RESULTS: Leveraging the power of both Illumina short-reads and Nanopore long-reads, we employed an Illumina-Nanopore hybrid assembly approach to construct MAGs with enhanced quality. The dereplication process, facilitated by the dRep tool, validated the efficiency of the hybrid assembly, yielding MAGs that reflected the intricate microbial diversity of these extreme ecosystems. The comprehensive analysis of these MAGs uncovered intriguing insights into the survival strategies of thermophilic taxa in the hot spring biofilms. Moreover, we examined the plant litter degradation potential within the biofilms, shedding light on the participation of diverse microbial taxa in the breakdown of starch, cellulose, and hemicellulose. We highlight that Chloroflexota and Armatimonadota MAGs exhibited a wide array of glycosyl hydrolases targeting various carbohydrate substrates, underscoring their metabolic versatility in utilisation of carbohydrates at elevated temperatures.
CONCLUSIONS: This study advances understanding of microbial ecology on plant litter under elevated temperature by revealing the functional adaptation of MAGs from hot spring biofilms. In addition, our findings highlight potential for biotechnology application through identification of thermophilic lignocellulose-degrading enzymes. By demonstrating the efficiency of hybrid assembly utilising Illumina-Nanopore reads, we highlight the value of combining multiple sequencing methods for a more thorough exploration of complex microbial communities.
CONCLUSION: The identification of a core microbiome furthers our understanding of mangrove microbial biodiversity, particularly in Southeast Asia where studies such as this are rare. The identification of significantly different microbial communities between sampling sites suggests environmental filtering is occurring, with hosts selecting for a microbial consortia most suitable for survival in their immediate environment. As climate change advances, many of these microbial communities are predicted to change, however, without knowing what is currently there, it is impossible to determine the magnitude of any deviations. This work provides an important baseline against which change in microbial community can be measured.
RESULTS: Here we combine quantitative microbiome profiling (QMP; parallelization of amplicon sequencing and 16S rRNA qPCR to estimate cell counts) and absolute resistome profiling (based on high-throughput qPCR) to quantify AR along an anthropogenically impacted river. We show QMP overcomes biases caused by relative taxa abundance data and show the benefits of using unified Hill number diversities to describe environmental microbial communities. Our approach overcomes weaknesses in previous methods and shows Hill numbers are better for QMP in diversity characterisation.
CONCLUSIONS: Methods here can be adapted for any microbiome and resistome research question, but especially providing more quantitative data for QMRA and other environmental applications.