Global and Spatial Metabolomics of Individual Cells Using a Tapered Pneumatically Assisted nano-DESI Probe

Single-cell metabolomics has the potential to reveal unique insights into intracellular mechanisms and biological processes. However, the detection of metabolites from individual cells is challenging due to their versatile chemical properties and concentrations. Here, we demonstrate a tapered probe for pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) mass spectrometry that enables both chemical imaging of larger cells and global metabolomics of smaller 15 μm cells. Additionally, by depositing cells in predefined arrays, we show successful metabolomics from three individual INS-1 cells per minute, which enabled the acquisition of data from 479 individual cells. Several cells were used to optimize analytical conditions, and 93 or 97 cells were used to monitor metabolome alterations in INS-1 cells after exposure to a low or high glucose concentration, respectively. Our analytical approach offers insights into cellular heterogeneity and provides valuable information about cellular processes and responses in individual cells.

Diagnostic classification of childhood cancer using multiscale transcriptomics

The causes of pediatric cancers' distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types.

scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) methods have been advantageous for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For scRNA-seq data, variability in gene expression reflects the degree of variation in gene expression from one cell to another. Analyses that focus on cell-cell variability therefore are useful for going beyond changes based on average expression and, instead, identifying genes with homogeneous expression versus those that vary widely from cell to cell.

RESULTS

We present a novel statistical framework, scShapes, for identifying differential distributions in single-cell RNA-sequencing data using generalized linear models. Most approaches for differential gene expression detect shifts in the mean value. However, as single-cell data are driven by overdispersion and dropouts, moving beyond means and using distributions that can handle excess zeros is critical. scShapes quantifies gene-specific cell-to-cell variability by testing for differences in the expression distribution while flexibly adjusting for covariates if required. We demonstrate that scShapes identifies subtle variations that are independent of altered mean expression and detects biologically relevant genes that were not discovered through standard approaches.

CONCLUSIONS

This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html).

Old plasma dilution reduces human biological age: a clinical study

This work extrapolates to humans the previous animal studies on blood heterochronicity and establishes a novel direct measurement of biological age. Our results support the hypothesis that, similar to mice, human aging is driven by age-imposed systemic molecular excess, the attenuation of which reverses biological age, defined in our work as a deregulation (noise) of 10 novel protein biomarkers. The results on biological age are strongly supported by the data, which demonstrates that rounds of therapeutic plasma exchange (TPE) promote a global shift to a younger systemic proteome, including youthfully restored pro-regenerative, anticancer, and apoptotic regulators and a youthful profile of myeloid/lymphoid markers in circulating cells, which have reduced cellular senescence and lower DNA damage. Mechanistically, the circulatory regulators of the JAK-STAT, MAPK, TGF-beta, NF-κB, and Toll-like receptor signaling pathways become more youthfully balanced through normalization of TLR4, which we define as a nodal point of this molecular rejuvenation. The significance of our findings is confirmed through big-data gene expression studies.

Keep calm and transcribe on: chromatin changes with age, but transcription can learn to live with it

Assessing age‐related tissue dysfunction represents an emerging field and involves analyses that are far from trivial, often requiring the integration of several large‐scale (“omic”) techniques. In their recent work, Tessarz and colleagues (Bozukova et al, 2022) characterize changes in the transcriptional machinery during aging in mice and report some surprising findings.

Aging is associated with increased chromatin accessibility and reduced polymerase pausing in liver

Regulation of gene expression is linked to the organization of the genome. With age, chromatin alterations occur on all levels of genome organization, accompanied by changes in the gene expression profile. However, little is known about the changes in the level of transcriptional regulation. Here, we used a multi‐omics approach and integrated ATAC‐, RNA‐ and NET‐seq to identify age‐related changes in the chromatin landscape of murine liver and to investigate how these are linked to transcriptional regulation. We provide the first systematic inventory of the connection between aging, chromatin accessibility, and transcriptional regulation in a whole tissue. Aging in murine liver is characterized by an increase in chromatin accessibility at promoter regions, but not in an increase in transcriptional output. Instead, aging is accompanied by a decrease in promoter‐proximal pausing of RNA polymerase II (Pol II), while initiation of transcription is not decreased as assessed by RNA polymerase mapping using CUT&RUN. Based on the data reported, we propose that these age‐related changes in transcriptional regulation are due to a reduced stability of the pausing complex.

Lack of evidence for increased transcriptional noise in aged tissues

Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA sequencing (scRNAseq). However, the diverse computational methods used for the quantification of age-related loss of cellular identity have prevented reaching meaningful conclusions by direct comparison of existing scRNAseq datasets. To address these issues we created Decibel, a Python toolkit that implements side-to-side four commonly used methods for the quantification of age-related transcriptional noise in scRNAseq data. Additionally, we developed Scallop, a novel computational method for the quantification of membership of single cells to their assigned cell type cluster. Cells with a greater Scallop membership score are transcriptionally more stable. Application of these computational tools to seven aging datasets showed large variability between tissues and datasets, suggesting that increased transcriptional noise is not a universal hallmark of aging. To understand the source of apparent loss of cell type identity associated with aging, we analyzed cell type-specific changes in transcriptional noise and the changes in cell type composition of the mammalian lung. No robust pattern of cell type-specific transcriptional noise alteration was found across aging lung datasets. In contrast, age-associated changes in cell type composition of the lung were consistently found, particularly of immune cells. These results suggest that claims of increased transcriptional noise of aged tissues should be reformulated.

The RNA-binding protein Puf5 contributes to buffering of mRNA upon chromatin-mediated changes in nascent transcription

Gene expression involves regulation of chromatin structure and transcription, as well as processing of the transcribed mRNA. While there are feedback mechanisms, it is not clear whether these include crosstalk between chromatin architecture and mRNA decay. To address this, we performed a genome-wide genetic screen using a Saccharomyces cerevisiae strain harbouring the H3K56A mutation, which is known to perturb chromatin structure and nascent transcription. We identified Puf5 (also known as Mpt5) as essential in an H3K56A background. Depletion of Puf5 in this background leads to downregulation of Puf5 targets. We suggest that Puf5 plays a role in post-transcriptional buffering of mRNAs, and support this by transcriptional shutoff experiments in which Puf5 mRNA targets are degraded slower in H3K56A cells compared to wild-type cells. Finally, we show that post-transcriptional buffering of Puf5 targets is widespread and does not occur only in an H3K56A mutant, but also in an H3K4R background, which leads to a global increase in nascent transcription. Our data suggest that Puf5 determines the fate of its mRNA targets in a context-dependent manner acting as an mRNA surveillance hub balancing deregulated nascent transcription to maintain physiological mRNA levels.

Principles of the Molecular and Cellular Mechanisms of Aging

Aging can be defined as a state of progressive functional decline accompanied by an increase in mortality. Time-dependent accumulation of cellular damage, namely lesions and mutations in the DNA and misfolded proteins, impair organellar and cellular function. Ensuing cell fate alterations lead to the accumulation of dysfunctional cells and hamper homeostatic processes, thus limiting regenerative potential; trigger low-grade inflammation; and alter intercellular and intertissue communication. The accumulation of molecular damage together with modifications in the epigenetic landscape, dysregulation of gene expression, and altered endocrine communication, drive the aging process and establish age as the main risk factor for age-associated diseases and multimorbidity.

Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers

While the majority of cells contain a single nucleus, cell types such as trophoblasts, osteoclasts, and skeletal myofibers require multinucleation. One advantage of multinucleation can be the assignment of distinct functions to different nuclei, but comprehensive interrogation of transcriptional heterogeneity within multinucleated tissues has been challenging due to the presence of a shared cytoplasm. Here, we utilized single-nucleus RNA-sequencing (snRNA-seq) to determine the extent of transcriptional diversity within multinucleated skeletal myofibers. Nuclei from mouse skeletal muscle were profiled across the lifespan, which revealed the presence of distinct myonuclear populations emerging in postnatal development as well as aging muscle. Our datasets also provided a platform for discovery of genes associated with rare specialized regions of the muscle cell, including markers of the myotendinous junction and functionally validated factors expressed at the neuromuscular junction. These findings reveal that myonuclei within syncytial muscle fibers possess distinct transcriptional profiles that regulate muscle biology.

A Single-Cell Transcriptomic Atlas of Human Skin Aging

Skin undergoes constant self-renewal, and its functional decline is a visible consequence of aging. Understanding human skin aging requires in-depth knowledge of the molecular and functional properties of various skin cell types. We performed single-cell RNA sequencing of human eyelid skin from healthy individuals across different ages and identified eleven canonical cell types, as well as six subpopulations of basal cells. Further analysis revealed progressive accumulation of photoaging-related changes and increased chronic inflammation with age. Transcriptional factors involved in the developmental process underwent early-onset decline during aging. Furthermore, inhibition of key transcription factors HES1 in fibroblasts and KLF6 in keratinocytes not only compromised cell proliferation, but also increased inflammation and cellular senescence during aging. Lastly, we found that genetic activation of HES1 or pharmacological treatment with quercetin alleviated cellular senescence of dermal fibroblasts. These findings provide a single-cell molecular framework of human skin aging, providing a rich resource for developing therapeutic strategies against aging-related skin disorders.

Capturing and Understanding the Dynamics and Heterogeneity of Gene Expression in the Living Cell

The regulation of gene expression is a fundamental process enabling cells to respond to internal and external stimuli or to execute developmental programs. Changes in gene expression are highly dynamic and depend on many intrinsic and extrinsic factors. In this review, we highlight the dynamic nature of transient gene expression changes to better understand cell physiology and development in general. We will start by comparing recent in vivo procedures to capture gene expression in real time. Intrinsic factors modulating gene expression dynamics will then be discussed, focusing on chromatin modifications. Furthermore, we will dissect how cell physiology or age impacts on dynamic gene regulation and especially discuss molecular insights into acquired transcriptional memory. Finally, this review will give an update on the mechanisms of heterogeneous gene expression among genetically identical individual cells. We will mainly focus on state-of-the-art developments in the yeast model but also cover higher eukaryotic systems.

Tissue-disruption-induced cellular stochasticity and epigenetic drift: Common origins of aging and cancer?

Age-related and cancer-related epigenomic modifications have been associated with enhanced cell-to-cell gene expression variability that characterizes increased cellular stochasticity. Since gene expression variability appears to be highly reduced by-and epigenetic and phenotypic stability acquired through-direct or long-range cellular interactions during cell differentiation, we propose a common origin for aging and cancer in the failure to control cellular stochasticity by cell-cell interactions. Tissue-disruption-induced cellular stochasticity associated with epigenetic drift would be at the origin of organ dysfunction because of an increase in phenotypic variation among cells, ultimately leading to cell death and organ failure through a loss of coordination in cellular functions, and eventually to cancerization. We propose mechanistic research perspectives to corroborate this hypothesis and explore its evolutionary consequences, highlighting a positive correlation between the median age of mass loss onset (a proxy for the onset of organ aging) and the median age at cancer diagnosis.

Single-cell transcriptomics allows novel insights into aging and circadian processes

Aging and circadian rhythms are two biological processes that affect an organism, although at different time scales. Nevertheless, due to the overlap of their actions, it was speculated that both interfere or interact with each other. However, to address this question, a much deeper insight into these processes is necessary, especially at the cellular level. New methods such as single-cell RNA-sequencing (scRNA-Seq) have the potential to close this gap in our knowledge. In this review, we analyze applications of scRNA-Seq from the aging and circadian rhythm fields and highlight new findings emerging from the analysis of single cells, especially in humans or rodents. Furthermore, we judge the potential of scRNA-Seq to identify common traits of both processes. Overall, this method offers several advantages over more traditional methods analyzing gene expression and will become an important tool to unravel the link between these biological processes.