Le-Viet, T. | Search bioRxiv

bioRxiv2021

Linking carbohydrate structure with function in the human gut microbiome using hybrid metagenome assemblies

BackgroundComplex carbohydrates that escape digestion in the small intestine, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between particular microbes and the host, resulting in metabolic products that influence host gut health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes is not fully understood. Here we take the approach of combining data from long and short read sequencing allowing recovery of large numbers of high quality genomes, from which we can predict carbohydrate degrading functions, and impact of carbohydrate on microbial communities. ResultsIn this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. We found dynamic variations in the microbiome amongst carbohydrate treatments, and over time. Using these data, the MAGs were characterised as primary (0h to 6h) and secondary degraders (12h to 24h). Annotating the MAGs with the Carbohydrate Active Enzyme (CAZyme) database we are able to identify species which are enriched through time and have the potential to actively degrade carbohydrate substrates. ConclusionsRecent advances in sequencing technology allowed us to identify significant unexplored diversity amongst starch degrading species in the human gut microbiota including CAZyme profiles and complete MAGs. We have identified changes in microbial community composition in response to structurally distinct carbohydrate substrates, which can be directly related to the CAZyme complement of the enriched MAGs. Through this approach, we have identified a number of species which have not previously been implicated in starch degradation, but which have the potential to play an important role.

microbiology↗

bioRxiv2020

CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with [≥] 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.

genomics↗