The time period of engineers handling unit operations powered by mixed microbial communities as a “black box” in their process are predicted to draw to a rapid close as the constantly evolving toolset available to explore the microbial ecology of niche habitats increasingly enables resolution of microbial communities to be carried out on a much more frequent and rigorous basis. This opens the potential for using microbial ecology as a monitoring tool to inform the process operation, and potentially design, of mixed culture microbial processes in industrial contexts. One such example is the biomining sector where mixed microbial communities are key in both value recovery and remediation processes.
In this paper, two case studies are presented to demonstrate the power of both quantitative and qualitative approaches for unravelling microbial communities in biomining. In the first, we focus on the bioleaching of mineral sulphides for value recovery. It is well recognised that these processes cycle through both temperature and physicochemical environments as the leaching process progresses, the extremity depending on process configuration. We use quantitative real-time PCR, 16S rRNA gene surveys and fluorescent in situ hybridization as tools in regular monitoring of the bacterial and archaeal components of the community facilitating mineral bioleaching in tank or heap systems. Through tracking of the dominant community members over time and spatially and relating these to the metadata on the physicochemical environment and process performance, we introduce insights into key operational aspects of these bioleaching processes for metal recovery. In the second case study, we report further on the potential to integrate understanding of the community diversity and dynamics, as well as its functional potential, derived from a metagenomics approach to propose key approaches to process optimisation, using the remediation of thiocyanate-bearing wastewaters as an example. The potential to build an integrated toolbox for exploiting knowledge of microbial ecology in the process environment is proposed, spanning the need for deep understanding of the community dynamics through to diagnostic monitoring.