Capybara: A computational tool to measure cell identity and fate transitions

Stemformatics data portal enables transcriptional benchmarking of lab-derived myeloid cells

Stemformatics.org has been serving the stem cell research community for over a decade, by making it easy for users to find and view transcriptional profiles of pluripotent and adult stem cells and their progeny, comparing data derived from multiple tissues and derivation methods. In recent years, Stemformatics has shifted its focus from curation to collation and integration of public data with shared phenotypes. It now hosts several integrated expression atlases based on human myeloid cells, which allow for easy cross-dataset comparisons and discovery of emerging cell subsets and activation properties. The atlases are designed for external users to benchmark their own data against a common reference. Here, we use case studies to illustrate how to find and explore previously published datasets of relevance and how in-vitro-derived cells can be transcriptionally matched to cells in the integrated atlas to highlight phenotypes of interest.

Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes

Complex gene regulatory mechanisms underlie differentiation and reprogramming. Contemporary single-cell lineage-tracing (scLT) methods use expressed, heritable DNA barcodes to combine cell lineage readout with single-cell transcriptomics. However, reliance on transcriptional profiling limits adaptation to other single-cell assays. With CellTag-multi, we present an approach that enables direct capture of heritable random barcodes expressed as polyadenylated transcripts, in both single-cell RNA sequencing and single-cell Assay for Transposase Accessible Chromatin using sequencing assays, allowing for independent clonal tracking of transcriptional and epigenomic cell states. We validate CellTag-multi to characterize progenitor cell lineage priming during mouse hematopoiesis. Additionally, in direct reprogramming of fibroblasts to endoderm progenitors, we identify core regulatory programs underlying on-target and off-target fates. Furthermore, we reveal the transcription factor Zfp281 as a regulator of reprogramming outcome, biasing cells toward an off-target mesenchymal fate. Our results establish CellTag-multi as a lineage-tracing method compatible with multiple single-cell modalities and demonstrate its utility in revealing fate-specifying gene regulatory changes across diverse paradigms of differentiation and reprogramming.

Topological and geometric analysis of cell states in single-cell transcriptomic data

Single-cell RNA sequencing (scRNA-seq) enables dissecting cellular heterogeneity in tissues, resulting in numerous biological discoveries. Various computational methods have been devised to delineate cell types by clustering scRNA-seq data, where clusters are often annotated using prior knowledge of marker genes. In addition to identifying pure cell types, several methods have been developed to identify cells undergoing state transitions, which often rely on prior clustering results. The present computational approaches predominantly investigate the local and first-order structures of scRNA-seq data using graph representations, while scRNA-seq data frequently display complex high-dimensional structures. Here, we introduce scGeom, a tool that exploits the multiscale and multidimensional structures in scRNA-seq data by analyzing the geometry and topology through curvature and persistent homology of both cell and gene networks. We demonstrate the utility of these structural features to reflect biological properties and functions in several applications, where we show that curvatures and topological signatures of cell and gene networks can help indicate transition cells and the differentiation potential of cells. We also illustrate that structural characteristics can improve the classification of cell types.

Programming human cell fate: overcoming challenges and unlocking potential through technological breakthroughs

In recent years, there have been notable advancements in the ability to programme human cell identity, enabling us to design and manipulate cell function in a Petri dish. However, current protocols for generating target cell types often lack efficiency and precision, resulting in engineered cells that do not fully replicate the desired identity or functional output. This applies to different methods of cell programming, which face similar challenges that hinder progress and delay the achievement of a more favourable outcome. However, recent technological and analytical breakthroughs have provided us with unprecedented opportunities to advance the way we programme cell fate. The Company of Biologists' 2023 workshop on 'Novel Technologies for Programming Human Cell Fate' brought together experts in human cell fate engineering and experts in single-cell genomics, manipulation and characterisation of cells on a single (sub)cellular level. Here, we summarise the main points that emerged during the workshop's themed discussions. Furthermore, we provide specific examples highlighting the current state of the field as well as its trajectory, offering insights into the potential outcomes resulting from the application of these breakthrough technologies in precisely engineering the identity and function of clinically valuable human cells.

Platform-agnostic CellNet enables cross-study analysis of cell fate engineering protocols

Optimization of cell engineering protocols requires standard, comprehensive quality metrics. We previously developed CellNet, a computational tool to quantitatively assess the transcriptional fidelity of engineered cells compared with their natural counterparts, based on bulk-derived expression profiles. However, this platform and others were limited in their ability to compare data from different sources, and no current tool makes it easy to compare new protocols with existing state-of-the-art protocols in a standardized manner. Here, we utilized our prior application of the top-scoring pair transformation to build a computational platform, platform-agnostic CellNet (PACNet), to address both shortcomings. To demonstrate the utility of PACNet, we applied it to thousands of samples from over 100 studies that describe dozens of protocols designed to produce seven distinct cell types. We performed an in-depth examination of hepatocyte and cardiomyocyte protocols to identify the best-performing methods, characterize the extent of intra-protocol and inter-lab variation, and identify common off-target signatures, including a surprising neural/neuroendocrine signature in primary liver-derived organoids. We have made PACNet available as an easy-to-use web application, allowing users to assess their protocols relative to our database of reference engineered samples, and as open-source, extensible code.

Lmo4 synergizes with Fezf2 to promote direct in vivo reprogramming of upper layer cortical neurons and cortical glia towards deep-layer neuron identities

In vivo direct neuronal reprogramming relies on the implementation of an exogenous transcriptional program allowing to achieve conversion of a particular neuronal or glial cell type towards a new identity. The transcription factor (TF) Fezf2 is known for its role in neuronal subtype specification of deep-layer (DL) subcortical projection neurons. High ectopic Fezf2 expression in mice can convert both upper-layer (UL) and striatal projection neurons into a corticofugal fate, even if at low efficiency. In this study, we show that Fezf2 synergizes with the nuclear co-adaptor Lmo4 to further enhance reprogramming of UL cortical pyramidal neurons into DL corticofugal neurons, at both embryonic and early postnatal stages. Reprogrammed neurons express DL molecular markers and project toward subcerebral targets, including thalamus, cerebral peduncle (CP), and spinal cord (SC). We also show that co-expression of Fezf2 with the reprogramming factors Neurog2 and Bcl2 in early postnatal mouse glia promotes glia-to-neuron conversion with partial hallmarks of DL neurons and with Lmo4 promoting further morphological complexity. These data support a novel role for Lmo4 in synergizing with Fezf2 during direct lineage conversion in vivo.

Recurrent composite markers of cell types and states

Determining concise sets of genomic markers that identify cell types and states within tissue ecosystems remains challenging. To address this challenge, we developed Recurrent Composite Markers for Biological Identities with Neighborhood Enrichment (RECOMBINE). Validations of RECOMBINE with simulation and transcriptomics data in bulk, single-cell and spatial resolutions demonstrated the method's ability for unbiased selection of composite markers that characterize biological subpopulations. RECOMBINE captured markers of mouse visual cortex from single-cell RNA sequencing data and provided a gene panel for targeted spatial transcriptomics profiling. RECOMBINE identified composite markers of CD8 T cell states including GZMK ⁺ HAVCR2 ^- effector memory cells associated with anti-PD1 therapy response. The method outperformed differential gene expression analysis in characterizing a rare cell subpopulation within mouse intestine. Using RECOMBINE, we uncovered hierarchical gene programs of inter- and intra-tumoral heterogeneity in breast and skin tumors. In conclusion, RECOMBINE offers a data-driven approach for unbiased selection of composite markers, resulting in improved interpretation, discovery, and validation of cell types and states.

Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: Reconciling controversy or fueling the debate?

The notion of exploiting the regenerative potential of the human brain in physiological aging or neurological diseases represents a particularly attractive alternative to conventional strategies for enhancing or restoring brain function. However, a major first question to address is whether the human brain does possess the ability to regenerate. The existence of human adult hippocampal neurogenesis (AHN) has been at the center of a fierce scientific debate for many years. The advent of single-cell transcriptomic technologies was initially viewed as a panacea to resolving this controversy. However, recent single-cell RNA sequencing studies in the human hippocampus yielded conflicting results. Here, we critically discuss and re-analyze previously published AHN-related single-cell transcriptomic datasets. We argue that, although promising, the single-cell transcriptomic profiling of AHN in the human brain can be confounded by methodological, conceptual, and biological factors that need to be consistently addressed across studies and openly discussed within the scientific community.

Single-cell lineage tracing reveals hierarchy and mechanism of adipocyte precursor maturation

White adipose tissue is crucial in various physiological processes. In response to high caloric intake, adipose tissue may expand by generating new adipocytes. Adipocyte precursor cells (progenitors and preadipocytes) are essential for generating mature adipocytes, and single-cell RNA sequencing provides new means to identify these populations. Here, we characterized adipocyte precursor populations in the skin, an adipose depot with rapid and robust generation of mature adipocytes. We identified a new population of immature preadipocytes, revealed a biased differentiation potential of progenitor cells, and identified Sox9 as a critical factor in driving progenitors toward adipose commitment, the first known mechanism of progenitor differentiation. These findings shed light on the specific dynamics and molecular mechanisms underlying rapid adipogenesis in the skin.

The advent of immune stimulating CAFs in cancer

The theory that cancer-associated fibroblasts (CAFs) are immunosuppressive cells has prevailed throughout the past decade. However, recent high-throughput, high-resolution mesenchyme-directed single-cell studies have harnessed computational advances to functionally characterize cell states, highlighting the existence of immunostimulatory CAFs. Our group and others have uncovered and experimentally substantiated key functions of cancer antigen-presenting CAFs in T cell immunity, both in vitro and in vivo, refuting the conventional assumption that CAFs impede adaptive immune rejection of tumours. In this Perspective, I unify the follicular and non-follicular, non-endothelial stroma of tumours under the 'peripheral adaptive immune mesenchyme' framework and position subsets of CAFs as direct positive regulators of the adaptive immune system. Building on the understanding of cancer antigen presentation by CAFs and the second touch hypothesis, which postulates that full T cell polarization requires interaction with antigen-presenting cells in the non-lymphoid tissue where the antigen resides, I re-design the 'cancer-immunity cycle' to incorporate intratumoural activation of cancer-specific CD4⁺ T cells. Lastly, a road map to therapeutic harnessing of immunostimulatory CAF states is proposed.

Gene regulatory network reconfiguration in direct lineage reprogramming

In direct lineage conversion, transcription factor (TF) overexpression reconfigures gene regulatory networks (GRNs) to reprogram cell identity. We previously developed CellOracle, a computational method to infer GRNs from single-cell transcriptome and epigenome data. Using inferred GRNs, CellOracle simulates gene expression changes in response to TF perturbation, enabling in silico interrogation of network reconfiguration. Here, we combine CellOracle analysis with lineage tracing of fibroblast to induced endoderm progenitor (iEP) conversion, a prototypical direct reprogramming paradigm. By linking early network state to reprogramming outcome, we reveal distinct network configurations underlying successful and failed fate conversion. Via in silico simulation of TF perturbation, we identify new factors to coax cells into successfully converting their identity, uncovering a central role for the AP-1 subunit Fos with the Hippo signaling effector, Yap1. Together, these results demonstrate the efficacy of CellOracle to infer and interpret cell-type-specific GRN configurations, providing new mechanistic insights into lineage reprogramming.

Targeting the Tumor-Tumor Microenvironment Crosstalk

INTRODUCTION

Cancer development and progression is a complex process influenced by co-evolution of the cancer cells and their microenvironment. However, traditional anti-cancer therapy is mostly targeted toward cancer cells. To improve the efficacy of cancer drugs, the complex interactions between the tumor (T) and the tumor microenvironment (TME) should be considered while developing therapeutics.

AREAS COVERED

The present review article will discuss the components of T-TME as well as the potential to co-target these two distinct elements. We document that these approaches have resulted in success in preventing tumor progression and metastasis, albeit in animal models in some cases. Lastly, it is important to consider the tissue context and tumor type as these could significantly modify the role of these molecules/pathways and hence the overall likelihood of response. Furthermore, we discuss the potential strategies to target the components of tumor microenvironment in anti-cancer therapy. PubMed and ClinicalTrials.gov was searched through May 2023.

EXPERT OPINION

The tumor-tumor microenvironment cross talk and heterogeneity are major mechanisms conferring resistance to standard of care. Better understanding of the tissue specific T-TME interactions and dual targeting has the promise of improving cancer control and clinical outcomes.

The Human Dendritic Cell Atlas: An Integrated Transcriptional Tool to Study Human Dendritic Cell Biology

Dendritic cells (DCs) are functionally diverse and are present in most adult tissues, but deep understanding of human DC biology is hampered by relatively small numbers of these in circulation and their short lifespan in human tissues. We built a transcriptional atlas of human DCs by combining samples from 14 expression profiling studies derived from 10 laboratories. We identified significant gene expression variation of DC subset-defining markers across tissue type and upon viral or bacterial stimulation. We further highlight critical gaps between in vitro-derived DC subsets and their in vivo counterparts and provide evidence that monocytes or cord blood progenitor in vitro-differentiated DCs fail to capture the repertoire of primary DC subsets or behaviors. In constructing a reference DC atlas, we provide an important resource for the community wishing to identify and annotate tissue-specific DC subsets from single-cell datasets, or benchmark new in vitro models of DC biology.

Cellular barcoding to decipher clonal dynamics in disease

Cellular barcodes are distinct DNA sequences that enable one to track specific cells across time or space. Recent advances in our ability to detect natural or synthetic cellular barcodes, paired with single-cell readouts of cell state, have markedly increased our knowledge of clonal dynamics and genealogies of the cells that compose a variety of tissues and organs. These advances hold promise to redefine our view of human disease. Here, we provide an overview of cellular barcoding approaches, discuss applications to gain new insights into disease mechanisms, and provide an outlook on future applications. We discuss unanticipated insights gained through barcoding in studies of cancer and blood cell production and describe how barcoding can be applied to a growing array of medical fields, particularly with the increasing recognition of clonal contributions in human diseases.

Cellular and transcriptional heterogeneity in the intrahepatic biliary epithelium

Epithelial tissues comprise heterogeneous cellular subpopulations, which often compartmentalize specialized functions like absorption and secretion to distinct cell types. In the liver, hepatocytes and biliary epithelial cells (BECs; also called cholangiocytes) are the two major epithelial lineages and play distinct roles in (1) metabolism, protein synthesis, detoxification, and (2) bile transport and modification, respectively. Recent technological advances, including single cell transcriptomic assays, have shed new light on well-established heterogeneity among hepatocytes, endothelial cells, and immune cells in the liver. However, a "ground truth" understanding of molecular heterogeneity in BECs has remained elusive, and the field currently lacks a set of consensus biomarkers for identifying BEC subpopulations. Here, we review long-standing definitions of BEC heterogeneity as well as emerging studies that aim to characterize BEC subpopulations using next generation single cell assays. Understanding cellular heterogeneity in the intrahepatic bile ducts holds promise for expanding our foundational mechanistic knowledge of BECs during homeostasis and disease.

Profiling intermediate cell states in high resolution

Kong et al. present Capybara, a computational method to identify cell states from single-cell gene expression data. Notably, Capybara can identify intermediate cell states and cell state transitions, offering biologists new means with which to interrogate the states and fates of cells.