Microbiome definition re-visited: old concepts and new challenges

peer-reviewedAbstract The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term “microbiome.” Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role. Video Abstrac

Factor H-related protein 1 drives disease susceptibility and prognosis in C3 glomerulopathy

17 p.-8 fig.Background: C3 glomerulopathy (C3G) is a heterogeneous group of chronic renal diseases characterized predominantly by glomerular C3 deposition and complement dysregulation. Mutations in factor H-related (FHR) proteins resulting in duplicated dimerization domains are prototypical of C3G, although the underlying pathogenic mechanism is unclear.Methods: Using in vitro and in vivo assays, we performed extensive characterization of an FHR-1 mutant with a duplicated dimerization domain. To assess the FHR-1 mutant's association with disease susceptibility and renal prognosis, we also analyzed CFHR1 copy number variations and FHR-1 plasma levels in two Spanish C3G cohorts and in a control population.Results: Duplication of the dimerization domain conferred FHR-1 with an increased capacity to interact with C3-opsonized surfaces, which resulted in an excessive activation of the alternative pathway. This activation does not involve C3b binding competition with factor H. These findings support a scenario in which mutant FHR-1 binds to C3-activated fragments and recruits native C3 and C3b; this leads to formation of alternative pathway C3 convertases, which increases deposition of C3b molecules, overcoming FH regulation. This suggests that a balanced FHR-1/FH ratio is crucial to control complement amplification on opsonized surfaces. Consistent with this conceptual framework, we show that the genetic deficiency of FHR-1 or decreased FHR-1 in plasma confers protection against developing C3G and associates with better renal outcome.Conclusions: Our findings explain how FHR-1 mutants with duplicated dimerization domains result in predisposition to C3G. They also provide a pathogenic mechanism that may be shared by other diseases, such as IgA nephropathy or age-related macular degeneration, and identify FHR-1 as a potential novel therapeutic target in C3G.E. Goicoechea de Jorge is supported by Ministerio de Ciencia e Innovación grant RTI2018-095955-B-100 and the European Union’s Horizon 2020 Framework Programme grant 899163. J. Gutiérrez-Tenorio is supported by Ministerio de Ciencia e Innovación grant BES-2015-073833. L. Lucientes Continente is supported by the Autonomous Region of Madrid grant S2017/BMD-3673. G. Fernández-Juarez, P. Sánchez-Corral, B. Márquez-Tirado, and M. Praga are supported by the Instituto de Salud Carlos III and the European Union’s European Regional Development Fund grants PI19/01695, PI19/00970, and PI19/01624, respectively. M.C. Pickering is a Wellcome Trust Senior Fellow in Clinical Science (212252/Z/18/Z). S. Rodríguez de Córdoba is supported by the Ministerio de Economía y Competitividad grant PID2019-104912RB-100 and Autonomous Region of Madrid grant S2017/BMD-3673.Peer reviewe

Microbiome definition re-visited: old concepts and new challenges

Abstract The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term “microbiome.” Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role. Video Abstrac

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts