Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations

Statistical Modeling of Trivariate Static Systems: Isotonic Models

This paper presents an improved version of a statistical trivariate modeling algorithm introduced in a short Letter by the first author. This paper recalls the fundamental concepts behind the proposed algorithm, evidences its criticalities and illustrates a number of improvements which lead to a functioning modeling algorithm. The present paper also illustrates the features of the improved statistical modeling algorithm through a comprehensive set of numerical experiments performed on four synthetic and five natural datasets. The obtained results confirm that the proposed algorithm is able to model the considered synthetic and the natural datasets faithfully.

Dynamic changes in human-gut microbiome in relation to a placebo-controlled anthelminthic trial in Indonesia

BACKGROUND

Microbiome studies suggest the presence of an interaction between the human gut microbiome and soil-transmitted helminth. Upon deworming, a complex interaction between the anthelminthic drug, helminths and microbiome composition might occur. To dissect this, we analyse the changes that take place in the gut bacteria profiles in samples from a double blind placebo controlled trial conducted in an area endemic for soil transmitted helminths in Indonesia.

METHODS

Either placebo or albendazole were given every three months for a period of one and a half years. Helminth infection was assessed before and at 3 months after the last treatment round. In 150 subjects, the bacteria were profiled using the 454 pyrosequencing. Statistical analysis was performed cross-sectionally at pre-treatment to assess the effect of infection, and at post-treatment to determine the effect of infection and treatment on microbiome composition using the Dirichlet-multinomial regression model.

RESULTS

At a phylum level, at pre-treatment, no difference was seen in microbiome composition in terms of relative abundance between helminth-infected and uninfected subjects and at post-treatment, no differences were found in microbiome composition between albendazole and placebo group. However, in subjects who remained infected, there was a significant difference in the microbiome composition of those who had received albendazole and placebo. This difference was largely attributed to alteration of Bacteroidetes. Albendazole was more effective against Ascaris lumbricoides and hookworms but not against Trichuris trichiura, thus in those who remained infected after receiving albendazole, the helminth composition was dominated by T. trichiura.

DISCUSSION

We found that overall, albendazole does not affect the microbiome composition. However, there is an interaction between treatment and helminths as in subjects who received albendazole and remained infected there was a significant alteration in Bacteroidetes. This helminth-albendazole interaction needs to be studied further to fully grasp the complexity of the effect of deworming on the microbiome.

TRIAL REGISTRATION

ISRCTN Registy, ISRCTN83830814.

Differential human gut microbiome assemblages during soil-transmitted helminth infections in Indonesia and Liberia

BACKGROUND

The human intestine and its microbiota is the most common infection site for soil-transmitted helminths (STHs), which affect the well-being of ~ 1.5 billion people worldwide. The complex cross-kingdom interactions are not well understood.

RESULTS

A cross-sectional analysis identified conserved microbial signatures positively or negatively associated with STH infections across Liberia and Indonesia, and longitudinal samples analysis from a double-blind randomized trial showed that the gut microbiota responds to deworming but does not transition closer to the uninfected state. The microbiomes of individuals able to self-clear the infection had more alike microbiome assemblages compared to individuals who remained infected. One bacterial taxon (Lachnospiracae) was negatively associated with infection in both countries, and 12 bacterial taxa were significantly associated with STH infection in both countries, including Olsenella (associated with reduced gut inflammation), which also significantly reduced in abundance following clearance of infection. Microbial community gene abundances were also affected by deworming. Functional categories identified as associated with STH infection included arachidonic acid metabolism; arachidonic acid is the precursor for pro-inflammatory leukotrienes that threaten helminth survival, and our findings suggest that some modulation of arachidonic acid activity in the STH-infected gut may occur through the increase of arachidonic acid metabolizing bacteria.

CONCLUSIONS

For the first time, we identify specific members of the gut microbiome that discriminate between moderately/heavily STH-infected and non-infected states across very diverse geographical regions using two different statistical methods. We also identify microbiome-encoded biological functions associated with the STH infections, which are associated potentially with STH survival strategies, and changes in the host environment. These results provide a novel insight of the cross-kingdom interactions in the human gut ecosystem by unlocking the microbiome assemblages at taxonomic, genetic, and functional levels so that advances towards key mechanistic studies can be made.

Numerical analyses of intestinal microbiota by data mining

The human intestinal microbiota has a close relationship with health control and causes of diseases, and a vast number of scientific papers on this topic have been published recently. Some progress has been made in identifying the causes or species of related microbiota, and successful results of data mining are reviewed here. Humans who are targets of a disease have their own individual characteristics, including various types of noise because of their individual life style and history. The quantitatively dominant bacterial species are not always deeply connected with a target disease. Instead of conventional simple comparisons of the statistical record, here the Gini-coefficient (i.e., evaluation of the uniformity of a group) was applied to minimize the effects of various types of noise in the data. A series of results were reviewed comparatively for normal daily life, disease and technical aspects of data mining. Some representative cases (i.e., heavy smokers, Crohn’s disease, coronary artery disease and prediction accuracy of diagnosis) are discussed in detail. In conclusion, data mining is useful for general diagnostic applications with reasonable cost and reproducibility.

A Multi-Omics Database for Parasitic Nematodes and Trematodes

Helminth.net ( www.helminth.net ) is a web-based resource that was launched in 2000 as simply " Nematode.net " to host and investigate gene sequences from nematode genomes. Over the years it has evolved to become the moniker for a collection of databases: Nematode.net and Trematode.net . These databases host information for 73 nematode (roundworms) and 17 trematode (flatworms) species and serve as backbone for a number of tools that allow users to query slices of the data for multifactorial combinations of species-omics properties. Recent focus has been on inclusion of gene and protein expression data, population genomics and cross-kingdom interactions (metagenomics datasets). This chapter describes the website, the available tools and some of the new features.