Biology subjects

Michaelsen, T. Y.

Publications and source records attributed to Michaelsen, T. Y..

4 recordsLinked to original sources

bioRxiv2021

Assessing long-read sequencing with Nanopore R9, R10, and PacBio CCS to obtain high-quality metagenome assembled genomes from complex microbial communities

Long-read Oxford Nanopore sequencing has democratized microbial genome sequencing and enables the recovery of highly contiguous microbial genomes from isolates or metagenomes. However, to obtain near-perfect genomes it has been necessary to include short-read polishing to correct insertions and deletions derived from homopolymer regions. Here, we show that Oxford Nanopore R10.4 can be used to generate near-perfect microbial genomes from isolates or metagenomes without shortread or reference polishing.

microbiology↗

bioRxiv2021

Infection, recovery and re-infection of farmed mink with SARS-CoV-2

Mink, on a farm with about 15,000 animals, became infected with SARS-CoV-2. Over 75% of tested animals were positive for SARS-CoV-2 RNA in throat swabs and 100% of tested animals were seropositive. The virus responsible had a deletion of nucleotides encoding residues H69 and V70 within the spike protein gene. The infected mink recovered and after free-testing of the mink, the animals remained seropositive. During follow-up studies, after a period of more than 2 months without virus detection, over 75% of tested animals scored positive again for SARS-CoV-2 RNA. Whole genome sequencing showed that the virus circulating during this re-infection was most closely related to the virus identified in the first outbreak on this farm but additional sequence changes had occurred. Animals had much higher levels of anti-SARS-CoV-2 antibodies after re-infection than at free-testing. Thus, following recovery from an initial infection, seropositive mink rapidly became susceptible to re-infection by SARS-CoV-2. Article Summary LineFollowing widespread infection with SARS-CoV-2 of mink on a farm, all tested animals had seroconverted and the farm was then tested free of infection; however, less than 3 months later, a further round of infection affected more than 75% of tested animals.

microbiology↗

bioRxiv2020

Connecting structure to function with the recovery of over 1000 high-quality activated sludge metagenome-assembled genomes encoding full-length rRNA genes using long-read sequencing

Microorganisms are critical to water recycling, pollution removal and resource recovery processes in the wastewater industry. While the structure of this complex community is increasingly understood based on 16S rRNA gene studies, this structure cannot currently be linked to functional potential due to the absence of high-quality metagenome-assembled genomes (MAGs) with full-length rRNA genes for nearly all species. Here, we sequence 23 Danish full-scale wastewater treatment plant metagenomes, producing >1 Tbp of long-read and >0.9 Tbp of short-read data. We recovered 1083 high-quality MAGs, including 57 closed circular genomes. The MAGs accounted for ~30% of the community, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We show how novel high-quality MAGs in combination with >13 years of amplicon data, Raman microspectroscopy and fluorescence in situ hybridisation can be used to uncover abundant undescribed lineages belonging to important functional groups.

microbiology↗

bioRxiv2019

The signal and the noise - characteristics of antisense RNA in complex microbial communities

High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With the onset of metatranscriptomics, it is now possible to interrogate the transcriptome of multiple organisms simultaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe relationships between gene expression levels and community characteristics. However, metatranscriptomic datasets contain a rich suite of additional information which is just beginning to be explored. In this minireview we discuss the different computational strategies for handling antisense expression in metatranscriptomic samples and highlight their potentially detrimental effects on downstream analysis and interpretation. We also surveyed the antisense transcriptome of multiple genomes and metagenome-assembled genomes (MAGs) from five different datasets and found high variability in the level of antisense transcription for individual species which were consistent across samples. Importantly, we tested the hypothesis that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from a compounded effect of both random, biological and technical factors. Antisense transcription can provide a rich set of information, from technical details about data quality to novel insight into the biology of complex microbial communities.\n\nKey pointsO_LISeveral fundamentally different approaches are used to handle antisense RNA\nC_LIO_LIPrevalence of antisense RNA is highly variable between communities, genomes, and genes.\nC_LIO_LIAntisense RNA is likely an opaque mixture of technical, biological and random effects\nC_LI

microbiology↗