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The ability to trace every cell in some model organisms has led to the fundamental understanding of development and cellular function. However, in plants the complexity of cell number, organ size, and developmental time makes this a challenge even in the diminutive model plant Arabidopsis (Arabidopsis thaliana). Duckweed, basal nongrass aquatic monocots, provide an opportunity to follow every cell of an entire plant due to their small size, reduced body plan, and fast clonal growth habit. Here we present a chromosome-resolved genome for the highly invasive Lesser Duckweed (Lemna minuta) and generate a preliminary cell atlas leveraging low cell coverage single-nuclei sequencing. We resolved the 360 megabase genome into 21 chromosomes, revealing a core nonredundant gene set with only the ancient tau whole-genome duplication shared with all monocots, and paralog expansion as a result of tandem duplications related to phytoremediation. Leveraging SMARTseq2 single-nuclei sequencing, which provided higher gene coverage yet lower cell count, we profiled 269 nuclei covering 36.9% (8,457) of the L. minuta transcriptome. Since molecular validation was not possible in this nonmodel plant, we leveraged gene orthology with model organism single-cell expression datasets, gene ontology, and cell trajectory analysis to define putative cell types. We found that the tissue that we computationally defined as mesophyll expressed high levels of elemental transport genes consistent with this tissue playing a role in L. minuta wastewater detoxification. The L. minuta genome and preliminary cell map provide a paradigm to decipher developmental genes and pathways for an entire plant.

Antimicrobial resistance (AMR) is a major global public health problem. Human gut microbiome plays an important role in modulating AMR. On one hand, the microbiome itself can serve as a reservoir of AMR genes, i.e. resistome. On the other hand, the microbiome performs colonization resistance, preventing invasive microbes from colonizing the gastrointestinal tract. In this study, we investigated how antibiotic treatment affects the resistome and colonization resistance of the gut microbiome in children receiving amoxicillin, amoxicillin-clavulanate, or no treatment for acute otitis media in a randomized clinical trial. Fecal samples from children receiving an antibiotic or no treatment before and after the treatment were analyzed using deep metagenomic sequencing. We used a flow cytometry-based approach to quantify the bacterial load in the fecal samples. Both metagenomic sequencing-based relative abundance and flow cytometry-based absolute abundance of the microbial species were analyzed. We found that the resistome fluctuated over time and in a small fraction (∼10%) of subjects, AMR genes increased rapidly due to colonization by AMR species, even in the control group without any antibiotic treatment. Amoxicillin significantly increased the risk for invasive species, especially pathogenic species carrying AMR genes, to colonize the gut. We also found that children lacking Blautia, Ruminococcus, Faecalibacterium, Roseburia, or Faecalitalea were more vulnerable to colonization by invasive AMR species in their gut microbiome.

von Economo neurons (VENs) are bipolar, spindle-shaped neurons restricted to layer 5 of human frontoinsula and anterior cingulate cortex that appear to be selectively vulnerable to neuropsychiatric and neurodegenerative diseases, although little is known about other VEN cellular phenotypes. Single nucleus RNA-sequencing of frontoinsula layer 5 identifies a transcriptomically-defined cell cluster that contained VENs, but also fork cells and a subset of pyramidal neurons. Cross-species alignment of this cell cluster with a well-annotated mouse classification shows strong homology to extratelencephalic (ET) excitatory neurons that project to subcerebral targets. This cluster also shows strong homology to a putative ET cluster in human temporal cortex, but with a strikingly specific regional signature. Together these results suggest that VENs are a regionally distinctive type of ET neuron. Additionally, we describe the first patch clamp recordings of VENs from neurosurgically-resected tissue that show distinctive intrinsic membrane properties relative to neighboring pyramidal neurons., Little is known about von Economo neurons, which have been described in a subset of mammals and appear to be selectively lost in several human neurological diseases. Here, authors reveal the gene expression profile of these cells and show that they are likely long-distance projection neurons.

Single-cell genomics is rapidly advancing our knowledge of the diversity of cell phenotypes, including both cell types and cell states. Driven by single-cell/-nucleus RNA sequencing (scRNA-seq), comprehensive cell atlas projects characterizing a wide range of organisms and tissues are currently underway. As a result, it is critical that the transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell types by surface protein expression to defining diseases by their molecular drivers. Here, we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the nonlinear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that optimally capture the cell type identity represented in complete scRNA-seq transcriptional profiles. The marker genes selected provide an expression barcode that serves as both a useful tool for downstream biological investigation and the necessary and sufficient characteristics for semantic cell type definition. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and noncoding RNAs in neuronal cell type identity.

Parallels among embryonic development, stem cells, and cancer have long been recognized. We identified, isolated, and characterized stem cells that first become committed to a mammary fate during embryogenesis; we refer to these cells as fetal mammary stem cells (fMaSCs). Lineage tracing, in vitro sphere formation, and in vivo transplantation studies by our group and many others all confirm that cells in the embryo are the bipotent progenitors of the mammary gland. There is debate, however, on whether such bipotent cells persist into the adult, or whether the luminal and basal lineages are maintained by unipotent progenitors. To gain insight into the relationships between fMaSCs and breast cancer, and to investigate their potential persistence in the adult, we have applied bulk and single cell RNA-sequencing (sc-RNA-seq) and single nucleus ATAC-sequencing (snATAC-seq) throughout mammary development. The results to be discussed demonstrate that fMaSC transcriptomes are heterogeneous, but all share co-expression of genes associated with luminal and basal cell fates. This fits a model in which the bipotent state is created by a balance of lineage specifiers. We also find that the fMaSC transcriptome is highly enriched in basal-like human breast cancers and identify potential embryonic pathways that correlate with poor prognosis. We used a variety of computational tools to infer the gene expression programs that ensue when fMaSCs commit to luminal and basal states. The data from scRNA-seq and snATAC-seq demonstrate that the transitions are gradual, not precipitous, and that luminal and basal cells exhibit significant transcriptomic and epigenetic heterogeneity. This challenges the notion that the mammary gland consists of discrete cell types defined by rigid transcriptomic parameters, and reveals a potential for intrinsic phenotypic plasticity of normal mammary cells. Using the combined databases, we identified Sox10 as a significantly differentially expressed cell state regulator. We show that tumors are heterogeneous with regard to Sox10 expression, and that locally invasive cells tend to express high Sox10 levels. Elevated Sox10 correlates with acquisition of a neural-crest like, EMT-related state. Implications for interception of metastasis by targeting neural crest-like cells will be discussed. Finally, we have generated a web resource that is available to the scientific community to enable the transcription and epigenetic characteristics of any gene of interest to be tracked through mammary development (https://wahl-labsalk.shinyapps.io/Mammary_snATAC/). Citation Format: GM Wahl, Z Ma, C Chung, C Dravis, BT Spike, RR Giraddi, O Balcioglu, C Fan, B Hagos, R Heinz, Herrera-Valdez J, X Hou, J Hwang, R Lasken, G Luna, NE Lytle, EM Mehrabad, M Novotny, CM Perou, O Poirion, S Preissl, B Ren, T Reya, CL Trejo, KT Varley. Understanding breast cancer using a developmental perspective [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr ES10-2.

The hadal zone remains one of the least studied environments because of its inaccessibility, in part because of hydrostatic pressures extending to 110 MPa. Few instruments are capable of sampling from such great depths. We have developed a full-ocean-depth-capable lander that can be fit with sampling packages for the collection of still images, video, motile megafauna, and hadal seawater. One payload includes a pressure-retaining sampler (PRS) able to maintain seawater samples under in situ pressure during recovery. We describe the technical specifications of the lander and the PRS and preliminary results from three deployments at depths in excess of 10,700 m in the Mariana Trench. Seawater from full-ocean depth was recovered at 81% of the in situ pressure. This facilitated the collection of microbial genomes affiliated with the family Flavobacteriaceae within the Bacteroidetes and the phylum Marinimicrobia. We show that these microbes are specifically enriched in hadal zones, representing novel trench lineages, and describe their adaptations for living in hadal environments. These findings highlight the utility of this lander system, which facilitates scientific inquiry at depths greater than 6000 m.

The ability to trace every cell in some model organisms has led to the fundamental understanding of development and cellular function. However, in plants the complexity of cell number, organ size and developmental times makes this a challenge even in the diminutive model plant Arabidopsis thaliana. Here we develop the Lesser Duckweed Lemna minuta as a model with a reduced body plan, small genome size and clonal growth pattern that enables simultaneous tracing of cells from the entire plant over the complete developmental cycle. We generated a chromosome-resolved genome for the 360 megabase genome and defined the growth trajectory of the entire plant with single nuclei RNA sequencing. The L. minuta gene complement represents a primarily non-redundant set with only the ancient tau whole genome duplication shared with all monocots, and paralog expansion as a result of tandem duplications related to phytoremediation. Thirteen distinct cell types representing meristem, the leaf-stem fusion called a frond, and root-like tissues were defined using gene orthology with single cell expression from model plants, gene ontology categories, and cell trajectory analysis. Dividing meristem cells give rise to two main branches of root-transition and mesophyll cells, which then give rise to terminally differentiated parenchyma, epidermal and root cells. Mesophyll tissues express high levels of elemental transport genes consistent with this tissue playing a role in L. minuta wastewater detoxification. The L. minuta genome and cell map provide a paradigm to decipher developmental genes and pathways for an entire plant.Sentence summaryGenome and single nuclei transcriptome of the Lesser Duckweed Lemna minuta enables tracing of all developmental, transitional and terminal cells of an entire plant.

Vaccination to prevent infectious disease is one of the most successful public health interventions ever developed. And yet, variability in individual vaccine effectiveness suggests a better mechanistic understanding of vaccine-induced immune responses could improve vaccine design and efficacy. We have previously shown that protective antibody levels could be elicited in a subset of recipients with only a single dose of the hepatitis B virus (HBV) vaccine. Why some, but not all, recipients responded in this way was not clear. Using single cell RNA sequencing of sorted innate immune cell subsets, we identified two distinct myeloid dendritic cell subsets (NDRG1-expressing mDC2 and CDKN1C-expressing mDC4), the ratio of which at baseline (pre-vaccination) predicted immune response to a single dose of HBV vaccine. Our results suggest that the participants in our vaccine study were in one of two different dendritic cell dispositional states at baseline – an NDRG2-mDC2 state in which the vaccine elicited an antibody response after a single immunization or a CDKN1C-mDC4 state in which the vaccine required two or three doses for induction of antibody responses. Genes expressed in these mDC subsets were used as an approach for feature selection prior to the construction of a predictive model using supervised canonical correlation machine learning. The resulting model showed an improved ability to predict serum antibody titers in response to vaccination. Taken together, these results suggest that the propensity of circulating dendritic cells toward either activation or suppression, their “dispositional endotype”, could dictate response to vaccination. The fact that these mDCs could be modulated via TLR stimulation could guide progress towards design of effective single dose vaccination strategies.

Despite signs of infection, the involvement of the oral cavity in COVID-19 is poorly understood. To address this, single-cell RNA sequencing data-sets were integrated from human minor salivary glands and gingiva to identify 11 epithelial, 7 mesenchymal, and 15 immune cell clusters. Analysis of SARS-CoV-2 viral entry factor expression showed enrichment in epithelia including the ducts and acini of the salivary glands and the suprabasal cells of the mucosae. COVID-19 autopsy tissues confirmed in vivo SARS-CoV-2 infection in the salivary glands and mucosa. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibitingACE2expression and SARS-CoV-2 RNA. Matched nasopharyngeal and saliva samples found distinct viral shedding dynamics and viral burden in saliva correlated with COVID-19 symptoms including taste loss. Upon recovery, this cohort exhibited salivary antibodies against SARS-CoV-2 proteins. Collectively, the oral cavity represents a robust site for COVID-19 infection and implicates saliva in viral transmission.

Single cell genomics is rapidly advancing our knowledge of cell phenotypic types and states. Driven by single cell/nucleus RNA sequencing (scRNA-seq) data, comprehensive atlas projects covering a wide range of organisms and tissues are currently underway. As a result, it is critical that the cell transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell-types by surface protein expression to defining diseases by molecular drivers. Here we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the non-linear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that precisely captures the cell type identity represented in the complete scRNA-seq transcriptional profiles. The marker genes selected provide a barcode of the necessary and sufficient characteristics for semantic cell type definition and serve as useful tools for downstream biological investigation. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and non-coding RNAs in neuronal cell type identity.

Neutrophils are the most abundant white blood cells in the human body responsible for fighting viral, bacterial and fungi infections. Out of the 100 billion neutrophils produced daily, it is estimated that 10 % of these cells end up in oral biofluids. Because saliva is a fluid accessible through non-invasive techniques, it is an optimal source of cells and molecule surveillance in health and disease. While neutrophils are abundant in saliva, scientific advancements in neutrophil biology have been hampered likely due to their short life span, inability to divide once terminally differentiated, sensitivity to physical stress, and low RNA content. Here, we devise a protocol aiming to understand neutrophil heterogeneity by improving isolation methods, single-cell RNA extraction, sequencing and bioinformatic pipelines. Advanced flow cytometry 3D analysis, and machine learning validated our gating system model, by including positive neutrophil markers and excluding other immune cells and uncovered neutrophil heterogeneity. Considering specific cell markers, unique mitochondrial content, stringent and less stringent filtering strategies, our transcriptome single cell findings unraveled novel neutrophil subpopulations. Collectively, this methodology accelerates the discovery of salivary immune landscapes, with the promise of improving the understanding of diversification mechanisms, clinical diagnostics in health and disease, and guide targeted therapies.

We describe convergent evidence from transcriptomics, morphology and physiology for a specialized GABAergic neuron subtype in human cortex. Using unbiased single nucleus RNA sequencing, we identify ten GABAergic interneuron subtypes with combinatorial gene signatures in human cortical layer 1 and characterize a novel group of human interneurons with anatomical features never described in rodents having large, “rosehip”-like axonal boutons and compact arborization. These rosehip cells show an immunohistochemical profile (GAD1/CCK-positive, CNR1/SST/CALB2/PVALB-negative) matching a single transcriptomically-defined cell type whose specific molecular marker signature is not seen in mouse cortex. Rosehip cells in layer 1 make homotypic gap junctions, predominantly target apical dendritic shafts of layer 3 pyramidal neurons and inhibit backpropagating pyramidal action potentials in microdomains of the dendritic tuft. These cells are therefore positioned for potent local control of distal dendritic computation in cortical pyramidal neurons.

Background A fundamental characteristic of multicellular organisms is the specialization of functional cell types through the process of differentiation. These specialized cell types not only characterize the normal functioning of different organs and tissues, they can also be used as cellular biomarkers of a variety of different disease states and therapeutic/vaccine responses. In order to serve as a reference for cell type representation, the Cell Ontology has been developed to provide a standard nomenclature of defined cell types for comparative analysis and biomarker discovery. Historically, these cell types have been defined based on unique cellular shapes and structures, anatomic locations, and marker protein expression. However, we are now experiencing a revolution in cellular characterization resulting from the application of new high-throughput, high-content cytometry and sequencing technologies. The resulting explosion in the number of distinct cell types being identified is challenging the current paradigm for cell type definition in the Cell Ontology. Results In this paper, we provide examples of state-of-the-art cellular biomarker characterization using high-content cytometry and single cell RNA sequencing, and present strategies for standardized cell type representations based on the data outputs from these cutting-edge technologies, including “context annotations” in the form of standardized experiment metadata about the specimen source analyzed and marker genes that serve as the most useful features in machine learning-based cell type classification models. We also propose a statistical strategy for comparing new experiment data to these standardized cell type representations. Conclusion The advent of high-throughput/high-content single cell technologies is leading to an explosion in the number of distinct cell types being identified. It will be critical for the bioinformatics community to develop and adopt data standard conventions that will be compatible with these new technologies and support the data representation needs of the research community. The proposals enumerated here will serve as a useful starting point to address these challenges.

Summary Candidate phyla (CP) are broad phylogenetic clusters of organisms that lack cultured representatives. Included in this fraction is the candidate Parcubacteria superphylum. Specific characteristics that have been ascribed to the Parcubacteria include reduced genome size, limited metabolic potential, and exclusive reliance on fermentation for energy acquisition. The study of new environmental niches, such as the marine versus terrestrial subsurface, often expands the understanding of the genetic potential of taxonomic groups. For this reason we analyzed twelve Parcubacteria single amplified genomes (SAGs) from sediment samples collected within the Challenger Deep of the Mariana Trench, obtained during the Deepsea Challenge (DSC) Expedition. Many of these SAGs are closely related to environmental sequences obtained from deep-sea environments based on 16S rRNA gene similarity and BLAST matches to predicted proteins. DSC SAGs encode features not previously identified in Parcubacteria obtained from other habitats. These include adaptation to oxidative stress, polysaccharide modification, and genes associated with respiratory nitrate reduction. The DSC SAGs are also distinguished by relative greater abundance of genes for nucleotide and amino acid biosynthesis, repair of alkylated DNA and the synthesis of mechanosensitive ion channels. These results present an expanded view of the Parcubacteria, among members residing in an ultra-deep hadal environment. This article is protected by copyright. All rights reserved.

Following its introduction into New York State (NYS) in 1999, West Nile virus (WNV; Flavivirus, Flaviviridae) underwent a rapid expansion throughout the USA and into Canada and Latin America. WNV has been characterized as being evolutionarily stable, with weak geographic structure, a dominance of purifying selection and limited adaptive change. We analyzed all available full-genome WNV sequences, focusing on the 543 available sequences from NYS, which included 495 newly sequenced 2000–15 isolates. In addition, we analyzed deep-sequencing data from 317 of these isolates. While our data are generally in agreement with the limited pace of evolutionary change and broad geographic and temporal mixing identified in other studies, we have identified some important exceptions. Most notably, there are 14 codons which demonstrated evidence of positive selection as determined by multiple models, including some positions with evidence of selection in NYS exclusively. Coincident with increased WNV activity, genotypes possessing one or more of these mutations, designated NY01, NY07, and NY10, have increased in prevalence in recent years and displaced historic strains. In addition, we have found a geographical bias with many of these mutations, which suggests selective pressures and adaptations could be regional. Lastly, our deep-sequencing data suggest both increased overall diversity in avian tissue isolates relative to mosquito isolates and multiple non-synonymous minority variants that are both host-specific and retained over time and space. Together, these data provide novel insight into the evolutionary pressures on WNV and the need for continued genetic surveillance and characterization of emergent strains.

The era of targeted therapies has seen significant improvements in depth of response, progression-free survival, and overall survival for patients with multiple myeloma. Despite these improvements in clinical outcome, patients inevitably relapse and require further treatment. Drug-resistant dormant myeloma cells that reside in specific niches within the skeleton are considered a basis of disease relapse but remain elusive and difficult to study. Here, we developed a method to sequence the transcriptome of individual dormant myeloma cells from the bones of tumor-bearing mice. Our analyses show that dormant myeloma cells express a distinct transcriptome signature enriched for immune genes and, unexpectedly, genes associated with myeloid cell differentiation. These genes were switched on by coculture with osteoblastic cells. Targeting AXL, a gene highly expressed by dormant cells, using small-molecule inhibitors released cells from dormancy and promoted their proliferation. Analysis of the expression of AXL and coregulated genes in human cohorts showed that healthy human controls and patients with monoclonal gammopathy of uncertain significance expressed higher levels of the dormancy signature genes than patients with multiple myeloma. Furthermore, in patients with multiple myeloma, the expression of this myeloid transcriptome signature translated into a twofold increase in overall survival, indicating that this dormancy signature may be a marker of disease progression. Thus, engagement of myeloma cells with the osteoblastic niche induces expression of a suite of myeloid genes that predicts disease progression and that comprises potential drug targets to eradicate dormant myeloma cells.

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at -80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

Since the EV-D68 outbreak during the summer of 2014, evidence of a causal link to a type of limb paralysis (AFM) has been mounting. In this article, we describe a neuronal cell culture model (SH-SY5Y cells) in which a subset of contemporary 2014 outbreak strains of EV-D68 show infectivity in neuronal cells, or neurotropism. We confirmed the difference in neurotropism in vitro using primary human neuron cell cultures and in vivo with a mouse paralysis model. Using the SH-SY5Y cell model, we determined that a barrier to viral entry is at least partly responsible for neurotropism. SH-SY5Y cells may be useful in determining if specific EV-D68 genetic determinants are associated with neuropathogenesis, and replication in this cell line could be used as rapid screening tool for identification of neurotropic EV-D68 strains. This may assist with better understanding of pathogenesis and epidemiology and with the development of potential therapies., Enterovirus D68 (EV-D68) has historically been associated with respiratory illnesses. However, in the summers of 2014 and 2016, EV-D68 outbreaks coincided with a spike in polio-like acute flaccid myelitis/paralysis (AFM/AFP) cases. This raised concerns that EV-D68 could be the causative agent of AFM during these recent outbreaks. To assess the potential neurotropism of EV-D68, we utilized the neuroblastoma-derived neuronal cell line SH-SY5Y as a cell culture model to determine if differential infection is observed for different EV-D68 strains. In contrast to HeLa and A549 cells, which support viral infection of all EV-D68 strains tested, SH-SY5Y cells only supported infection by a subset of contemporary EV-D68 strains, including isolates from the 2014 outbreak. Viral replication and infectivity in SH-SY5Y were assessed using multiple assays: virus production, cytopathic effects, cellular ATP release, and VP1 capsid protein production. Similar differential neurotropism was also observed in differentiated SH-SY5Y cells, primary human neuron cultures, and a mouse paralysis model. Using the SH-SY5Y cell culture model, we determined that barriers to viral binding and entry were at least partly responsible for the differential infectivity phenotype. Transfection of genomic RNA into SH-SY5Y generated virions for all EV-D68 isolates, but only a single round of replication was observed from strains that could not directly infect SH-SY5Y. In addition to supporting virus replication and other functional studies, this cell culture model may help identify the signatures of virulence to confirm epidemiological associations between EV-D68 strains and AFM and allow for the rapid identification and characterization of emerging neurotropic strains.

Historically, enterovirus D68 (EV-D68) has primarily been associated with respiratory illnesses. However, in the summers of 2014 and 2016 EV-D68 outbreaks coincided with a spike in polio-like acute flaccid myelitis/paralysis (AFM/AFP) cases. This raised concerns that the EV-D68 virus could be the causative agent of AFM during these recent outbreaks. To assess the neurotropic capacity of EV-D68, we explored the use of the neuroblastoma-derived neuronal cell line, SH-SY5Y, as a tissue culture model to determine if differential infection permissibility is observed for different EV-D68 strains. In contrast to HeLa and A549 cells, which support viral infection of all EV-D68 strains tested, SH-SY5Y cells only supported infection by a subset of contemporary EV-D68 strains, including members from the 2014 outbreak. Viral replication and infectivity in SH-SY5Y was assessed using four different assays – infectious virus production, cytopathic effects, cellular ATP release, and VP1 capsid protein production – with similar results. Similar differential neurotropism was also observed in differentiated SH-SY5Y cells, primary human neuron cultures, and a mouse paralysis model. Using the SH-SY5Y cell culture model, we determined that barriers to viral entry was at least partly responsible for the differential infectivity phenotype, since transfection of genomic RNA into SH-SY5Y generated virions for all EV-D68 isolates, but only a single round of replication was observed from strains which could not directly infect SH-SY5Y. In addition to supporting virus replication and other functional studies, this cell culture model may help confirm epidemiological associations between EV-D68 strains and AFM and allow for the rapid identification of emerging neurotropic strains.Author SummarySince the outbreak during the summer of 2014, EV-D68 has been linked to a type of limb paralysis referred to as acute flaccid myelitis (AFM), with evidence mounting for the causal link of EV-D68 to AFM. Among these AFM cases, concurrent EV-D68 infection was confirmed in several independent epidemiological clusters in four continents. In this report, we describe a neuronal cell culture model (SH-SY5Y cells) where only a subset of contemporary 2014 outbreak strains of EV-D68 show infectivity in neuronal cells, or neurotropism, based on four different assays of viral replication and infection. We further confirmed the observed difference in neurotropismin vitrousing primary human neuron cell cultures andin vivowith a mouse paralysis model. Using the SH-SY5Y cell model, we determined that a barrier to viral entry is at least partly responsible for neurotropism. SH-SY5Y cells may be useful in determining if specific EV-D68 genetic determinants are associated with neuropathogenesis, and replication in this cell line could be used as rapid screening tool for identifying neurotropic EV-D68 strains. This may assist with better understanding of pathogenesis and epidemiology, and with the development of potential therapies.

Cells are fundamental function units of multicellular organisms, with different cell types playing distinct physiological roles in the body. The recent advent of single-cell transcriptional profiling using RNA sequencing is producing ‘big data’, enabling the identification of novel human cell types at an unprecedented rate. In this review, we summarize recent work characterizing cell types in the human central nervous and immune systems using single-cell and single-nuclei RNA sequencing, and discuss the implications that these discoveries are having on the representation of cell types in the reference Cell Ontology (CL). We propose a method, based on random forest machine learning, for identifying sets of necessary and sufficient marker genes, which can be used to assemble consistent and reproducible cell type definitions for incorporation into the CL. The representation of defined cell type classes and their relationships in the CL using this strategy will make the cell type classes being identified by high-throughput/high-content technologies findable, accessible, interoperable and reusable (FAIR), allowing the CL to serve as a reference knowledgebase of information about the role that distinct cellular phenotypes play in human health and disease.

Cells are fundamental functional units of multicellular organisms, with different cell types playing distinct physiological roles in the body. The recent advent of single cell transcriptional profiling using RNA sequencing is producing “big data”, enabling the identification of novel human cell types at an unprecedented rate. In this review, we summarize recent work characterizing cell types in the human central nervous and immune systems using single cell and single nuclei RNA sequencing, and discuss the implications that these discoveries are having on the representation of cell types in the reference Cell Ontology (CL). We propose a method based on random forest machine learning for identifying sets of necessary and sufficient marker genes that can be used to assemble consistent and reproducible cell type definitions for incorporation into the CL. The representation of defined cell type classes and their relationships in the CL using this strategy will make the cell type classes findable, accessible, interoperable, and reusable (FAIR), allowing the CL to serve as a reference knowledgebase of information about the role that distinct cellular phenotypes play in human health and disease.

Hadal ecosystems are found at a depth of 6,000 m below sea level and below, occupying less than 1% of the total area of the ocean. The microbial communities and metabolic potential in these ecosystems are largely uncharacterized. Here, we present four single amplified genomes (SAGs) obtained from 8,219 m below the sea surface within the hadal ecosystem of the Puerto Rico Trench (PRT). These SAGs are derived from members of deep-sea clades, including the Thaumarchaeota and SAR11 clade, and two are related to previously isolated piezophilic (high-pressure-adapted) microorganisms. In order to identify genes that might play a role in adaptation to deep-sea environments, comparative analyses were performed with genomes from closely related shallow-water microbes. The archaeal SAG possesses genes associated with mixotrophy, including lipoylation and the glycine cleavage pathway. The SAR11 SAG encodes glycolytic enzymes previously reported to be missing from this abundant and cosmopolitan group. The other SAGs, which are related to piezophilic isolates, possess genes that may supplement energy demands through the oxidation of hydrogen or the reduction of nitrous oxide. We found evidence for potential trench-specific gene distributions, as several SAG genes were observed only in a PRT metagenome and not in shallower deep-sea metagenomes. These results illustrate new ecotype features that might perform important roles in the adaptation of microorganisms to life in hadal environments.

We describe convergent evidence from transcriptomics, morphology and physiology for a specialized GABAergic neuron subtype in human cortex. Using unbiased single nucleus RNA sequencing, we identify ten GABAergic interneuron subtypes with combinatorial gene signatures in human cortical layer 1 and characterize a novel group of human interneurons with anatomical features never described in rodents having large, “rosehip”-like axonal boutons and compact arborization. These rosehip cells show an immunohistochemical profile (GAD1/CCK-positive, CNR1/SST/CALB2/PVALB-negative) matching a single transcriptomically-defined cell type whose molecular signature is not seen in mouse cortex. Rosehip cells make homotypic gap junctions, predominantly target apical dendritic shafts of layer 3 pyramidal neurons and inhibit backpropagating pyramidal action potentials in microdomains of the dendritic tuft. These cells are therefore positioned for potent local control of distal dendritic computation in cortical pyramidal neurons.

SUMMARY The mammary gland consists of cells with gene expression patterns reflecting their cellular origins, function, and spatiotemporal context. However, knowledge of developmental kinetics and mechanisms of lineage specification is lacking. We address this significant knowledge gap by generating a single-cell transcriptome atlas encompassing embryonic, postnatal, and adult mouse mammary development. From these data, we map the chronology of transcriptionally and epigenetically distinct cell states and distinguish fetal mammary stem cells (fMaSCs) from their precursors and progeny. fMaSCs show balanced co-expression of factors associated with discrete adult lineages and a metabolic gene signature that subsides during maturation but reemerges in some human breast cancers and metastases. These data provide a useful resource for illuminating mammary cell heterogeneity, the kinetics of differentiation, and developmental correlates of tumorigenesis., Graphical Abstract, In Brief Single-cell RNA sequencing of developing mouse mammary epithelia reveals the timing of lineage specification. Giraddi et al. find that fetal mammary stem cells co-express factors that define distinct lineages in their progeny and bear functionally relevant metabolic program signatures that change with differentiation and are resurrected in human breast cancers and metastases.

It has recently been established that synthesis of double-stranded cDNA can be done from a single cell for use in DNA sequencing. Global gene expression can be quantified from the number of reads mapping to each gene, and mutations and mRNA splicing variants determined from the sequence reads. Here we demonstrate that this method of transcriptomic analysis can be done using the extremely low levels of mRNA in a single nucleus, isolated from a mouse neural progenitor cell line and from dissected hippocampal tissue. This method is characterized by excellent coverage and technical reproducibility. On average, more than 16,000 of the 24,057 mouse protein-coding genes were detected from single nuclei, and the amount of gene-expression variation was similar when measured between single nuclei and single cells. Several major advantages of the method exist: first, nuclei, compared with whole cells, have the advantage of being easily isolated from complex tissues and organs, such as those in the CNS. Second, the method can be widely applied to eukaryotic species, including those of different kingdoms. The method also provides insight into regulatory mechanisms specific to the nucleus. Finally, the method enables dissection of regulatory events at the single-cell level; pooling of 10 nuclei or 10 cells obscures some of the variability measured in transcript levels, implying that single nuclei and cells will be extremely useful in revealing the physiological state and interconnectedness of gene regulation in a manner that avoids the masking inherent to conventional transcriptomics using bulk cells or tissues.

The majority of microbial genomic diversity remains unexplored. This is largely due to our inability to culture most microorganisms in isolation, which is a prerequisite for traditional genome sequencing. Single-cell sequencing has allowed researchers to circumvent this limitation. DNA is amplified directly from a single cell using the whole-genome amplification technique of multiple displacement amplification (MDA). However, MDA from a single chromosome copy suffers from amplification bias and a large loss of specificity from even very small amounts of DNA contamination, which makes assembling a genome difficult and completely finishing a genome impossible except in extraordinary circumstances. Gel microdrop cultivation allows culturing of a diverse microbial community and provides hundreds to thousands of genetically identical cells as input for an MDA reaction. We demonstrate the utility of this approach by comparing sequencing results of gel microdroplets and single cells following MDA. Bias is reduced in the MDA reaction and genome sequencing, and assembly is greatly improved when using gel microdroplets. We acquired multiple near-complete genomes for two bacterial species from human oral and stool microbiome samples. A significant amount of genome diversity, including single nucleotide polymorphisms and genome recombination, is discovered. Gel microdroplets offer a powerful and high-throughput technology for assembling whole genomes from complex samples and for probing the pan-genome of naturally occurring populations.

The healthy human brain is a mosaic of varied genomes. Using a single cell sequencing approach targeting L1 elements, the authors show that the contribution of L1 to somatic mosaicism goes beyond retrotransposition and includes deletion of genomic regions associated with L1. The healthy human brain is a mosaic of varied genomes. Long interspersed element-1 (LINE-1 or L1) retrotransposition is known to create mosaicism by inserting L1 sequences into new locations of somatic cell genomes. Using a machine learning-based, single-cell sequencing approach, we discovered that somatic L1-associated variants (SLAVs) are composed of two classes: L1 retrotransposition insertions and retrotransposition-independent L1-associated variants. We demonstrate that a subset of SLAVs comprises somatic deletions generated by L1 endonuclease cutting activity. Retrotransposition-independent rearrangements in inherited L1s resulted in the deletion of proximal genomic regions. These rearrangements were resolved by microhomology-mediated repair, which suggests that L1-associated genomic regions are hotspots for somatic copy number variants in the brain and therefore a heritable genetic contributor to somatic mosaicism. We demonstrate that SLAVs are present in crucial neural genes, such as DLG2 (also called PSD93), and affect 44–63% of cells of the cells in the healthy brain.

Next generation sequencing of the RNA content of single cells or single nuclei (sc/nRNA-seq) has become a powerful approach to understand the cellular complexity and diversity of multicellular organisms and environmental ecosystems. However, the fact that the procedure begins with a relatively small amount of starting material, thereby pushing the limits of the laboratory procedures required, dictates that careful approaches for sample quality control (QC) are essential to reduce the impact of technical noise and sample bias in downstream analysis applications. Here we present a preliminary framework for sample level quality control that is based on the collection of a series of quantitative laboratory and data metrics that are used as features for the construction of QC classification models using random forest machine learning approaches. We've applied this initial framework to a dataset comprised of 2272 single nuclei RNA-seq results and determined that ~79% of samples were of high quality. Removal of the poor quality samples from downstream analysis was found to improve the cell type clustering results. In addition, this approach identified quantitative features related to the proportion of unique or duplicate reads and the proportion of reads remaining after quality trimming as useful features for pass/fail classification. The construction and use of classification models for the identification of poor quality samples provides for an objective and scalable approach to sc/nRNA-seq quality control.

Chest pain is a leading reason patients seek medical evaluation. While assays to detect myocyte death are used to diagnose a heart attack (acute myocardial infarction, AMI), there is no biomarker to indicate an impending cardiac event. Transcriptional patterns present in circulating endothelial cells (CEC) may provide a window into the plaque rupture process and identify a proximal biomarker for AMI. Thus, we aimed to identify a transcriptomic signature of AMI present in whole blood, but derived from CECs. Candidate genes indicative of AMI were nominated from microarray of enriched CEC samples, and then verified for detectability and predictive potential via qPCR in whole blood. This signature was validated in an independent cohort. Our findings suggest that a whole blood CEC-derived molecular signature identifies patients with AMI and sets the framework to potentially identify the earlier stages of an impending cardiac event when used in concert with clinical history and other diagnostics where conventional biomarkers indicative of myonecrosis remain undetected.

Marine cyanobacteria of the genus Prochlorococcus represent numerically dominant photoautotrophs residing throughout the euphotic zones in the open oceans and are major contributors to the global carbon cycle. Prochlorococcus has remained a genetically intractable bacterium due to slow growth rates and low transformation efficiencies using standard techniques. Our recent successes in cloning and genetically engineering the AT-rich, 1.1 Mb Mycoplasma mycoides genome in yeast encouraged us to explore similar methods with Prochlorococcus. Prochlorococcus MED4 has an AT-rich genome, with a GC content of 30.8%, similar to that of Saccharomyces cerevisiae (38%), and contains abundant yeast replication origin consensus sites (ACS) evenly distributed around its 1.66 Mb genome. Unlike Mycoplasma cells, which use the UGA codon for tryptophane, Prochlorococcus uses the standard genetic code. Despite this, we observed no toxic effects of several partial and 15 whole Prochlorococcus MED4 genome clones in S. cerevisiae. Sequencing of a Prochlorococcus genome purified from yeast identified 14 single base pair missense mutations, one frameshift, one single base substitution to a stop codon and one dinucleotide transversion compared to the donor genomic DNA. We thus provide evidence of transformation, replication and maintenance of this 1.66 Mb intact bacterial genome in S. cerevisiae.

Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25-1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition.

Vaccination as a strategy for the prevention of infectious disease has been one of the greatest success stories in modern medicine, resulting in the complete eradication of smallpox, the near eradication of polio, and the drastic lowering in the incidences of measles, mumps, influenza and other common diseases. In contrast to these remarkable successes, recent failures in the development of effective vaccines against other major public health threats, including HIV, TB and malaria have highlighted the limitations to the current approach of empirical vaccine design and the need to better understand the basic principles of how to recognize and elicit immune responses that generate effective and durable protective immunity. Single cell transcriptional profiling by RNA sequencing (scRNAseq) is a powerful tool for exploring the phenotypic diversity of cell populations present in peripheral blood and other tissue specimens in an unbiased fashion. We applied scRNAseq to FACS sorted blood samples collected from participants before and after challenge with the licensed Hepatitis B vaccine, and identified several innate cell subtypes using unbiased clustering analysis. Marker genes specific for each cell subtype were identified using random forest machine learning for use in qPCR. Our results suggest that the relative levels of myeloid dendritic cells (mDCs) specifically expressing the N-myc target gene, NDRG2, prior to vaccination predict serum antibody responses to the HepB vaccine.

In the version of this article initially published, NIH grant U01 MH106882 to F.H.G. was missing from the Acknowledgments. The error has been corrected in the HTML and PDF versions of the article.

Recently developed techniques allow genomic DNA sequencing from single microbial cells [Lasken RS: Single-cell genomic sequencing using multiple displacement amplification. Curr Opin Microbiol 2007, 10:510-516]. Here, we focus on research strategies for putting these methods into practice in the laboratory setting. An immediate consequence of single-cell sequencing is that it provides an alternative to culturing organisms as a prerequisite for genomic sequencing. The microgram amounts of DNA required as template are amplified from a single bacterium by a method called multiple displacement amplification (MDA) avoiding the need to grow cells. The ability to sequence DNA from individual cells will likely have an immense impact on microbiology considering the vast numbers of novel organisms, which have been inaccessible unless culture-independent methods could be used. However, special approaches have been necessary to work with amplified DNA. MDA may not recover the entire genome from the single copy present in most bacteria. Also, some sequence rearrangements can occur during the DNA amplification reaction. Over the past two years many research groups have begun to use MDA, and some practical approaches to single-cell sequencing have been developed. We review the consensus that is emerging on optimum methods, reliability of amplified template, and the proper interpretation of 'composite' genomes which result from the necessity of combining data from several single-cell MDA reactions in order to complete the assembly. Preferred laboratory methods are considered on the basis of experience at several large sequencing centers where >70% of genomes are now often recovered from single cells. Methods are reviewed for preparation of bacterial fractions from environmental samples, single-cell isolation, DNA amplification by MDA, and DNA sequencing.

Dioxygenases of the TET (Ten-Eleven Translocation) family produce oxidized methylcytosines, intermediates in DNA demethylation, as well as new epigenetic marks. Here we show data suggesting that TET proteins maintain the consistency of gene transcription. Embryos lacking Tet1 and Tet3 (Tet1/3 DKO) displayed a strong loss of 5-hydroxymethylcytosine (5hmC) and a concurrent increase in 5-methylcytosine (5mC) at the eight-cell stage. Single cells from eight-cell embryos and individual embryonic day 3.5 blastocysts showed unexpectedly variable gene expression compared with controls, and this variability correlated in blastocysts with variably increased 5mC/5hmC in gene bodies and repetitive elements. Despite the variability, genes encoding regulators of cholesterol biosynthesis were reproducibly down-regulated in Tet1/3 DKO blastocysts, resulting in a characteristic phenotype of holoprosencephaly in the few embryos that survived to later stages. Thus, TET enzymes and DNA cytosine modifications could directly or indirectly modulate transcriptional noise, resulting in the selective susceptibility of certain intracellular pathways to regulation by TET proteins.

Nat. Neurosci. 19, 1583–1591 (2016); published online 12 September 2016; corrected after print 13 July 2017 In the version of this article initially published, NIH grant T32 CA009370 to F.H.G. was missing from the Acknowledgments. The error has been corrected in the HTML and PDF versions of the article.