Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development

Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.

Rapid and synchronous chemical induction of replicative-like senescence via a small molecule inhibitor

Cellular senescence is acknowledged as a key contributor to organismal ageing and late-life disease. Though popular, the study of senescence in vitro can be complicated by the prolonged and asynchronous timing of cells committing to it and by its paracrine effects. To address these issues, we repurposed a small molecule inhibitor, inflachromene (ICM), to induce senescence to human primary cells. Within 6 days of treatment with ICM, senescence hallmarks, including the nuclear eviction of HMGB1 and -B2, are uniformly induced across IMR90 cell populations. By generating and comparing various high throughput datasets from ICM-induced and replicative senescence, we uncovered a high similarity of the two states. Notably though, ICM suppresses the pro-inflammatory secretome associated with senescence, thus alleviating most paracrine effects. In summary, ICM rapidly and synchronously induces a senescent-like phenotype thereby allowing the study of its core regulatory program without confounding heterogeneity.

Single cell transcriptomics reveals cell type specific features of developmentally regulated responses to lipopolysaccharide between birth and 5 years

Background

Human perinatal life is characterized by a period of extraordinary change during which newborns encounter abundant environmental stimuli and exposure to potential pathogens. To meet such challenges, the neonatal immune system is equipped with unique functional characteristics that adapt to changing conditions as development progresses across the early years of life, but the molecular characteristics of such adaptations remain poorly understood. The application of single cell genomics to birth cohorts provides an opportunity to investigate changes in gene expression programs elicited downstream of innate immune activation across early life at unprecedented resolution.

Methods

In this study, we performed single cell RNA-sequencing of mononuclear cells collected from matched birth cord blood and 5-year peripheral blood samples following stimulation (18hrs) with two well-characterized innate stimuli; lipopolysaccharide (LPS) and Polyinosinic:polycytidylic acid (Poly(I:C)).

Results

We found that the transcriptional response to LPS was constrained at birth and predominantly partitioned into classical proinflammatory gene upregulation primarily by monocytes and Interferon (IFN)-signaling gene upregulation by lymphocytes. Moreover, these responses featured substantial cell-to-cell communication which appeared markedly strengthened between birth and 5 years. In contrast, stimulation with Poly(I:C) induced a robust IFN-signalling response across all cell types identified at birth and 5 years. Analysis of gene regulatory networks revealed IRF1 and STAT1 were key drivers of the LPS-induced IFN-signaling response in lymphocytes with a potential developmental role for IRF7 regulation.

Conclusion

Additionally, we observed distinct activation trajectory endpoints for monocytes derived from LPS-treated cord and 5-year blood, which was not apparent among Poly(I:C)-induced monocytes. Taken together, our findings provide new insight into the gene regulatory landscape of immune cell function between birth and 5 years and point to regulatory mechanisms relevant to future investigation of infection susceptibility in early life.

Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

Clonal evolution and hierarchy in myeloid malignancies

Myeloid malignancies, a group of hematopoietic disorders that includes acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs), are caused by the accumulation of genetic and epigenetic changes in hematopoietic stem and progenitor cells (HSPCs) over time. Despite the relatively low number of genomic drivers compared with other forms of cancer, the process by which these changes shape the genomic architecture of myeloid malignancies remains elusive. Recent advancements in clonal hematopoiesis research and the use of cutting-edge single cell technologies have shed new light on the developmental process of myeloid malignancies. In this review, we delve into the intricacies of clonal evolution in myeloid malignancies and its implications for the development of new diagnostic and therapeutic approaches.

Single cell genomics as a transformative approach for aquaculture research and innovation

Single cell genomics encompasses a suite of rapidly maturing technologies that measure the molecular profiles of individual cells within target samples. These approaches provide a large up-step in biological information compared to long-established 'bulk' methods that profile the average molecular profiles of all cells in a sample, and have led to transformative advances in understanding of cellular biology, particularly in humans and model organisms. The application of single cell genomics is fast expanding to non-model taxa, including aquaculture species, where numerous research applications are underway with many more envisaged. In this review, we highlight the potential transformative applications of single cell genomics in aquaculture research, considering barriers and potential solutions to the broad uptake of these technologies. Focusing on single cell transcriptomics, we outline considerations for experimental design, including the essential requirement to obtain high quality cells/nuclei for sequencing in ectothermic aquatic species. We further outline data analysis and bioinformatics considerations, tailored to studies with the under-characterized genomes of aquaculture species, where our knowledge of cellular heterogeneity and cell marker genes is immature. Overall, this review offers a useful source of knowledge for researchers aiming to apply single cell genomics to address biological challenges faced by the global aquaculture sector though an improved understanding of cell biology.

Single cell analysis of transcriptome and open chromatin reveals the dynamics of hair follicle stem cell aging

Aging is defined as the functional decline of tissues and organisms, leading to many human conditions, such as cancer, neurodegenerative diseases, and hair loss. Although stem cell exhaustion is widely recognized as a hallmark of aging, our understanding of cell state changes-specifically, the dynamics of the transcriptome and open chromatin landscape, and their relationship with aging-remains incomplete. Here we present a longitudinal, single-cell atlas of the transcriptome and open chromatin landscape for epithelia cells of the skin across various hair cycle stages and ages in mice. Our findings reveal fluctuating hair follicle stem cell (HF-SC) states, some of which are associated with the progression of the hair cycle during aging. Conversely, inner bulge niche cells display a more linear progression, seemingly less affected by the hair cycle. Further analysis of the open chromatin landscape, determined by single-cell Assay for Transposase-Accessible Chromatin (ATAC) sequencing, demonstrates that reduced open chromatin regions in HF-SCs are associated with differentiation, whereas gained open chromatin regions in HF-SCs are linked to the transcriptional control of quiescence. These findings enhance our understanding of the transcriptional dynamics in HF-SC aging and lay the molecular groundwork for investigating and potentially reversing the aging process in future experimental studies.

Clonal transcriptomics identifies mechanisms of chemoresistance and empowers rational design of combination therapies

Tumour heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here, we utilise clonal transcriptomics with WILD-seq; Wholistic Interrogation of Lineage Dynamics by sequencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy. These analyses revealed oxidative stress protection by NRF2 as a major mechanism of taxane resistance and led to the discovery that our tumour models are collaterally sensitive to asparagine deprivation therapy using the clinical stage drug L-asparaginase after frontline treatment with docetaxel. In summary, clonal transcriptomics with WILD-seq identifies mechanisms of resistance to chemotherapy that are also operative in patients and pin points asparagine bioavailability as a druggable vulnerability of taxane-resistant lineages.

Novel Molecular Insights into Leukemic Evolution of Myeloproliferative Neoplasms: A Single Cell Perspective

Myeloproliferative neoplasms (MPNs) are clonal disorders originated by the serial acquisition of somatic mutations in hematopoietic stem/progenitor cells. The major clinical entities are represented by polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF), that are caused by driver mutations affecting JAK2, MPL or CALR. Disease progression is related to molecular and clonal evolution. PV and ET can progress to secondary myelofibrosis (sMF) but can also evolve to secondary acute myeloid leukemia (sAML). PMF is associated with the highest frequency of leukemic transformation, which represents the main cause of death. sAML is associated with a dismal prognosis and clinical features that differ from those of de novo AML. The molecular landscape distinguishes sAML from de novo AML, since the most frequent hits involve TP53, epigenetic regulators, spliceosome modulators or signal transduction genes. Single cell genomic studies provide novel and accurate information about clonal architecture and mutation acquisition order, allowing the reconstruction of clonal dynamics and molecular events that accompany leukemic transformation. In this review, we examine our current understanding of the genomic heterogeneity in MPNs and how it affects disease progression and leukemic transformation. We focus on molecular events elicited by somatic mutations acquisition and discuss the emerging findings coming from single cell studies.

A Roadmap for the Human Oral and Craniofacial Cell Atlas

Oral and craniofacial tissues are uniquely adapted for continuous and intricate functioning, including breathing, feeding, and communication. To achieve these vital processes, this complex is supported by incredible tissue diversity, variously composed of epithelia, vessels, cartilage, bone, teeth, ligaments, and muscles, as well as mesenchymal, adipose, and peripheral nervous tissue. Recent single cell and spatial multiomics assays-specifically, genomics, epigenomics, transcriptomics, proteomics, and metabolomics-have annotated known and new cell types and cell states in human tissues and animal models, but these concepts remain limitedly explored in the human postnatal oral and craniofacial complex. Here, we highlight the collaborative and coordinated efforts of the newly established Oral and Craniofacial Bionetwork as part of the Human Cell Atlas, which aims to leverage single cell and spatial multiomics approaches to first understand the cellular and molecular makeup of human oral and craniofacial tissues in health and to then address common and rare diseases. These powerful assays have already revealed the cell types that support oral tissues, and they will unravel cell types and molecular networks utilized across development, maintenance, and aging as well as those affected in diseases of the craniofacial complex. This level of integration and cell annotation with partner laboratories across the globe will be critical for understanding how multiple variables, such as age, sex, race, and ancestry, influence these oral and craniofacial niches. Here, we 1) highlight these recent collaborative efforts to employ new single cell and spatial approaches to resolve our collective biology at a higher resolution in health and disease, 2) discuss the vision behind the Oral and Craniofacial Bionetwork, 3) outline the stakeholders who contribute to and will benefit from this network, and 4) outline directions for creating the first Human Oral and Craniofacial Cell Atlas.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Machine-learning-optimized Cas12a barcoding enables the recovery of single-cell lineages and transcriptional profiles

The development of CRISPR-based barcoding methods creates an exciting opportunity to understand cellular phylogenies. We present a compact, tunable, high-capacity Cas12a barcoding system called dual acting inverted site array (DAISY). We combined high-throughput screening and machine learning to predict and optimize the 60-bp DAISY barcode sequences. After optimization, top-performing barcodes had ∼10-fold increased capacity relative to the best random-screened designs and performed reliably across diverse cell types. DAISY barcode arrays generated ∼12 bits of entropy and ∼66,000 unique barcodes. Thus, DAISY barcodes-at a fraction of the size of Cas9 barcodes-achieved high-capacity barcoding. We coupled DAISY barcoding with single-cell RNA-seq to recover lineages and gene expression profiles from ∼47,000 human melanoma cells. A single DAISY barcode recovered up to ∼700 lineages from one parental cell. This analysis revealed heritable single-cell gene expression and potential epigenetic modulation of memory gene transcription. Overall, Cas12a DAISY barcoding is an efficient tool for investigating cell-state dynamics.

Oceanic Crustal Fluid Single Cell Genomics Complements Metagenomic and Metatranscriptomic Surveys With Orders of Magnitude Less Sample Volume

Fluids circulating through oceanic crust play important roles in global biogeochemical cycling mediated by their microbial inhabitants, but studying these sites is challenged by sampling logistics and low biomass. Borehole observatories installed at the North Pond study site on the western flank of the Mid-Atlantic Ridge have enabled investigation of the microbial biosphere in cold, oxygenated basaltic oceanic crust. Here we test a methodology that applies redox-sensitive fluorescent molecules for flow cytometric sorting of cells for single cell genomic sequencing from small volumes of low biomass (approximately 103 cells ml-1) crustal fluid. We compare the resulting genomic data to a recently published paired metagenomic and metatranscriptomic analysis from the same site. Even with low coverage genome sequencing, sorting cells from less than one milliliter of crustal fluid results in similar interpretation of dominant taxa and functional profiles as compared to 'omics analysis that typically filter orders of magnitude more fluid volume. The diverse community dominated by Gammaproteobacteria, Bacteroidetes, Desulfobacterota, Alphaproteobacteria, and Zetaproteobacteria, had evidence of autotrophy and heterotrophy, a variety of nitrogen and sulfur cycling metabolisms, and motility. Together, results indicate fluorescence activated cell sorting methodology is a powerful addition to the toolbox for the study of low biomass systems or at sites where only small sample volumes are available for analysis.

A pipeline for copy number profiling of single circulating tumor cells to assess intra-patient tumor heterogeneity

Intrapatient tumour heterogeneity is likely a major determinant of clinical outcome in cancer patients. To assess heterogeneity in a minimally invasive manner, methods to perform single circulating tumour cell (CTC) genomics at high resolution are necessary. However, due to the rarity of CTCs, development of such methods is challenging. Here, we developed a modular single CTC analysis pipeline to assess intrapatient heterogeneity by copy number (CN) profiling. To optimize this pipeline, spike‐in experiments using MCF‐7 breast cancer cells were performed. The VyCAP puncher system was used to isolate single cells. The quality of whole genome amplification (WGA) products generated by REPLI‐g and Ampli1™ methods, as well as the results from the Illumina Truseq and the Ampli1™ LowPass library preparation techniques, was compared. Moreover, a bioinformatic pipeline was designed to generate CN profiles from single CTCs. The optimal combination of Ampli1™ WGA and Illumina Truseq library preparation was successfully validated on patient‐derived CTCs. In conclusion, we developed a novel modular pipeline to isolate single CTCs and subsequently generate detailed patient‐derived CN profiles that allow assessment of intrapatient heterogeneity in future studies.

Glomerular Kidney Diseases in the Single-Cell Era

Recent advances in single-cell technology have enabled investigation of genomic profiles and molecular crosstalk among individual cells obtained from tissues and biofluids at unprecedented resolution. Glomerular diseases, either primary or secondary to systemic diseases, often manifest elements of inflammation and of innate and adaptive immune responses. Application of single-cell methods have revealed cellular signatures of inflammation, cellular injury, and fibrosis. From these signatures, potential therapeutic targets can be inferred and in theory, this approach might facilitate identification of precision therapeutics for these diseases. Single-cell analyses of urine samples and skin lesions from patients with lupus nephritis and of urine samples from patients with diabetic nephropathy and focal segmental glomerulosclerosis have presented potential novel approaches for the diagnosis and monitoring of disease activity. These single-cell approaches, in contrast to kidney biopsy, are non-invasive and could be repeated multiple times as needed.

Single-Cell Genomics: Catalyst for Cell Fate Engineering

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.

Application of single cell genomics to focal epilepsies: A call to action

Focal epilepsies are the largest epilepsy subtype and associated with significant morbidity. Somatic variation is a newly recognized genetic mechanism underlying a subset of focal epilepsies, but little is known about the processes through which somatic mosaicism causes seizures, the cell types carrying the pathogenic variants, or their developmental origin. Meanwhile, the inception of single cell biology has completely revolutionized the study of neurological diseases and has the potential to answer some of these key questions. Focusing on single cell genomics, transcriptomics, and epigenomics in focal epilepsy research, circumvents the averaging artifact associated with studying bulk brain tissue and offers the kind of granularity that is needed for investigating the consequences of somatic mosaicism. Here we have provided a brief overview of some of the most developed single cell techniques and the major considerations around applying them to focal epilepsy research.

Integrated analysis of multimodal single-cell data

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10⁻⁷⁶, r = 0.24; cohen’s D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

Repression of endogenous retroviruses prevents antiviral immune response and is required for mammary gland development

The role of heterochromatin in cell fate specification during development is unclear. We demonstrate that loss of the lysine 9 of histone H3 (H3K9) methyltransferase G9a in the mammary epithelium results in de novo chromatin opening, aberrant formation of the mammary ductal tree, impaired stem cell potential, disrupted intraductal polarity, and loss of tissue function. G9a loss derepresses long terminal repeat (LTR) retroviral sequences (predominantly the ERVK family). Transcriptionally activated endogenous retroviruses generate double-stranded DNA (dsDNA) that triggers an antiviral innate immune response, and knockdown of the cytosolic dsDNA sensor Aim2 in G9a knockout (G9acKO) mammary epithelium rescues mammary ductal invasion. Mammary stem cell transplantation into immunocompromised or G9acKO-conditioned hosts shows partial dependence of the G9acKO mammary morphological defects on the inflammatory milieu of the host mammary fat pad. Thus, altering the chromatin accessibility of retroviral elements disrupts mammary gland development and stem cell activity through both cell-autonomous and non-autonomous mechanisms.

Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer

Cell function and activity are regulated through integration of signaling, epigenetic, transcriptional, and metabolic pathways. Here, we introduce INs-seq, an integrated technology for massively parallel recording of single-cell RNA sequencing (scRNA-seq) and intracellular protein activity. We demonstrate the broad utility of INs-seq for discovering new immune subsets by profiling different intracellular signatures of immune signaling, transcription factor combinations, and metabolic activity. Comprehensive mapping of Arginase 1-expressing cells within tumor models, a metabolic immune signature of suppressive activity, discovers novel Arg1⁺ Trem2⁺ regulatory myeloid (Mreg) cells and identifies markers, metabolic activity, and pathways associated with these cells. Genetic ablation of Trem2 in mice inhibits accumulation of intra-tumoral Mreg cells, leading to a marked decrease in dysfunctional CD8⁺ T cells and reduced tumor growth. This study establishes INs-seq as a broadly applicable technology for elucidating integrated transcriptional and intra-cellular maps and identifies the molecular signature of myeloid suppressive cells in tumors.

Computational methods for the integrative analysis of single-cell data

Recent advances in single-cell technologies are providing exciting opportunities for dissecting tissue heterogeneity and investigating cell identity, fate and function. This is a pristine, exploding field that is flooding biologists with a new wave of data, each with its own specificities in terms of complexity and information content. The integrative analysis of genomic data, collected at different molecular layers from diverse cell populations, holds promise to address the full-scale complexity of biological systems. However, the combination of different single-cell genomic signals is computationally challenging, as these data are intrinsically heterogeneous for experimental, technical and biological reasons. Here, we describe the computational methods for the integrative analysis of single-cell genomic data, with a focus on the integration of single-cell RNA sequencing datasets and on the joint analysis of multimodal signals from individual cells.

Advancing Cancer Research and Medicine with Single-Cell Genomics

Single-cell sequencing (SCS) has impacted many areas of cancer research and improved our understanding of intratumor heterogeneity, the tumor microenvironment, metastasis, and therapeutic resistance. The development and refinement of SCS technologies has led to massive reductions in costs, increased cell throughput, and improved reproducibility, paving the way for clinical applications. However, before translational applications can be realized, there are a number of logistical and technical challenges that must be overcome. This review discusses past cancer research studies, emerging technologies, and future clinical applications that are bound to transform cancer medicine.

Transcriptional Atlas of Intestinal Immune Cells Reveals that Neuropeptide α-CGRP Modulates Group 2 Innate Lymphoid Cell Responses

Signaling abnormalities in immune responses in the small intestine can trigger chronic type 2 inflammation involving interaction of multiple immune cell types. To systematically characterize this response, we analyzed 58,067 immune cells from the mouse small intestine by single-cell RNA sequencing (scRNA-seq) at steady state and after induction of a type 2 inflammatory reaction to ovalbumin (OVA). Computational analysis revealed broad shifts in both cell-type composition and cell programs in response to the inflammation, especially in group 2 innate lymphoid cells (ILC2s). Inflammation induced the expression of exon 5 of Calca, which encodes the alpha-calcitonin gene-related peptide (α-CGRP), in intestinal KLRG1⁺ ILC2s. α-CGRP antagonized KLRG1⁺ ILC2s proliferation but promoted IL-5 expression. Genetic perturbation of α-CGRP increased the proportion of intestinal KLRG1⁺ ILC2s. Our work highlights a model where α-CGRP-mediated neuronal signaling is critical for suppressing ILC2 expansion and maintaining homeostasis of the type 2 immune machinery.

Single Cell Genomics-Based Analysis of Gene Content and Expression of Prophages in a Diffuse-Flow Deep-Sea Hydrothermal System

Phage–host interactions likely play a major role in the composition and functioning of many microbiomes, yet remain poorly understood. Here, we employed single cell genomics to investigate phage–host interactions in a diffuse-flow, low-temperature hydrothermal vent that may be reflective of a broadly distributed biosphere in the subseafloor. We identified putative prophages in 13 of 126 sequenced single amplified genomes (SAGs), with no evidence for lytic infections, which is in stark contrast to findings in the surface ocean. Most were distantly related to known prophages, while their hosts included bacterial phyla Campylobacterota, Bacteroidetes, Chlorobi, Proteobacteria, Lentisphaerae, Spirochaetes, and Thermotogae. Our results suggest the predominance of lysogeny over lytic interaction in diffuse-flow, deep-sea hydrothermal vents, despite the high activity of the dominant Campylobacteria that would favor lytic infections. We show that some of the identified lysogens have co-evolved with their host over geological time scales and that their genes are transcribed in the environment. Functional annotations of lysogeny-related genes suggest involvement in horizontal gene transfer enabling host’s protection against toxic metals and antibacterial compounds.

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics

Lineage tracing provides key insights into the fate of individual cells in complex organisms. Although effective genetic labeling approaches are available in model systems, in humans, most approaches require detection of nuclear somatic mutations, which have high error rates, limited scale, and do not capture cell state information. Here, we show that somatic mutations in mtDNA can be tracked by single-cell RNA or assay for transposase accessible chromatin (ATAC) sequencing. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their utility as highly accurate clonal markers to infer cellular relationships. We track native human cells both in vitro and in vivo and relate clonal dynamics to gene expression and chromatin accessibility. Our approach should allow clonal tracking at a 1,000-fold greater scale than with nuclear genome sequencing, with simultaneous information on cell state, opening the way to chart cellular dynamics in human health and disease.

Single Cell Transcriptomics Reveal Abnormalities in Neurosensory Patterning of the Chd7 Mutant Mouse Ear

The chromatin remodeling protein CHD7 is critical for proper formation of the mammalian inner ear. Humans with heterozygous pathogenic variants in CHD7 exhibit CHARGE syndrome, characterized by hearing loss and inner ear dysplasia, including abnormalities of the semicircular canals and Mondini malformations. Chd7^Gt/+ heterozygous null mutant mice also exhibit dysplastic semicircular canals and hearing loss. Prior studies have demonstrated that reduced Chd7 dosage in the ear disrupts expression of genes involved in morphogenesis and neurogenesis, yet the relationships between these changes in gene expression and otic patterning are not well understood. Here, we sought to define roles for CHD7 in global regulation of gene expression and patterning in the developing mouse ear. Using single-cell multiplex qRT-PCR, we analyzed expression of 192 genes in FAC sorted cells from Pax2Cre;mT/mGFP wild type and Chd7^Gt/+ mutant microdissected mouse otocysts. We found that Chd7 haploinsufficient otocysts exhibit a relative enrichment of cells adopting a neuroblast (vs. otic) transcriptional identity compared with wild type. Additionally, we uncovered disruptions in pro-sensory and pro-neurogenic gene expression with Chd7 loss, including genes encoding proteins that function in Notch signaling. Our results suggest that Chd7 is required for early cell fate decisions in the developing ear that involve highly specific aspects of otic patterning and differentiation.

Single-Cell Genomics Reveals a Diverse Metabolic Potential of Uncultivated Desulfatiglans-Related Deltaproteobacteria Widely Distributed in Marine Sediment

Desulfatiglans-related organisms comprise one of the most abundant deltaproteobacterial lineages in marine sediments where they occur throughout the sediment column in a gradient of increasing sulfate and organic carbon limitation with depth. Characterized Desulfatiglans isolates are dissimilatory sulfate reducers able to grow by degrading aromatic hydrocarbons. The ecophysiology of environmental Desulfatiglans-populations is poorly understood, however, possibly utilization of aromatic compounds may explain their predominance in marine subsurface sediments. We sequenced and analyzed seven Desulfatiglans-related single-cell genomes (SAGs) from Aarhus Bay sediments to characterize their metabolic potential with regard to aromatic compound degradation and energy metabolism. The average genome assembly size was 1.3 Mbp and completeness estimates ranged between 20 and 50%. Five of the SAGs (group 1) originated from the sulfate-rich surface part of the sediment while two (group 2) originated from sulfate-depleted subsurface sediment. Based on 16S rRNA gene amplicon sequencing group 2 SAGs represent the more frequent types of Desulfatiglans-populations in Aarhus Bay sediments. Genes indicative of aromatic compound degradation could be identified in both groups, but the two groups were metabolically distinct with regard to energy conservation. Group 1 SAGs carry a full set of genes for dissimilatory sulfate reduction, whereas the group 2 SAGs lacked any genetic evidence for sulfate reduction. The latter may be due to incompleteness of the SAGs, but as alternative energy metabolisms group 2 SAGs carry the genetic potential for growth by acetogenesis and fermentation. Group 1 SAGs encoded reductive dehalogenase genes, allowing them to access organohalides and possibly conserve energy by their reduction. Both groups possess sulfatases unlike their cultured relatives allowing them to utilize sulfate esters as source of organic carbon and sulfate. In conclusion, the uncultivated marine Desulfatiglans populations are metabolically diverse, likely reflecting different strategies for coping with energy and sulfate limitation in the subsurface seabed.

Programming Morphogenesis through Systems and Synthetic Biology

Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids.

Bacterial Succession on Sinking Particles in the Ocean's Interior

Sinking particles formed in the photic zone and moving vertically through the water column are a main mechanism for nutrient transport to the deep ocean, and a key component of the biological carbon pump. The particles appear to be processed by a microbial community substantially different from the surrounding waters. Single cell genomics and metagenomics were employed to describe the succession of dominant bacterial groups during particle processing. Sinking particles were extracted from sediment traps at Station Aloha in the North Pacific Subtropical Gyre (NPSG) during two different trap deployments conducted in July and August 2012. The microbial communities in poisoned vs. live sediment traps differed significantly from one another, consistent with prior observations by Fontanez et al. (2015). Partial genomes from these communities were sequenced from cells belonging to the genus Arcobacter (commensalists potentially associated with protists such as Radiolaria), and Vibrio campbellii (a group previously reported to be associated with crustacea). These bacteria were found in the particle-associated communities at specific depths in both trap deployments, presumably due to their specific host-associations. Partial genomes were also sequenced from cells belonging to Idiomarina and Kangiella that were enriched in live traps over a broad depth range, that represented a motile copiotroph and a putatively non-motile algicidal saprophyte, respectively. Planktonic bacterial cells most likely caught in the wake of the particles belonging to Actinomarina and the SAR11 clade were also sequenced. Our results suggest that similar groups of eukaryote-associated bacteria are consistently found on sinking particles at different times, and that particle remineralization involves specific, reproducible bacterial succession events in oligotrophic ocean waters.

Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells

Gaining insights into the regulatory mechanisms that underlie the transcriptional variation observed between individual cells necessitates the development of methods that measure chromatin organization in single cells. Here I adapted Nucleosome Occupancy and Methylome-sequencing (NOMe-seq) to measure chromatin accessibility and endogenous DNA methylation in single cells (scNOMe-seq). scNOMe-seq recovered characteristic accessibility and DNA methylation patterns at DNase hypersensitive sites (DHSs). An advantage of scNOMe-seq is that sequencing reads are sampled independently of the accessibility measurement. scNOMe-seq therefore controlled for fragment loss, which enabled direct estimation of the fraction of accessible DHSs within individual cells. In addition, scNOMe-seq provided high resolution of chromatin accessibility within individual loci which was exploited to detect footprints of CTCF binding events and to estimate the average nucleosome phasing distances in single cells. scNOMe-seq is therefore well-suited to characterize the chromatin organization of single cells in heterogeneous cellular mixtures.

De novo synthesis and functional analysis of the phosphatase-encoding gene acI-B of uncultured Actinobacteria from Lake Stechlin (NE Germany)

The National Center for Biotechnology Information [http://www.ncbi.nlm.nih.gov/guide/taxonomy/] database enlists more than 15,500 bacterial species. But this also includes a plethora of uncultured bacterial representations. Owing to their metabolism, they directly influence biogeochemical cycles, which underscores the the important status of bacteria on our planet. To study the function of a gene from an uncultured bacterium, we have undertaken a de novo gene synthesis approach. Actinobacteria of the acI-B subcluster are important but yet uncultured members of the bacterioplankton in temperate lakes of the northern hemisphere such as oligotrophic Lake Stechlin (NE Germany). This lake is relatively poor in phosphate (P) and harbors on average ~1.3 x 10 6 bacterial cells/ml, whereby Actinobacteria of the ac-I lineage can contribute to almost half of the entire bacterial community depending on seasonal variability. Single cell genome analysis of Actinobacterium SCGC AB141-P03, a member of the acI-B tribe in Lake Stechlin has revealed several phosphate-metabolizing genes. The genome of acI-B Actinobacteria indicates potential to degrade polyphosphate compound. To test for this genetic potential, we targeted the exoP-annotated gene potentially encoding polyphosphatase and synthesized it artificially to examine its biochemical role. Heterologous overexpression of the gene in Escherichia coli and protein purification revealed phosphatase activity. Comparative genome analysis suggested that homologs of this gene should be also present in other Actinobacteria of the acI lineages. This strategic retention of specialized genes in their genome provides a metabolic advantage over other members of the aquatic food web in a P-limited ecosystem. [Int Microbiol 2016; 19(1):39-47].

Culture Independent Genomic Comparisons Reveal Environmental Adaptations for Altiarchaeales

The recently proposed candidatus order Altiarchaeales remains an uncultured archaeal lineage composed of genetically diverse, globally widespread organisms frequently observed in anoxic subsurface environments. In spite of 15 years of studies on the psychrophilic biofilm-producing Candidatus Altiarchaeum hamiconexum and its close relatives, very little is known about the phylogenetic and functional diversity of the widespread free-living marine members of this taxon. From methanogenic sediments in the White Oak River Estuary, NC, USA, we sequenced a single cell amplified genome (SAG), WOR_SM1_SCG, and used it to identify and refine two high-quality genomes from metagenomes, WOR_SM1_79 and WOR_SM1_86-2, from the same site. These three genomic reconstructions form a monophyletic group, which also includes three previously published genomes from metagenomes from terrestrial springs and a SAG from Sakinaw Lake in a group previously designated as pMC2A384. A synapomorphic mutation in the Altiarchaeales tRNA synthetase β subunit, pheT, caused the protein to be encoded as two subunits at non-adjacent loci. Consistent with the terrestrial spring clades, our estuarine genomes contained a near-complete autotrophic metabolism, H2 or CO as potential electron donors, a reductive acetyl-CoA pathway for carbon fixation, and methylotroph-like NADP(H)-dependent dehydrogenase. Phylogenies based on 16S rRNA genes and concatenated conserved proteins identified two distinct sub-clades of Altiarchaeales, Alti-1 populated by organisms from actively flowing springs, and Alti-2 which was more widespread, diverse, and not associated with visible mats. The core Alti-1 genome suggested Alti-1 is adapted for the stream environment with lipopolysaccharide production capacity and extracellular hami structures. The core Alti-2 genome suggested members of this clade are free-living with distinct mechanisms for energy maintenance, motility, osmoregulation, and sulfur redox reactions. These data suggested that the hamus structures found in Candidatus Altiarchaeum hamiconexum are not present outside of stream-adapted Altiarchaeales. Homologs to a Na(+) transporter and membrane bound coenzyme A disulfide reductase that were unique to the brackish sediment Alti-2 genomes, could indicate adaptations to the estuarine, sulfur-rich environment.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Single neuron transcriptome analysis can reveal more than cell type classification: Does it matter if every neuron is unique?

A recent single cell mRNA sequencing study by Dueck et al. compares neuronal transcriptomes to the transcriptomes of adipocytes and cardiomyocytes. Single cell omic approaches such as those used by the authors are at the leading edge of molecular and biophysical measurement. Many groups are currently employing single cell sequencing approaches to understand cellular heterogeneity in cancer and during normal development. These single cell approaches also are beginning to address long-standing questions regarding nervous system diversity. Beyond an innate interest in cataloging cell type diversity in the brain, single cell neuronal diversity has important implications for neurotypic neural circuit function and for neurological disease. Herein, we review the authors' methods and findings, which most notably include evidence of unique expression profiles in some single neurons.

Abundant Atribacteria in deep marine sediment from the Adélie Basin, Antarctica

Bacteria belonging to the newly classified candidate phylum “Atribacteria” (formerly referred to as “OP9” and “JS1”) are common in anoxic methane-rich sediments. However, the metabolic functions and biogeochemical role of these microorganisms in the subsurface remains unrealized due to the lack of pure culture representatives. In this study of deep sediment from Antarctica’s Adélie Basin, collected during Expedition 318 of the Integrated Ocean Drilling Program (IODP), Atribacteria-related sequences of the 16S rRNA gene were abundant (up to 51% of the sequences) and steadily increased in relative abundance with depth throughout the methane-rich zones. To better understand the metabolic potential of Atribacteria within this environment, and to compare with phylogenetically distinct Atribacteria from non-deep-sea environments, individual cells were sorted for single cell genomics from sediment collected from 97.41 m below the seafloor from IODP Hole U1357C. As observed for non-marine Atribacteria, a partial single cell genome suggests a heterotrophic metabolism, with Atribacteria potentially producing fermentation products such as acetate, ethanol, and CO₂. These products may in turn support methanogens within the sediment microbial community and explain the frequent occurrence of Atribacteria in anoxic methane-rich sediments. This first report of a single cell genome from deep sediment broadens the known diversity within the Atribacteria phylum and highlights the potential role of Atribacteria in carbon cycling in deep sediment.

Single cell genomics indicates horizontal gene transfer and viral infections in a deep subsurface Firmicutes population

A major fraction of Earth's prokaryotic biomass dwells in the deep subsurface, where cellular abundances per volume of sample are lower, metabolism is slower, and generation times are longer than those in surface terrestrial and marine environments. How these conditions impact biotic interactions and evolutionary processes is largely unknown. Here we employed single cell genomics to analyze cell-to-cell genome content variability and signatures of horizontal gene transfer (HGT) and viral infections in five cells of Candidatus Desulforudis audaxviator, which were collected from a 3 km-deep fracture water in the 2.9 Ga-old Witwatersrand Basin of South Africa. Between 0 and 32% of genes recovered from single cells were not present in the original, metagenomic assembly of Desulforudis, which was obtained from a neighboring subsurface fracture. We found a transposable prophage, a retron, multiple clustered regularly interspaced short palindromic repeats (CRISPRs) and restriction-modification systems, and an unusually high frequency of transposases in the analyzed single cell genomes. This indicates that recombination, HGT and viral infections are prevalent evolutionary events in the studied population of microorganisms inhabiting a highly stable deep subsurface environment.

Combining genomic sequencing methods to explore viral diversity and reveal potential virus-host interactions

Viral diversity and virus-host interactions in oxygen-starved regions of the ocean, also known as oxygen minimum zones (OMZs), remain relatively unexplored. Microbial community metabolism in OMZs alters nutrient and energy flow through marine food webs, resulting in biological nitrogen loss and greenhouse gas production. Thus, viruses infecting OMZ microbes have the potential to modulate community metabolism with resulting feedback on ecosystem function. Here, we describe viral communities inhabiting oxic surface (10 m) and oxygen-starved basin (200 m) waters of Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia using viral metagenomics and complete viral fosmid sequencing on samples collected between April 2007 and April 2010. Of 6459 open reading frames (ORFs) predicted across all 34 viral fosmids, 77.6% (n = 5010) had no homology to reference viral genomes. These fosmids recruited a higher proportion of viral metagenomic sequences from Saanich Inlet than from nearby northeastern subarctic Pacific Ocean (Line P) waters, indicating differences in the viral communities between coastal and open ocean locations. While functional annotations of fosmid ORFs were limited, recruitment to NCBI's non-redundant “nr” database and publicly available single-cell genomes identified putative viruses infecting marine thaumarchaeal and SUP05 proteobacteria to provide potential host linkages with relevance to coupled biogeochemical cycling processes in OMZ waters. Taken together, these results highlight the power of coupled analyses of multiple sequence data types, such as viral metagenomic and fosmid sequence data with prokaryotic single cell genomes, to chart viral diversity, elucidate genomic and ecological contexts for previously unclassifiable viral sequences, and identify novel host interactions in natural and engineered ecosystems.

The use of evolutionary approaches to understand single cell genomes

The vast majority of environmental bacteria and archaea remain uncultivated, yet their genome sequences are rapidly becoming available through single cell sequencing technologies. Reconstructing metabolism is one common way to make use of genome sequences of ecologically important bacteria, but molecular evolutionary analysis is another approach that, while currently underused, can reveal important insights into the function of these uncultivated microbes in nature. Because genome sequences from single cells are often incomplete, metabolic reconstruction based on genome content can be compromised. However, this problem does not necessarily impede the use of phylogenomic and population genomic approaches that are based on patterns of polymorphisms and substitutions at nucleotide and amino acid sites. These approaches explore how various evolutionary forces act to assemble genetic diversity within and between lineages. In this mini-review, I present examples illustrating the benefits of analyzing single cell genomes using evolutionary approaches.

Gene swapping in the dead zone

Viruses can swap DNA between bacteria that live in regions of the oceans with little or no oxygen.

Ecology and evolution of viruses infecting uncultivated SUP05 bacteria as revealed by single-cell- and meta-genomics

Viruses modulate microbial communities and alter ecosystem functions. However, due to cultivation bottlenecks, specific virus-host interaction dynamics remain cryptic. In this study, we examined 127 single-cell amplified genomes (SAGs) from uncultivated SUP05 bacteria isolated from a model marine oxygen minimum zone (OMZ) to identify 69 viral contigs representing five new genera within dsDNA Caudovirales and ssDNA Microviridae. Infection frequencies suggest that ∼1/3 of SUP05 bacteria is viral-infected, with higher infection frequency where oxygen-deficiency was most severe. Observed Microviridae clonality suggests recovery of bloom-terminating viruses, while systematic co-infection between dsDNA and ssDNA viruses posits previously unrecognized cooperation modes. Analyses of 186 microbial and viral metagenomes revealed that SUP05 viruses persisted for years, but remained endemic to the OMZ. Finally, identification of virus-encoded dissimilatory sulfite reductase suggests SUP05 viruses reprogram their host's energy metabolism. Together, these results demonstrate closely coupled SUP05 virus-host co-evolutionary dynamics with the potential to modulate biogeochemical cycling in climate-critical and expanding OMZs.

Advancements toward a systems level understanding of the human oral microbiome

Oral microbes represent one of the most well studied microbial communities owing to the fact that they are a fundamental part of human development influencing health and disease, an easily accessible human microbiome, a highly structured and remarkably resilient biofilm as well as a model of bacteria-bacteria and bacteria-host interactions. In the last 80 years since oral plaque was first characterized for its functionally stable physiological properties such as the highly repeatable rapid pH decrease upon carbohydrate addition and subsequent recovery phase, the fundamental approaches to study the oral microbiome have cycled back and forth between community level investigations and characterizing individual model isolates. Since that time, many individual species have been well characterized and the development of the early plaque community, which involves many cell-cell binding interactions, has been carefully described. With high throughput sequencing enabling the enormous diversity of the oral cavity to be realized, a number of new challenges to progress were revealed. The large number of uncultivated oral species, the high interpersonal variability of taxonomic carriage and the possibility of multiple pathways to dysbiosis pose as major hurdles to obtain a systems level understanding from the community to the gene level. It is now possible however to start connecting the insights gained from single species with community wide approaches. This review will discuss some of the recent insights into the oral microbiome at a fundamental level, existing knowledge gaps, as well as challenges that have surfaced and the approaches to address them.

Exploring biotic interactions within protist cell populations using network methods

The study of diseased human cells and of cells isolated from the natural environment will likely be revolutionized by single cell genomics (SCG). Here, we used protein similarity networks to explore within- and between-cell DNA differences from SCG data derived from six individual rhizarian cells related to Paulinella ovalis and proteins from the complete genome of another rhizarian, Bigelowiella natans. We identified shared and distinct DNA components within our SCG data and between P. ovalis and B. natans. We show that network properties such as assortativity and degree effectively discriminate genome features between SCG assemblies and that SCG data follow the power law with a small number of protein families dominating networks.

Heterogeneity in immune responses: from populations to single cells

The mammalian immune system is tasked with protecting the host against a broad range of threats. Understanding how immune populations leverage cellular diversity to achieve this breadth and flexibility, particularly during dynamic processes such as differentiation and antigenic response, is a core challenge that is well suited for single cell analysis. Recent years have witnessed transformative and intersecting advances in nanofabrication and genomics that enable deep profiling of individual cells, affording exciting opportunities to study heterogeneity in the immune response at an unprecedented scope. In light of these advances, here we review recent work exploring how immune populations generate and leverage cellular heterogeneity at multiple molecular and phenotypic levels. Additionally, we highlight opportunities for single cell technologies to shed light on the causes and consequences of heterogeneity in the immune system.

The others: our biased perspective of eukaryotic genomes

Understanding the origin and evolution of the eukaryotic cell and the full diversity of eukaryotes is relevant to many biological disciplines. However, our current understanding of eukaryotic genomes is extremely biased, leading to a skewed view of eukaryotic biology. We argue that a phylogeny-driven initiative to cover the full eukaryotic diversity is needed to overcome this bias. We encourage the community: (i) to sequence a representative of the neglected groups available at public culture collections, (ii) to increase our culturing efforts, and (iii) to embrace single cell genomics to access organisms refractory to propagation in culture. We hope that the community will welcome this proposal, explore the approaches suggested, and join efforts to sequence the full diversity of eukaryotes.

Identification of a Marine Cyanophage in a Protist Single-cell Metagenome Assembly

Analysis of microbial biodiversity is hampered by a lack of reference genomes from most bacteria, viruses, and algae. This necessitates either the cultivation of a restricted number of species for standard sequencing projects or the analysis of highly complex environmental DNA metagenome data. Single-cell genomics (SCG) offers a solution to this problem by constraining the studied DNA sample to an individual cell and its associated symbionts, prey, and pathogens. We used SCG to study marine heterotrophic amoebae related to Paulinella ovalis (A. Wulff) P.W. Johnson, P.E. Hargraves & J.M. Sieburth (Rhizaria). The genus Paulinella is best known for its photosynthetic members such as P. chromatophora Lauterborn that is the only case of plastid primary endosymbiosis known outside of algae and plants. Here, we studied the phagotrophic sister taxa of P. chromatophora that are related to P. ovalis and found one SCG assembly to contain α-cyanobacterial DNA. These cyanobacterial contigs are presumably derived from prey. We also uncovered an associated cyanophage lineage (provisionally named phage PoL_MC2). Phylogenomic analysis of the fragmented genome assembly suggested a minimum genome size of 200 Kbp for phage PoL_MC2 that encodes 179 proteins and is most closely related to Synechococcus phage S-SM2. For this phage, gene network analysis demonstrates a highly modular genome structure typical of other cyanophages. Our work demonstrates that SCG is a powerful approach for discovering algal and protist biodiversity and for elucidating biotic interactions in natural samples.