Biology subjects

Sorensen, S. J.

Publications and source records attributed to Sorensen, S. J..

5 recordsLinked to original sources

bioRxiv2018

The scent of symbiosis: gut bacteria affect social interactions in leafcutting ants

Animal gut microbiota affect host physiology and behaviour. In eusocial Hymenoptera, where colony-level integrity is preserved via a nestmate discrimination system based on cuticular hydrocarbon mixtures, microorganismal effects may influence social dynamics. Although nestmate recognition has undergone a thorough exploration during the last four decades, few studies have investigated the putative role of gut microbes. Here we integrate metagenomic, chemical and behavioural approaches to test whether gut microbes affect nestmate recognition in Acromyrmex echinatior leaf-cutting ants. Treating workers with a sterile diet or with antibiotics resulted in a substantial alteration of their gut microbial communities. In pairwise social interactions, untreated vs. antibiotic-treated nestmates behaved more aggressively than other nestmate and non-nestmate pairs, suggesting that the suppression of microbes indirectly alters chemical social cues and triggers aggressive behaviour. Chemical analyses on treated individuals revealed a decrease in the abundance of two metapleural gland antifungal compounds, and we confirmed the correspondence between aggression levels and chemical profile differences. Feeding microbiota-remodelled ants with conspecific faecal droplets partially restored the original bacterial communities. Furthermore, non-nestmates fed with faecal droplets from different colonies were unusually aggressive compared to pairs fed with faecal droplets from the same colony. This suggests that chemicals derived from microbial strains may shape nestmate recognition, opening novel questions about the role of microorganisms in the evolution of social behaviour.

evolutionary biology↗

bioRxiv2018

Deep mutational scanning by FACS-sorting of encapsulated E. coli micro-colonies

We present a method for high-throughput screening of protein variants where the signal is enhanced by micro-encapsulation of single cells into 20-30 m agarose beads. Cells inside beads are propagated using standard agitation in liquid media and grow clonally into micro-colonies harboring several hundred bacteria. We have, as a proof-of-concept, analyzed random amino acid substitutions in the five C-terminal {beta}-strands of the Green Fluorescent Protein (GFP). Starting from libraries of variants, each bead represents a clonal line of cells that can be separated by Fluorescence Activated Cell Sorting (FACS). Pools representing collections of individual variants with desired properties are subsequently analyzed by deep sequencing. Notably, the encapsulation approach described holds the potential for high-throughput analysis of systems where the fluorescence signal from a single cell is insufficient for detection. Fusion to GFP, or use of fluorogenic substrates, allows coupling protein levels or activity to sequence for a wide range of proteins. Here we analyzed more than 10,000 individual variants to gauge the effect of mutations on GFP-fluorescence. In the mutated region, we observed virtually all amino acid substitutions that are accessible by single nucleotide exchange. Lastly, we assessed the performance of biophysical protein stability predictors, FoldX and Rosetta, in predicting the outcome of the experiment. Both tools display good performance on average, suggesting that loss of thermodynamic stability is a key mechanism for the observed variation of the mutants. This, in turn, suggests that deep mutational scanning datasets may be used to more efficiently fine-tune such predictors, especially for mutations poorly covered by current biophysical data.

bioengineering↗

bioRxiv2018

DAtest: a framework for choosing differential abundance or expression method

DAtest is an R package for directly comparing different statistical methods for differential abundance and expression analysis on a dataset of interest; be it data from RNA-seq, proteomics, metabolomics or a microbial marker-gene survey. A myriad of statistical methods exists for conducting these analyses, and with this tool we give the analyst an empirical foundation for choosing a method suitable for a specific dataset. The package supports categorical and quantitative variables, paired/block experimental designs, and the inclusion of covariates. It is freely available at GitHub: https://github.com/Russel88/DAtest along with detailed instructions.

bioinformatics↗

bioRxiv2017

Plasmids, Viruses, And Other Circular Elements In Rat Gut

Circular DNA such as plasmids and some viruses is the major source of genetic variation in bacteria and thus has the same important evolutionary function as sexual reproduction in eukaryotic species: It allows dissemination of advantageous traits through bacterial populations. Here, we present the largest collection of novel complete extrachromosomal genetic elements to date, and compare the diversity, distribution, and content of circular sequences from 12 rat cecum samples from the pristine Falkland Islands and Danish hospital sewers, two environments with contrasting anthropogenic impact. Using a validated pipeline, we find 1,869 complete, circular, non-redundant sequences, of which only 114 are previously described. While sequences of similar size from the two environments share general features, the size distribution of the elements between environments differs significantly, with hospital sewer samples hosting larger circular elements than Falkland Island samples, a possible consequence of the massive anthropogenic influence in the hospital sewer environment. Several antibiotic resistance genes have been identified with a notably larger diversity in hospital sewer samples than in Falkland Islands samples in concordance with expectations. Our findings suggest that even though sequences of similar length carry similar traits, the mobilome of rat gut bacteria are affected by human activities in that sewer rats have larger elements and more diverse large elements than pristine island rats. More than 1000 novel and not classified small sequences was identified and hint the existence of a biological unit not previously described on a community level.\n\nList of figures O_LISampling sites and Rat gut anatomy\nC_LIO_LIRarefaction curves of circular elements\nC_LIO_LIElements shared between environments\nC_LIO_LISize distribution plots of rep, mob, stab, capsid carrying elements.\nC_LIO_LIGraphical representation of representative elements\nC_LIO_LIReplication genes content, diversity\nC_LIO_LIRep_2 plasmid replication gene phylogeny\nC_LIO_LITable Resfams findings\nC_LI\n\nList of appendices O_LIbasic statistics table\nC_LIO_LIPhylogeny of plasmid replication genes\nC_LIO_LIList of known plasmids and circular sequences found in 1869 elements\nC_LIO_LIAutomatic identification of identical circular elements with different breaking points\nC_LIO_LITest of separation of plasmids and viruses based on predicted, annotated genes\nC_LIO_LINo false positive circular sequences from MG1655 genomic sequencing.\nC_LI

microbiology↗

bioRxiv2017

Critical Assessment of Metagenome Interpretation - a benchmark of computational metagenomics software

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

bioinformatics↗