Structural Probing with MNase Tethered to Ribosome Assembly Factors Resolves Flexible RNA Regions within the Nascent Pre-Ribosomal RNA

The synthesis of ribosomes involves the correct folding of the pre-ribosomal RNA within pre-ribosomal particles. The first ribosomal precursor or small subunit processome assembles stepwise on the nascent transcript of the 35S gene. At the earlier stages, the pre-ribosomal particles undergo structural and compositional changes, resulting in heterogeneous populations of particles with highly flexible regions. Structural probing methods are suitable for resolving these structures and providing evidence about the architecture of ribonucleoprotein complexes. Our approach used MNase tethered to the assembly factors Nan1/Utp17, Utp10, Utp12, and Utp13, which among other factors, initiate the formation of the small subunit processome. Our results provide dynamic information about the folding of the pre-ribosomes by elucidating the relative organization of the 5′ETS and ITS1 regions within the 35S and U3 snoRNA around the C-terminal domains of Nan1/Utp17, Utp10, Utp12, and Utp13.

Deformation of the nucleus by TGFβ1 via the remodeling of nuclear envelope and histone isoforms

The cause of nuclear shape abnormalities which are often seen in pre-neoplastic and malignant tissues is not clear. In this study we report that deformation of the nucleus can be induced by TGFβ1 stimulation in several cell lines including Huh7. In our results, the upregulated histone H3.3 expression downstream of SMAD signaling contributed to TGFβ1-induced nuclear deformation, a process of which requires incorporation of the nuclear envelope (NE) proteins lamin B1 and SUN1. During this process, the NE constitutively ruptured and reformed. Contrast to lamin B1 which was relatively stationary around the nucleus, the upregulated lamin A was highly mobile, clustering at the nuclear periphery and reintegrating into the nucleoplasm. The chromatin regions that lost NE coverage formed a supra-nucleosomal structure characterized by elevated histone H3K27me3 and histone H1, the formation of which depended on the presence of lamin A. These results provide evidence that shape of the nucleus can be modulated through TGFβ1-induced compositional changes in the chromatin and nuclear lamina.

Effects of special additives in wheat dough system measured by Mixolab technique

Three novel bread additives were developed, namely wheat bran (WB), wheat aleurone-rich flour (ARF) fraction and germinated soybean [sprouted soy-based additive (YASO)]. Their applications were tested in bread dough systems. The additives showed different chemical compositions targeting different nutritional effects in bread. In each case, three different concentration ranges were used (WB 10–30%, ARF 10–30%, YASO 10–50%). Rheological differences were sensitively detected by the Mixolab technique in the mixed dough. So the rheological effects caused by compositional changes were reflected by the results of the above-mentioned technique. Based on Mixolab curves, optimal levels of applied additives (WB 14%, ARF 25% and YASO 30%) were defined. These are acceptable from a compositional and rheological point of view as well. The optimised mixtures were tested with the measurements of Rapid Visco Analyser (RVA) in slurry form, and characteristic effects of additives were observed. Based on Mixolab and RVA techniques, valuable rheological 'fingerprints' could be generated. These support the conscious and planned modification of rheological properties of bread products and the application of novel bread additives.

Assessing the Contribution of Seasonality, Tides, and Microbial Processing to Dissolved Organic Matter Composition Variability in a Southeastern U.S. Estuary

Uncovering which biogeochemical processes have a critical role controlling dissolved organic matter (DOM) compositional changes in complex estuarine environments remains a challenge. In this context, the aim of this study is to characterize the dominant patterns of variability modifying the DOM composition in an estuary off the Southeastern U.S. We collected water samples during three seasons (July and October 2014 and April 2015) at both high and low tides and conducted short- (1 day) and long-term (60 days) dark incubations. Samples were analyzed for bulk DOC concentration, and optical (CDOM) and molecular (FT-ICR MS) compositions and bacterial cells were collected for metatranscriptomics. Results show that the dominant pattern of variability in DOM composition occurs at seasonal scales, likely associated with the seasonality of river discharge. After seasonal variations, long-term biodegradation was found to be comparatively more important in the fall, while tidal variability was the second most important factor correlated to DOM composition in spring, when the freshwater content in the estuary was high. Over shorter time scales, however, the influence of microbial processing was small. Microbial data revealed a similar pattern, with variability in gene expression occurring primarily at the seasonal scale and tidal influence being of secondary importance. Our analyses suggest that future changes in the seasonal delivery of freshwater to this system have the potential to significantly impact DOM composition. Changes in residence time may also be important, helping control the relative contribution of tides and long-term biodegradation to DOM compositional changes in the estuary.

tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data

Accurate generative statistical modeling of count data is of critical relevance for the analysis of biological datasets from high-throughput sequencing technologies. Important instances include the modeling of microbiome compositions from amplicon sequencing surveys and the analysis of cell type compositions derived from single-cell RNA sequencing. Microbial and cell type abundance data share remarkably similar statistical features, including their inherent compositionality and a natural hierarchical ordering of the individual components from taxonomic or cell lineage tree information, respectively. To this end, we introduce a Bayesian model for tree-aggregated amplicon and single-cell compositional data analysis (tascCODA) that seamlessly integrates hierarchical information and experimental covariate data into the generative modeling of compositional count data. By combining latent parameters based on the tree structure with spike-and-slab Lasso penalization, tascCODA can determine covariate effects across different levels of the population hierarchy in a data-driven parsimonious way. In the context of differential abundance testing, we validate tascCODA’s excellent performance on a comprehensive set of synthetic benchmark scenarios. Our analyses on human single-cell RNA-seq data from ulcerative colitis patients and amplicon data from patients with irritable bowel syndrome, respectively, identified aggregated cell type and taxon compositional changes that were more predictive and parsimonious than those proposed by other schemes. We posit that tascCODA1 constitutes a valuable addition to the growing statistical toolbox for generative modeling and analysis of compositional changes in microbial or cell population data.

Potential Link between Ectomycorrhizal Community Composition and Host Tree Phenology

The timing of leaf phenology tends to be crucial in controlling ecosystem processes such as the acquisition of carbon and water loss as well as in controlling tree nutrient cycling. To date, tree phenology has mostly been associated with environmental control (e.g., temperature and photoperiod) in a relationship with inheritance, while it has rarely been linked with ectomycorrhizal community compositional changes through the host tree’s phenological stages. Seasonal variations of fungal communities have been widely studied, but little is known about mycorrhiza community composition changes along phenological stages. Therefore, we analyzed ectomycorrhizal communities associated with silver fir and their compositional changes during the transition between phenological stages. The phenological stages of each individual tree and time of bud break were monitored weekly for two years and, at the same time, ectomycorrhiza was harvested from selected silver fir trees. In total, 60 soil cores were analyzed for differences in the ectomycorrhizal community between phenological stages using Sanger sequencing of individual ectomycorrhizal morphotypes. A significant difference in beta diversity for an overall ectomycorrhizal community was confirmed between analyzed time periods for both sampled years. Species-specific reactions to transitions between phenological stages were confirmed for 18 different ectomycorrhizal taxa, where a positive correlation of Russula ochroleuca, Russula illota, Tomentella sublilacina, and Tylospora fibrillosa was observed with the phenological stage of bud burst.

Longitudinal study of DNA methylation and epigenetic clocks prior to and following test-confirmed COVID-19 and mRNA vaccination

The host epigenetic landscape is rapidly changed during SARS-CoV-2 infection and evidence suggests that severe COVID-19 is associated with durable scars to the epigenome. Specifically, aberrant DNA methylation changes in immune cells and alterations to epigenetic clocks in blood relate to severe COVID-19. However, a longitudinal assessment of DNA methylation states and epigenetic clocks in blood from healthy individuals prior to and following test-confirmed non-hospitalized COVID-19 has not been performed. Moreover, the impact of mRNA COVID-19 vaccines upon the host epigenome remains understudied. Here, we first examined DNA methylation states in blood of 21 participants prior to and following test confirmed COVID-19 diagnosis at a median timeframe of 8.35 weeks. 261 CpGs were identified as differentially methylated following COVID-19 diagnosis in blood at an FDR adjusted P value <0.05. These CpGs were enriched in gene body and northern and southern shelf regions of genes involved in metabolic pathways. Integrative analysis revealed overlap among genes identified in transcriptional SARS-CoV-2 infection datasets. Principal component-based epigenetic clock estimates of PhenoAge and GrimAge significantly increased in people over 50 following infection by an average of 2.1 and 0.84 years. In contrast, PCPhenoAge significantly decreased in people under 50 following infection by an average of 2.06 years. This observed divergence in epigenetic clocks following COVID-19 was related to age and immune cell-type compositional changes in CD4+ T cells, B cells, granulocytes, plasmablasts, exhausted T cells, and naïve T cells. Complementary longitudinal epigenetic clock analyses of 36 participants prior to and following Pfizer and Moderna mRNA-based COVID-19 vaccination revealed vaccination significantly reduced principal component-based Horvath epigenetic clock estimates in people over 50 by an average of 3.91 years for those that received Moderna. This reduction in epigenetic clock estimates was significantly related to chronological age and immune cell-type compositional changes in B cells and plasmablasts pre- and post-vaccination. These findings suggest the potential utility of epigenetic clocks as a biomarker of COVID-19 vaccine responses. Future research will need to unravel the significance and durability of short-term changes in epigenetic age related to COVID-19 exposure and mRNA vaccination.

scCODA is a Bayesian model for compositional single-cell data analysis

Compositional changes of cell types are main drivers of biological processes. Their detection through single-cell experiments is difficult due to the compositionality of the data and low sample sizes. We introduce scCODA (https://github.com/theislab/scCODA), a Bayesian model addressing these issues enabling the study of complex cell type effects in disease, and other stimuli. scCODA demonstrated excellent detection performance, while reliably controlling for false discoveries, and identified experimentally verified cell type changes that were missed in original analyses.

Laser Irradiation of a Bio-Waste Derived Carbon Unlocks Performance Enhancement in Secondary Lithium Batteries

Pyrolyzed carbons from bio-waste sources are renewable nanomaterials for sustainable negative electrodes in Li- and Na-ion batteries. Here, carbon derived from a hazelnut shell has been obtained by hydrothermal processing of the bio-waste followed by thermal treatments and laser irradiation in liquid. A non-focused nanosecond pulsed laser source has been used to irradiate pyrolyzed carbon particles suspended in acetonitrile to modify the surface and morphology. Morphological, structural, and compositional changes have been investigated by microscopy, spectroscopy, and diffraction to compare the materials properties after thermal treatments as well as before and after the irradiation. Laser irradiation in acetonitrile induces remarkable alteration in the nanomorphology, increase in the surface area and nitrogen enrichment of the carbon surfaces. These materials alterations are beneficial for the electrochemical performance in lithium half cells as proved by galvanostatic cycling at room temperature.