Single cell RNA-sequencing identifies a metabolic aspect of apoptosis in Rbf mutant

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Insect Insights at the Single-Cell Level: Technologies and Applications

Single-cell techniques are a promising way to unravel the complexity and heterogeneity of transcripts at the cellular level and to reveal the composition of different cell types and functions in a tissue or organ. In recent years, advances in single-cell RNA sequencing (scRNA-seq) have further changed our view of biological systems. The application of scRNA-seq in insects enables the comprehensive characterization of both common and rare cell types and cell states, the discovery of new cell types, and revealing how cell types relate to each other. The recent application of scRNA-seq techniques to insect tissues has led to a number of exciting discoveries. Here we provide an overview of scRNA-seq and its application in insect research, focusing on biological applications, current challenges, and future opportunities to make new discoveries with scRNA-seq in insects.

A single cell genomics atlas of the Drosophila larval eye reveals distinct photoreceptor developmental timelines

The Drosophila eye is a powerful model system to study the dynamics of cell differentiation, cell state transitions, cell maturation, and pattern formation. However, a high-resolution single cell genomics resource that accurately profiles all major cell types of the larval eye disc and their spatiotemporal relationships is lacking. Here, we report transcriptomic and chromatin accessibility data for all known cell types in the developing eye. Photoreceptors appear as strands of cells that represent their dynamic developmental timelines. As photoreceptor subtypes mature, they appear to assume a common transcriptomic profile that is dominated by genes involved in axon function. We identify cell type maturation genes, enhancers, and potential regulators, as well as genes with distinct R3 or R4 photoreceptor specific expression. Finally, we observe that the chromatin accessibility between cones and photoreceptors is distinct. These single cell genomics atlases will greatly enhance the power of the Drosophila eye as a model system.

Combined inactivation of RB and Hippo converts differentiating Drosophila photoreceptors into eye progenitor cells through derepression of homothorax

The retinoblastoma (RB) and Hippo pathways interact to regulate cell proliferation and differentiation. However, the mechanism of interaction is not fully understood. Drosophila photoreceptors with inactivated RB and Hippo pathways specify normally but fail to maintain their neuronal identity and dedifferentiate. We performed single-cell RNA sequencing to elucidate the cause of dedifferentiation and to determine the fate of these cells. We find that dedifferentiated cells adopt a progenitor-like fate due to inappropriate activation of the retinal differentiation suppressor homothorax (hth) by Yki/Sd. This results in the activation of a distinct Yki/Hth transcriptional program, driving photoreceptor dedifferentiation. We show that Rbf physically interacts with Yki and, together with the GAGA factor, inhibits the hth expression. Thus, RB and Hippo pathways cooperate to maintain photoreceptor differentiation by preventing inappropriate expression of hth in differentiating photoreceptors. Our work highlights the importance of both RB and Hippo pathway activities for maintaining the state of terminal differentiation.

Artificial Intelligence Models for Cell Type and Subtype Identification Based on Single-Cell RNA Sequencing Data in Vision Science

Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various tissues. However, scRNA-seq based identification of discrete cell-types is still labor intensive and depends on prior molecular knowledge. Artificial intelligence has provided faster, more accurate, and user-friendly approaches for cell-type identification. In this review, we discuss recent advances in cell-type identification methods using artificial intelligence techniques based on single-cell and single-nucleus RNA sequencing data in vision science. The main purpose of this review paper is to assist vision scientists not only to select suitable datasets for their problems, but also to be aware of the appropriate computational tools to perform their analysis. Developing novel methods for scRNA-seq data analysis remains to be addressed in future studies.

Combined inactivation of RB and Hippo pathways converts differentiating photoreceptors into eye progenitor cells through derepression of homothorax

The RB and Hippo pathways interact to regulate cell proliferation and differentiation. However, their mechanism of interaction is not fully understood. Drosophila photoreceptors with inactivated RB and Hippo pathways specify normally but fail to maintain neuronal identity and dedifferentiate. We performed single-cell RNA-sequencing to elucidate the cause of dedifferentiation and the fate of these cells. We find that dedifferentiated cells adopt a progenitor-like fate due to inappropriate activation of the retinal differentiation suppressor homothorax (hth) by Yki/Sd. This results in activation of the Yki/Hth transcriptional program, driving photoreceptor dedifferentiation. We show that Rbf physically interacts with Yki which, together with the GAGA factor, inhibits hth expression. Thus, RB and Hippo pathways cooperate to maintain photoreceptor differentiation by preventing inappropriate expression of hth in differentiating photoreceptors. Our work accentuates the importance of both RB and Hippo pathway activity for maintaining the state of terminal differentiation.

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.

Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material

Background

Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.

Results

We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.

Conclusion

We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.

Single-Cell Atlas of the Drosophila Leg Disc Identifies a Long Non-Coding RNA in Late Development

The Drosophila imaginal disc has been an excellent model for the study of developmental gene regulation. In particular, long non-coding RNAs (lncRNAs) have gained widespread attention in recent years due to their important role in gene regulation. Their specific spatiotemporal expressions further support their role in developmental processes and diseases. In this study, we explored the role of a novel lncRNA in Drosophila leg development by dissecting and dissociating w¹¹¹⁸ third-instar larval third leg (L3) discs into single cells and single nuclei, and performing single-cell RNA-sequencing (scRNA-seq) and single-cell assays for transposase-accessible chromatin (scATAC-seq). Single-cell transcriptomics analysis of the L3 discs across three developmental timepoints revealed different cell types and identified lncRNA:CR33938 as a distal specific gene with high expression in late development. This was further validated by fluorescence in-situ hybridization (FISH). The scATAC-seq results reproduced the single-cell transcriptomics landscape and elucidated the distal cell functions at different timepoints. Furthermore, overexpression of lncRNA:CR33938 in the S2 cell line increased the expression of leg development genes, further elucidating its potential role in development.

Isolation and RNA sequencing of single nuclei from Drosophila tissues

Many insect cells are encapsulated within the exoskeleton and cannot be dissociated intact, making them inaccessible to single-cell transcriptomic profiling. We have used single-nucleus RNA sequencing to extract transcriptomic information from multiple Drosophila tissues. Here, we describe procedures for the (1) dissociation of single nuclei, (2) isolation of single nuclei using two popular cell sorters, and (3) preparation of libraries for Smart-seq2 and 10× Genomics. This protocol enables generation of high-quality transcriptomes from single nuclei and can be applied to other species. For complete details on the use and execution of this protocol, please refer to McLaughlin et al. (2021) and Li et al. (2022).

High-resolution 3D spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae

Drosophila has long been a successful model organism in multiple biomedical fields. Spatial gene expression patterns are critical for the understanding of complex pathways and interactions, whereas temporal gene expression changes are vital for studying highly dynamic physiological activities. Systematic studies in Drosophila are still impeded by the lack of spatiotemporal transcriptomic information. Here, utilizing spatial enhanced resolution omics-sequencing (Stereo-seq), we dissected the spatiotemporal transcriptomic changes of developing Drosophila with high resolution and sensitivity. We demonstrated that Stereo-seq data can be used for the 3D reconstruction of the spatial transcriptomes of Drosophila embryos and larvae. With these 3D models, we identified functional subregions in embryonic and larval midguts, uncovered spatial cell state dynamics of larval testis, and revealed known and potential regulons of transcription factors within their topographic background. Our data provide the Drosophila research community with useful resources of organism-wide spatiotemporally resolved transcriptomic information across developmental stages.

Cell cycle expression of polarity genes features Rb targeting of Vang

Specification of cellular polarity is vital to normal tissue development and function. Pioneering studies in Drosophila and C. elegans have elucidated the composition and dynamics of protein complexes critical for establishment of cell polarity, which is manifest in processes such as cell migration and asymmetric cell division. Conserved throughout metazoans, planar cell polarity (PCP) genes are implicated in disease, including neural tube closure defects associated with mutations in VANGL1/2. PCP protein regulation is well studied; however, relatively little is known about transcriptional regulation of these genes. Our earlier study revealed an unexpected role for the fly Rbf1 retinoblastoma corepressor protein, a regulator of cell cycle genes, in transcriptional regulation of polarity genes. Here we analyze the physiological relevance of the role of E2F/Rbf proteins in the transcription of the key core polarity gene Vang. Targeted mutations to the E2F site within the Vang promoter disrupts binding of E2F/Rbf proteins in vivo, leading to polarity defects in wing hairs. E2F regulation of Vang is supported by the requirement for this motif in a reporter gene. Interestingly, the promoter is repressed by overexpression of E2F1, a transcription factor generally identified as an activator. Consistent with the regulation of this polarity gene by E2F and Rbf factors, expression of Vang and other polarity genes is found to peak in G2/M phase in cells of the embryo and wing imaginal disc, suggesting that cell cycle signals may play a role in regulation of these genes. These findings suggest that the E2F/Rbf complex mechanistically links cell proliferation and polarity.

Metabolism Characteristics of Th17 and Regulatory T Cells in Autoimmune Diseases

The abnormal number and functional deficiency of immune cells are the pathological basis of various diseases. Recent years, the imbalance of Th17/regulatory T (Treg) cell underlies the occurrence and development of inflammation in autoimmune diseases (AID). Currently, studies have shown that material and energy metabolism is essential for maintaining cell survival and normal functions and the altered metabolic state of immune cells exists in a variety of AID. This review summarizes the biology and functions of Th17 and Treg cells in AID, with emphasis on the advances of the roles and regulatory mechanisms of energy metabolism in activation, differentiation and physiological function of Th17 and Treg cells, which will facilitate to provide targets for the treatment of immune-mediated diseases.

A non-catalytic scaffolding activity of hexokinase 2 contributes to EMT and metastasis

Hexokinase 2 (HK2), which catalyzes the first committed step in glucose metabolism, is induced in cancer cells. HK2's role in tumorigenesis has been attributed to its glucose kinase activity. Here, we describe a kinase independent HK2 activity, which contributes to metastasis. HK2 binds and sequesters glycogen synthase kinase 3 (GSK3) and acts as a scaffold forming a ternary complex with the regulatory subunit of protein kinase A (PRKAR1a) and GSK3β to facilitate GSK3β phosphorylation and inhibition by PKA. Thus, HK2 functions as an A-kinase anchoring protein (AKAP). Phosphorylation by GSK3β targets proteins for degradation. Consistently, HK2 increases the level and stability of GSK3 targets, MCL1, NRF2, and particularly SNAIL. In addition to GSK3 inhibition, HK2 kinase activity mediates SNAIL glycosylation, which prohibits its phosphorylation by GSK3. Finally, in mouse models of breast cancer metastasis, HK2 deficiency decreases SNAIL protein levels and inhibits SNAIL-mediated epithelial mesenchymal transition and metastasis.

Analysis of Single-Cell Transcriptome Data in Drosophila

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.

mDrop-Seq: Massively Parallel Single-Cell RNA-Seq of Saccharomyces cerevisiae and Candida albicans

Advances in high-throughput single-cell RNA sequencing (scRNA-seq) have been limited by technical challenges such as tough cell walls and low RNA quantity that prevent transcriptomic profiling of microbial species at throughput. We present microbial Drop-seq or mDrop-seq, a high-throughput scRNA-seq technique that is demonstrated on two yeast species, Saccharomyces cerevisiae, a popular model organism, and Candida albicans, a common opportunistic pathogen. We benchmarked mDrop-seq for sensitivity and specificity and used it to profile 35,109 S. cerevisiae cells to detect variation in mRNA levels between them. As a proof of concept, we quantified expression differences in heat shock S. cerevisiae using mDrop-seq. We detected differential activation of stress response genes within a seemingly homogenous population of S. cerevisiae under heat shock. We also applied mDrop-seq to C. albicans cells, a polymorphic and clinically relevant species of yeast with a thicker cell wall compared to S. cerevisiae. Single-cell transcriptomes in 39,705 C. albicans cells were characterized using mDrop-seq under different conditions, including exposure to fluconazole, a common anti-fungal drug. We noted differential regulation in stress response and drug target pathways between C. albicans cells, changes in cell cycle patterns and marked increases in histone activity when treated with fluconazole. We demonstrate mDrop-seq to be an affordable and scalable technique that can quantify the variability in gene expression in different yeast species. We hope that mDrop-seq will lead to a better understanding of genetic variation in pathogens in response to stimuli and find immediate applications in investigating drug resistance, infection outcome and developing new drugs and treatment strategies.

Single-cell RNA sequencing in Drosophila: Technologies and applications

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under:   Technologies > Analysis of the Transcriptome.

Emerging Single-Cell Technological Approaches to Investigate Chromatin Dynamics and Centromere Regulation in Human Health and Disease

Epigenetic regulators play a crucial role in establishing and maintaining gene expression states. To date, the main efforts to study cellular heterogeneity have focused on elucidating the variable nature of the chromatin landscape. Specific chromatin organisation is fundamental for normal organogenesis and developmental homeostasis and can be affected by different environmental factors. The latter can lead to detrimental alterations in gene transcription, as well as pathological conditions such as cancer. Epigenetic marks regulate the transcriptional output of cells. Centromeres are chromosome structures that are epigenetically regulated and are crucial for accurate segregation. The advent of single-cell epigenetic profiling has provided finer analytical resolution, exposing the intrinsic peculiarities of different cells within an apparently homogenous population. In this review, we discuss recent advances in methodologies applied to epigenetics, such as CUT&RUN and CUT&TAG. Then, we compare standard and emerging single-cell techniques and their relevance for investigating human diseases. Finally, we describe emerging methodologies that investigate centromeric chromatin specification and neocentromere formation.

Single-cell transcriptomics in the Drosophila visual system: Advances and perspectives on cell identity regulation, connectivity, and neuronal diversity evolution

The Drosophila visual system supports complex behaviors and shares many of its anatomical and molecular features with the vertebrate brain. Yet, it contains a much more manageable number of neurons and neuronal types. In addition to the extensive Drosophila genetic toolbox, this relative simplicity has allowed decades of work to yield a detailed account of its neuronal type diversity, morphology, connectivity and specification mechanisms. In the past three years, numerous studies have applied large scale single-cell transcriptomic approaches to the Drosophila visual system and have provided access to the complete gene expression profile of most neuronal types throughout development. This makes the fly visual system particularly well suited to perform detailed studies of the genetic mechanisms underlying the evolution and development of neuronal systems. Here, we highlight how these transcriptomic resources allow exploring long-standing biological questions under a new light. We first present the efforts made to characterize neuronal diversity in the Drosophila visual system and suggest ways to further improve this description. We then discuss current advances allowed by the single-cell datasets, and envisage how these datasets can be further leveraged to address fundamental questions regarding the regulation of neuronal identity, neuronal circuit development and the evolution of neuronal diversity.

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.

Interplay between sex determination cascade and major signaling pathways during Drosophila eye development: Perspectives for future research

Understanding molecular mechanisms of sexually dimorphic organ growth is a fundamental problem of developmental biology. Recent quantitative studies showed that the Drosophila compound eye is a convenient model to study the determination of the final organ size. In Drosophila, females have larger eyes than males and this is evident even after correction for the larger body size. Moreover, female eyes include more ommatidia (photosensitive units) than male eyes and this difference is specified at the third larval instar in the eye primordia called eye imaginal discs. This may result in different visual capabilities between the two sexes and have behavioral consequences. Despite growing evidence on the genetic bases of eye size variation between different Drosophila species and strains, mechanisms responsible for within-species sexual dimorphism still remain elusive. Here, we discuss a presumptive crosstalk between the sex determination cascade and major signaling pathways during dimorphic eye development. Male- and female-specific isoforms of Doublesex (Dsx) protein are known to control sex-specific differentiation in the somatic tissues. However, no data on Dsx function during eye disc growth and patterning are currently available. Remarkably, Sex lethal (Sxl), the sex determination switch protein, was shown to directly affect Hedgehog (Hh) and Notch (N) signaling in the Drosophila wing disc. The similarity of signaling pathways involved in the wing and eye disc growth suggests that Sxl might be integrated into regulation of eye development. Dsx role in the eye disc requires further investigation. We discuss currently available data on sex-biased gene expression in the Drosophila eye and highlight perspectives for future studies.

Single-cell transcriptomics of the Drosophila wing disc reveals instructive epithelium-to-myoblast interactions

In both vertebrates and invertebrates, generating a functional appendage requires interactions between ectoderm-derived epithelia and mesoderm-derived cells. To investigate such interactions, we used single-cell transcriptomics to generate a temporal cell atlas of the Drosophila wing disc from two developmental time points. Using these data, we visualized gene expression using a multilayered model of the wing disc and cataloged ligand–receptor pairs that could mediate signaling between epithelial cells and adult muscle precursors (AMPs). We found that localized expression of the fibroblast growth factor ligands, Thisbe and Pyramus, in the disc epithelium regulates the number and location of the AMPs. In addition, Hedgehog ligand from the epithelium activates a specific transcriptional program within adjacent AMP cells, defined by AMP-specific targets Neurotactin and midline, that is critical for proper formation of direct flight muscles. More generally, our annotated temporal cell atlas provides an organ-wide view of potential cell–cell interactions between epithelial and myogenic cells.

Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila

Single-cell RNA sequencing (scRNAseq) experiments provide a powerful means to identify clusters of cells that share common gene expression signatures. A major challenge in scRNAseq studies is to map the clusters to specific anatomical regions along the body and within tissues. Existing data, such as information obtained from large-scale in situ RNA hybridization studies, cell type specific transcriptomics, gene expression reporters, antibody stainings, and fluorescent tagged proteins, can help to map clusters to anatomy. However, in many cases, additional validation is needed to precisely map the spatial location of cells in clusters. Several approaches are available for spatial resolution in Drosophila, including mining of existing datasets, and use of existing or new tools for direct or indirect detection of RNA, or direct detection of proteins. Here, we review available resources and emerging technologies that will facilitate spatial mapping of scRNAseq clusters at high resolution in Drosophila. Importantly, we discuss the need, available approaches, and reagents for multiplexing gene expression detection in situ, as in most cases scRNAseq clusters are defined by the unique coexpression of sets of genes.

Recent advances in understanding the role of metabolic heterogeneities in cell migration

Migration is an energy-intensive, multi-step process involving cell adhesion, protrusion, and detachment. Each of these steps require cells to generate and consume energy, regulating their morphological changes and force generation. Given the need for energy to move, cellular metabolism has emerged as a critical regulator of both single cell and collective migration. Recently, metabolic heterogeneity has been highlighted as a potential determinant of collective cell behavior, as individual cells may play distinct roles in collective migration. Several tools and techniques have been developed and adapted to study cellular energetics during migration including live-cell probes to characterize energy utilization and metabolic state and methodologies to sort cells based on their metabolic profile. Here, we review the recent advances in techniques, parsing the metabolic heterogeneities inherent in cell populations and their contributions to cell migration.

Toward a Consensus in the Repertoire of Hemocytes Identified in Drosophila

The catalog of the Drosophila immune cells was until recently limited to three major cell types, based on morphology, function and few molecular markers. Three recent single cell studies highlight the presence of several subgroups, revealing a large diversity in the molecular signature of the larval immune cells. Since these studies rely on somewhat different experimental and analytical approaches, we here compare the datasets and identify eight common, robust subgroups associated to distinct functions such as proliferation, immune response, phagocytosis or secretion. Similar comparative analyses with datasets from different stages and tissues disclose the presence of larval immune cells resembling embryonic hemocyte progenitors and the expression of specific properties in larval immune cells associated with peripheral tissues.

Immunometabolism in the Single-Cell Era

Emerging research has identified metabolic pathways that are crucial for the proper regulation of immune cells and how, when deranged, they can cause immune dysfunction and disease progression. However, due to technical limitations such insights have relied heavily on bulk measurements in immune cells, often activated in vitro. But with the emergence of single-cell applications, researchers can now estimate the metabolic state of individual immune cells in clinical samples. Here, we review these single-cell techniques and their ability to validate common principles in immunometabolism, while also revealing context-dependent metabolic heterogeneity within the immune cell compartment. We also discuss current gaps and limitations, as well as identify future opportunities to move the field forward toward the development of therapeutic targets and improved diagnostic capabilities.

From whole-mount to single-cell spatial assessment of gene expression in 3D

Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics.

Amalgam regulates the receptor tyrosine kinase pathway through Sprouty in glial cell development in the Drosophila larval brain

The receptor tyrosine kinase (RTK) pathway plays an essential role in development and disease by controlling cell proliferation and differentiation. Here, we profile the Drosophila larval brain by single-cell RNA-sequencing and identify Amalgam (Ama), which encodes a cell adhesion protein of the immunoglobulin IgLON family, as regulating the RTK pathway activity during glial cell development. Depletion of Ama reduces cell proliferation, affects glial cell type composition and disrupts the blood-brain barrier (BBB), which leads to hemocyte infiltration and neuronal death. We show that Ama depletion lowers RTK activity by upregulating Sprouty (Sty), a negative regulator of the RTK pathway. Knockdown of Ama blocks oncogenic RTK signaling activation in the Drosophila glioma model and halts malignant transformation. Finally, knockdown of a human ortholog of Ama, LSAMP, results in upregulation of SPROUTY2 in glioblastoma cell lines, suggesting that the relationship between Ama and Sty is conserved.

A cell atlas of adult muscle precursors uncovers early events in fibre-type divergence in Drosophila

In Drosophila, the wing disc‐associated muscle precursor cells give rise to the fibrillar indirect flight muscles (IFM) and the tubular direct flight muscles (DFM). To understand early transcriptional events underlying this muscle diversification, we performed single‐cell RNA‐sequencing experiments and built a cell atlas of myoblasts associated with third instar larval wing disc. Our analysis identified distinct transcriptional signatures for IFM and DFM myoblasts that underlie the molecular basis of their divergence. The atlas further revealed various states of differentiation of myoblasts, thus illustrating previously unappreciated spatial and temporal heterogeneity among them. We identified and validated novel markers for both IFM and DFM myoblasts at various states of differentiation by immunofluorescence and genetic cell‐tracing experiments. Finally, we performed a systematic genetic screen using a panel of markers from the reference cell atlas as an entry point and found a novel gene, Amalgam which is functionally important in muscle development. Our work provides a framework for leveraging scRNA‐seq for gene discovery and details a strategy that can be applied to other scRNA‐seq datasets.

NatB regulates Rb mutant cell death and tumor growth by modulating EGFR/MAPK signaling through the N-end rule pathways

Inactivation of the Rb tumor suppressor causes context-dependent increases in cell proliferation or cell death. In a genetic screen for factors that promoted Rb mutant cell death in Drosophila, we identified Psid, a regulatory subunit of N-terminal acetyltransferase B (NatB). We showed that NatB subunits were required for elevated EGFR/MAPK signaling and Rb mutant cell survival. We showed that NatB regulates the posttranscriptional levels of the highly conserved pathway components Grb2/Drk, MAPK, and PP2AC but not that of the less conserved Sprouty. Interestingly, NatB increased the levels of positive pathway components Grb2/Drk and MAPK while decreased the levels of negative pathway component PP2AC, which were mediated by the distinct N-end rule branch E3 ubiquitin ligases Ubr4 and Cnot4, respectively. These results suggest a novel mechanism by which NatB and N-end rule pathways modulate EGFR/MAPK signaling by inversely regulating the levels of multiple conserved positive and negative pathway components. As inactivation of Psid blocked EGFR signaling-dependent tumor growth, this study raises the possibility that NatB is potentially a novel therapeutic target for cancers dependent on deregulated EGFR/Ras signaling.

Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics

Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. Here, we generate independent single-cell RNA-seq and single-cell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics the organization of the 2D tissue using ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering). To validate spatially predicted enhancers, we use a large collection of enhancer-reporter lines and identify ~ 85% of enhancers in which chromatin accessibility and enhancer activity are coupled. Next, we infer enhancer-to-gene relationships in the virtual space, finding that genes are mostly regulated by multiple, often redundant, enhancers. Exploiting cell type-specific enhancers, we deconvolute cell type-specific effects of bulk-derived chromatin accessibility QTLs. Finally, we discover that Prospero drives neuronal differentiation through the binding of a GGG motif. In summary, we provide a comprehensive spatial characterization of gene regulation in a 2D tissue.

Deciphering Metabolic Heterogeneity by Single-Cell Analysis

Single-cell analysis provides insights into cellular heterogeneity and dynamics of individual cells. This Feature highlights recent developments in key analytical techniques suited for single-cell metabolic analysis with a special focus on mass spectrometry-based analytical platforms and RNA-seq as well as imaging techniques that reveal stochasticity in metabolism.

Drosophila Model in Cancer: An Introduction

Cancer is a cumulative manifestation of several complicated disease states that affect multiple organs. Over the last few decades, the fruit fly Drosophila melanogaster, has become a successful model for studying human cancers. The genetic simplicity and vast arsenal of genetic tools available in Drosophila provides a unique opportunity to address questions regarding cancer initiation and progression that would be extremely challenging in other model systems. In this chapter we provide a historical overview of Drosophila as a model organism for cancer research, summarize the multitude of genetic tools available, offer a brief comparison between different model organisms and cell culture platforms used in cancer studies and briefly discuss some of the latest models and concepts in recent Drosophila cancer research.