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Hercog, R.

Publications and source records attributed to Hercog, R..

2 recordsLinked to original sources

Drivers and Determinants of Strain Dynamics Following Faecal Microbiota Transplantation

Faecal microbiota transplantation (FMT) is an efficacious therapeutic intervention, but its clinical mode of action and underlying microbiome dynamics remain poorly understood. Here, we analysed the metagenomes associated with 142 FMTs, in a time series-based meta-study across five disease indications. We quantified strain-level dynamics of 1,089 microbial species based on their pangenome, complemented with 47,548 newly constructed metagenome-assembled genomes. Using subsets of procedural-, host- and microbiome-based variables, LASSO-regularised regression models accurately predicted the colonisation and resilience of donor and recipient microbes, as well as turnover of individual species. Linking this to putative ecological mechanisms, we found these sets of variables to be informative of the underlying processes that shape the post-FMT gut microbiome. Recipient factors and complementarity of donor and recipient microbiomes, encompassing entire communities to individual strains, were the main determinants of individual strain population dynamics, and mostly independent of clinical outcomes. Recipient community state and the degree of residual strain depletion provided a neutral baseline for donor strain colonisation success, in addition to inhibitive priority effects between species and conspecific strains, as well as putatively adaptive processes. Our results suggest promising tunable parameters to enhance donor flora colonisation or recipient flora displacement in clinical practice, towards the development of more targeted and personalised therapies.

microbiology↗

Extensive OMICS resource for Sf21 and Tni cell lines

Insect-derived cell lines, from Spodoptera frugiperda (Sf21) and from Trichoplusia ni (Tni), are the two most widely used cell lines for recombinant protein expression in combination with the Baculoviral Expression Vector System (BEVS). Genomic sequences and annotations are still incomplete for Sf21 and absent for Tni. In this study, we present an approach using different sequencing data types, including short-read sequencing, long synthetic and Oxford Nanopore reads, to build genomes. The Sf21 and Tni assemblies contain 4,020 scaffolds of 463 Mb in size with N50 of 364 Kb and 2,954 scaffolds of 332 Mb in size with N50 of 326 Kb, respectively. Furthermore, we built a new gene prediction workflow, which integrates transcriptome and proteome information using pre-existing tools. Using this approach, we predicted 21,506 Sf21 and 14,159 Tni genes, generated and integrated proteomic datasets to validate predicted genes and could identify 5577 and 4919 proteins in the Sf21 and Tni cell lines respectively. This integrative approach could be theoretically applied to any uncharacterized genome and result in valuable new resources. With this information available, Sf21 and Tni cells will become even better tools for protein expression and could be used in a wider range of applications, from promoter identification to genome engineering and editing.

genomics↗