MICHELINdb – a new online platform for mining available data on worm-microbiome crosstalk

Today, Riccardo Scotti and Cinzia Cantacessi discuss the 'MICrobiome HELminth INteractions database' (MICHELINdb), an online resource created to facilitate the mining of worm-microbiota interaction datasets. The database is described in full in their paper Scotti et al.,  published recently in Microbiome.

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In the world, over 1.5 billion people are infected by parasitic helminths (worms), mainly in areas of Africa, South America and South-East Asia characterised by poor sanitation and sub-optimal hygiene standards. Moreover, worms of livestock significantly affect the health and welfare of infected animals, leading to dramatic production losses for farmers worldwide and representing a major food safety concern.

Worm infections are traditionally treated with the administration of anthelmintic drugs in both humans and animals; however, resistance to all classes of wormers is widespread in parasites of livestock, and there is a significant risk that worms of humans will develop similar strategies to survive drug treatment. Thus, fundamental knowledge of the biology of parasites and of their interactions with the human and animal hosts is necessary in order to find new ‘Achille’s heels’ that might be targeted in future studies aimed to discover new means of worm control.

Uncovering the nature of this crosstalk might lead to new ways to control worm infections

Over the past few decades, research into host-parasite interaction mechanisms has largely involved two players: the worm and the human or animal host. Nevertheless, another major player is likely to participate in this crosstalk, i.e. the gut microbiome. Indeed, a large proportion of worms live in the host gastrointestinal tract, thus sharing their ‘home’ with trillions of bacteria, viruses and eukaryotes with key functions in host nutrition, immune development and defense against pathogens. Therefore, it is likely that the strategies that worms employ to colonise the host gut might be dependent, at least in part, on communications with the host microbiota. Thus, uncovering the nature of this crosstalk might lead to new ways to control worm infections.

Research into parasite-microbiota crosstalk is booming; however, data published thus far is riddled with inconsistent and often contradictory findings. Moreover, comparisons between datasets generated in different host-parasite pairs are made difficult by the sheer variety of experimental protocols and microbiota characterisation techniques that might significantly affect the data.

In order to facilitate the logical mining of worm-microbiota interaction datasets, we developed the MICrobiome HELminth INteraction database (MICHELINdb), an online-based freely available platform in which information generated from individual studies of helminth-microbiota interactions are stored together with associated metadata on host and parasite species, infection site, sample type and metagenomic sequencing strategy (amongst others), and links to raw sequence data and published papers.

By increasing the accessibility of these datasets, we aim to provide the scientific community with a platform to identify gut microbial signatures that occur across several host-helminth systems, and facilitate the design of experiments aimed to disentangle the cause(s) and effect(s) of helminth-microbiota relationships.

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