Aged intestinal stem cells propagate cell-intrinsic sources of inflammaging in mice.

Low-grade chronic inflammation is a hallmark of ageing, associated with impaired tissue function and disease development. However, how cell-intrinsic and -extrinsic factors collectively establish this phenotype, termed inflammaging, remains poorly understood. We addressed this question in the mouse intestinal epithelium, using mouse organoid cultures to dissect stem cell-intrinsic and -extrinsic sources of inflammaging. At the single-cell level, we found that inflammaging is established differently along the crypt-villus axis, with aged intestinal stem cells (ISCs) strongly upregulating major histocompatibility complex class II (MHC-II) genes. Importantly, the inflammaging phenotype was stably propagated by aged ISCs in organoid cultures and associated with increased chromatin accessibility at inflammation-associated loci in vivo and ex vivo, indicating cell-intrinsic inflammatory memory. Mechanistically, we show that the expression of inflammatory genes is dependent on STAT1 signaling. Together, our data identify that intestinal inflammaging in mice is promoted by a cell-intrinsic mechanism, stably propagated by ISCs, and associated with a disbalance in immune homeostasis.

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data.

BACKGROUND: Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. RESULTS: To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community. CONCLUSIONS: Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used.

Prediction of Protein Configurational Entropy (Popcoen).

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

Luminopsins integrate opto- and chemogenetics by using physical and biological light sources for opsin activation.

Luminopsins are fusion proteins of luciferase and opsin that allow interrogation of neuronal circuits at different temporal and spatial resolutions by choosing either extrinsic physical or intrinsic biological light for its activation. Building on previous development of fusions of wild-type Gaussia luciferase with channelrhodopsin, here we expanded the utility of luminopsins by fusing bright Gaussia luciferase variants with either channelrhodopsin to excite neurons (luminescent opsin, LMO) or a proton pump to inhibit neurons (inhibitory LMO, iLMO). These improved LMOs could reliably activate or silence neurons in vitro and in vivo. Expression of the improved LMO in hippocampal circuits not only enabled mapping of synaptic activation of CA1 neurons with fine spatiotemporal resolution but also could drive rhythmic circuit excitation over a large spatiotemporal scale. Furthermore, virus-mediated expression of either LMO or iLMO in the substantia nigra in vivo produced not only the expected bidirectional control of single unit activity but also opposing effects on circling behavior in response to systemic injection of a luciferase substrate. Thus, although preserving the ability to be activated by external light sources, LMOs expand the use of optogenetics by making the same opsins accessible to noninvasive, chemogenetic control, thereby allowing the same probe to manipulate neuronal activity over a range of spatial and temporal scales.

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.