Abstract
BackgroundBiogas production is an attractive technology for a sustainable generation of renewable energy. Although the microbial community is fundamental for such production, the process control is still limited to technological and chemical parameters. Currently, most of the efforts on microbial management system (MiMaS) are focused on process-specific marker species and community dynamics, but a practical implementation is in its infancy. The high number of unknown and uncharacterized microorganisms in general is one of the reasons hindering further advancements.ResultsA Biogas Metagenomics Hybrid Assembly (BioMETHA) database, derived from microbiomes of biogas plants, was generated using a dedicated assembly strategy for different metagenomic datasets. Long reads from nanopore sequencing (MinION) were combined with short, more accurate second-generation sequencing reads (Illumina). The hybrid assembly resulted in 231 genomic bins each representing a taxonomic unit with an average completeness of 47%. Functional annotation identified 13,190 non-redundant genes covering roughly 207 k coding sequences. Mapping rates of metagenomics DNA derived from diverse biogas plants and laboratory reactors increased up to 73%. In addition, an EC (enzyme commission) reference sequence collection (ERSC) was generated whose genes are crucial for biogas-related processes, consisting of 235 unique EC numbers organized in 52 metabolic modules. Mapping rates of metatranscriptomic data to this ERSC revealed coverages of up to 93%. Process parameters and imbalances of laboratory reactors could be reconstructed by evaluating abundance of biogas-specific metabolic modules using metatranscriptomic data derived from various fermenter systems.ConclusionThis newly established metagenomic hybrid assembly in combination with an EC reference sequence collection might help to shed light on the microbial dark matter of biogas plants by contributing to the development of a reference for biogas plant microbiome-specific gene sequences. Considering a biogas microbiome as a complex meta-organism expressing a meta-transcriptome, the approach established here could lay the foundation for a function-based microbial management system.
Highlights
Biogas production is an attractive technology for a sustainable generation of renewable energy
Establishment of BioMETHA—a comprehensive biogas metagenomics database Assembly of short sequencing reads has some inherent difficulties related to genomes containing tandem repeats that can span over thousands of bases [8]
For BioMETHA assembly, we combined 154.3 million Illumina quality-trimmed read pairs with 326,223 quality-trimmed MinION reads revealing a mean length of 3852 bp generated from biogas plants 1–4 (Table 1 and Additional file 1)
Summary
Biogas production is an attractive technology for a sustainable generation of renewable energy. The microbial community is fundamental for such production, the process control is still limited to technological and chemical parameters. Most of the efforts on microbial management system (MiMaS) are focused on process-specific marker species and community dynamics, but a practical implementation is in its infancy. Anaerobic digestion (AD) combines organic waste management with the generation of biogas (methane), as a renewable source of energy. Microbial communities are fundamental for biogas production, the regulation of the underlying processes is still based on optimization of technical and chemical parameters yet. The need for microbial management and monitoring systems (MiMaS) has been highlighted and many efforts have been made to optimize them [2, 3]. Existing databases still are limited to fully cover the phylogenic diversity and metabolic potential of many different environmental sources used to seed biogas plants
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
