Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

Comparative Analysis of Single-Cell RNA Sequencing Methods.

Technical advances have enabled the collection of genome and transcriptome data sets with single-cell resolution. However, single-cell characterization of the epigenome has remained challenging. Furthermore, because cells must be physically separated before biochemical processing, conventional single-cell preparatory methods scale linearly. We applied combinatorial cellular indexing to measure chromatin accessibility in thousands of single cells per assay, circumventing the need for compartmentalization of individual cells. We report chromatin accessibility profiles from more than 15,000 single cells and use these data to cluster cells on the basis of chromatin accessibility landscapes. We identify modules of coordinately regulated chromatin accessibility at the level of single cells both between and within cell types, with a scalable method that may accelerate progress toward a human cell atlas.

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Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing.

The traditional view of the adult brain as a static organ has changed in the past three decades, with the emergence of evidence that it remains plastic and has some regenerative capacity after injury. In the injured brain, microglia and macrophages clear cellular debris and orchestrate neuronal restorative processes. However, activation of these cells can also hinder CNS repair and expand tissue damage. Polarization of macrophage populations toward different phenotypes at different stages of injury might account for this dual role. This Perspectives article highlights the specific roles of polarized microglial and macrophage populations in CNS repair after acute injury, and argues that therapeutic approaches targeting cerebral inflammation should shift from broad suppression of microglia and macrophages towards subtle adjustment of the balance between their phenotypes. Breakthroughs in the identification of regulatory molecules that control these phenotypic shifts could ultimately accelerate research towards curing brain disorders.

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Microglial and Macrophage polarization—new Prospects for Brain Repair

Advances in single-cell RNA sequencing (scRNA-seq) have allowed for comprehensive analysis of the immune system. In this Review, we briefly describe the available scRNA-seq technologies together with their corresponding strengths and weaknesses. We discuss in depth how scRNA-seq can be used to deconvolve immune system heterogeneity by identifying novel distinct immune cell subsets in health and disease, characterizing stochastic heterogeneity within a cell population and building developmental 'trajectories' for immune cells. Finally, we discuss future directions of the field and present integrated approaches to complement molecular information from a single cell with studies of the environment, epigenetic state and cell lineage.

Single-cell RNA sequencing to explore immune cell heterogeneity.

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here—each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.

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Single-cell RNA-seq: advances and future challenges

A comprehensive understanding of host-pathogen interactions requires a knowledge of the associated gene expression changes in both the pathogen and the host. Traditional, probe-dependent approaches using microarrays or reverse transcription PCR typically require the pathogen and host cells to be physically separated before gene expression analysis. However, the development of the probe-independent RNA sequencing (RNA-seq) approach has begun to revolutionize transcriptomics. Here, we assess the feasibility of taking transcriptomics one step further by performing 'dual RNA-seq', in which gene expression changes in both the pathogen and the host are analysed simultaneously.

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Dual RNA-seq of pathogen and host

Bacteria express many small RNAs for which the regulatory roles in pathogenesis have remained poorly understood due to a paucity of robust phenotypes in standard virulence assays. Here we use a generic 'dual RNA-seq' approach to profile RNA expression simultaneously in pathogen and host during Salmonella enterica serovar Typhimurium infection and reveal the molecular impact of bacterial riboregulators. We identify a PhoP-activated small RNA, PinT, which upon bacterial internalization temporally controls the expression of both invasion-associated effectors and virulence genes required for intracellular survival. This riboregulatory activity causes pervasive changes in coding and noncoding transcripts of the host. Interspecies correlation analysis links PinT to host cell JAK-STAT signalling, and we identify infection-specific alterations in multiple long noncoding RNAs. Our study provides a paradigm for a sensitive RNA-based analysis of intracellular bacterial pathogens and their hosts without physical separation, as well as a new discovery route for hidden functions of pathogen genes.

Dual RNA-seq unveils noncoding RNA functions in host–pathogen interactions

Many bacterial infections are hard to treat and tend to relapse, possibly due to the presence of antibiotic-tolerant persisters. In vitro, persister cells appear to be dormant. After uptake of Salmonella species by macrophages, nongrowing persisters also occur, but their physiological state is poorly understood. In this work, we show that Salmonella persisters arising during macrophage infection maintain a metabolically active state. Persisters reprogram macrophages by means of effectors secreted by the Salmonella pathogenicity island 2 type 3 secretion system. These effectors dampened proinflammatory innate immune responses and induced anti-inflammatory macrophage polarization. Such reprogramming allowed nongrowing Salmonella cells to survive for extended periods in their host. Persisters undermining host immune defenses might confer an advantage to the pathogen during relapse once antibiotic pressure is relieved.

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Salmonella persisters undermine host immune defenses during antibiotic treatment

The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables “dual RNA-seq” studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique.

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Alexander J. Westermann

Papers

Single-cell RNA-seq: advances and future challenges

Dual RNA-seq of pathogen and host

Dual RNA-seq unveils noncoding RNA functions in host–pathogen interactions

Salmonella persisters undermine host immune defenses during antibiotic treatment

Resolving host-pathogen interactions by dual RNA-seq