Comparison of transformations for single-cell RNA-seq data.

The count table, a numeric matrix of genes × cells, is the basic input data structure in the analysis of single-cell RNA-sequencing data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so that the variance is similar across the dynamic range. These steps are intended to make subsequent application of generic statistical methods more palatable. Here, we describe four transformation approaches based on the delta method, model residuals, inferred latent expression state and factor analysis. We compare their strengths and weaknesses and find that the latter three have appealing theoretical properties; however, in benchmarks using simulated and real-world data, it turns out that a rather simple approach, namely, the logarithm with a pseudo-count followed by principal-component analysis, performs as well or better than the more sophisticated alternatives. This result highlights limitations of current theoretical analysis as assessed by bottom-line performance benchmarks.

The S-palmitoylome and DHHC-PAT interactome of Drosophila melanogaster S2R+ cells indicate a high degree of conservation to mammalian palmitoylomes.

Protein S-palmitoylation, the addition of a long-chain fatty acid to target proteins, is among the most frequent reversible protein modifications in Metazoa, affecting subcellular protein localization, trafficking and protein-protein interactions. S-palmitoylated proteins are abundant in the neuronal system and are associated with neuronal diseases and cancer. Despite the importance of this post-translational modification, it has not been thoroughly studied in the model organism Drosophila melanogaster. Here we present the palmitoylome of Drosophila S2R+ cells, comprising 198 proteins, an estimated 3.5% of expressed genes in these cells. Comparison of orthologs between mammals and Drosophila suggests that S-palmitoylated proteins are more conserved between these distant phyla than non-S-palmitoylated proteins. To identify putative client proteins and interaction partners of the DHHC family of protein acyl-transferases (PATs) we established DHHC-BioID, a proximity biotinylation-based method. In S2R+ cells, ectopic expression of the DHHC-PAT dHip14-BioID in combination with Snap24 or an interaction-deficient Snap24-mutant as a negative control, resulted in biotinylation of Snap24 but not the Snap24-mutant. DHHC-BioID in S2R+ cells using 10 different DHHC-PATs as bait identified 520 putative DHHC-PAT interaction partners of which 48 were S-palmitoylated and are therefore putative DHHC-PAT client proteins. Comparison of putative client protein/DHHC-PAT combinations indicates that CG8314, CG5196, CG5880 and Patsas have a preference for transmembrane proteins, while S-palmitoylated proteins with the Hip14-interaction motif are most enriched by DHHC-BioID variants of approximated and dHip14. Finally, we show that BioID is active in larval and adult Drosophila and that dHip14-BioID rescues dHip14 mutant flies, indicating that DHHC-BioID is non-toxic. In summary we provide the first systematic analysis of a Drosophila palmitoylome. We show that DHHC-BioID is sensitive and specific enough to identify DHHC-PAT client proteins and provide DHHC-PAT assignment for ca. 25% of the S2R+ cell palmitoylome, providing a valuable resource. In addition, we establish DHHC-BioID as a useful concept for the identification of tissue-specific DHHC-PAT interactomes in Drosophila.

glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data.

MOTIVATION: The Gamma-Poisson distribution is a theoretically and empirically motivated model for the sampling variability of single cell RNA-sequencing counts and an essential building block for analysis approaches including differential expression analysis, principal component analysis and factor analysis. Existing implementations for inferring its parameters from data often struggle with the size of single cell datasets, which can comprise millions of cells; at the same time, they do not take full advantage of the fact that zero and other small numbers are frequent in the data. These limitations have hampered uptake of the model, leaving room for statistically inferior approaches such as logarithm(-like) transformation. RESULTS: We present a new R package for fitting the Gamma-Poisson distribution to data with the characteristics of modern single cell datasets more quickly and more accurately than existing methods. The software can work with data on disk without having to load them into RAM simultaneously. AVAILABILITYAND IMPLEMENTATION: The package glmGamPoi is available from Bioconductor for Windows, macOS and Linux, and source code is available on github.com/const-ae/glmGamPoi under a GPL-3 license. The scripts to reproduce the results of this paper are available on github.com/const-ae/glmGamPoi-Paper. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Backbone circularization of Bacillus subtilis family 11 xylanase increases its thermostability and its resistance against aggregation.

The activity of proteins is dictated by their three-dimensional structure, the native state, and is influenced by their ability to remain in or return to the folded native state under physiological conditions. Backbone circularization is thought to increase protein stability by decreasing the conformational entropy in the unfolded state. A positive effect of circularization on stability has been shown for several proteins. Here, we report the development of a cloning standard that facilitates implementing the SICLOPPS technology to circularize proteins of interest using split inteins. To exemplify the usage of the cloning standard we constructed two circularization vectors based on the Npu DnaE and gp41-1 split inteins, respectively. We use these vectors to overexpress in Escherichia coli circular forms of the Bacillus subtilis enzyme family 11 xylanase that differ in the identity and number of additional amino acids used for circularization (exteins). We found that the variant circularized with only one additional serine has increased thermostability of 7 °C compared to native xylanase. The variant circularized with six additional amino acids has only a mild increase in thermostability compared to the corresponding exteins-bearing linear xylanase, but is less stable than native xylanase. However, this circular xylanase retains more than 50% of its activity after heat shock at elevated temperatures, while native xylanase and the corresponding exteins-bearing linear xylanase are largely inactivated. We correlate this residual activity to the fewer protein aggregates found in the test tubes of circular xylanase after heat shock, suggesting that circularization protects the protein from aggregation under these conditions. Taken together, these data indicate that backbone circularization has a positive effect on xylanase and can lead to increased thermostability, provided the appropriate exteins are selected. We believe that our cloning standard and circularization vectors will facilitate testing the effects of circularization on other proteins.