A brain-specific pgc1α fusion transcript affects gene expression and behavioural outcomes in mice.

PGC1α is a transcriptional coactivator in peripheral tissues, but its function in the brain remains poorly understood. Various brain-specific Pgc1α isoforms have been reported in mice and humans, including two fusion transcripts (FTs) with non-coding repetitive sequences, but their function is unknown. The FTs initiate at a simple sequence repeat locus ∼570 Kb upstream from the reference promoter; one also includes a portion of a short interspersed nuclear element (SINE). Using publicly available genomics data, here we show that the SINE FT is the predominant form of Pgc1α in neurons. Furthermore, mutation of the SINE in mice leads to altered behavioural phenotypes and significant up-regulation of genes in the female, but not male, cerebellum. Surprisingly, these genes are largely involved in neurotransmission, having poor association with the classical mitochondrial or antioxidant programs. These data expand our knowledge on the role of Pgc1α in neuronal physiology and suggest that different isoforms may have distinct functions. They also highlight the need for further studies before modulating levels of Pgc1α in the brain for therapeutic purposes.

Patterns, Profiles, and Parsimony: Dissecting Transcriptional Signatures From Minimal Single-Cell RNA-Seq Output With SALSA.

Single-cell RNA sequencing (scRNA-seq) technologies have precipitated the development of bioinformatic tools to reconstruct cell lineage specification and differentiation processes with single-cell precision. However, current start-up costs and recommended data volumes for statistical analysis remain prohibitively expensive, preventing scRNA-seq technologies from becoming mainstream. Here, we introduce single-cell amalgamation by latent semantic analysis (SALSA), a versatile workflow that combines measurement reliability metrics with latent variable extraction to infer robust expression profiles from ultra-sparse sc-RNAseq data. SALSA uses a matrix focusing approach that starts by identifying facultative genes with expression levels greater than experimental measurement precision and ends with cell clustering based on a minimal set of Profiler genes, each one a putative biomarker of cluster-specific expression profiles. To benchmark how SALSA performs in experimental settings, we used the publicly available 10X Genomics PBMC 3K dataset, a pre-curated silver standard from human frozen peripheral blood comprising 2,700 single-cell barcodes, and identified 7 major cell groups matching transcriptional profiles of peripheral blood cell types and driven agnostically by < 500 Profiler genes. Finally, we demonstrate successful implementation of SALSA in a replicative scRNA-seq scenario by using previously published DropSeq data from a multi-batch mouse retina experimental design, thereby identifying 10 transcriptionally distinct cell types from > 64,000 single cells across 7 independent biological replicates based on < 630 Profiler genes. With these results, SALSA demonstrates that robust pattern detection from scRNA-seq expression matrices only requires a fraction of the accrued data, suggesting that single-cell sequencing technologies can become affordable and widespread if meant as hypothesis-generation tools to extract large-scale differential expression effects.

Single-cell analyses identify dysfunctional CD16+ CD8 T cells in smokers.

Tobacco smoke exposure contributes to the global burden of communicable and chronic diseases. To identify immune cells affected by smoking, we use single-cell RNA sequencing on peripheral blood from smokers and nonsmokers. Transcriptomes reveal a subpopulation of FCGR3A (CD16)-expressing Natural Killer (NK)-like CD8 T lymphocytes that increase in smokers. Mass cytometry confirms elevated CD16+ CD8 T cells in smokers. Inferred as highly differentiated by pseudotime analysis, NK-like CD8 T cells express markers characteristic of effector memory re-expressing CD45RA T (TEMRA) cells. Indicative of immune aging, smokers' CD8 T cells are biased toward differentiated cells and smokers have fewer naïve cells than nonsmokers. DNA methylation-based models show that smoking dose is associated with accelerated aging and decreased telomere length, a biomarker of T cell senescence. Immune aging accompanies T cell senescence, which can ultimately lead to impaired immune function. This suggests a role for smoking-induced, senescence-associated immune dysregulation in smoking-mediated pathologies.

Single Nucleotide Resolution Analysis Reveals Pervasive, Long-Lasting DNA Methylation Changes by Developmental Exposure to a Mitochondrial Toxicant.

Mitochondrial-driven alterations of the epigenome have been reported, but whether they are relevant at the organismal level remains unknown. The viable yellow agouti mouse (Avy) is a powerful epigenetic biosensor model that reports on the DNA methylation status of the Avy locus, which is established prior to the three-germ-layer separation, through the coat color of the animals. Here we show that maternal exposure to rotenone, a potent mitochondrial complex I inhibitor, not only changes the DNA methylation status of the Avy locus in the skin but broadly affects the liver DNA methylome of the offspring. These effects are accompanied by altered gene expression programs that persist throughout life, and which associate with impairment of antioxidant activity and mitochondrial function in aged animals. These pervasive and lasting genomic effects suggest a putative role for mitochondria in regulating life-long gene expression programs through developmental nuclear epigenetic remodeling.

Mitochondrial acetyl-CoA reversibly regulates locus-specific histone acetylation and gene expression.

The impact of mitochondrial dysfunction in epigenetics is emerging, but our understanding of this relationship and its effect on gene expression remains incomplete. We previously showed that acute mitochondrial DNA (mtDNA) loss leads to histone hypoacetylation. It remains to be defined if these changes are maintained when mitochondrial dysfunction is chronic and if they alter gene expression. To fill these gaps of knowledge, we here studied a progressive and a chronic model of mtDNA depletion using biochemical, pharmacological, genomics, and genetic assays. We show that histones are primarily hypoacetylated in both models. We link these effects to decreased histone acetyltransferase activity unrelated to changes in ATP citrate lyase, acetyl coenzyme A synthetase 2, or pyruvate dehydrogenase activities, which can be reversibly modulated by altering the mitochondrial pool of acetyl-coenzyme A. Also, we determined that the accompanying changes in histone acetylation regulate locus-specific gene expression and physiological outcomes, including the production of prostaglandins. These results may be relevant to the pathophysiology of mtDNA depletion syndromes and to understanding the effects of environmental agents that lead to physical or functional mtDNA loss.

A Leveraged Signal-to-Noise Ratio (LSTNR) Method to Extract Differentially Expressed Genes and Multivariate Patterns of Expression From Noisy and Low-Replication RNAseq Data.

To life scientists, one important feature offered by RNAseq, a next-generation sequencing tool used to estimate changes in gene expression levels, lies in its unprecedented resolution. It can score countable differences in transcript numbers among thousands of genes and between experimental groups, all at once. However, its high cost limits experimental designs to very small sample sizes, usually N = 3, which often results in statistically underpowered analysis and poor reproducibility. All these issues are compounded by the presence of experimental noise, which is harder to distinguish from instrumental error when sample sizes are limiting (e.g., small-budget pilot tests), experimental populations exhibit biologically heterogeneous or diffuse expression phenotypes (e.g., patient samples), or when discriminating among transcriptional signatures of closely related experimental conditions (e.g., toxicological modes of action, or MOAs). Here, we present a leveraged signal-to-noise ratio (LSTNR) thresholding method, founded on generalized linear modeling (GLM) of aligned read detection limits to extract differentially expressed genes (DEGs) from noisy low-replication RNAseq data. The LSTNR method uses an agnostic independent filtering strategy to define the dynamic range of detected aggregate read counts per gene, and assigns statistical weights that prioritize genes with better sequencing resolution in differential expression analyses. To assess its performance, we implemented the LSTNR method to analyze three separate datasets: first, using a systematically noisy in silico dataset, we demonstrated that LSTNR can extract pre-designed patterns of expression and discriminate between "noise" and "true" differentially expressed pseudogenes at a 100% success rate; then, we illustrated how the LSTNR method can assign patient-derived breast cancer specimens correctly to one out of their four reported molecular subtypes (luminal A, luminal B, Her2-enriched and basal-like); and last, we showed the ability to retrieve five different modes of action (MOA) elicited in livers of rats exposed to three toxicants under three nutritional routes by using the LSTNR method. By combining differential measurements with resolving power to detect DEGs, the LSTNR method offers an alternative approach to interrogate noisy and low-replication RNAseq datasets, which handles multiple biological conditions at once, and defines benchmarks to validate RNAseq experiments with standard benchtop assays.

Mitochondrial nicotinamide adenine dinucleotide reduced (NADH) oxidation links the tricarboxylic acid (TCA) cycle with methionine metabolism and nuclear DNA methylation.

Mitochondrial function affects many aspects of cellular physiology, and, most recently, its role in epigenetics has been reported. Mechanistically, how mitochondrial function alters DNA methylation patterns in the nucleus remains ill defined. Using a cell culture model of induced mitochondrial DNA (mtDNA) depletion, in this study we show that progressive mitochondrial dysfunction leads to an early transcriptional and metabolic program centered on the metabolism of various amino acids, including those involved in the methionine cycle. We find that this program also increases DNA methylation, which occurs primarily in the genes that are differentially expressed. Maintenance of mitochondrial nicotinamide adenine dinucleotide reduced (NADH) oxidation in the context of mtDNA loss rescues methionine salvage and polyamine synthesis and prevents changes in DNA methylation and gene expression but does not affect serine/folate metabolism or transsulfuration. This work provides a novel mechanistic link between mitochondrial function and epigenetic regulation of gene expression that involves polyamine and methionine metabolism responding to changes in the tricarboxylic acid (TCA) cycle. Given the implications of these findings, future studies across different physiological contexts and in vivo are warranted.

Universally Conserved Relationships between Nuclear Shape and Cytoplasmic Mechanical Properties in Human Stem Cells.

The ability of cells to proliferate, differentiate, transduce extracellular signals and assemble tissues involves structural connections between nucleus and cytoskeleton. Yet, how the mechanics of these connections vary inside stem cells is not fully understood. To address those questions, we combined two-dimensional particle-tracking microrheology and morphological measures using variable reduction techniques to measure whether cytoplasmic mechanics allow for discrimination between different human adherent stem cell types and across different culture conditions. Here we show that nuclear shape is a quantifiable discriminant of mechanical properties in the perinuclear cytoskeleton (pnCSK) of various stem cell types. Also, we find the pnCSK is a region with different mechanical properties than elsewhere in the cytoskeleton, with heterogeneously distributed locations exhibiting subdiffusive features, and which obeys physical relations conserved among various stem cell types. Finally, we offer a prospective basis to discriminate between stem cell types by coupling perinuclear mechanical properties to nuclear shape.

Morphogenetic Implications of Peristalsis-Driven Fluid Flow in the Embryonic Lung.

Epithelial organs are almost universally secretory. The lung secretes mucus of extremely variable consistency. In the early prenatal period, the secretions are of largely unknown composition, consistency, and flow rates. In addition to net outflow from secretion, the embryonic lung exhibits transient reversing flows from peristalsis. Airway peristalsis (AP) begins as soon as the smooth muscle forms, and persists until birth. Since the prenatal lung is liquid-filled, smooth muscle action can transport fluid far from the immediately adjacent tissues. The sensation of internal fluid flows has been shown to have potent morphogenetic effects, as has the transport of morphogens. We hypothesize that these effects play an important role in lung morphogenesis. To test these hypotheses in a quantitative framework, we analyzed the fluid-structure interactions between embryonic tissues and lumen fluid resulting from peristaltic waves that partially occlude the airway. We found that if the airway is closed, fluid transport is minimal; by contrast, if the trachea is open, shear rates can be very high, particularly at the stenosis. We performed a parametric analysis of flow characteristics' dependence on tissue stiffnesses, smooth muscle force, geometry, and fluid viscosity, and found that most of these relationships are governed by simple ratios. We measured the viscosity of prenatal lung fluid with passive bead microrheology. This paper reports the first measurements of the viscosity of embryonic lung lumen fluid. In the range tested, lumen fluid can be considered Newtonian, with a viscosity of 0.016 ± 0.008 Pa-s. We analyzed the interaction between the internal flows and diffusion and conclude that AP has a strong effect on flow sensing away from the tip and on transport of morphogens. These effects may be the intermediate mechanisms for the enhancement of branching seen in occluded embryonic lungs.

Mechanical control of spheroid growth: distinct morphogenetic regimes.

We develop a model of transport and growth in epithelio-mesenchymal interactions. Analysis of the growth of an avascular solid spheroid inside a passive mesenchyme or gel shows that sustained volumetric growth requires four generic mechanisms: (1) growth factor, (2) protease, (3) control of cellularity, and (4) swelling. The model reveals a bifurcation delineating two distinct morphogenetic regimes: (A) steady growth, (B) growth arrested by capsule formation in the mesenchyme. In both morphogenetic regimes, growth velocity is constant unless and until a complete capsule forms. Comprehensive exploration of the large parameter space reveals that the bifurcation is determined by just two ratios representing the relative strengths of growth and proteolytic activity. Growth velocity is determined only by the ratio governing growth, independent of proteolytic activity. There is a continuum of interior versus surface growth, with fastest growth at the surface. The model provides a theoretical basis for explaining observations of growth arrest despite proteolysis of surrounding tissue, and gives a quantitative framework for the design and interpretation of experiments involving spheroids, and tissues which are locally equivalent to spheroids.

Regulation of hepatic stem/progenitor phenotype by microenvironment stiffness in hydrogel models of the human liver stem cell niche.

Human livers have maturational lineages of cells within liver acini, beginning periportally in stem cell niches, the canals of Hering, and ending in polyploid hepatocytes pericentrally and cholangiocytes in bile ducts. Hepatic stem cells (hHpSCs) in vivo are partnered with mesenchymal precursors to endothelia (angioblasts) and stellate cells, and reside in regulated microenvironments, stem cell niches, containing hyaluronans (HA). The in vivo hHpSC niche is modeled in vitro by growing hHpSC in two-dimensional (2D) cultures on plastic. We investigated effects of 3D microenvironments, mimicking the liver's stem cell niche, on these hHpSCs by embedding them in HA-based hydrogels prepared with Kubota's Medium (KM), a serum-free medium tailored for endodermal stem/progenitors. The KM-HA hydrogels mimicked the niches, matched diffusivity of culture medium, exhibited shear thinning and perfect elasticity under mechanical loading, and had predictable stiffness depending on their chemistry. KM-HA hydrogels, which supported cell attachment, survival and expansion of hHpSC colonies, induced transition of hHpSC colonies towards stable heterogeneous populations of hepatic progenitors depending on KM-HA hydrogel stiffness, as shown by both their gene and protein expression profile. These acquired phenotypes did not show morphological evidence of fibrotic responses. In conclusion, this study shows that the mechanical properties of the microenvironment can regulate differentiation in endodermal stem cell populations.