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Network analysis highlights complex interactions between pathogen, host and commensal microbiota.

ABSTRACT: Interactions between bacteria and their host represent a full continuum from pathogenicity to mutualism. From an evolutionary perspective, host-bacteria relationships are no longer considered a two-component system but rather a complex network. In this study, we focused on the relationship between brook charr (Salvelinus fontinalis) and bacterial communities developing on skin mucus. We hypothesized that stressful conditions such as those occurring in aquaculture production induce shifts in the bacterial community of healthy fish, thus allowing pathogens to cause infections. The results showed that fish skin mucus microbiota taxonomical structure is highly specific, its diversity being partly influenced by the surrounding water bacterial community. Two types of taxonomic co-variation patterns emerged across 121 contrasted communities' samples: one encompassing four genera well known for their probiotic properties, the other harboring five genera mostly associated with pathogen species. The homeostasis of fish bacterial community was extensively disturbed by induction of physiological stress in that both: 1) the abundance of probiotic-like bacteria decreased after stress exposure; and 2) pathogenic bacteria increased following stress exposure. This study provides further insights regarding the role of mutualistic bacteria as a primary host protection barrier.

SUBMITTER: Boutin S

PROVIDER: S-EPMC3871659 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Network analysis highlights complex interactions between pathogen, host and commensal microbiota.

Boutin Sébastien S Bernatchez Louis L Audet Céline C Derôme Nicolas N

PloS one 20131223 12

Interactions between bacteria and their host represent a full continuum from pathogenicity to mutualism. From an evolutionary perspective, host-bacteria relationships are no longer considered a two-component system but rather a complex network. In this study, we focused on the relationship between brook charr (Salvelinus fontinalis) and bacterial communities developing on skin mucus. We hypothesized that stressful conditions such as those occurring in aquaculture production induce shifts in the ...[more]

PMID: 24376845

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Project description:BackgroundIxodid ticks, particularly Rhipicephalus sanguineus s.l., are important vectors of various disease-causing agents in dogs and humans in Cuba. However, our understading of interactions among tick-borne pathogens (TBPs) in infected dogs or the vector R. sanguineus s.l. remains limited. This study integrates microfluidic-based high-throughput real-time PCR data, Yule's Q statistic, and network analysis to elucidate pathogen-pathogen interactions in dogs and ticks in tropical western Cuba.MethodsA cross-sectional study involving 46 client-owned dogs was conducted. Blood samples were collected from these dogs, and ticks infesting the same dogs were morphologically and molecularly identified. Nucleic acids were extracted from both canine blood and tick samples. Microfluidic-based high-throughput real-time PCR was employed to detect 25 bacterial species, 10 parasite species, 6 bacterial genera, and 4 parasite taxa, as well as to confirm the identity of the collected ticks. Validation was performed through end-point PCR assays and DNA sequencing analysis. Yule's Q statistic and network analysis were used to analyse the associations between different TBP species based on binary presence-absence data.ResultsThe study revealed a high prevalence of TBPs in both dogs and R. sanguineus s.l., the only tick species found on the dogs. Hepatozoon canis and Ehrlichia canis were among the most common pathogens detected. Co-infections were observed, notably between E. canis and H. canis. Significant correlations were found between the presence of Anaplasma platys and H. canis in both dogs and ticks. A complex co-occurrence network among haemoparasite species was identified, highlighting potential facilitative and inhibitory roles. Notably, H. canis was found as a highly interconnected node, exhibiting significant positive associations with various taxa, including A. platys, and E. canis, suggesting facilitative interactions among these pathogens. Phylogenetic analysis showed genetic diversity in the detected TBPs.ConclusionsOverall, this research enhances our understanding of TBPs in Cuba, providing insights into their prevalence, associations, and genetic diversity, with implications for disease surveillance and management.

Project description:BackgroundInfectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.ResultsAs host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins' marker.ConclusionsDifferent centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens' favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.

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Network analysis highlights complex interactions between pathogen, host and commensal microbiota.

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Network analysis highlights complex interactions between pathogen, host and commensal microbiota.

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