The ecological network approach to algal-bacterial relationships: Review and prospects

Abstract

<p indent=0mm>Algae and bacteria numerically dominate oceanic and freshwater planktonic communities. They play a central biogeochemical role in the marine ecosystem, including producing biomass to support aquatic food webs, cycling nutrients and trace elements, and decomposing organic matter. Algae and bacteria synergistically affect each other’s physiology and metabolism and have coexisted ever since the early stages of evolution that revolutionized many aspects of life on Earth. The relationship between algae and bacteria influences ecosystems and represents all conceivable modes of interaction from mutualism to parasitism. The interactions between these two groups of plankton, and the influence of their interaction on each other and on a global scale have, therefore, become the focus of recent research interest. Previous studies have summarized a variety of algal-bacterial interactions and aimed to reveal the essence of those interactions. However, it is clear that their interactions are diverse and not static, and can be initiated and broken in response to environmental and developmental cues. Traditional research methods have been unable to reveal the complexity behind algal-bacterial symbiosis. As microbial omics technology has developed and the influence of global change on marine ecosystems has become apparent, the research perspective on algal-bacterial relationships has gradually risen to the level of systemic ecology. The rapid-blooming of high-throughput sequencing technology and the ability to analyze big data offer new opportunities for a thorough study of algal-bacterial interaction. Ecological networks are prominent among these new methods: They can integrate multiple types of information and might represent systems-level behavior. Network theory methods are powerful approaches for quantifying relationships between biological components and their relevance to phenotypes, environmental conditions or other external variables within a system. In this paper, we review the research advances in the algal-bacterial ecological network based on big data. We begin by introducing the network parameters and attributes commonly used in ecological network analysis and review the existing network modeling methods in microbial studies and algorithm features and application scenarios. By comparing some common algorithms or software, researchers can choose appropriate network construction methods when confronted with different data characteristics. Next, the ecological network analysis used in the study of algal-bacterial relationships is presented at multiple layers from taxonomy to function (e.g., molecular and metabolic networks). The problems and experiences encountered during research into algal-bacterial relationships are then discussed. For example, when focusing on the interaction between host and microorganism, the time/space shift correlations among the variables will lead to wrong conclusions, including false-positive or false-negative results. We also attempt to introduce metabolic and dynamic biological networks into the study of the algal-bacterial relationship to reveal further the mechanism of their interaction from the perspectives of function and causality. Finally, our novel proposal to establish a knowledge network database of algal-bacterial interactions and a graphic database of photosphere biological profiles is discussed. We highlight the need for microbial ecological network inference and suggest strategies to infer networks more reliably. Our study aimed to explore the holistic information behind algal-bacterial relationships and provide new cues for further revealing the molecular mechanisms of algal-bacterial interactions.