61 Matching Annotations
  1. Apr 2019
    1. founder effects

      The long-lasting and persistent effects of reduced genetic diversity due to the small number of individuals that initially colonized a certain environment.

    2. enterotypes

      A classification of living organisms, similar to ecosystems, based on their bacteriological ecosystem. They are identifiable constellations of intestinal bacteria, biological communities of microorganisms in the gut. Dr. Peer Bork discovered three human gut types in April 2011: Bacteroides, Prevotella and Ruminococcus.

    3. I. Martínez et al., Cell Rep. 11, 527–538 (2015).

      Martinez and colleagues compared the gut microbiome of individuals from Papua New Guinea and the United States. Individuals from Papua New Guinea had greater bacterial diversity and abundances, suggesting that industrialization may have an impact on the gut microbiome and, consequently, human health.

    4. J. K. Goodrich et al., Cell 159, 789–799 (2014).

      Goodrich and colleagues compared the gut microbiomes from individuals in the TwinsUK population and found that there is a correlation between the host genetics, metabolism, and gut microbiome.

    5. T. Yatsunenko et al., Nature 486, 222–227 (2012).

      Yatsunenko and colleagues sequenced the gut microbiome of three vastly different populations and found that there were pronounced differences between individuals from the United States than from Venezuela or Malawi. They suggest that the gut microbiome may be impacted by human development and Westernization.

    6. the second bicluster, consisting of seven genera, including Bacteroides and Parabacteroides, comprised individuals with reduced microbiome diversity. Characterization of these individuals revealed a preference for white, low-fiber bread [bread being the major source of carbohydrates in an average Belgian diet (34)] and higher prevalence of recent amoxicillin treatment.

      The other subset of individuals was characterized by lower microbiome diversity, having only seven genera (compared to 15 genera in the first subset). These individuals showed a preference for white bread and were associated with recent antibiotic treatment.

    7. ulcerative colitis

      Chronic intestinal disease characterized by flares of inflammation of the innermost lining of the large intestine and rectum. Symptoms such as diarrhea, abdominal cramps, and bloody stools may occur alternating with quiescent (inactive/dormant) periods. Patients with ulcerative colitis are at an increased risk of developing colon cancer.

    8. Years of disease-targeted microbiome research have generated an extensive inventory of bacterial genera with a reported association with one or more pathologies.

      There is a huge variety of diseases associated with bacteria. The connections between bacteria and pathologies are only beginning to be uncovered, in part due to research into the microbiome.

      To get an overview of the types of diseases caused by bacteria, check out this resource from the University of Utah: https://learn.genetics.utah.edu/content/microbiome/disease/

    9. Bristol stool scale

      A diagnostic tool used to classify human faeces into seven categories based on its shape, texture, and consistency. The chart allows patients with gastrointestinal symptoms to describe their bowel movements without needed to provide a sample.

      Learn more about BSS from this article in The Conversation: https://theconversation.com/what-the-consistency-of-your-poo-says-about-your-health-65106

    10. generalized linear model analysis

      A statistical model used to describe associations between multiple independent and dependent variables. The goal is the optimal linear combination of parameters to explain an observation.

    11. Moreover, correlations between RBC counts and Faecalibacterium abundances are in line with the known oxygen requirements of this genus

      They found that red blood cell counts were also associated with the relative abundance of Faecalibacterium. As oxygen transport is the most important function of red blood cells, this fits the oxygen requirements of this genus.

    12. dietary information (including fiber uptake, bread preference, and fruit consumption

      O'Toole and colleagues found that changes in the gut microbiome composition were associated with chronic conditions like obesity and inflammation. They were able to show that these changes were partially driven by diet in aging populations.

    13. alpha-diversity

      Alpha-diversity is a measurement of the diversity within a single community/ecosystem. In this study, the researchers found that all of the 69 factors correlated with both the average species diversity and abundance in all samples.

      Check out this video to learn more about alpha-diversity in the context of the microbiome.

    14. unconstrained canonical correspondence analysis

      Refers to a statistical method that searches for multivariate relationships between two data sets.

      This method is most often used in genetics and ecological sciences. Learn more about why, how, and when to use it here.

    15. 308 samples collected in Papua New Guinea (15), Peru (16), and Tanzania (17) reduced the size of the human core microbiota to 14 genera. Notably, Alistipes, Clostridium IV, Parabacteroides, and all Actinobacteria were excluded from the global core composition

      When data was collected from samples outside of Europe and the United States, the core microbiota (which is defined as a genus that is common to at least 95% of samples) decreased to 14 genera.

    16. core microbiota (i.e., the genera shared by 95% of samples) composed of 17 genera with a median core abundance (MA) of 72.20%

      They found that the core microbiota—defined by being shared by 95% of samples from the United Kingdom, United States, FGFP, and LLDeep data sets—was 17 genera. The median abundance of these genera was 72.20%.

    17. Combined, these data sets comprised a total richness of 664 genera (fig. S2A). Extrapolation estimated total western genus richness at 784 ± 40 (fig. S2B), suggesting that total western richness is still undersampled. Observing total richness would require sampling an estimated additional 40,739 individuals

      The overall microbiota richness of their samples accounted for 664 genera, but does not cover all 784 genera expected for the entire Western population. They calculate that in order to observe all 784 genera, they would need to sample over 40,000 more individuals.

    18. other U.K. and U.S. studies

      Gordon and colleagues conducted a similar gut microbiome study in 2012 but focused on how they differed across populations, comparing healthy individuals from Venezuela, Malawi, and the United States.

    19. major challenges still hamper the once assumed imminent translation of microbiome monitoring into diagnostic and clinical practice

      Probiotics are live microorganisms that are sold as a therapeutic food used to treat gut microbiome imbalances, but their usefulness has not yet been conclusively demonstrated. To market these probiotics, some diagnostic centers offer a microbiome analysis to characterize shifts from the "normal" composition, even while the definition of "normal" has yet to be broadly defined. In some countries such as the United States, food supplements are not regulated the same as drugs. New policies on therapeutic foods will need to be developed as personalized nutrition and precision medicine become a reality. Read more from the Regulatory Affairs Professionals Society.

    20. F. H. Karlsson et al., Nature 498, 99–103 (2013).

      Karlsson and colleagues characterized the fecal microbiota of European women and found that predictive tools for type-2 diabetes-associated markers could be useful if the age and location of the individual is accounted for.

    21. The discovery of these associations has stimulated the search for specific microbiome-based biomarkers for a wide range of pathologies

      Gut microbiome studies have suggested many associations between composition and human health. This has prompted the development of fecal transplants for the treatment of Clostridium difficile infections, a bacterium that causes intestinal symptoms like diarrhea. Based on the success of fecal microbiota transfer in recurrent C. diff infections, this potential "treatment" is now being studied for all kinds of diseases that are being linked to the intestinal microbiome, from obesity to autism spectrum disorders.

      Read more in The Guardian: https://www.theguardian.com/science/2013/mar/31/bacteria-faecal-transplant-gut-mary-roach-gulp

    22. microbiome

      The combined genetic information of microorganisms, such as bacteria and viruses, that are found in a specific environment.

  2. Mar 2019
    1. false discovery rate

      Describes the frequency of false positives, which can be reduced by more robust experimental design, higher quality samples, or improved analytical techniques.

    2. covariates

      Parameters that vary with the variation in what is being studied; here, the microbiome covariates are variables taken from clinical and questionnaire data that are strongly correlated with the abundance and diversity of various genera.

    3. Bray-Curtis dissimilarity

      A statistical method used to quantify the compositional difference in species populations between samples. The value is always a number between 0 and 1, where 0 indicates that the samples share all the same species and 1 indicates that the samples don't have any species in common.

    4. confounding factors

      Parameters that blur results by having an effect on what is studied. These factors may mask or falsely show associations between the independent and dependent variables, resulting in biased conclusions.

    5. some of the medical conditions targeted by fecal microbiota research have much smaller microbiome effect sizes than commonly assumed. However, some of the covariates that we identified (such as BSS and medication) are currently largely ignored and should be taken into account in future clinical studies

      They conclude that some medical conditions do not have as great of an impact on gut microbiota as previously thought. However, other covariables are under accounted for in these types of clinical studies.

    6. We could detect a 9% difference between taxon proportions with 400 samples per group at a power above 95% and a 5% difference with 500 samples per group at a power of 80%

      The authors were able to show that with 800 samples, they could detect a 9% difference in taxon proportions at a power above 95% and a 5% difference in taxon proportions with 1000 samples at a power of 80%. The latter means: 80% probability of detecting 5% deviations in taxon proportion between samples.

    7. intake of several of these substances was associated with community composition variation (Fig. 5A and table S15). The only drugs significantly associated with the abundance of specific genera in phenotype-matched case-control analyses were β-lactam antibiotics (FDR <5%).

      While several medications were associated with variation in microbiota composition, the researchers found for only one drug significant associations with the abundance of specific genera (when comparing matched cases and controls), namely for beta-lactam antibiotics.

    8. was also negatively associated with insulin resistance risk factors such as BMI and blood triglyceride concentrations

      They found that the abundance of Akkermansia was negatively associated with insulin resistance risk factors. This means that samples with higher amounts of Akkermansia belonged to subjects with lower risk of insulin resistance based on BMI and blood triglyceride values. Insulin resistance is a condition in which your cells cannot use insulin (a hormone) effectively, preventing them from absorbing glucose. This condition may result in diabetes, which is characterized by a buildup of glucose in the blood.

    9. features losing most explanatory power were time since previous relief (also indicative of passage rates), blood uric acid and hemoglobin levels, BMI, gender, and frequency of beer consumption

      Stool consistency correlated with other factors like the time since previous defecation, blood uric acid (a chemical produced by the breakdown of food) and hemoglobin (a protein responsible for transporting oxygen in blood) levels, BMI, gender, and frequency of beer consumption.

    10. 12 out of 20 of the FGFP 99% core genera covary with BSS scores, with overall core abundance increasing in looser stools

      In the FGFP cohort, the researchers observed that the overall abundance of core genera was higher in looser stools.

    11.  Faecalibacterium numbers were, as discussed, dependent on RBC counts, but our analysis did find a decreased abundance in ulcerative colitis patients

      They found that red blood cell counts were also associated with the relative abundance of Faecalibacterium. As oxygen transport is the most important function of red blood cells, this fits the oxygen requirements of this genus.

    12. set of 18 variables (Fig. 3B and table S10) with a cumulative (nonredundant) effect size on community variation of 7.63%. Here, we identified stool consistency as the top single, nonredundant microbiome covariate in the FGFP metadata

      When modelling the 69 covariates that had a significant impact on the gut microbiota composition (to see which combination of parameters could best explain the variation), a combination of 18 variables was found, that accounted for 7.63% of the variation. Stool consistency on its own accounted for most of the variation.

    13. Ruminococcaceae, Bacteroides, and Prevotella; all previously proposed as enterotype identifiers

      Bork and colleagues proposed that humans have three different gut types based on the most abundant bacterial taxa. The types of bacteria present are independent of an individual's age, sex, or nationality but they found some correlation between some characteristics and bacterial function. For example, the abundance of Bacteroides, which break down carbohydrates, was found to increase with age.

  3. Oct 2018
    1. that Akkermansia abundance positively correlated with time since previous relief

      Raes and colleagues found through 16S rDNA sequencing that time since last bowel movement was linked to Akkermansia abundance, a bacterial genus that has been linked to improved metabolic health.

    2. BSS score has been put forward as an indicative measure of transit time

      Heaton and colleagues showed that the BSS could be used to indirectly measure the rate at which food moves through the digestive tract.

    3. stochastic

      Refers to anything that has a random probability distribution that can be analyzed statistically, but not precisely predicted. Here, the researchers suggest that some variation in genera abundance might be due to random, uncontrollable factors.

    4. J. C. Clemente, L. K. Ursell, L. W. Parfrey, R. Knight, Cell 148, 1258–1270 (2012).

      Clemente and colleagues review the interactions between microbes in the human gut and their effect on the host's immune system.

    5. J. F. Cryan, T. G. Dinan, Nat. Rev. Neurosci. 13, 701–712 (2012).

      Dinan and Cyran suggest that the gut microbiome may have a role in regulating and influencing brain function and behavior.

    6. E. Le Chatelier et al., Nature 500, 541–546 (2013).

      Le Chatelier and colleagues conduct a similar study on non-obese and obese Danish individuals. They find that they are able to classify subsets of individuals that may be at risk of obesity or associated comorbidities based on variation in the gut microbiota.

    7. J. Qin et al., Nature 490, 55–60 (2012).

      Qin and colleagues conducted a metagenome-wide association study in Chinese individuals. They identified type-2 diabetes-associated markers based on sequencing of the gut microbiome.

    8. M. Rajilić-Stojanović et al., Am. J. Gastroenterol. 110, 278–287 (2015).

      Rajilić-Stojanović and colleagues provide a review of current research on and suggest mechanisms regarding the impact of diet and the intestinal microbiome on irritable bowel syndrome symptoms.

    9. revealed associations between genus abundances and hip circumference, uric acid concentrations, amoxicillin intake, and chocolate-type preference (namely, an increased abundance of unclassified Lachnospiraceae in participants with a preference for dark chocolate).

      Similar to how red blood cell counts were associated with differing abundances of Faecaelibacterium, the researchers also showed that there were associations between other genera and hip circumference (the distance around the largest part of your hips or the widest part of your buttocks), uric acid concentrations (a compound that is excreted in urine; high uric acid concentrations can indicate poor kidney function and low concentrations can indicate gout, a form of arthritis), amoxicillin (a type of antibiotic) intake, and chocolate preference.

    10. forward stepwise redundancy analysis (RDA)

      This is a statistical technique used to describe linear relationships between components of dependent variables that can be explained by a set of independent variables. Here, the independent variables were the 69 covariates and the dependent variable was the microbiota variation in each sample.

    11. 24 matching covariates were found to be significantly associated with microbiome composition in the LLDeep cohort

      Of the 26 covariates that were comparable in both the FGFP and LLDeep data, 24 factors were found to be significantly associated with microbiome composition in the LLDeep cohort.

    12. large-scale cross-sectional fecal sampling effort in a confined geographic region

      Many other gut flora projects have since followed, including one that suggested there may be an association between household cleaners and BMI due to varying abundance of the microbe, Lachnospiraceae.

      Read more: https://www.theglobeandmail.com/life/article-household-cleaners-may-alter-kids-gut-flora-contribute-to-being-2/

    13. Of the covariate interactions detected, 63% was driven by medication (Fig. 5B). This result highlights the versatility of drug-microbiome associations and stresses their importance as potentially confounding factors in clinical studies.

      They found that medication influenced 63% of the interactions between variables and may confuse or bias results in clinical studies.

    14. benzodiazepines

      A class of psychoactive drugs commonly used to treat anxiety.

    15. osmotic laxatives

      This type of medication eases constipation by pulling water back into the colon to soften stool.

    16. anthropometric features

      Refers to traits that describe dimensions of the human body; like height, weight, or body fat composition.

    17. metadata

      A set of data that gives information about another set of data. For example, the author and date describe a document.

    18. PCoA

      Stands for Principal Coordinate Analysis, a statistical technique used to visualize similarities between variables by representing the variance in as few axes/dimensions as possible. The arrows show the direction of the original variables and the angle between arrows gives a rough estimate of the correlation between features.

    19. 16S ribosomal RNA (rRNA) gene amplicon sequencing

      Almost all bacteria have a copy of the 16S rRNA gene. Comparing their sequences is a common tool to identify and differentiate bacteria at the species level.

      Learn more about how bacteria are identified with this resource from iBiology: https://www.ibiology.org/microbiology/genome-sequencing/

    20. phylogenetic profiling

      Refers to a bioinformatics technique in which the presence or absence of traits across a large number of species can be used to infer biological connections.

    21. anamnesis

      A patient's account of their medical history.

    22. cold chain monitoring

      A practice in which the storage, shipping, and distribution of samples are continuously kept in a temperature controlled environment. This prevents samples that may be sensitive to temperature fluctuations from degrading.

    23. cumulative, nonredundant effect size of 7.63%. This suggests the influence of additional, currently unknown covariates as well as intrinsic microbial ecological processes

      Since their metadata could only explain less than 8% of the variation, the researchers suggest that there are other factors that were not accounted for in their study. This may be intrinsic properties to microbes, such as interactions between species.

    24. analyses revealed that effect size is small but significant (table S10). Notably, previously unidentified factors such as red blood cell (RBC) count and hemoglobin concentration indicated covariation of microbiome composition with blood oxygen uptake capacity

      They showed that there is a significant association between the microbiome composition and body mass index. They also found new correlations, like red blood cell count, with the microbiome composition.

    25. Previous work in mice has shown an effect of oxygen diffusion on the microbiota

      Wu and colleagues quantified gut oxygen levels in mice and found that there was a correlation between the distribution of oxygen and nutrients and the microbiome composition.

    26. medication had the largest explanatory power on microbiome composition, including 10.04% of community variation

      Medication has an impact on the microbiome composition and accounted for 10.04% of the differences between samples.