Expression of Atoh1, Gfi1, and Pou4f3 in the mature cochlea reprograms nonsensory cells into hair cells.

Mechanosensory hair cells of the mature mammalian organ of Corti do not regenerate; consequently, loss of hair cells leads to permanent hearing loss. Although nonmammalian vertebrates can regenerate hair cells from neighboring supporting cells, many humans with severe hearing loss lack both hair cells and supporting cells, with the organ of Corti being replaced by a flat epithelium of nonsensory cells. To determine whether the mature cochlea can produce hair cells in vivo, we reprogrammed nonsensory cells adjacent to the organ of Corti with three hair cell transcription factors: Gfi1, Atoh1, and Pou4f3. We generated numerous hair cell-like cells in nonsensory regions of the cochlea and new hair cells continued to be added over a period of 9 wk. Significantly, cells adjacent to reprogrammed hair cells expressed markers of supporting cells, suggesting that transcription factor reprogramming of nonsensory cochlear cells in adult animals can generate mosaics of sensory cells like those seen in the organ of Corti. Generating such sensory mosaics by reprogramming may represent a potential strategy for hearing restoration in humans.

Decision making at a subcellular level determines the outcome of bacteriophage infection.

When the process of cell-fate determination is examined at single-cell resolution, it is often observed that individual cells undergo different fates even when subject to identical conditions. This "noisy" phenotype is usually attributed to the inherent stochasticity of chemical reactions in the cell. Here we demonstrate how the observed single-cell heterogeneity can be explained by a cascade of decisions occurring at the subcellular level. We follow the postinfection decision in bacteriophage lambda at single-virus resolution, and show that a choice between lysis and lysogeny is first made at the level of the individual virus. The decisions by all viruses infecting a single cell are then integrated in a precise (noise-free) way, such that only a unanimous vote by all viruses leads to the establishment of lysogeny. By detecting and integrating over the subcellular "hidden variables," we are able to predict the level of noise measured at the single-cell level.

Addiction to Golgi-resident PI4P synthesis in chromosome 1q21.3-amplified lung adenocarcinoma cells.

A chromosome 1q21.3 region that is frequently amplified in diverse cancer types encodes phosphatidylinositol (PI)-4 kinase IIIß (PI4KIIIß), a key regulator of secretory vesicle biogenesis and trafficking. Chromosome 1q21.3-amplified lung adenocarcinoma (1q-LUAD) cells rely on PI4KIIIß for Golgi-resident PI-4-phosphate (PI4P) synthesis, prosurvival effector protein secretion, and cell viability. Here, we show that 1q-LUAD cells subjected to prolonged PI4KIIIß antagonist treatment acquire tolerance by activating an miR-218-5p-dependent competing endogenous RNA network that up-regulates PI4KIIα, which provides an alternative source of Golgi-resident PI4P that maintains prosurvival effector protein secretion and cell viability. These findings demonstrate an addiction to Golgi-resident PI4P synthesis in a genetically defined subset of cancers.

Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming.

Blockade of angiogenesis can retard tumour growth, but may also paradoxically increase metastasis. This paradox may be resolved by vessel normalization, which involves increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability, and consequently mitigated hypoxia. Although these processes alter tumour progression, their regulation is poorly understood. Here we show that type 1 T helper (TH1) cells play a crucial role in vessel normalization. Bioinformatic analyses revealed that gene expression features related to vessel normalization correlate with immunostimulatory pathways, especially T lymphocyte infiltration or activity. To delineate the causal relationship, we used various mouse models with vessel normalization or T lymphocyte deficiencies. Although disruption of vessel normalization reduced T lymphocyte infiltration as expected, reciprocal depletion or inactivation of CD4+ T lymphocytes decreased vessel normalization, indicating a mutually regulatory loop. In addition, activation of CD4+ T lymphocytes by immune checkpoint blockade increased vessel normalization. TH1 cells that secrete interferon-γ are a major population of cells associated with vessel normalization. Patient-derived xenograft tumours growing in immunodeficient mice exhibited enhanced hypoxia compared to the original tumours in immunocompetent humans, and hypoxia was reduced by adoptive TH1 transfer. Our findings elucidate an unexpected role of TH1 cells in vasculature and immune reprogramming. TH1 cells may be a marker and a determinant of both immune checkpoint blockade and anti-angiogenesis efficacy.

Effective detection of variation in single-cell transcriptomes using MATQ-seq.

The quantification of transcriptional variation in single cells, particularly within the same cell population, is currently limited by the low sensitivity and high technical noise of single-cell RNA-seq assays. We report multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq), a highly sensitive and quantitative method for single-cell sequencing of total RNA. By systematically determining technical noise, we show that MATQ-seq captures genuine biological variation between whole transcriptomes of single cells.

Rare event of histone demethylation can initiate singular gene expression of olfactory receptors.

Mammals sense odors through the gene family of olfactory receptors (ORs). Despite the enormous number of OR genes (∼1,400 in mouse), each olfactory sensory neuron expresses one, and only one, of them. In neurobiology, it remains a long-standing mystery how this singularity can be achieved despite intrinsic stochasticity of gene expression. Recent experiments showed an epigenetic mechanism for maintaining singular OR expression: Once any ORs are activated, their expression inhibits further OR activation by down-regulating a histone demethylase Lsd1 (also known as Aof2 or Kdm1a), an enzyme required for the removal of the repressive histone marker H3K9me3 on OR genes. However, it remains unclear at a quantitative level how singularity can be initiated in the first place. In particular, does a simple activation/feedback scheme suffice to generate singularity? Here we show theoretically that rare events of histone demethylation can indeed produce robust singularity by separating two timescales: slow OR activation by stepwise H3K9me3 demethylation, and fast feedback to turn off Lsd1. Given a typical 1-h response of transcriptional feedback, to achieve the observed extent of singularity (only 2% of neurons express more than one ORs), we predict that OR activation must be as slow as 5­10 d-a timescale compatible with experiments. Our model further suggests H3K9me3-to-H3K9me2 demethylation as an additional rate-limiting step responsible for OR singularity. Our conclusions may be generally applicable to other systems where monoallelic expression is desired, and provide guidelines for the design of a synthetic system of singular expression.

Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients.

Circulating tumor cells (CTCs) enter peripheral blood from primary tumors and seed metastases. The genome sequencing of CTCs could offer noninvasive prognosis or even diagnosis, but has been hampered by low single-cell genome coverage of scarce CTCs. Here, we report the use of the recently developed multiple annealing and looping-based amplification cycles for whole-genome amplification of single CTCs from lung cancer patients. We observed characteristic cancer-associated single-nucleotide variations and insertions/deletions in exomes of CTCs. These mutations provided information needed for individualized therapy, such as drug resistance and phenotypic transition, but were heterogeneous from cell to cell. In contrast, every CTC from an individual patient, regardless of the cancer subtypes, exhibited reproducible copy number variation (CNV) patterns, similar to those of the metastatic tumor of the same patient. Interestingly, different patients with the same lung cancer adenocarcinoma (ADC) shared similar CNV patterns in their CTCs. Even more interestingly, patients of small-cell lung cancer have CNV patterns distinctly different from those of ADC patients. Our finding suggests that CNVs at certain genomic loci are selected for the metastasis of cancer. The reproducibility of cancer-specific CNVs offers potential for CTC-based cancer diagnostics.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors.

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

Characterization of Cancer Evolution Landscape Based on Accurate Detection of Somatic Mutations in Single Tumor Cells.

Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution.

Droplet-based transcriptome profiling of individual synapses.

Synapses are crucial structures that mediate signal transmission between neurons in complex neural circuits and display considerable morphological and electrophysiological heterogeneity. So far we still lack a high-throughput method to profile the molecular heterogeneity among individual synapses. In the present study, we develop a droplet-based single-cell (sc) total-RNA-sequencing platform, called Multiple-Annealing-and-Tailing-based Quantitative scRNA-seq in Droplets, for transcriptome profiling of individual neurites, primarily composed of synaptosomes. In the synaptosome transcriptome, or 'synaptome', profiling of both mouse and human brain samples, we detect subclusters among synaptosomes that are associated with neuronal subtypes and characterize the landscape of transcript splicing that occurs within synapses. We extend synaptome profiling to synaptopathy in an Alzheimer's disease (AD) mouse model and discover AD-associated synaptic gene expression changes that cannot be detected by single-nucleus transcriptome profiling. Overall, our results show that this platform provides a high-throughput, single-synaptosome transcriptome profiling tool that will facilitate future discoveries in neuroscience.

Single-cell Damagenome Profiling by Linear Copying and Splitting based Whole Genome Amplification (LCS-WGA).

Spontaneous DNA damage frequently occurs on the human genome, and it could alter gene expression by inducing mutagenesis or epigenetic changes. Therefore, it is highly desired to profile DNA damage distribution on the human genome and identify the genes that are prone to DNA damage. Here, we present a novel single-cell whole-genome amplification method which employs linear-copying followed by a split-amplification scheme, to efficiently remove amplification errors and achieve accurate detection of DNA damage in individual cells. In comparison to previous methods that measure DNA damage, our method uses a next-generation sequencing platform to detect misincorporated bases derived from spontaneous DNA damage with single-cell resolution.

Lysogen stability is determined by the frequency of activity bursts from the fate-determining gene.

The ability of living cells to maintain an inheritable memory of their gene-expression state is key to cellular differentiation. Bacterial lysogeny serves as a simple paradigm for long-term cellular memory. In this study, we address the following question: in the absence of external perturbation, how long will a cell stay in the lysogenic state before spontaneously switching away from that state? We show by direct measurement that lysogen stability exhibits a simple exponential dependence on the frequency of activity bursts from the fate-determining gene, cI. We quantify these gene-activity bursts using single-molecule-resolution mRNA measurements in individual cells, analyzed using a stochastic mathematical model of the gene-network kinetics. The quantitative relation between stability and gene activity is independent of the fine details of gene regulation, suggesting that a quantitative prediction of cell-state stability may also be possible in more complex systems.

Protein structure prediction: do hydrogen bonding and water-mediated interactions suffice?

The many-body physics of hydrogen bond formation in alpha-helices of globular proteins was investigated using a simple physics-based model. Specifically, a context-sensitive hydrogen bond potential, which depends on residue identity and degree of solvent exposure, was used in the framework of the Associated Memory Hamiltonian codes developed previously but without using local-sequence structure matches ("memories"). Molecular dynamics simulations employing the energy function using the context-sensitive hydrogen bond potential alone (the "amnesiac" model) were used to generate low energy structures for three alpha-helical test proteins. The resulting structures were compared to both the X-ray crystal structures of the test proteins and the results obtained using the full Associated Memory Hamiltonian previously used. Results show that the amnesiac Hamiltonian was able to generate structures with reasonably high structural similarity (Q approximately 0.4) to that of the native protein but only with the use of predicted secondary structure information encoding local steric signals. Low energy structures obtained using the amnesiac Hamiltonian without any a priori secondary structure information had considerably less similarity to the native protein structures (Q approximately 0.3). Both sets of results utilizing the amnesiac Hamiltonian are poorer than when local-sequence structure matches are used.

Single-cell damagenome profiling unveils vulnerable genes and functional pathways in human genome toward DNA damage.

We report a novel single-cell whole-genome amplification method (LCS-WGA) that can efficiently capture spontaneous DNA damage existing in single cells. We refer to these damage-associated single-nucleotide variants as "damSNVs," and the whole-genome distribution of damSNVs as the damagenome. We observed that in single human neurons, the damagenome distribution was significantly correlated with three-dimensional genome structures. This nonuniform distribution indicates different degrees of DNA damage effects on different genes. Next, we identified the functionals that were significantly enriched in the high-damage genes. Similar functionals were also enriched in the differentially expressed genes (DEGs) detected by single-cell transcriptome of both Alzheimer's disease (AD) and autism spectrum disorder (ASD). This result can be explained by the significant enrichment of high-damage genes in the DEGs of neurons for both AD and ASD. The discovery of high-damage genes sheds new lights on the important roles of DNA damage in human diseases and disorders.

Single-PanIN-seq unveils that ARID1A deficiency promotes pancreatic tumorigenesis by attenuating KRAS-induced senescence.

ARID1A is one of the most frequently mutated epigenetic regulators in a wide spectrum of cancers. Recent studies have shown that ARID1A deficiency induces global changes in the epigenetic landscape of enhancers and promoters. These broad and complex effects make it challenging to identify the driving mechanisms of ARID1A deficiency in promoting cancer progression. Here, we identified the anti-senescence effect of Arid1a deficiency in the progression of pancreatic intraepithelial neoplasia (PanIN) by profiling the transcriptome of individual PanINs in a mouse model. In a human cell line model, we found that ARID1A deficiency upregulates the expression of aldehyde dehydrogenase 1 family member A1 (ALDH1A1), which plays an essential role in attenuating the senescence induced by oncogenic KRAS through scavenging reactive oxygen species. As a subunit of the SWI/SNF chromatin remodeling complex, our ATAC sequencing data showed that ARID1A deficiency increases the accessibility of the enhancer region of ALDH1A1. This study provides the first evidence that ARID1A deficiency promotes pancreatic tumorigenesis by attenuating KRAS-induced senescence through the upregulation of ALDH1A1 expression.

Contextual cues from cancer cells govern cancer-associated fibroblast heterogeneity.

Cancer cells function as primary architects of the tumor microenvironment. However, the molecular features of cancer cells that govern stromal cell phenotypes remain unclear. Here, we show that cancer-associated fibroblast (CAF) heterogeneity is driven by lung adenocarcinoma (LUAD) cells at either end of the epithelial-to-mesenchymal transition (EMT) spectrum. LUAD cells that have high expression of the EMT-activating transcription factor ZEB1 reprogram CAFs through a ZEB1-dependent secretory program and direct CAFs to the tips of invasive projections through a ZEB1-driven CAF repulsion process. The EMT, in turn, sensitizes LUAD cells to pro-metastatic signals from CAFs. Thus, CAFs respond to contextual cues from LUAD cells to promote metastasis.

Fibroblast heterogeneity and its impact on extracellular matrix and immune landscape remodeling in cancer.

Tumor progression is marked by dense collagenous matrix accumulations that dynamically reorganize to accommodate a growing and invasive tumor mass. Cancer-associated fibroblasts (CAFs) play an essential role in matrix remodeling and influence other processes in the tumor microenvironment, including angiogenesis, immunosuppression, and invasion. These findings have spawned efforts to elucidate CAF functionality at the single-cell level. Here, we will discuss how those efforts have impacted our understanding of the ways in which CAFs govern matrix remodeling and the influence of matrix remodeling on the development of an immunosuppressive tumor microenvironment.

Dissolvable Polyacrylamide Beads for High-Throughput Droplet DNA Barcoding.

Droplet-based single cell sequencing technologies, such as inDrop, Drop-seq, and 10X Genomics, are catalyzing a revolution in the understanding of biology. Barcoding beads are key components for these technologies. What is limiting today are barcoding beads that are easy to fabricate, can efficiently deliver primers into drops, and thus achieve high detection efficiency. Here, this work reports an approach to fabricate dissolvable polyacrylamide beads, by crosslinking acrylamide with disulfide bridges that can be cleaved with dithiothreitol. The beads can be rapidly dissolved in drops and release DNA barcode primers. The dissolvable beads are easy to synthesize, and the primer cost for the beads is significantly lower than that for the previous barcoding beads. Furthermore, the dissolvable beads can be loaded into drops with >95% loading efficiency of a single bead per drop and the dissolution of beads does not influence reverse transcription or the polymerase chain reaction (PCR) in drops. Based on this approach, the dissolvable beads are used for single cell RNA and protein analysis.

Single-Cell RNA-Seq by Multiple Annealing and Tailing-Based Quantitative Single-Cell RNA-Seq (MATQ-Seq).

Single-cell technologies have emerged as advanced tools to study various biological processes that demand the single cell resolution. To detect subtle heterogeneity in the transcriptome, high accuracy and sensitivity are still desired for single-cell RNA-seq. We describe here multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq) with ~90% capture efficiency. In addition, MATQ-seq is a total RNA assay allowing for detection of nonpolyadenylated transcripts.