Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells.

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.

Allele-specific RNA imaging shows that allelic imbalances can arise in tissues through transcriptional bursting.

Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting.

Visualizing adenosine-to-inosine RNA editing in single mammalian cells.

Conversion of adenosine to inosine is a frequent type of RNA editing, but important details about the biology of this conversion remain unknown because of a lack of imaging tools. We developed inoFISH to directly visualize and quantify adenosine-to-inosine-edited transcripts in situ. We found that editing of the GRIA2, EIF2AK2, and NUP43 transcripts is uncorrelated with nuclear localization and paraspeckle association. Further, NUP43 exhibits constant editing levels between single cells, while GRIA2 editing levels vary.

Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?

Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines.

Conditionals by inversion provide a universal method for the generation of conditional alleles.

Conditional mutagenesis is becoming a method of choice for studying gene function, but constructing conditional alleles is often laborious, limited by target gene structure, and at times, prone to incomplete conditional ablation. To address these issues, we developed a technology termed conditionals by inversion (COIN). Before activation, COINs contain an inverted module (COIN module) that lies inertly within the antisense strand of a resident gene. When inverted into the sense strand by a site-specific recombinase, the COIN module causes termination of the target gene's transcription and simultaneously provides a reporter for tracking this event. COIN modules can be inserted into natural introns (intronic COINs) or directly into coding exons as part of an artificial intron (exonic COINs), greatly simplifying allele design and increasing flexibility over previous conditional KO approaches. Detailed analysis of over 20 COIN alleles establishes the reliability of the method and its broad applicability to any gene, regardless of exon-intron structure. Our extensive testing provides rules that help ensure success of this approach and also explains why other currently available conditional approaches often fail to function optimally. Finally, the ability to split exons using the COIN's artificial intron opens up engineering modalities for the generation of multifunctional alleles.

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells.

BACKGROUND: Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and conditions. How the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. RESULTS: We analyze existing bulk and single-cell transcriptomic datasets to uncover the prevalence of transcriptional adaptation in mammalian systems across diverse contexts and cell types. We perform regulon gene expression analyses of transcription factor target sets in both bulk and pooled single-cell genetic perturbation datasets. Our results reveal greater robustness in expression of regulons of transcription factors exhibiting transcriptional adaptation compared to those of transcription factors that do not. Stochastic mathematical modeling of minimal compensatory gene networks qualitatively recapitulates several aspects of transcriptional adaptation, including paralog upregulation and robustness to mutation. Combined with machine learning analysis of network features of interest, our framework offers potential explanations for which regulatory steps are most important for transcriptional adaptation. CONCLUSIONS: Our integrative approach identifies several putative hits-genes demonstrating possible transcriptional adaptation-to follow-up on experimentally and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

XBB.1.5 monovalent mRNA vaccine booster elicits robust neutralizing antibodies against XBB subvariants and JN.1.

COVID-19 vaccines have recently been updated to specifically encode or contain the spike protein of the SARS-CoV-2 XBB.1.5 subvariant, but their immunogenicity in humans has yet to be fully evaluated and reported, particularly against emergent viruses that are rapidly expanding. We now report that administration of an updated monovalent mRNA vaccine booster (XBB.1.5 MV) to previously uninfected individuals boosted serum virus-neutralizing antibodies significantly against not only XBB.1.5 (27.0-fold increase) and EG.5.1 (27.6-fold increase) but also key emerging viruses such as HV.1, HK.3, JD.1.1, and JN.1 (13.3- to 27.4-fold increase). Individuals previously infected by an Omicron subvariant had the highest overall serum neutralizing titers (ID50 1,504-22,978) against all viral variants tested. While immunological imprinting was still evident with the updated vaccines, it was not nearly as severe as observed with the previously authorized bivalent BA.5 vaccine. Our findings strongly support the official recommendation to widely apply the updated COVID-19 vaccines.

Robust SARS-CoV-2-neutralizing antibodies sustained through 6 months post XBB.1.5 mRNA vaccine booster.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies are substantially expanded 1 month after a shot of XBB.1.5 monovalent mRNA vaccine (XBB.1.5 MV) booster, but the durability of this response remains unknown. Here, we address this question by performing neutralization assays on four viral variants (D614G, BA.5, XBB.1.5, and JN.1) using sera from participants obtained at ∼1 month, ∼3 months, and ∼6 months post an XBB.1.5 MV booster. Our findings indicate that the resulting neutralizing antibody titers are robust and generally remain at stable levels for the study period, similar to those following XBB infection. Importantly, this durability of neutralizing antibody titers contrasts with the decline observed after a booster of the original monovalent or BA.5 bivalent mRNA vaccine. Our results are in line with the recent national data from the Centers for Disease Control and Prevention, showing that the efficacy against symptomatic SARS-CoV-2 infection is sustained for up to 4 months after an XBB.1.5 MV booster.

Recurrent SARS-CoV-2 spike mutations confer growth advantages to select JN.1 sublineages.

The recently dominant SARS-CoV-2 Omicron JN.1 has evolved into multiple sublineages, with recurrent spike mutations R346T, F456L, and T572I, some of which exhibit growth advantages, such as KP.2 and KP.3. We investigated these mutations in JN.1, examining their individual and combined effects on immune evasion, ACE2 receptor affinity, and in vitro infectivity. F456L increased resistance to neutralization by human sera, including those after JN.1 breakthrough infections, and by RBD class-1 monoclonal antibodies, significantly altering JN.1 antigenicity. R346T enhanced ACE2-binding affinity and modestly boosted the infectivity of JN.1 pseudovirus, without a discernible effect on serum neutralization, while T572I slightly bolstered evasion of SD1-directed mAbs against JN.1's ancestor, BA.2, possibly by altering SD1 conformation. Importantly, expanding sublineages such as KP.2 containing R346T, F456L, and V1104L, showed similar neutralization resistance as JN.1 with R346T and F456L, suggesting V1104L does not appreciably affect antibody evasion. Furthermore, the hallmark mutation Q493E in KP.3 significantly reduced ACE2-binding affinity and viral infectivity, without noticeably impacting serum neutralization. Our findings illustrate how certain JN.1 mutations confer growth advantages in the population and could inform the design of the next COVID-19 vaccine booster.

SARS-CoV-2 omicron BA.2.87.1 exhibits higher susceptibility to serum neutralization than EG.5.1 and JN.1.

As SARS-CoV-2 continues to spread and mutate, tracking the viral evolutionary trajectory and understanding the functional consequences of its mutations remain crucial. Here, we characterized the antibody evasion, ACE2 receptor engagement, and viral infectivity of the highly mutated SARS-CoV-2 Omicron subvariant BA.2.87.1. Compared with other Omicron subvariants, including EG.5.1 and the current predominant JN.1, BA.2.87.1 exhibits less immune evasion, reduced viral receptor engagement, and comparable infectivity in Calu-3 lung cells. Intriguingly, two large deletions (Δ15-26 and Δ136-146) in the N-terminal domain (NTD) of the spike protein facilitate subtly increased antibody evasion but significantly diminish viral infectivity. Collectively, our data support the announcement by the USA CDC that the public health risk posed by BA.2.87.1 appears to be low.

Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells.

Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short timescales and stochastic at long timescales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells.

Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene can trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, to date, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and contexts. Moreover, how the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. Here we combine computational analysis of existing datasets with stochastic mathematical modeling and machine learning to uncover the widespread prevalence of transcriptional adaptation in mammalian systems and the diverse single-cell manifestations of minimal compensatory gene networks. Regulon gene expression analysis of a pooled single-cell genetic perturbation dataset recapitulates important model predictions. Our integrative approach uncovers several putative hits-genes demonstrating possible transcriptional adaptation-to follow up on experimentally, and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

Evolving antibody evasion and receptor affinity of the Omicron BA.2.75 sublineage of SARS-CoV-2.

SARS-CoV-2 Omicron BA.2.75 has diversified into multiple subvariants with additional spike mutations and several are expanding in prevalence, particularly CH.1.1 and BN.1. Here, we investigated the viral receptor affinities and neutralization evasion properties of major BA.2.75 subvariants actively circulating in different regions worldwide. We found two distinct evolutionary pathways and three newly identified mutations that shaped the virological features of these subvariants. One phenotypic group exhibited a discernible decrease in viral receptor affinities, but a noteworthy increase in resistance to antibody neutralization, as exemplified by CH.1.1, which is apparently as resistant as XBB.1.5. In contrast, a second group demonstrated a substantial increase in viral receptor affinity but only a moderate increase in antibody evasion, as exemplified by BN.1. We also observed that all prevalent SARS-CoV-2 variants in the circulation presently, except for BN.1, exhibit profound levels of antibody evasion, suggesting this is the dominant determinant of virus transmissibility today.

Retrospective identification of intrinsic factors that mark pluripotency potential in rare somatic cells.

Pluripotency can be induced in somatic cells by the expression of the four "Yamanaka" factors OCT4, KLF4, SOX2, and MYC. However, even in homogeneous conditions, usually only a rare subset of cells admit reprogramming, and the molecular characteristics of this subset remain unknown. Here, we apply retrospective clone tracing to identify and characterize the individual human fibroblast cells that are primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis led to increased reprogramming efficiency, identifying it as a barrier to reprogramming. Changing the frequency of reprogramming by inhibiting the activity of LSD1 led to an enlarging of the pool of cells that were primed for reprogramming. Our results show that even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

Cell type determination for cardiac differentiation occurs soon after seeding of human-induced pluripotent stem cells.

BACKGROUND: Cardiac differentiation of human-induced pluripotent stem (hiPS) cells consistently produces a mixed population of cardiomyocytes and non-cardiac cell types, even when using well-characterized protocols. We sought to determine whether different cell types might result from intrinsic differences in hiPS cells prior to the onset of differentiation. RESULTS: By associating individual differentiated cells that share a common hiPS cell precursor, we tested whether expression variability is predetermined from the hiPS cell state. In a single experiment, cells that shared a progenitor were more transcriptionally similar to each other than to other cells in the differentiated population. However, when the same hiPS cells were differentiated in parallel, we did not observe high transcriptional similarity across differentiations. Additionally, we found that substantial cell death occurs during differentiation in a manner that suggested all cells were equally likely to survive or die, suggesting that there is no intrinsic selection bias for cells descended from particular hiPS cell progenitors. We thus wondered how cells grow spatially during differentiation, so we labeled cells by expression of marker genes and found that cells expressing the same marker tended to occur in patches. Our results suggest that cell type determination across multiple cell types, once initiated, is maintained in a cell-autonomous manner for multiple divisions. CONCLUSIONS: Altogether, our results show that while substantial heterogeneity exists in the initial hiPS cell population, it is not responsible for the variability observed in differentiated outcomes; instead, factors specifying the various cell types likely act during a window that begins shortly after the seeding of hiPS cells for differentiation.

Responsiveness to perturbations is a hallmark of transcription factors that maintain cell identity in vitro.

Identifying the particular transcription factors that maintain cell type in vitro is important for manipulating cell type. Identifying such transcription factors by their cell-type-specific expression or their involvement in developmental regulation has had limited success. We hypothesized that because cell type is often resilient to perturbations, the transcriptional response to perturbations would reveal identity-maintaining transcription factors. We developed perturbation panel profiling (P3) as a framework for perturbing cells across many conditions and measuring gene expression responsiveness transcriptome-wide. In human iPSC-derived cardiac myocytes, P3 showed that transcription factors important for cardiac myocyte differentiation and maintenance were among the most frequently upregulated (most responsive). We reasoned that one function of responsive genes may be to maintain cellular identity. We identified responsive transcription factors in fibroblasts using P3 and found that suppressing their expression led to enhanced reprogramming. We propose that responsiveness to perturbations is a property of transcription factors that help maintain cellular identity in vitro. A record of this paper's transparent peer review process is included in the supplemental information.

Genetic screening for single-cell variability modulators driving therapy resistance.

Cellular plasticity describes the ability of cells to transition from one set of phenotypes to another. In melanoma, transient fluctuations in the molecular state of tumor cells mark the formation of rare cells primed to survive BRAF inhibition and reprogram into a stably drug-resistant fate. However, the biological processes governing cellular priming remain unknown. We used CRISPR-Cas9 genetic screens to identify genes that affect cell fate decisions by altering cellular plasticity. We found that many factors can independently affect cellular priming and fate decisions. We discovered a new plasticity-based mode of increasing resistance to BRAF inhibition that pushes cells towards a more differentiated state. Manipulating cellular plasticity through inhibition of DOT1L before the addition of the BRAF inhibitor resulted in more therapy resistance than concurrent administration. Our results indicate that modulating cellular plasticity can alter cell fate decisions and may prove useful for treating drug resistance in other cancers.

Remodeling of the Collagen Matrix in Aging Skin Promotes Melanoma Metastasis and Affects Immune Cell Motility.

Physical changes in skin are among the most visible signs of aging. We found that young dermal fibroblasts secrete high levels of extracellular matrix (ECM) constituents, including proteoglycans, glycoproteins, and cartilage-linking proteins. The most abundantly secreted was HAPLN1, a hyaluronic and proteoglycan link protein. HAPLN1 was lost in aged fibroblasts, resulting in a more aligned ECM that promoted metastasis of melanoma cells. Reconstituting HAPLN1 inhibited metastasis in an aged microenvironment, in 3-D skin reconstruction models, and in vivo. Intriguingly, aged fibroblast-derived matrices had the opposite effect on the migration of T cells, inhibiting their motility. HAPLN1 treatment of aged fibroblasts restored motility of mononuclear immune cells, while impeding that of polymorphonuclear immune cells, which in turn affected regulatory T-cell recruitment. These data suggest that although age-related physical changes in the ECM can promote tumor cell motility, they may adversely affect the motility of some immune cells, resulting in an overall change in the immune microenvironment. Understanding the physical changes in aging skin may provide avenues for more effective therapy for older patients with melanoma. SIGNIFICANCE: These data shed light on the mechanochemical interactions that occur between aged skin, tumor, and immune cell populations, which may affect tumor metastasis and immune cell infiltration, with implications for the efficacy of current therapies for melanoma.See related commentary by Marie and Merlino, p. 19.This article is highlighted in the In This Issue feature, p. 1.

ClampFISH detects individual nucleic acid molecules using click chemistry-based amplification.

Methods for detecting single nucleic acids in cell and tissues, such as fluorescence in situ hybridization (FISH), are limited by relatively low signal intensity and nonspecific probe binding. Here we present click-amplifying FISH (clampFISH), a method for fluorescence detection of nucleic acids that achieves high specificity and high-gain (>400-fold) signal amplification. ClampFISH probes form a 'C' configuration upon hybridization to the sequence of interest in a double helical manner. The ends of the probes are ligated together using bio-orthogonal click chemistry, effectively locking the probes around the target. Iterative rounds of hybridization and click amplify the fluorescence intensity. We show that clampFISH enables the detection of RNA species with low-magnification microscopy and in RNA-based flow cytometry. Additionally, we show that the modular design of clampFISH probes allows multiplexing of RNA and DNA detection, that the locking mechanism prevents probe detachment in expansion microscopy, and that clampFISH can be applied in tissue samples.