers a renewed promise in obtaining a more complete understanding of chicken gastrointestinal microbiome dynamics and their contributions to increasing productivity, food value, security, and safety as well as reducing the public health impact of raising production animals. Here, we contextualize the contributions molecular biology has already made to our understanding of the chicken gastrointestinal microbiome and propose targeted research directions that could further exploit molecular technologies to improve the economy of the poultry industry.

Quantification of the relative roles of niche and neutral processes in structuring gastrointestinal microbiomes

The theoretical description of the forces that shape ecological communities focuses around two classes of models. In niche theory, deterministic interactions between species, individuals, and the environment are considered the dominant factor, whereas in neutral theory, stochastic forces, such as demographic noise, speciation, and immigration, are dominant. Species abundance distributions predicted by the two classes of theory are difficult to distinguish empirically, making it problematic to deduce ecological dynamics from typical measures of diversity and community structure. Here, we show that the fusion of species abundance data with genome-derived measures of evolutionary distance can provide a clear indication of ecological dynamics, capable of quantifying the relative roles played by niche and neutral forces. We apply this technique to six gastrointestinal microbiomes drawn from three different domesticated vertebrates, using high-resolution surveys of microbial species abundance obtained from carefully curated deep 16S rRNA hypervariable tag sequencing data. Although the species abundance patterns are seemingly well fit by the neutral theory of metacommunity assembly, we show that this theory cannot account for the evolutionary patterns in the genomic data; moreover, our analyses strongly suggest that these microbiomes have, in fact, been assembled through processes that involve a significant nonneutral (niche) contribution. Our results demonstrate that high-resolution genomics can remove the ambiguities of process inference inherent in classic ecological measures and permits quantification of the forces shaping complex microbial communities.

Pregnancy's Stronghold on the Vaginal Microbiome

Objective To assess the vaginal microbiome throughout full-term uncomplicated pregnancy. Methods Vaginal swabs were obtained from twelve pregnant women at 8-week intervals throughout their uncomplicated pregnancies. Patients with symptoms of vaginal infection or with recent antibiotic use were excluded. Swabs were obtained from the posterior fornix and cervix at 8–12, 17–21, 27–31, and 36–38 weeks of gestation. The microbial community was profiled using hypervariable tag sequencing of the V3–V5 region of the 16S rRNA gene, producing approximately 8 million reads on the Illumina MiSeq. Results Samples were dominated by a single genus, Lactobacillus, and exhibited low species diversity. For a majority of the patients (n = 8), the vaginal microbiome was dominated by Lactobacillus crispatus throughout pregnancy. Two patients showed Lactobacillus iners dominance during the course of pregnancy, and two showed a shift between the first and second trimester from L. crispatus to L. iners dominance. In all of the samples only these two species were identified, and were found at an abundance of higher than 1% in this study. Comparative analyses also showed that the vaginal microbiome during pregnancy is characterized by a marked dominance of Lactobacillus species in both Caucasian and African-American subjects. In addition, our Caucasian subject population clustered by trimester and progressed towards a common attractor while African-American women clustered by subject instead and did not progress towards a common attractor. Conclusion Our analyses indicate normal pregnancy is characterized by a microbiome that has low diversity and high stability. While Lactobacillus species strongly dominate the vaginal environment during pregnancy across the two studied ethnicities, observed differences between the longitudinal dynamics of the analyzed populations may contribute to divergent risk for pregnancy complications. This helps establish a baseline for investigating the role of the microbiome in complications of pregnancy such as preterm labor and preterm delivery.

On the suitability of short reads of 16S rRNA for phylogeny-based analyses in environmental surveys

Pyrosequencing platforms have been widely used in 16S rRNA deep sequencing of organisms sampled from environmental surveys. Despite the massive number of reads generated by these platforms, the reads only cover short regions of the gene, and the use of these short reads has recently been called into question for phylogeny-based and diversity analyses. We explore the limits of the use of short reads by quantifying the loss of information, and its effect on phylogeny. Using available nearly-full-length reads from published clone libraries and databases, and simulated short reads created from these reads, we show that for selected regions of the gene, short reads contain a surprisingly high amount of biological information, making them suitable to resolve an approximate phylogeny. In particular, we find that the V6 region is significantly poorer than the V1-V3 region in its representation of phylogenetic relationships. We conclude that the use of short reads, combined with a careful choice of the gene region used, and a thorough alignment procedure, can yield phylogenetic information comparable with that obtained from nearly-full-length 16S rRNA reads.

IM-TORNADO: A tool for comparison of 16S reads from paired-end libraries

Motivation 16S rDNA hypervariable tag sequencing has become the de facto method for accessing microbial diversity. Illumina paired-end sequencing, which produces two separate reads for each DNA fragment, has become the platform of choice for this application. However, when the two reads do not overlap, existing computational pipelines analyze data from read separately and underutilize the information contained in the paired-end reads. Results We created a workflow known as Illinois Mayo Taxon Organization from RNA Dataset Operations (IM-TORNADO) for processing non-overlapping reads while retaining maximal information content. Using synthetic mock datasets, we show that the use of both reads produced answers with greater correlation to those from full length 16S rDNA when looking at taxonomy, phylogeny, and beta-diversity. Availability and Implementation IM-TORNADO is freely available at http://sourceforge.net/projects/imtornado and produces BIOM format output for cross compatibility with other pipelines such as QIIME, mothur, and phyloseq.

Human Gut‐Derived Prevotella histicola Suppresses Inflammatory Arthritis in Humanized Mice

The gut microbiome regulates host immune homeostasis. Rheumatoid arthritis (RA) is associated with intestinal dysbiosis. This study was undertaken to test the ability of a human gut‐derived commensal to modulate immune response and treat arthritis in a humanized mouse model.

Suppression of Inflammatory Arthritis by Human Gut-Derived Prevotella histicola in Humanized Mice

The gut microbiome regulates host immune homeostasis. Rheumatoid arthritis (RA) is associated with intestinal dysbiosis. This study was undertaken to test the ability of a human gut‐derived commensal to modulate immune response and treat arthritis in a humanized mouse model.