Networks encode the interactions between the components in complex systems and play an essential role in understanding complex systems. Microbial ecological networks provide a system-level insight for comprehensively understanding complex microbial interactions, which play important roles in microbial community assembly. However, microbial ecological networks are in their infancy of both network inference and biological interpretation. In this perspective, we articulate the theory gaps and limitations in building and interpreting microbial ecological networks, emphasize developing tools for evaluating the predicted microbial interaction relationships, and predict the potential applications of microbial ecological networks in the long run.

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The isolation chip method (iChip) provides a novel approach for culturing previously uncultivable microorganisms; this method is currently limited by the user being unable to ensure single-cell loading within individual wells. To address this limitation, we integrated flow cytometry-based fluorescence-activated cell sorting with a modified iChip (FACS-iChip) to effectively mine microbial dark matter in soils. This method was used for paddy soils with the aim of mining uncultivable microorganisms and making preliminary comparisons between the cultured microorganisms and the bulk soil via 16S rRNA gene sequencing. Results showed that the FACS-iChip achieved a culture recovery rate of almost 40% and a culture retrieval rate of 25%. Although nearly 500 strains were cultured from 19 genera with 8 FACS-iChip plates, only six genera could be identified via 16S rRNA gene amplification. This result suggests that the FACS-iChip is capable of detecting strains in the currently dead spaces of PCR-based sequencing technology. We, therefore, conclude that the FACS-iChip system provides a highly efficient and readily available approach for microbial 'dark matter' mining. Keywords FACS-iChip • Microbial 'dark matter' • In situ cultivation • Single cell sorting SPECIAL TOPIC: Cultivation of the uncultured microorganisms. Haoze Liu, Ran Xue and Yiling Wang contributed equally. Edited by Chengchao Chen.

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