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Fabbrini et al. Microbiome Res Rep 2023;2:25 Microbiome Research
DOI: 10.20517/mrr.2023.25
Reports

Review Open Access

Connect the dots: sketching out microbiome
interactions through networking approaches

2
2,#
Marco Fabbrini 1,2,# , Daniel Scicchitano , Marco Candela , Silvia Turroni 2 , Simone Rampelli 2
1
Microbiomics Unit, Department of Medical and Surgical Sciences, University of Bologna, Bologna 40138, Italy.
2
Unit of Microbiome Science and Biotechnology, Department of Pharmacy and Biotechnology, University of Bologna, Bologna
40126, Italy.
#
Authors contributed equally.
Correspondence to: Prof. Silvia Turroni, Unit of Microbiome Science and Biotechnology, Department of Pharmacy and
Biotechnology, University of Bologna, Via Belmeloro 6, Bologna 40126, Italy. E-mail: silvia.turroni@unibo.it
How to cite this article: Fabbrini M, Scicchitano D, Candela M, Turroni S, Rampelli S. Connect the dots: sketching out
microbiome interactions through networking approaches. Microbiome Res Rep 2023;2:25.
https://dx.doi.org/10.20517/mrr.2023.25
Received: 14 Apr 2023 First Decision: 21 Jun 2023 Revised: 5 Jul 2023 Accepted: 12 Jul 2023 Published: 18 Jul 2023

Academic Editor: Gabriele Andrea Lugli Copy Editor: Lin He Production Editor: Lin He

Abstract
Microbiome networking analysis has emerged as a powerful tool for studying the complex interactions among
microorganisms in various ecological niches, including the human body and several environments. This analysis has
been used extensively in both human and environmental studies, revealing key taxa and functional units peculiar to
the ecosystem considered. In particular, it has been mainly used to investigate the effects of environmental
stressors, such as pollution, climate change or therapies, on host-associated microbial communities and ecosystem
function. In this review, we discuss the latest advances in microbiome networking analysis, including methods for
constructing and analyzing microbiome networks, and provide a case study on how to use these tools. These
analyses typically involve constructing a network that represents interactions among microbial taxa or functional
units, such as genes or metabolic pathways. Such networks can be based on a variety of data sources, including 16S
rRNA sequencing, metagenomic sequencing, and metabolomics data. Once constructed, these networks can be
analyzed to identify key nodes or modules important for the stability and function of the microbiome. By providing
insights into essential ecological features of microbial communities, microbiome networking analysis has the
potential to transform our understanding of the microbial world and its impact on human health and the
environment.
Keywords: Microbial networks, network interaction, network topology, ecological networks, community modeling,
network approaches, shotgun metagenomics

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

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