Sensitive and powerful single-cell RNA sequencing using mcSCRB-seq

All-optical voltage imaging-guided postsynaptic single-cell transcriptome profiling with Voltage-Seq

Neuronal pathways recruit large postsynaptic populations and maintain connections via distinct postsynaptic response types (PRTs). Until recently, PRTs were accessible as a selection criterion for single-cell RNA sequencing only through probing by low-throughput whole-cell electrophysiology. To overcome these limitations and target neurons on the basis of specific PRTs for soma collection and subsequent single-cell RNA sequencing, we developed Voltage-Seq using the genetically encoded voltage indicator Voltron in acute brain slices from mice. We also created an onsite analysis tool, VoltView, to guide soma collection of specific PRTs using a classifier based on a previously acquired database of connectomes from multiple animals. Here we present our procedure for preparing the optical path, the imaging setup and detailing the imaging and analysis steps, as well as a complete procedure for sequencing library preparation. This enables researchers to conduct our high-throughput all-optical synaptic assay and to obtain single-cell transcriptomic data from selected postsynaptic neurons. This also allows researchers to resolve the connectivity ratio of a specific pathway and explore the diversity of PRTs within that connectome. Furthermore, combining high throughput with quick analysis gives unique access to find specific connections within a large postsynaptic connectome. Voltage-Seq also allows the investigation of correlations between connectivity and gene expression changes in a postsynaptic cell-type-specific manner for both excitatory and inhibitory connections. The Voltage-Seq workflow can be completed in ~6 weeks, including 4-5 weeks for viral expression of the Voltron sensor. The technique requires knowledge of basic laboratory techniques, micromanipulator handling skills and experience in molecular biology and bioinformatics.

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. The standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

HybriSeq: Probe-based Device-free Single-cell RNA Profiling

We have developed the HybriSeq method for single-cell RNA profiling, which utilizes in situ hybridization of multiple probes for targeted transcripts, followed by split-pool barcoding and sequencing analysis of the probes. We have shown that HybriSeq can achieve high sensitivity for RNA detection with multiple probes and profile differential splicing. The utility of HybriSeq is demonstrated in characterizing cell-to-cell heterogeneities of a panel of 95 cell-cycle-related genes and the detection of misannotated transcripts.

Novel protocol for the transcriptomic analysis of endothelial extracellular vesicles in atherosclerosis

INTRODUCTION

Despite the key role of the endothelium in atherosclerosis, there are no direct techniques for its analysis. The study of extracellular vesicles of endothelial origin (EEVs), might lead to the identification of molecular signatures and early biomarkers of atherosclerosis. The aim of this work was to set up the methods for EEVs separation and transcriptomic analysis.

METHODS

We adapted an antibody-magnetic-bead based immunocapture protocol for plasma EEVs separation from control (G1), subclinical atherosclerosis (G2) and peripheral artery disease subjects (PAD) (G3), and modified an ultra-low input RNASeq method (n=5/group). By bioinformatics analysis we compared the transcriptome of plasma EEVs with that of human aortic endothelial cells (TeloHAECs), and then, searched for differentially expressed genes (DEG) among EEVs of G1, G2 and G3. From those DEG, UCP2 was selected for further validation in plasma EVs (qPCR), and in vitro, in stimulated TeloHAECs (IL-1β, TNFα, oxLDL and hypoxia).

RESULTS

The RNASeq analysis of plasma EEVs rendered 1667 genes enriched in transcripts expressed by TeloHAECs (NES: 1.93, p adjust=1.4e-73). One hundred seventy DEGs were identified between G2 vs G1, and 180 between G3 vs G1, of which 17 were similarly expressed in G2 and G3 vs control, including UCP2. IL-1β and TNFα (10ng/mL, p<0.05), hypoxia (1% O2, p=0.05) and oxLDL (100μg/mL, p=0.055) reduced UCP2 expression in TeloHAECs.

CONCLUSIONS

We set up a protocol for EEVs separation and sequencing that might be useful for the identification of early markers of endothelial dysfunction in atherosclerosis.

Spontaneously regenerative corticospinal neurons in mice

The spinal cord receives inputs from the cortex via corticospinal neurons (CSNs). While predominantly a contralateral projection, a less-investigated minority of its axons terminate in the ipsilateral spinal cord. We analyzed the spatial and molecular properties of these ipsilateral axons and their post-synaptic targets in mice and found they project primarily to the ventral horn, including directly to motor neurons. Barcode-based reconstruction of the ipsilateral axons revealed a class of primarily bilaterally-projecting CSNs with a distinct cortical distribution. The molecular properties of these ipsilaterally-projecting CSNs (IP-CSNs) are strikingly similar to the previously described molecular signature of embryonic-like regenerating CSNs. Finally, we show that IP-CSNs are spontaneously regenerative after spinal cord injury. The discovery of a class of spontaneously regenerative CSNs may prove valuable to the study of spinal cord injury. Additionally, this work suggests that the retention of juvenile-like characteristics may be a widespread phenomenon in adult nervous systems.

The heterogeneity of erythroid cells: insight at the single-cell transcriptome level

Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.

Rapid discovery of monoclonal antibodies by microfluidics-enabled FACS of single pathogen-specific antibody-secreting cells

Monoclonal antibodies are increasingly used to prevent and treat viral infections and are pivotal in pandemic response efforts. Antibody-secreting cells (ASCs; plasma cells and plasmablasts) are an excellent source of high-affinity antibodies with therapeutic potential. Current methods to study antigen-specific ASCs either have low throughput, require expensive and labor-intensive screening or are technically demanding and therefore not widely accessible. Here we present a straightforward technology for the rapid discovery of monoclonal antibodies from ASCs. Our approach combines microfluidic encapsulation of single cells into an antibody capture hydrogel with antigen bait sorting by conventional flow cytometry. With our technology, we screened millions of mouse and human ASCs and obtained monoclonal antibodies against severe acute respiratory syndrome coronavirus 2 with high affinity (<1 pM) and neutralizing capacity (<100 ng ml-1) in 2 weeks with a high hit rate (>85% of characterized antibodies bound the target). By facilitating access to the underexplored ASC compartment, the approach enables efficient antibody discovery and immunological studies into the generation of protective antibodies.

Identification of novel cattle (Bos taurus) genes and biological insights of their function in pre-implantation embryo development

BACKGROUND

Appropriate regulation of genes expressed in oocytes and embryos is essential for acquisition of developmental competence in mammals. Here, we hypothesized that several genes expressed in oocytes and pre-implantation embryos remain unknown. Our goal was to reconstruct the transcriptome of oocytes (germinal vesicle and metaphase II) and pre-implantation cattle embryos (blastocysts) using short-read and long-read sequences to identify putative new genes.

RESULTS

We identified 274,342 transcript sequences and 3,033 of those loci do not match a gene present in official annotations and thus are potential new genes. Notably, 63.67% (1,931/3,033) of potential novel genes exhibited coding potential. Also noteworthy, 97.92% of the putative novel genes overlapped annotation with transposable elements. Comparative analysis of transcript abundance identified that 1,840 novel genes (recently added to the annotation) or potential new genes were differentially expressed between developmental stages (FDR < 0.01). We also determined that 522 novel or potential new genes (448 and 34, respectively) were upregulated at eight-cell embryos compared to oocytes (FDR < 0.01). In eight-cell embryos, 102 novel or putative new genes were co-expressed (|r|> 0.85, P < 1 × 10-8) with several genes annotated with gene ontology biological processes related to pluripotency maintenance and embryo development. CRISPR-Cas9 genome editing confirmed that the disruption of one of the novel genes highly expressed in eight-cell embryos reduced blastocyst development (ENSBTAG00000068261, P = 1.55 × 10-7).

CONCLUSIONS

Our results revealed several putative new genes that need careful annotation. Many of the putative new genes have dynamic regulation during pre-implantation development and are important components of gene regulatory networks involved in pluripotency and blastocyst formation.

In vivo interaction screening reveals liver-derived constraints to metastasis

It is estimated that only 0.02% of disseminated tumour cells are able to seed overt metastases1. While this suggests the presence of environmental constraints to metastatic seeding, the landscape of host factors controlling this process remains largely unclear. Here, combining transposon technology2 and fluorescence niche labelling3, we developed an in vivo CRISPR activation screen to systematically investigate the interactions between hepatocytes and metastatic cells. We identify plexin B2 as a critical host-derived regulator of liver colonization in colorectal and pancreatic cancer and melanoma syngeneic mouse models. We dissect a mechanism through which plexin B2 interacts with class IV semaphorins on tumour cells, leading to KLF4 upregulation and thereby promoting the acquisition of epithelial traits. Our results highlight the essential role of signals from the liver parenchyma for the seeding of disseminated tumour cells before the establishment of a growth-promoting niche. Our findings further suggest that epithelialization is required for the adaptation of CRC metastases to their new tissue environment. Blocking the plexin-B2-semaphorin axis abolishes metastatic colonization of the liver and therefore represents a therapeutic strategy for the prevention of hepatic metastases. Finally, our screening approach, which evaluates host-derived extrinsic signals rather than tumour-intrinsic factors for their ability to promote metastatic seeding, is broadly applicable and lays a framework for the screening of environmental constraints to metastasis in other organs and cancer types.

A spatial expression atlas of the adult human proximal small intestine

The mouse small intestine shows profound variability in gene expression along the crypt-villus axis1,2. Whether similar spatial heterogeneity exists in the adult human gut remains unclear. Here we use spatial transcriptomics, spatial proteomics and single-molecule fluorescence in situ hybridization to reconstruct a comprehensive spatial expression atlas of the adult human proximal small intestine. We describe zonated expression and cell type representation for epithelial, mesenchymal and immune cell types. We find that migrating enterocytes switch from lipid droplet assembly and iron uptake at the villus bottom to chylomicron biosynthesis and iron release at the tip. Villus tip cells are pro-immunogenic, recruiting γδ T cells and macrophages to the tip, in contrast to their immunosuppressive roles in mouse. We also show that the human small intestine contains abundant serrated and branched villi that are enriched at the tops of circular folds. Our study presents a detailed resource for understanding the biology of the adult human small intestine.

Exploring the impact of primer length on efficient gene detection via high-throughput sequencing

Reverse transcription (RT) is a crucial step in most RNA analysis methods. Optimizing protocols for this initial stage is critical for effective target detection, particularly when working with limited input RNA. Several factors, such as the input material quality and reaction conditions, influence RT efficiency. However, the effect of RT primer length on gene detection efficiency remains largely unknown. Thus, we investigate its impact by generating RNA-seq libraries with random RT primers of 6, 12, 18, or 24 nucleotides. To our surprise, the 18mer primer shows superior efficiency in overall transcript detection compared to the commonly used 6mer primer, especially in detecting longer RNA transcripts in complex human tissue samples. This study highlights the critical role of primer length in RT efficiency, which has significant potential to benefit various transcriptomic assays, from basic research to clinical diagnostics, given the central role of RT in RNA-related analyses.

Transcriptomic Approaches to Cardiomyocyte-Biomaterial Interactions: A Review

Biomaterials, essential for supporting, enhancing, and repairing damaged tissues, play a critical role in various medical applications. This Review focuses on the interaction of biomaterials and cardiomyocytes, emphasizing the unique significance of transcriptomic approaches in understanding their interactions, which are pivotal in cardiac bioengineering and regenerative medicine. Transcriptomic approaches serve as powerful tools to investigate how cardiomyocytes respond to biomaterials, shedding light on the gene expression patterns, regulatory pathways, and cellular processes involved in these interactions. Emerging technologies such as bulk RNA-seq, single-cell RNA-seq, single-nucleus RNA-seq, and spatial transcriptomics offer promising avenues for more precise and in-depth investigations. Longitudinal studies, pathway analyses, and machine learning techniques further improve the ability to explore the complex regulatory mechanisms involved. This review also discusses the challenges and opportunities of utilizing transcriptomic techniques in cardiomyocyte-biomaterial research. Although there are ongoing challenges such as costs, cell size limitation, sample differences, and complex analytical process, there exist exciting prospects in comprehensive gene expression analyses, biomaterial design, cardiac disease treatment, and drug testing. These multimodal methodologies have the capacity to deepen our understanding of the intricate interaction network between cardiomyocytes and biomaterials, potentially revolutionizing cardiac research with the aim of promoting heart health, and they are also promising for studying interactions between biomaterials and other cell types.

Autophagy counters inflammation-driven glycolytic impairment in aging hematopoietic stem cells

Autophagy is central to the benefits of longevity signaling programs and to hematopoietic stem cell (HSC) response to nutrient stress. With age, a subset of HSCs increases autophagy flux and preserves regenerative capacity, but the signals triggering autophagy and maintaining the functionality of autophagy-activated old HSCs (oHSCs) remain unknown. Here, we demonstrate that autophagy is an adaptive cytoprotective response to chronic inflammation in the aging murine bone marrow (BM) niche. We find that inflammation impairs glucose uptake and suppresses glycolysis in oHSCs through Socs3-mediated inhibition of AKT/FoxO-dependent signaling, with inflammation-mediated autophagy engagement preserving functional quiescence by enabling metabolic adaptation to glycolytic impairment. Moreover, we show that transient autophagy induction via a short-term fasting/refeeding paradigm normalizes glycolytic flux and significantly boosts oHSC regenerative potential. Our results identify inflammation-driven glucose hypometabolism as a key driver of HSC dysfunction with age and establish autophagy as a targetable node to reset oHSC regenerative capacity.

Direct neuronal reprogramming of mouse astrocytes is associated with multiscale epigenome remodeling and requires Yy1

Direct neuronal reprogramming is a promising approach to regenerate neurons from local glial cells. However, mechanisms of epigenome remodeling and co-factors facilitating this process are unclear. In this study, we combined single-cell multiomics with genome-wide profiling of three-dimensional nuclear architecture and DNA methylation in mouse astrocyte-to-neuron reprogramming mediated by Neurogenin2 (Ngn2) and its phosphorylation-resistant form (PmutNgn2), respectively. We show that Ngn2 drives multilayered chromatin remodeling at dynamic enhancer-gene interaction sites. PmutNgn2 leads to higher reprogramming efficiency and enhances epigenetic remodeling associated with neuronal maturation. However, the differences in binding sites or downstream gene activation cannot fully explain this effect. Instead, we identified Yy1, a transcriptional co-factor recruited by direct interaction with Ngn2 to its target sites. Upon deletion of Yy1, activation of neuronal enhancers, genes and ultimately reprogramming are impaired without affecting Ngn2 binding. Thus, our work highlights the key role of interactors of proneural factors in direct neuronal reprogramming.

Depletion-assisted multiplexed cell-free RNA sequencing reveals distinct human and microbial signatures in plasma versus extracellular vesicles

BACKGROUND

Cell-free long RNAs in human plasma and extracellular vesicles (EVs) have shown promise as biomarkers in liquid biopsy, despite their fragmented nature.

METHODS

To investigate these fragmented cell-free RNAs (cfRNAs), we developed a cost-effective cfRNA sequencing method called DETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing). DETECTOR-seq utilised a meticulously tailored set of customised guide RNAs to remove large amounts of unwanted RNAs (i.e., fragmented ribosomal and mitochondrial RNAs) in human plasma. Early barcoding strategy was implemented to reduce costs and minimise plasma requirements.

RESULTS

Using DETECTOR-seq, we conducted a comprehensive analysis of cell-free transcriptomes in both whole human plasma and EVs. Our analysis revealed discernible distributions of RNA types in plasma and EVs. Plasma exhibited pronounced enrichment in structured circular RNAs, tRNAs, Y RNAs and viral RNAs, while EVs showed enrichment in messenger RNAs (mRNAs) and signal recognition particle RNAs (srpRNAs). Functional pathway analysis highlighted RNA splicing-related ribonucleoproteins (RNPs) and antimicrobial humoral response genes in plasma, while EVs demonstrated enrichment in transcriptional activity, cell migration and antigen receptor-mediated immune signals. Our study indicates the comparable potential of cfRNAs from whole plasma and EVs in distinguishing cancer patients (i.e., colorectal and lung cancer) from healthy donors. And microbial cfRNAs in plasma showed potential in classifying specific cancer types.

CONCLUSIONS

Our comprehensive analysis of total and EV cfRNAs in paired plasma samples provides valuable insights for determining the need for EV purification in cfRNA-based studies. We envision the cost effectiveness and efficiency of DETECTOR-seq will empower transcriptome-wide investigations in the fields of cfRNAs and liquid biopsy.

KEYPOINTS

DETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing) enabled efficient and specific depletion of sequences derived from fragmented ribosomal and mitochondrial RNAs in plasma. Distinct human and microbial cell-free RNA (cfRNA) signatures in whole Plasma versus extracellular vesicles (EVs) were revealed. Both Plasma and EV cfRNAs were capable of distinguishing cancer patients from normal individuals, while microbial RNAs in Plasma cfRNAs enabled better classification of cancer types than EV cfRNAs.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity

Host-microbe interactions are complex and ever-changing, especially during infections, which can significantly impact human physiology in both health and disease by influencing metabolic and immune functions. Infections caused by pathogens such as bacteria, viruses, fungi, and parasites are the leading cause of global mortality. Microbes have evolved various immune evasion strategies to survive within their hosts, which presents a multifaceted challenge for detection. Intracellular microbes, in particular, target specific cell types for survival and replication and are influenced by factors such as functional roles, nutrient availability, immune evasion, and replication opportunities. Identifying intracellular microbes can be difficult because of the limitations of traditional culture-based methods. However, advancements in integrated host microbiome single-cell genomics and transcriptomics provide a promising basis for personalized treatment strategies. Understanding host-microbiota interactions at the cellular level may elucidate disease mechanisms and microbial pathogenesis, leading to targeted therapies. This article focuses on how intracellular microbes reside in specific cell types, modulating functions through persistence strategies to evade host immunity and prolong colonization. An improved understanding of the persistent intracellular microbe-induced differential disease outcomes can enhance diagnostics, therapeutics, and preventive measures.

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential-often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel-a commonly used chemotherapeutic -displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.

scLENS: data-driven signal detection for unbiased scRNA-seq data analysis

High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning.

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes

Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.

Rapid generation of human recombinant monoclonal antibodies from antibody-secreting cells using ferrofluid-based technology

Monoclonal antibodies (mAbs) are one of the most important classes of biologics with high therapeutic and diagnostic value, but traditional methods for mAbs generation, such as hybridoma screening and phage display, have limitations, including low efficiency and loss of natural chain pairing. To overcome these challenges, novel single B cell antibody technologies have emerged, but they also have limitations such as in vitro differentiation of memory B cells and expensive cell sorters. In this study, we present a rapid and efficient workflow for obtaining human recombinant monoclonal antibodies directly from single antigen-specific antibody secreting cells (ASCs) in the peripheral blood of convalescent COVID-19 patients using ferrofluid technology. This process allows the identification and expression of recombinant antigen-specific mAbs in less than 10 days, using RT-PCR to generate linear Ig heavy and light chain gene expression cassettes, called "minigenes", for rapid expression of recombinant antibodies without cloning procedures. This approach has several advantages. First, it saves time and resources by eliminating the need for in vitro differentiation. It also allows individual antigen-specific ASCs to be screened for effector function prior to recombinant antibody cloning, enabling the selection of mAbs with desired characteristics and functional activity. In addition, the method allows comprehensive analysis of variable region repertoires in combination with functional assays to evaluate the specificity and function of the generated antigen-specific antibodies. Our approach, which rapidly generates recombinant monoclonal antibodies from single antigen-specific ASCs, could help to identify functional antibodies and deepen our understanding of antibody dynamics in the immune response through combined antibody repertoire sequence analysis and functional reactivity testing.

PABPN1 loss-of-function causes APA-shift in oculopharyngeal muscular dystrophy

Alternative polyadenylation (APA) at the 3' UTR of transcripts contributes to the cell transcriptome. APA is suppressed by the nuclear RNA-binding protein PABPN1. Aging-associated reduced PABPN1 levels in skeletal muscles lead to muscle wasting. Muscle weakness in oculopharyngeal muscular dystrophy (OPMD) is caused by short alanine expansion in PABPN1 exon1. The expanded PABPN1 forms nuclear aggregates, an OPMD hallmark. Whether the expanded PABPN1 affects APA and how it contributes to muscle pathology is unresolved. To investigate these questions, we developed a procedure including RNA library preparation and a simple pipeline calculating the APA-shift ratio as a readout for PABPN1 activity. Comparing APA-shift results to previously published PAS utilization and APA-shift results, we validated this procedure. The procedure was then applied on the OPMD cell model and on RNA from OPMD muscles. APA-shift was genome-wide in the mouse OPMD model, primarily affecting muscle transcripts. In OPMD individuals, APA-shift was enriched with muscle transcripts. In an OPMD cell model APA-shift was not significant. APA-shift correlated with reduced expression levels of a subset of PABPN1 isoforms, whereas the expression of the expanded PABPN1 did not correlate with APA-shift. PABPN1 activity is not affected by the expression of expanded PABPN1, but rather by reduced PABPN1 expression levels. In muscles, PABPN1 activity initially affects muscle transcripts. We suggest that muscle weakness in OPMD is caused by PABPN1 loss-of-function leading to APA-shift that primarily affects in muscle transcripts.

Direct neuronal reprogramming of NDUFS4 patient cells identifies the unfolded protein response as a novel general reprogramming hurdle

Mitochondria account for essential cellular pathways, from ATP production to nucleotide metabolism, and their deficits lead to neurological disorders and contribute to the onset of age-related diseases. Direct neuronal reprogramming aims at replacing neurons lost in such conditions, but very little is known about the impact of mitochondrial dysfunction on the direct reprogramming of human cells. Here, we explore the effects of mitochondrial dysfunction on the neuronal reprogramming of induced pluripotent stem cell (iPSC)-derived astrocytes carrying mutations in the NDUFS4 gene, important for Complex I and associated with Leigh syndrome. This led to the identification of the unfolded protein response as a major hurdle in the direct neuronal conversion of not only astrocytes and fibroblasts from patients but also control human astrocytes and fibroblasts. Its transient inhibition potently improves reprogramming by influencing the mitochondria-endoplasmic-reticulum-stress-mediated pathways. Taken together, disease modeling using patient cells unraveled novel general hurdles and ways to overcome these in human astrocyte-to-neuron reprogramming.

Defining an Optimized Workflow for Enriching and Analyzing Residual Tumor Populations Using Intracellular Markers

Tumor relapse is well recognized to arise from treatment-resistant residual populations. Strategies enriching such populations for in-depth downstream analyses focus on tumor-specific surface markers; however, enrichment using intracellular biomarkers remains challenging. Using B-cell lymphoma as an exemplar, we demonstrate feasibility to enrich B-cell lymphoma 2 (BCL2)high populations, a surrogate marker for t(14;18)+ lymphomas, for use in downstream applications. Different fixation protocols were assessed for impact on antibody expression and RNA integrity; glyoxal fixation demonstrated superior results regarding minimal effects on surface and intracellular expression, and RNA quality, compared with alternative fixatives evaluated. Furthermore, t(14;18)+ B cells were effectively detected using intracellular BCL2 overexpression to facilitate tumor cell enrichment. Tumor cell populations were enriched using the cellenONE F1.4 single-cell sorting platform, which detected and dispensed BCL2high-expressing cells directly into library preparation reagents for transcriptome analyses. Sorted glyoxal-fixed cells generated good quality sequencing libraries, with high concordance between live and fixed single-cell transcriptomic profiles, discriminating cell populations predominantly on B-cell biology. Overall, we successfully developed a proof-of-concept workflow employing a robust cell preparation protocol for intracellular markers combined with cell enrichment using the cellenONE platform, providing an alternative to droplet-based technologies when cellular input is low or requires prior enrichment to detect rare populations. This workflow has wider prognostic and therapeutic potential to study residual cells in a pan-cancer setting.

Sampling efficiency and screening of Aedes albopictus for yellow fever virus in Niger Delta region of Nigeria

Introduction

Aedes albopictus, like Aedes aegypti, is a virulent vector of arboviruses especially the well-documented spread of yellow fever around the world. Although yellow fever is prevalent in Nigeria, there is a paucity of information in the Niger Delta region on the distribution of Aedes mosquito vectors and molecular detection of the virus in infected mosquitoes. This study sampled Aedes mosquitoes around houses associated with farms from four communities (Otolokpo, Ute-Okpu, Umunede, and Ute Alohen) in Ika North-East Local Government Area of Delta State, Nigeria.

Methods

various sampling methods were used in Aedes mosquito collection to test their efficacy in the survey. Mosquitoes in holding cages were killed by freezing and morphologically identified. A pool of 15 mosquitoes per Eppendorf tube was preserved in RNAi later for yellow fever virus screening. Two samples were molecularly screened for each location.

Results

seven hundred and twenty-five (725) mosquitoes were obtained from the various traps. The mean abundance of the mosquitoes was highest in m-HLC (42.9) compared to the mosquitoes sampled using other techniques (p<0.0001). The mean abundance of mosquitoes was lowest in Center for Disease Control (CDC) light traps without attractant (0.29). No yellow fever virus strain was detected in all the mosquitoes sampled at the four locations.

Conclusion

this study suggests that Aedes albopictus are the mosquitoes commonly biting around houses associated with farms. More so, yellow fever virus was not detected in the mosquitoes probably due to the mass vaccination exercise that was carried out the previous year in the study area. More studies are required using the m-HLC to determine the infection rate in this endemic area.

Advances in single-cell omics and multiomics for high-resolution molecular profiling

Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk omics approaches average signals from heterogeneous cell populations, thereby obscuring important cellular nuances. Single-cell omics studies enable the analysis of individual cells and reveal diverse cell types, dynamic cellular states, and rare cell populations. These techniques offer unprecedented resolution and sensitivity, enabling researchers to unravel the molecular landscape of individual cells. Furthermore, the integration of multimodal omics data within a single cell provides a comprehensive and holistic view of cellular processes. By combining multiple omics dimensions, multimodal omics approaches can facilitate the elucidation of complex cellular interactions, regulatory networks, and molecular mechanisms. This integrative approach enhances our understanding of cellular systems, from development to disease. This review provides an overview of the recent advances in single-cell and multimodal omics for high-resolution molecular profiling. We discuss the principles and methodologies for representatives of each omics method, highlighting the strengths and limitations of the different techniques. In addition, we present case studies demonstrating the applications of single-cell and multimodal omics in various fields, including developmental biology, neurobiology, cancer research, immunology, and precision medicine.

A time- and single-cell-resolved model of murine bone marrow hematopoiesis

The paradigmatic hematopoietic tree model is increasingly recognized to be limited, as it is based on heterogeneous populations largely defined by non-homeostatic assays testing cell fate potentials. Here, we combine persistent labeling with time-series single-cell RNA sequencing to build a real-time, quantitative model of in vivo tissue dynamics for murine bone marrow hematopoiesis. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of differentiation at specific stages of erythroid and neutrophil production, illustrating how the model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a kinetoscope allows sequential images to merge into a movie. We posit that this approach is generally applicable to understanding tissue-scale dynamics at high resolution.

Tracking early mammalian organogenesis - prediction and validation of differentiation trajectories at whole organism scale

Early organogenesis represents a key step in animal development, during which pluripotent cells diversify to initiate organ formation. Here, we sampled 300,000 single-cell transcriptomes from mouse embryos between E8.5 and E9.5 in 6-h intervals and combined this new dataset with our previous atlas (E6.5-E8.5) to produce a densely sampled timecourse of >400,000 cells from early gastrulation to organogenesis. Computational lineage reconstruction identified complex waves of blood and endothelial development, including a new programme for somite-derived endothelium. We also dissected the E7.5 primitive streak into four adjacent regions, performed scRNA-seq and predicted cell fates computationally. Finally, we defined developmental state/fate relationships by combining orthotopic grafting, microscopic analysis and scRNA-seq to transcriptionally determine cell fates of grafted primitive streak regions after 24 h of in vitro embryo culture. Experimentally determined fate outcomes were in good agreement with computationally predicted fates, demonstrating how classical grafting experiments can be revisited to establish high-resolution cell state/fate relationships. Such interdisciplinary approaches will benefit future studies in developmental biology and guide the in vitro production of cells for organ regeneration and repair.

An improved method for the highly specific detection of transcription start sites

Precise detection of the transcriptional start site (TSS) is a key for characterizing transcriptional regulation of genes and for annotation of newly sequenced genomes. Here, we describe the development of an improved method, designated 'TSS-seq2.' This method is an iterative improvement of TSS-seq, a previously published enzymatic cap-structure conversion method to detect TSSs in base sequences. By modifying the original procedure, including by introducing split ligation at the key cap-selection step, the yield and the accuracy of the reaction has been substantially improved. For example, TSS-seq2 can be conducted using as little as 5 ng of total RNA with an overall accuracy of 96%; this yield a less-biased and more precise detection of TSS. We then applied TSS-seq2 for TSS analysis of four plant species that had not yet been analyzed by any previous TSS method.

Timing and precision of rattlesnake spinal motoneurons are determined by the KV72/3 potassium channel

The evolution of novel motor behaviors requires modifications in the central pattern generators (CPGs) controlling muscle activity. How such changes gradually lead to novel behaviors remains enigmatic due to the long time course of evolution. Rattlesnakes provide a unique opportunity to investigate how a locomotor CPG was evolutionarily modified to generate a novel behavior-in this case, acoustic signaling. We show that motoneurons (MNs) in the body and tail spinal cord of rattlesnakes possess fundamentally different physiological characteristics, which allow MNs in the tail to integrate and transmit CPG output for controlling superfast muscles with high temporal precision. Using patch-clamp electrophysiology, we demonstrate that these differences in locomotor and rattle MNs are mainly determined by KV72/3 potassium channels. However, although KV72/3 exerted a significantly different influence on locomotor and rattle MN physiology, single-cell RNA-seq unexpectedly did not reveal any differences in KV72/3 channels' expression. VIDEO ABSTRACT.

Application of Single-Cell Sequencing Technology in Research on Colorectal Cancer

Colorectal cancer (CRC) is the third most prevalent and second most lethal cancer globally, with gene mutations and tumor metastasis contributing to its poor prognosis. Single-cell sequencing technology enables high-throughput analysis of the genome, transcriptome, and epigenetic landscapes at the single-cell level. It offers significant insights into analyzing the tumor immune microenvironment, detecting tumor heterogeneity, exploring metastasis mechanisms, and monitoring circulating tumor cells (CTCs). This article provides a brief overview of the technical procedure and data processing involved in single-cell sequencing. It also reviews the current applications of single-cell sequencing in CRC research, aiming to enhance the understanding of intratumoral heterogeneity, CRC development, CTCs, and novel drug targets. By exploring the diverse molecular and clinicopathological characteristics of tumor heterogeneity using single-cell sequencing, valuable insights can be gained into early diagnosis, therapy, and prognosis of CRC. Thus, this review serves as a valuable resource for identifying prognostic markers, discovering new therapeutic targets, and advancing personalized therapy in CRC.

Antisense oligonucleotide-mediated disruption of HTT caspase-6 cleavage site ameliorates the phenotype of YAC128 Huntington disease mice

In Huntington disease, cellular toxicity is particularly caused by toxic protein fragments generated from the mutant huntingtin (HTT) protein. By modifying the HTT protein, we aim to reduce proteolytic cleavage and ameliorate the consequences of mutant HTT without lowering total HTT levels. To that end, we use an antisense oligonucleotide (AON) that targets HTT pre-mRNA and induces partial skipping of exon 12, which contains the critical caspase-6 cleavage site. Here, we show that AON-treatment can partially restore the phenotype of YAC128 mice, a mouse model expressing the full-length human HTT gene including 128 CAG-repeats. Wild-type and YAC128 mice were treated intracerebroventricularly with AON12.1, scrambled AON or vehicle starting at 6 months of age and followed up to 12 months of age, when MRI was performed and mice were sacrificed. AON12.1 treatment induced around 40% exon skip and protein modification. The phenotype on body weight and activity, but not rotarod, was restored by AON treatment. Genes differentially expressed in YAC128 striatum changed toward wild-type levels and striatal volume was preserved upon AON12.1 treatment. However, scrambled AON also showed a restorative effect on gene expression and appeared to generally increase brain volume.

Single-Cell Sequencing of 3' RNA Transcripts

Single-cell RNA sequencing (scRNA-seq) enables the measurement of RNA expressed from individual cells within a tissue or population. RNA expression profiles may be used to draw conclusions about cellular states, cell subtypes within the population, responses to perturbations, and cellular behavior in the context of disease. Here we describe a method for scRNA-seq via single-cell encapsulation and capture of the polyadenosine tails at the 3' end of mRNA transcripts combined with cell and molecular barcoding, allowing for the sequencing of 3' untranslated regions in order to identify expressed genes from a cell.

Bacterial single-cell transcriptomics: Recent technical advances and future applications in dentistry

Metagenomics and metatranscriptomics have enhanced our understanding of the oral microbiome and its impact on oral health. However, these approaches have inherent limitations in exploring individual cells and the heterogeneity within mixed microbial communities, which restricts our current understanding to bulk cells and species-level information. Fortunately, recent technical advances have enabled the application of single-cell RNA sequencing (scRNA-seq) for studying bacteria, shedding light on cell-to-cell diversity and interactions between host-bacterial cells at the single-cell level. Here, we address the technical barriers in capturing RNA from single bacterial cells and highlight pioneering studies from the past decade. We also discuss recent achievements in host-bacterial dual transcriptional profiling at the single-cell level. Bacterial scRNA-seq provides advantages in various research fields, including the investigation of phenotypic heterogeneity within genetically identical bacteria, identification of rare cell types, detection of antibiotic-resistant or persistent cells, analysis of individual gene expression patterns and metabolic activities, and characterization of specific microbe-host interactions. Integrating single-cell techniques with bulk approaches is essential to gain a comprehensive understanding of oral diseases and develop targeted and personalized treatment in dentistry. The reviewed pioneering studies are expected to inspire future research on the oral microbiome at the single-cell level.

The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC

The growth and advancement of ccRCC are strongly associated with the presence of immune infiltration and the tumor microenvironment, comprising tumor cells, immune cells, stromal cells, vascular cells, myeloid-derived cells, and extracellular matrix (ECM). Nevertheless, as a result of the diverse and constantly evolving characteristics of the tumor microenvironment, prior advanced sequencing methods have frequently disregarded specific less prevalent cellular traits at varying intervals, thereby concealing their significance. The advancement and widespread use of single-cell sequencing technology enable us to comprehend the source of individual tumor cells and the characteristics of a greater number of individual cells. This, in turn, minimizes the impact of intercellular heterogeneity and temporal heterogeneity of the same cell on experimental outcomes. This review examines the attributes of the tumor microenvironment in ccRCC and provides an overview of the progress made in single-cell sequencing technology and its particular uses in the current focus of immune infiltration in ccRCC.

The cellular states and fates of shed intestinal cells

The intestinal epithelium is replaced every few days1. Enterocytes are shed into the gut lumen predominantly from the tips of villi2,3 and have been believed to rapidly die upon their dissociation from the tissue4,5. However, technical limitations prohibited studying the cellular states and fates of shed intestinal cells. Here we show that shed epithelial cells remain viable and upregulate distinct anti-microbial programmes upon shedding, using bulk and single-cell RNA sequencing of male mouse intestinal faecal washes. We further identify abundant shedding of immune cells, which is elevated in mice with dextran sulfate sodium-induced colitis. We find that faecal host transcriptomics reflect changes in the intestinal tissue following perturbations. Our study suggests potential functions of shed cells in the intestinal lumen and demonstrates that host cell transcriptomes in intestinal washes can be used to probe tissue states.

Affordable, accurate and unbiased RNA sequencing by manual library miniaturization: A case study in barley

We present an easy-to-reproduce manual miniaturized full-length RNA sequencing (RNAseq) library preparation workflow that does not require the upfront investment in expensive lab equipment or long setup times. With minimal adjustments to an established commercial protocol, we were able to manually miniaturize the RNAseq library preparation by a factor of up to 1:8. This led to cost savings for miniaturized library preparation of up to 86.1% compared to the gold standard. The resulting data were the basis of a rigorous quality control analysis that inspected: sequencing quality metrics, gene body coverage, raw read duplications, alignment statistics, read pair duplications, detected transcripts and sequence variants. We also included a deep dive data analysis identifying rRNA contamination and suggested ways to circumvent these. In the end, we could not find any indication of biases or inaccuracies caused by the RNAseq library miniaturization. The variance in detected transcripts was minimal and not influenced by the miniaturization level. Our results suggest that the workflow is highly reproducible and the sequence data suitable for downstream analyses such as differential gene expression analysis or variant calling.

Ablation of OCT4 function in cattle embryos by double electroporation of CRISPR-Cas for DNA and RNA targeting (CRISPR-DART)

CRISPR-Cas ribonucleoproteins (RNPs) are important tools for gene editing in preimplantation embryos. However, the inefficient production of biallelic deletions in cattle zygotes has hindered mechanistic studies of gene function. In addition, the presence of maternal RNAs that support embryo development until embryonic genome activation may cause confounding phenotypes. Here, we aimed to improve the efficiency of biallelic deletions and deplete specific maternal RNAs in cattle zygotes using CRISPR-Cas editing technology. Two electroporation sessions with Cas9D10A RNPs targeting exon 1 and the promoter of OCT4 produced biallelic deletions in 91% of the embryos tested. In most cases, the deletions were longer than 1,000 nucleotides long. Electroporation of Cas13a RNPs prevents the production of the corresponding proteins. We electroporated Cas9D10A RNPs targeting exon 1, including the promoter region, of OCT4 in two sessions with inclusion of Cas13a RNPs targeting OCT4 mRNAs in the second session to ablate OCT4 function in cattle embryos. A lack of OCT4 resulted in embryos arresting development prior to blastocyst formation at a greater proportion (13%) than controls (31.6%, P < 0.001). The few embryos that developed past the morula stage did not form a normal inner cell mass. Transcriptome analysis of single blastocysts, confirmed to lack exon 1 and promoter region of OCT4, revealed a significant (False Discovery Rate, FDR < 0.1) reduction in transcript abundance of many genes functionally connected to stemness, including markers of pluripotency (CADHD1, DPPA4, GNL3, RRM2). The results confirm that OCT4 is a key regulator of genes that modulate pluripotency and is required to form a functional blastocyst in cattle.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

CSF3R T618I Collaborates With RUNX1-RUNX1T1 to Expand Hematopoietic Progenitors and Sensitizes to GLI Inhibition

Activating colony-stimulating factor-3 receptor gene (CSF3R) mutations are recurrent in acute myeloid leukemia (AML) with t(8;21) translocation. However, the nature of oncogenic collaboration between alterations of CSF3R and the t(8;21) associated RUNX1-RUNX1T1 fusion remains unclear. In CD34+ hematopoietic stem and progenitor cells from healthy donors, double oncogene expression led to a clonal advantage, increased self-renewal potential, and blast-like morphology and distinct immunophenotype. Gene expression profiling revealed hedgehog signaling as a potential mechanism, with upregulation of GLI2 constituting a putative pharmacological target. Both primary hematopoietic cells and the t(8;21) positive AML cell line SKNO-1 showed increased sensitivity to the GLI inhibitor GANT61 when expressing CSF3R T618I. Our findings suggest that during leukemogenesis, the RUNX1-RUNXT1 fusion and CSF3R mutation act in a synergistic manner to alter hedgehog signaling, which can be exploited therapeutically.

Application of single-cell multi-omics approaches in horticulture research

Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.

Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.

spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

Approaches for single-cell RNA sequencing across tissues and cell types

Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.

Wound infiltrating adipocytes are not myofibroblasts

The origins of wound myofibroblasts and scar tissue remains unclear, but it is assumed to involve conversion of adipocytes into myofibroblasts. Here, we directly explore the potential plasticity of adipocytes and fibroblasts after skin injury. Using genetic lineage tracing and live imaging in explants and in wounded animals, we observe that injury induces a transient migratory state in adipocytes with vastly distinct cell migration patterns and behaviours from fibroblasts. Furthermore, migratory adipocytes, do not contribute to scar formation and remain non-fibrogenic in vitro, in vivo and upon transplantation into wounds in animals. Using single-cell and bulk transcriptomics we confirm that wound adipocytes do not convert into fibrogenic myofibroblasts. In summary, the injury-induced migratory adipocytes remain lineage-restricted and do not converge or reprogram into a fibrosing phenotype. These findings broadly impact basic and translational strategies in the regenerative medicine field, including clinical interventions for wound repair, diabetes, and fibrotic pathologies.

A CRISPR interference strategy for gene expression silencing in multiple myeloma cell lines

BACKGROUND

Multiple myeloma (MM) is the second most common hematologic neoplasm which is characterized by proliferation and infiltration of plasmatic cells in the bone marrow. Currently, MM is considered incurable due to resistance to treatment. The CRISPR/Cas9 system has emerged as a powerful tool for understanding the role of different genetic alterations in the pathogenesis of hematologic malignancies in both cell lines and mouse models. Despite current advances of gene editing tools, the use of CRISPR/Cas9 technology for gene editing of MM have not so far been extended. In this work, we want to repress Rnd3 expression, an atypical Rho GTPase involved in several cellular processes, in MM cell lines using a CRISPR interference strategy.

RESULTS

We have designed different guide RNAs and cloning them into a lentiviral plasmid, which contains all the machinery necessary for developing the CRISPR interference strategy. We co-transfected the HEK 293T cells with this lentiviral plasmid and 3rd generation lentiviral envelope and packaging plasmids to produce lentiviral particles. The lentiviral particles were used to transduce two different multiple myeloma cell lines, RPMI 8226 and JJN3, and downregulate Rnd3 expression. Additionally, the impact of Rnd3 expression absence was analyzed by a transcriptomic analysis consisting of 3' UTR RNA sequencing. The Rnd3 knock-down cells showed a different transcriptomic profile in comparison to control cells.

CONCLUSIONS

We have developed a CRISPR interference strategy to generate stable Rnd3 knockdown MM cell lines by lentiviral transduction. We have evaluated this strategy in two MM cell lines, and we have demonstrated that Rnd3 silencing works both at transcriptional and protein level. Therefore, we propose CRISPR interference strategy as an alternative tool to silence gene expression in MM cell lines. Furthermore, Rnd3 silencing produces changes in the cellular transcriptomic profile.

Comparison of transformations for single-cell RNA-seq data

The count table, a numeric matrix of genes × cells, is the basic input data structure in the analysis of single-cell RNA-sequencing data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so that the variance is similar across the dynamic range. These steps are intended to make subsequent application of generic statistical methods more palatable. Here, we describe four transformation approaches based on the delta method, model residuals, inferred latent expression state and factor analysis. We compare their strengths and weaknesses and find that the latter three have appealing theoretical properties; however, in benchmarks using simulated and real-world data, it turns out that a rather simple approach, namely, the logarithm with a pseudo-count followed by principal-component analysis, performs as well or better than the more sophisticated alternatives. This result highlights limitations of current theoretical analysis as assessed by bottom-line performance benchmarks.

Improved Bacterial Single-Cell RNA-Seq through Automated MATQ-Seq and Cas9-Based Removal of rRNA Reads

Bulk RNA sequencing technologies have provided invaluable insights into host and bacterial gene expression and associated regulatory networks. Nevertheless, the majority of these approaches report average expression across cell populations, hiding the true underlying expression patterns that are often heterogeneous in nature. Due to technical advances, single-cell transcriptomics in bacteria has recently become reality, allowing exploration of these heterogeneous populations, which are often the result of environmental changes and stressors. In this work, we have improved our previously published bacterial single-cell RNA sequencing (scRNA-seq) protocol that is based on multiple annealing and deoxycytidine (dC) tailing-based quantitative scRNA-seq (MATQ-seq), achieving a higher throughput through the integration of automation. We also selected a more efficient reverse transcriptase, which led to reduced cell loss and higher workflow robustness. Moreover, we successfully implemented a Cas9-based rRNA depletion protocol into the MATQ-seq workflow. Applying our improved protocol on a large set of single Salmonella cells sampled over different growth conditions revealed improved gene coverage and a higher gene detection limit compared to our original protocol and allowed us to detect the expression of small regulatory RNAs, such as GcvB or CsrB at a single-cell level. In addition, we confirmed previously described phenotypic heterogeneity in Salmonella in regard to expression of pathogenicity-associated genes. Overall, the low percentage of cell loss and high gene detection limit makes the improved MATQ-seq protocol particularly well suited for studies with limited input material, such as analysis of small bacterial populations in host niches or intracellular bacteria. IMPORTANCE Gene expression heterogeneity among isogenic bacteria is linked to clinically relevant scenarios, like biofilm formation and antibiotic tolerance. The recent development of bacterial single-cell RNA sequencing (scRNA-seq) enables the study of cell-to-cell variability in bacterial populations and the mechanisms underlying these phenomena. Here, we report a scRNA-seq workflow based on MATQ-seq with increased robustness, reduced cell loss, and improved transcript capture rate and gene coverage. Use of a more efficient reverse transcriptase and the integration of an rRNA depletion step, which can be adapted to other bacterial single-cell workflows, was instrumental for these improvements. Applying the protocol to the foodborne pathogen Salmonella, we confirmed transcriptional heterogeneity across and within different growth phases and demonstrated that our workflow captures small regulatory RNAs at a single-cell level. Due to low cell loss and high transcript capture rates, this protocol is uniquely suited for experimental settings in which the starting material is limited, such as infected tissues.

Trajectory reconstruction identifies dysregulation of perinatal maturation programs in pluripotent stem cell-derived cardiomyocytes

A limitation in the application of pluripotent stem cell-derived cardiomyocytes (PSC-CMs) is the failure of these cells to achieve full functional maturity. The mechanisms by which directed differentiation differs from endogenous development, leading to consequent PSC-CM maturation arrest, remain unclear. Here, we generate a single-cell RNA sequencing (scRNA-seq) reference of mouse in vivo CM maturation with extensive sampling of previously difficult-to-isolate perinatal time periods. We subsequently generate isogenic embryonic stem cells to create an in vitro scRNA-seq reference of PSC-CM-directed differentiation. Through trajectory reconstruction, we identify an endogenous perinatal maturation program that is poorly recapitulated in vitro. By comparison with published human datasets, we identify a network of nine transcription factors (TFs) whose targets are consistently dysregulated in PSC-CMs across species. Notably, these TFs are only partially activated in common ex vivo approaches to engineer PSC-CM maturation. Our study can be leveraged toward improving the clinical viability of PSC-CMs.

Sexing of cattle embryos using RNA-sequencing data or polymerase chain reaction based on a complete sequence of cattle chromosome Y

When necessary, RNA-sequencing data or polymerase chain reaction (PCR) assays can be used to determine the presence of the chromosome Y (ChrY) in samples. This information allows for biological variation due to sexual dimorphism to be studied. A prime example is when researchers conduct RNA-sequencing of single embryos, or conceptuses, prior to the development of gonads. A recent publication of a complete sequence of the ChrY has removed limitations for the development of these procedures in cattle, otherwise imposed by the absence of a ChrY in the reference genome. Using the sequence of the cattle ChrY and transcriptome data, we conducted a systematic search for genes in the ChrY that are exclusively expressed in male tissues. The genes ENSBIXG00000029763, ENSBIXG00000029774, ENSBIXG00000029788, and ENSBIXG00000029892 were consistently expressed across male tissues and lowly expressed or absent in female samples. We observed that the cumulative values of counts per million were 2688-fold greater in males than the equivalent values in female samples. Thus, we deemed these genes suitable for the sexing of samples using RNA-sequencing data. We successfully used this set of genes to infer the sex of 22 cattle blastocysts (8 females and 14 males). Additionally, the completed sequence of the cattle ChrY has segments in the male-specific region that are not repeated. We designed a pair of oligonucleotides that targets one of these non-repeated regions in the male-specific sequence of the ChrY. Using this pair of oligonucleotides, in a multiplexed PCR assay with oligonucleotides that anneal to an autosome chromosome, we accurately identified the sex of cattle blastocysts. We developed efficient procedures for the sexing of samples in cattle using either transcriptome data or their DNA. The procedures using RNA-sequencing will greatly benefit researchers who work with samples limited in cell numbers which are only sufficient to produce transcriptome data. The oligonucleotides used for the accurate sexing of samples using PCR are transferable to other cattle tissue samples.