Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols.

Successful immunotherapy relies on triggering complex responses involving T cell dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this, we developed a framework for in vivo tracking of tumor-specific CD8+ T cells over time and at single-cell resolution. Our tools facilitate the modeling of gene program dynamics in the tumor microenvironment (TME) and the tumor-draining lymph node (tdLN). Using this approach, we characterize two modes of anti-programmed cell death protein 1 (PD-1) activity, decoupling induced differentiation of tumor-specific activated precursor cells from conventional type 1 dendritic cell (cDC1)-dependent proliferation and recruitment to the TME. We demonstrate that combining anti-PD-1 therapy with anti-4-1BB agonist enhances the recruitment and proliferation of activated precursors, resulting in tumor control. These data suggest that effective response to anti-PD-1 therapy is dependent on sufficient influx of activated precursor CD8+ cells to the TME and highlight the importance of understanding system-level dynamics in optimizing immunotherapies.

Single cell Hi-C identifies plastic chromosome conformations underlying the gastrulation enhancer landscape.

Embryonic development involves massive proliferation and differentiation of cell lineages. This must be supported by chromosome replication and epigenetic reprogramming, but how proliferation and cell fate acquisition are balanced in this process is not well understood. Here we use single cell Hi-C to map chromosomal conformations in post-gastrulation mouse embryo cells and study their distributions and correlations with matching embryonic transcriptional atlases. We find that embryonic chromosomes show a remarkably strong cell cycle signature. Despite that, replication timing, chromosome compartment structure, topological associated domains (TADs) and promoter-enhancer contacts are shown to be variable between distinct epigenetic states. About 10% of the nuclei are identified as primitive erythrocytes, showing exceptionally compact and organized compartment structure. The remaining cells are broadly associated with ectoderm and mesoderm identities, showing only mild differentiation of TADs and compartment structures, but more specific localized contacts in hundreds of ectoderm and mesoderm promoter-enhancer pairs. The data suggest that while fully committed embryonic lineages can rapidly acquire specific chromosomal conformations, most embryonic cells are showing plastic signatures driven by complex and intermixed enhancer landscapes.

Single-cell analysis of regions of interest (SCARI) using a photosensitive tag.

The functional activity and differentiation potential of cells are determined by their interactions with surrounding cells. Approaches that allow unbiased characterization of cell states while at the same time providing spatial information are of major value to assess this environmental influence. However, most current techniques are hampered by a tradeoff between spatial resolution and cell profiling depth. Here, we develop a photocage-based technology that allows isolation and in-depth analysis of live cells from regions of interest in complex ex vivo systems, including primary human tissues. The use of a highly sensitive 4-nitrophenyl(benzofuran) cage coupled to a set of nanobodies allows high-resolution photo-uncaging of different cell types in areas of interest. Single-cell RNA-sequencing of spatially defined CD8+ T cells is used to exemplify the feasibility of identifying location-dependent cell states. The technology described here provides a valuable tool for the analysis of spatially defined cells in diverse biological systems, including clinical samples.

Metabolic Imaging Detects Resistance to PI3Kα Inhibition Mediated by Persistent FOXM1 Expression in ER+ Breast Cancer.

PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor (ER)-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. FOXM1 drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II). The downstream metabolic changes can therefore be detected using MRI of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by positron emission tomography measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose. Rapid assessment of treatment response in breast cancer using this imaging method could help identify patients that benefit from PI3Kα inhibition and design drug combinations to counteract the emergence of resistance.

MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions.

scRNA-seq profiles each represent a highly partial sample of mRNA molecules from a unique cell that can never be resampled, and robust analysis must separate the sampling effect from biological variance. We describe a methodology for partitioning scRNA-seq datasets into metacells: disjoint and homogenous groups of profiles that could have been resampled from the same cell. Unlike clustering analysis, our algorithm specializes at obtaining granular as opposed to maximal groups. We show how to use metacells as building blocks for complex quantitative transcriptional maps while avoiding data smoothing. Our algorithms are implemented in the MetaCell R/C++ software package.

Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma.

Tumor immune cell compositions play a major role in response to immunotherapy, but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here, we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted are in fact a highly proliferating, clonal, and dynamically differentiating cell population within the human tumor microenvironment.

Single-cell characterization of haematopoietic progenitors and their trajectories in homeostasis and perturbed haematopoiesis.

The dynamics of haematopoietic stem cell differentiation and the hierarchy of oligopotent stem cells in the bone marrow remain controversial. Here we dissect haematopoietic progenitor populations at single cell resolution, deriving an unbiased reference model of transcriptional states in normal and perturbed murine bone marrow. We define the signature of the naive haematopoietic stem cell and find a continuum of core progenitor states. Core cell populations mix transcription of pre-myeloid and pre-lymphoid programs, but do not mix erythroid or megakaryocyte programs with other fates. CRISP-seq perturbation analysis confirms our models and reveals that Cebpa regulates entry into all myeloid fates, while Irf8 and PU.1 deficiency block later differentiation towards monocyte or granulocyte fates. Our transcriptional map defines a reference network model for blood progenitors and their differentiation trajectories during normal and perturbed haematopoiesis.

Multiscale 3D Genome Rewiring during Mouse Neural Development.

Chromosome conformation capture technologies have revealed important insights into genome folding. Yet, how spatial genome architecture is related to gene expression and cell fate remains unclear. We comprehensively mapped 3D chromatin organization during mouse neural differentiation in vitro and in vivo, generating the highest-resolution Hi-C maps available to date. We found that transcription is correlated with chromatin insulation and long-range interactions, but dCas9-mediated activation is insufficient for creating TAD boundaries de novo. Additionally, we discovered long-range contacts between gene bodies of exon-rich, active genes in all cell types. During neural differentiation, contacts between active TADs become less pronounced while inactive TADs interact more strongly. An extensive Polycomb network in stem cells is disrupted, while dynamic interactions between neural transcription factors appear in vivo. Finally, cell type-specific enhancer-promoter contacts are established concomitant to gene expression. This work shows that multiple factors influence the dynamics of chromatin interactions in development.

Cell-cycle dynamics of chromosomal organization at single-cell resolution.

Chromosomes in proliferating metazoan cells undergo marked structural metamorphoses every cell cycle, alternating between highly condensed mitotic structures that facilitate chromosome segregation, and decondensed interphase structures that accommodate transcription, gene silencing and DNA replication. Here we use single-cell Hi-C (high-resolution chromosome conformation capture) analysis to study chromosome conformations in thousands of individual cells, and discover a continuum of cis-interaction profiles that finely position individual cells along the cell cycle. We show that chromosomal compartments, topological-associated domains (TADs), contact insulation and long-range loops, all defined by bulk Hi-C maps, are governed by distinct cell-cycle dynamics. In particular, DNA replication correlates with a build-up of compartments and a reduction in TAD insulation, while loops are generally stable from G1 to S and G2 phase. Whole-genome three-dimensional structural models reveal a radial architecture of chromosomal compartments with distinct epigenomic signatures. Our single-cell data therefore allow re-interpretation of chromosome conformation maps through the prism of the cell cycle.

Capturing pairwise and multi-way chromosomal conformations using chromosomal walks.

Chromosomes are folded into highly compacted structures to accommodate physical constraints within nuclei and to regulate access to genomic information. Recently, global mapping of pairwise contacts showed that loops anchoring topological domains (TADs) are highly conserved between cell types and species. Whether pairwise loops synergize to form higher-order structures is still unclear. Here we develop a conformation capture assay to study higher-order organization using chromosomal walks (C-walks) that link multiple genomic loci together into proximity chains in human and mouse cells. This approach captures chromosomal structure at varying scales. Inter-chromosomal contacts constitute only 7-10% of the pairs and are restricted by interfacing TADs. About half of the C-walks stay within one chromosome, and almost half of those are restricted to intra-TAD spaces. C-walks that couple 2-4 TADs indicate stochastic associations between transcriptionally active, early replicating loci. Targeted analysis of thousands of 3-walks anchored at highly expressed genes support pairwise, rather than hub-like, chromosomal topology at active loci. Polycomb-repressed Hox domains are shown by the same approach to enrich for synergistic hubs. Together, the data indicate that chromosomal territories, TADs, and intra-TAD loops are primarily driven by nested, possibly dynamic, pairwise contacts.

UMI-4C for quantitative and targeted chromosomal contact profiling.

We developed a targeted chromosome conformation capture (4C) approach that uses unique molecular identifiers (UMIs) to derive high-complexity quantitative chromosome contact profiles with controlled signal-to-noise ratios. UMI-4C detects chromosomal interactions with improved sensitivity and specificity, and it can easily be multiplexed to allow robust comparison of contact distributions between loci and conditions. This approach may open the way to the incorporation of contact distributions into quantitative models of gene regulation.

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell.

Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.

Single-cell Hi-C reveals cell-to-cell variability in chromosome structure.

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture (3C) assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single-cell Hi-C, combined with genome-wide statistical analysis and structural modelling of single-copy X chromosomes, to show that individual chromosomes maintain domain organization at the megabase scale, but show variable cell-to-cell chromosome structures at larger scales. Despite this structural stochasticity, localization of active gene domains to boundaries of chromosome territories is a hallmark of chromosomal conformation. Single-cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organization underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns.

Nucleosome maps of the human cytomegalovirus genome reveal a temporal switch in chromatin organization linked to a major IE protein.

Human CMV (hCMV) establishes lifelong infections in most of us, causing developmental defects in human embryos and life-threatening disease in immunocompromised individuals. During productive infection, the viral >230,000-bp dsDNA genome is expressed widely and in a temporal cascade. The hCMV genome does not carry histones when encapsidated but has been proposed to form nucleosomes after release into the host cell nucleus. Here, we present hCMV genome-wide nucleosome occupancy and nascent transcript maps during infection of permissive human primary cells. We show that nucleosomes occupy nuclear viral DNA in a nonrandom and highly predictable fashion. At early times of infection, nucleosomes associate with the hCMV genome largely according to their intrinsic DNA sequence preferences, indicating that initial nucleosome formation is genetically encoded in the virus. However, as infection proceeds to the late phase, nucleosomes redistribute extensively to establish patterns mostly determined by nongenetic factors. We propose that these factors include key regulators of viral gene expression encoded at the hCMV major immediate-early (IE) locus. Indeed, mutant virus genomes deficient for IE1 expression exhibit globally increased nucleosome loads and reduced nucleosome dynamics compared with WT genomes. The temporal nucleosome occupancy differences between IE1-deficient and WT viruses correlate inversely with changes in the pattern of viral nascent and total transcript accumulation. These results provide a framework of spatial and temporal nucleosome organization across the genome of a major human pathogen and suggest that an hCMV major IE protein governs overall viral chromatin structure and function.

An integrated open framework for thermodynamics of reactions that combines accuracy and coverage.

MOTIVATION: The laws of thermodynamics describe a direct, quantitative relationship between metabolite concentrations and reaction directionality. Despite great efforts, thermodynamic data suffer from limited coverage, scattered accessibility and non-standard annotations. We present a framework for unifying thermodynamic data from multiple sources and demonstrate two new techniques for extrapolating the Gibbs energies of unmeasured reactions and conditions. RESULTS: Both methods account for changes in cellular conditions (pH, ionic strength, etc.) by using linear regression over the ΔG(○) of pseudoisomers and reactions. The Pseudoisomeric Reactant Contribution method systematically infers compound formation energies using measured K' and pK(a) data. The Pseudoisomeric Group Contribution method extends the group contribution method and achieves a high coverage of unmeasured reactions. We define a continuous index that predicts the reversibility of a reaction under a given physiological concentration range. In the characteristic physiological range 3µM-3mM, we find that roughly half of the reactions in Escherichia coli's metabolism are reversible. These new tools can increase the accuracy of thermodynamic-based models, especially in non-standard pH and ionic strengths. The reversibility index can help modelers decide which reactions are reversible in physiological conditions. AVAILABILITY: Freely available on the web at: http://equilibrator.weizmann.ac.il. Website implemented in Python, MySQL, Apache and Django, with all major browsers supported. The framework is open-source (code.google.com/p/milo-lab), implemented in pure Python and tested mainly on Linux. CONTACT: ron.milo@weizmann.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Compensation for differences in gene copy number among yeast ribosomal proteins is encoded within their promoters.

Coordinate regulation of ribosomal protein (RP) genes is key for controlling cell growth. In yeast, it is unclear how this regulation achieves the required equimolar amounts of the different RP components, given that some RP genes exist in duplicate copies, while others have only one copy. Here, we tested whether the solution to this challenge is partly encoded within the DNA sequence of the RP promoters, by fusing 110 different RP promoters to a fluorescent gene reporter, allowing us to robustly detect differences in their promoter activities that are as small as ~10%. We found that single-copy RP promoters have significantly higher activities, suggesting that proper RP stoichiometry is indeed partly encoded within the RP promoters. Notably, we also partially uncovered how this regulation is encoded by finding that RP promoters with higher activity have more nucleosome-disfavoring sequences and characteristic spatial organizations of these sequences and of binding sites for key RP regulators. Mutations in these elements result in a significant decrease of RP promoter activity. Thus, our results suggest that intrinsic (DNA-dependent) nucleosome organization may be a key mechanism by which genomes encode biologically meaningful promoter activities. Our approach can readily be applied to uncover how transcriptional programs of other promoters are encoded.

High nucleosome occupancy is encoded at X-linked gene promoters in C. elegans.

We mapped nucleosome occupancy by paired-end Illumina sequencing in C. elegans embryonic cells, adult somatic cells, and a mix of adult somatic and germ cells. In all three samples, the nucleosome occupancy of gene promoters on the X chromosome differed from autosomal promoters. While both X and autosomal promoters exhibit a typical nucleosome-depleted region upstream of transcript start sites and a well-positioned +1 nucleosome, X-linked gene promoters on average exhibit higher nucleosome occupancy relative to autosomal promoters. We show that the difference between X and autosomes does not depend on the somatic dosage compensation machinery. Instead, the chromatin difference at promoters is partly encoded by DNA sequence, because a model trained on nucleosome sequence preferences from S. cerevisiae in vitro data recapitulate nearly completely the experimentally observed difference between X and autosomal promoters. The model predictions also correlate very well with experimentally determined occupancy values genome-wide. The nucleosome occupancy differences observed on X promoters may bear on mechanisms of X chromosome dosage compensation in the soma, and chromosome-wide repression of X in the germline.

p53 binds preferentially to genomic regions with high DNA-encoded nucleosome occupancy.

The human transcription factor TP53 is a pivotal roadblock against cancer. A key unresolved question is how the p53 protein selects its genomic binding sites in vivo out of a large pool of potential consensus sites. We hypothesized that chromatin may play a significant role in this site-selection process. To test this, we used a custom DNA microarray to measure p53 binding at approximately 2000 sites predicted to possess high-sequence specificity, and identified both strongly bound and weakly bound sites. When placed within a plasmid, weakly bound sites become p53 responsive and regain p53 binding when stably integrated into random genomic locations. Notably, strongly bound sites reside preferentially within genomic regions whose DNA sequence is predicted to encode relatively high intrinsic nucleosome occupancy. Using in vivo nucleosome occupancy measurements under conditions where p53 is inactive, we experimentally confirmed this prediction. Furthermore, upon p53 activation, nucleosomes are partially displaced from a relatively broad region surrounding the bound p53 sites, and this displacement is rapidly reversed upon inactivation of p53. Thus, in contrast to the general assumption that transcription-factor binding is preferred in sites that have low nucleosome occupancy prior to factor activation, we find that p53 binding occurs preferentially within a chromatin context of high intrinsic nucleosome occupancy.

Gene expression divergence in yeast is coupled to evolution of DNA-encoded nucleosome organization.

Eukaryotic transcription occurs within a chromatin environment, whose organization has an important regulatory function and is partly encoded in cis by the DNA sequence itself. Here, we examine whether evolutionary changes in gene expression are linked to changes in the DNA-encoded nucleosome organization of promoters. We find that in aerobic yeast species, where cellular respiration genes are active under typical growth conditions, the promoter sequences of these genes encode a relatively open (nucleosome-depleted) chromatin organization. This nucleosome-depleted organization requires only DNA sequence information, is independent of any cofactors and of transcription, and is a general property of growth-related genes. In contrast, in anaerobic yeast species, where cellular respiration genes are relatively inactive under typical growth conditions, respiration gene promoters encode relatively closed (nucleosome-occupied) chromatin organizations. Our results suggest a previously unidentified genetic mechanism underlying phenotypic diversity, consisting of DNA sequence changes that directly alter the DNA-encoded nucleosome organization of promoters.