TOR regulates variability of protein synthesis rates

Cellular processes are subject to inherent variability, but the extent to which cells can regulate this variability has received little investigation. Here, we explore the characteristics of the rate of cellular protein synthesis in single cells of the eukaryote fission yeast. Strikingly, this rate is highly variable despite protein synthesis being dependent on hundreds of reactions which might be expected to average out at the overall cellular level. The rate is variable over short time scales, and exhibits homoeostatic behaviour at the population level. Cells can regulate the level of variability through processes involving the TOR pathway, suggesting there is an optimal level of variability conferring a selective advantage. While this could be an example of bet-hedging, but we propose an alternative explanation: regulated 'loose' control of complex processes of overall cellular metabolism such as protein synthesis, may lead to this variability. This could ensure cells are fluid in control and agile in response to changing conditions, and may constitute a novel organisational principle of complex metabolic cellular systems.

Multiplex Single-Cell Bioprinting for Engineering of Heterogeneous Tissue Constructs with Subcellular Spatial Resolution

Tissue development, function, and disease are largely driven by the spatial organization of individual cells and their cell-cell interactions. Precision engineered tissues with single-cell spatial resolution, therefore, have tremendous potential for next generation disease models, drug discovery, and regenerative therapeutics. Despite significant advancements in biofabrication approaches to improve feature resolution, strategies to fabricate tissues with the exact same organization of individual cells in their native cellular microenvironment have remained virtually non-existent to date. Here we report a method to spatially pattern single cells with up to eight cell phenotypes and subcellular spatial precision. As proof-of-concept we first demonstrate the ability to systematically assess the influence of cellular microenvironments on cell behavior by controllably altering the spatial arrangement of cell types in bioprinted precision cell-cell interaction arrays. We then demonstrate, for the first time, the ability to produce high-fidelity replicas of a patient's annotated cancer biopsy with subcellular resolution. The ability to replicate native cellular microenvironments marks a significant advancement for precision biofabricated in-vitro models, where heterogenous tissues can be engineered with single-cell spatial precision to advance our understanding of complex biological systems in a controlled and systematic manner.

Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data

Motivation

Recently, single-cell DNA sequencing (scDNA-seq) and multi-modal profiling with the addition of cell-surface antibodies (scDAb-seq) have provided key insights into cancer heterogeneity. Scaling these technologies across large patient cohorts, however, is cost and time prohibitive. Multiplexing, in which cells from unique patients are pooled into a single experiment, offers a possible solution. While multiplexing methods exist for scRNAseq, accurate demultiplexing in scDNAseq remains an unmet need.

Results

Here, we introduce SNACS: Single-Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting. SNACS relies on a combination of patient-level cell-surface identifiers and natural variation in genetic polymorphisms to demultiplex scDNAseq data. We demonstrated the performance of SNACS on a dataset consisting of multi-sample experiments from patients with leukemia where we knew truth from single-sample experiments from the same patients. Using SNACS, accuracy ranged from 0.948 - 0.991 vs 0.552 - 0.934 using demultiplexing methods from the single-cell literature.

Correlative Cellular Mass Spectrometry Imaging and Amperometry Show Dose Dependent Changes in Lipid Composition and Exocytosis

Aberrant functioning of the proteasome has been associated with crucial pathologic conditions including neurodegeneration. Yet, the complex underlying causes at the cellular level remain unclear and there are conflicting reports of neuroprotective to neurodegenerative effects of proteasomal inhibitors such as lactacystin that are utilised as models for neurodegenerative diseases. The conflicting results may be associated with different dose regimes of lactacystin and hence we have performed a dose dependent study of the effects of lactacystin to identify concurrent changes in the cell membrane lipid profile and the dynamics of exocytosis using a combination of surface sensitive mass spectrometry and single cell amperometry. Significant changes of negatively charged lipids were associated with different lactacystin doses that showed a weak correlation with exocytosis while changes in PE and PE-O lipids showed dose dependent changes correlated with initial pore formation and total release of vesicle content respectively.

Single-Cell Analysis Reveals Unexpected Cellular Changes and Transposon Expression Signatures in the Colonic Epithelium of Treatment-Naïve Adult Crohn's Disease Patients

BACKGROUND & AIMS

The intestinal barrier comprises a monolayer of specialized intestinal epithelial cells (IECs) that are critical in maintaining mucosal homeostasis. Dysfunction within various IEC fractions can alter intestinal permeability in a genetically susceptible host, resulting in a chronic and debilitating condition known as Crohn's disease (CD). Defining the molecular changes in each IEC type in CD will contribute to an improved understanding of the pathogenic processes and the identification of cell type-specific therapeutic targets. We performed, at single-cell resolution, a direct comparison of the colonic epithelial cellular and molecular landscape between treatment-naïve adult CD and non-inflammatory bowel disease control patients.

METHODS

Colonic epithelial-enriched, single-cell sequencing from treatment-naïve adult CD and non-inflammatory bowel disease patients was investigated to identify disease-induced differences in IEC types.

RESULTS

Our analysis showed that in CD patients there is a significant skew in the colonic epithelial cellular distribution away from canonical LGR5+ stem cells, located at the crypt bottom, and toward one specific subtype of mature colonocytes, located at the crypt top. Further analysis showed unique changes to gene expression programs in every major cell type, including a previously undescribed suppression in CD of most enteroendocrine driver genes as well as L-cell markers including GCG. We also dissect an incompletely understood SPIB+ cell cluster, revealing at least 4 subclusters that likely represent different stages of a maturational trajectory. One of these SPIB+ subclusters expresses crypt-top colonocyte markers and is up-regulated significantly in CD, whereas another subcluster strongly expresses and stains positive for lysozyme (albeit no other canonical Paneth cell marker), which surprisingly is greatly reduced in expression in CD. In addition, we also discovered transposable element markers of colonic epithelial cell types as well as transposable element families that are altered significantly in CD in a cell type-specific manner. Finally, through integration with data from genome-wide association studies, we show that genes implicated in CD risk show heretofore unknown cell type-specific patterns of aberrant expression in CD, providing unprecedented insight into the potential biological functions of these genes.

CONCLUSIONS

Single-cell analysis shows a number of unexpected cellular and molecular features, including transposable element expression signatures, in the colonic epithelium of treatment-naïve adult CD.

Prognostic significance of tumor-associated macrophages: past, present and future

Tumor tissues are populated by a multitude of macrophages, highly different in functional activity, localization and morphology. A clear contribution to disease progression has been shown in multiple cancer types, holding promise for the development of innovative macrophage-based prognostic tools. Current studies aimed at assessing the prognostic role of macrophages have documented the relevance of the macrophage population as a whole. However, dissecting the diversity of mononuclear phagocytes in tumor tissues has provided important information about the coexistence of distinct populations of macrophages with different prognostic significance. Here we summarize evidence of macrophage prognostic function in human cancer and focus on classical and modern strategies aimed at measuring macrophage features and deciphering their diversity. The wealth of new data generated will reshape our knowledge of macrophage complexity and hopefully foster the forthcoming development of these new metrics into prognostic tools as well as new therapeutic strategies.

FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data

Background

A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates.

Results

To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene ‘signatures’) are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms.

Conclusions

Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1176-5) contains supplementary material, which is available to authorized users.