Rethinking about the sustainability of natural resources has become a hot topic in today’s world. Seeking renewable resources and utilization of new technologies are the potential means to cope with the challenges facing society such as scarcity of resources and environmental pollution. Many underlying resources including cellulose, chitin, and keratin are being exploited to satisfy the needs of industrial development. Keratinous materials are one of the most abundant proteins from vertebrates, representing an enormous feasible protein source, particularly from the commercial slaughterhouses or poultry farms. Nevertheless, keratin possesses unique biological characteristics such as insolubility and complicated molecular structures. The complete keratinolytic process is still not clarified clearly. Many attempts have been made to hydrolyze keratinous materials in terms of physicochemical treatment and enzymatic hydrolysis. Nevertheless, these approaches still have evident defects with regard to efficiency, environmental harm and practicality. A new strategy needs to be developed, raising the potential values and expanding the application prospect to keratinous materials.
The major objective of this research project has therefore been to try and explore the novel perspective to valorize keratinous materials using microbial consortia. This thesis is composed of four themed chapters. In the introductory thesis chapter, the structural characteristics of keratin and the potential application values are introduced and subsequently the current main methods used to hydrolyze keratinous materials are presented. Thereafter, the focus shifts to the mechanism of keratinolysis on the basis of different processing methods. Following, I describe several considerable aspects to determine the optimal approach for the valorization of keratinous materials. In the end, microbial consortia and metagenomics are proposed for extensive applications in bioconversion, which also possess a great potential to probe into keratin degradation. This PhD-thesis has resulted in one published manuscript in a peerreviewed journal and the production of two draft manuscripts. All three manuscripts are the result of a sequential logical effort to explore ways of keratinous valorization.
Manuscript I describes the enrichment process of microbial consortium KMCG6 from environmental samples. KMCG6 possesses efficient keratinolytic activity and high degrading reproducibility. The compositional change of microbes was observed based on 16s rRNA gene amplicon sequencing along with the sequential cultivation. Additionally, the nutrient content of keratin substrates was analyzed before and after microbial degradation. This explains that microbial consortia can be obtained and used to degrade keratinous materials effectively.
The enriched KMCG6 is high in diversity with more 21 dominating OTUs, which may cause potential problems in terms of controllability and applied prospect. In Manuscript II, we applied the dilution-to-extinction cultures to construct various simplified microbial consortia through optimizing the dilution and functional assessment. The relationship between different strains was evaluated by using correlation network. This study demonstrates that simplified microbial consortia can be constructed from KMCG6 via the strategy combining enrichment and dilution-to-extinction cultures. This strategy is also expected to be transferred into other fields associated with microbial consortia.
The metagenomics analysis of KMCG6 was extended in Manuscript III, where functional potential, peptidase families and keratinases were predicted from metagenome to thoroughly understand the enzymatic activities in the degrading process. The microbial genomes were reconstructed from metagenome and the metabolic pathways that may have an association to keratin hydrolysis were mapped to the genomes. This work discovers the potential keratinases and cellular metabolic activities, which could contribute to revealing the degradation mechanism and valorization of keratinous materials.