Massively parallel base editing to map variant effects in human hematopoiesis.

Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow for rich phenotyping through single-cell RNA sequencing readouts and separately for characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.

Mapping transcriptomic vector fields of single cells.

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

Deciphering cell states and genealogies of human haematopoiesis.

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.

Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape.

Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function. However, the intricate subcellular dynamics of RNA remain obscured due to the limitations of existing transcriptomics methods. Here, we report TEMPOmap-a method that uncovers subcellular RNA profiles across time and space at the single-cell level. TEMPOmap integrates pulse-chase metabolic labeling with highly multiplexed three-dimensional in situ sequencing to simultaneously profile the age and location of individual RNA molecules. Using TEMPOmap, we constructed the subcellular RNA kinetic landscape in various human cells from transcription and translocation to degradation. Clustering analysis of RNA kinetic parameters across single cells revealed 'kinetic gene clusters' whose expression patterns were shaped by multistep kinetic sculpting. Importantly, these kinetic gene clusters are functionally segregated, suggesting that subcellular RNA kinetics are differentially regulated in a cell-state- and cell-type-dependent manner. Spatiotemporally resolved transcriptomics provides a gateway to uncovering new spatiotemporal gene regulation principles.

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data.

Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of "chromatin hubs"-they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD1 in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. Our strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.

The single-cell transcriptional landscape of mammalian organogenesis.

Mammalian organogenesis is a remarkable process. Within a short timeframe, the cells of the three germ layers transform into an embryo that includes most of the major internal and external organs. Here we investigate the transcriptional dynamics of mouse organogenesis at single-cell resolution. Using single-cell combinatorial indexing, we profiled the transcriptomes of around 2 million cells derived from 61 embryos staged between 9.5 and 13.5 days of gestation, in a single experiment. The resulting 'mouse organogenesis cell atlas' (MOCA) provides a global view of developmental processes during this critical window. We use Monocle 3 to identify hundreds of cell types and 56 trajectories, many of which are detected only because of the depth of cellular coverage, and collectively define thousands of corresponding marker genes. We explore the dynamics of gene expression within cell types and trajectories over time, including focused analyses of the apical ectodermal ridge, limb mesenchyme and skeletal muscle.

Inferring gene regulation from stochastic transcriptional variation across single cells at steady state.

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

The cis-regulatory dynamics of embryonic development at single-cell resolution.

Understanding how gene regulatory networks control the progressive restriction of cell fates is a long-standing challenge. Recent advances in measuring gene expression in single cells are providing new insights into lineage commitment. However, the regulatory events underlying these changes remain unclear. Here we investigate the dynamics of chromatin regulatory landscapes during embryogenesis at single-cell resolution. Using single-cell combinatorial indexing assay for transposase accessible chromatin with sequencing (sci-ATAC-seq), we profiled chromatin accessibility in over 20,000 single nuclei from fixed Drosophila melanogaster embryos spanning three landmark embryonic stages: 2-4 h after egg laying (predominantly stage 5 blastoderm nuclei), when each embryo comprises around 6,000 multipotent cells; 6-8 h after egg laying (predominantly stage 10-11), to capture a midpoint in embryonic development when major lineages in the mesoderm and ectoderm are specified; and 10-12 h after egg laying (predominantly stage 13), when each of the embryo's more than 20,000 cells are undergoing terminal differentiation. Our results show that there is spatial heterogeneity in the accessibility of the regulatory genome before gastrulation, a feature that aligns with future cell fate, and that nuclei can be temporally ordered along developmental trajectories. During mid-embryogenesis, tissue granularity emerges such that individual cell types can be inferred by their chromatin accessibility while maintaining a signature of their germ layer of origin. Analysis of the data reveals overlapping usage of regulatory elements between cells of the endoderm and non-myogenic mesoderm, suggesting a common developmental program that is reminiscent of the mesendoderm lineage in other species. We identify 30,075 distal regulatory elements that exhibit tissue-specific accessibility. We validated the germ-layer specificity of a subset of these predicted enhancers in transgenic embryos, achieving an accuracy of 90%. Overall, our results demonstrate the power of shotgun single-cell profiling of embryos to resolve dynamic changes in the chromatin landscape during development, and to uncover the cis-regulatory programs of metazoan germ layers and cell types.

Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq.

Single-cell RNA sequencing offers snapshots of whole transcriptomes but obscures the temporal RNA dynamics. Here we present single-cell metabolically labeled new RNA tagging sequencing (scNT-seq), a method for massively parallel analysis of newly transcribed and pre-existing mRNAs from the same cell. This droplet microfluidics-based method enables high-throughput chemical conversion on barcoded beads, efficiently marking newly transcribed mRNAs with T-to-C substitutions. Using scNT-seq, we jointly profiled new and old transcriptomes in ~55,000 single cells. These data revealed time-resolved transcription factor activities and cell-state trajectories at the single-cell level in response to neuronal activation. We further determined rates of RNA biogenesis and decay to uncover RNA regulatory strategies during stepwise conversion between pluripotent and rare totipotent two-cell embryo (2C)-like stem cell states. Finally, integrating scNT-seq with genetic perturbation identifies DNA methylcytosine dioxygenase as an epigenetic barrier into the 2C-like cell state. Time-resolved single-cell transcriptomic analysis thus opens new lines of inquiry regarding cell-type-specific RNA regulatory mechanisms.

Optimization of Electron Transport Pathway: A Novel Strategy to Solve the Photocorrosion of Ag-Based Photocatalysts.

Although Ag-containing photocatalysts exhibit excellent photocatalytic ability, they present great challenges owing to their photocorrosion and ease of reduction. Herein, an electron acceptor platform of Ag2O/La(OH)3/polyacrylonitrile (PAN) fiber was constructed using a heterojunction strategy and electrospinning technology to develop a novel photocatalytic membrane with a redesigned electron transport pathway. Computational and experimental results demonstrate that the optimized electron transport pathway included intercrystal electron transfer induced by the La-O bond between Ag2O and La(OH)3 as well as electron transfer between the catalyst crystal and electrophilic PAN membrane interface. In addition, the photocatalytic performance of the Ag2O/La(OH)3 membrane for tetracycline (TC) removal was still above 97% after five photocatalytic reaction cycles. Furthermore, the carrier life was greatly extended. Mechanistic study revealed that photogenerated holes on the Ag2O/La(OH)3 membrane were the main reactive species in TC degradation. Overall, this study proposes a novel electron transport pathway strategy that effectively solves the problems of photocatalyst photocorrosion and structural instability.

Fabrication of Pd/Sludge-biochar electrode with high electrochemical activity on reductive degradation of 4-chlorophenol in wastewater.

Effective treatment and utilization of sludge contribute to achieve conventional carbon emission reduction and resource recovery, which is of great significance to realize carbon neutralization of WWTPs. Sludge carbonization derived biochar has attracted more interest because of high potential as catalytic materials. Therein, sludge-derived electrode exhibits a promising potential in the case of sludge utilization for electrocatalysis, however, electrocatalytic performance of the already reported sludge-derived electrode is unsatisfactory due to insufficient active sites. In this study, an efficient Pd/sludge-biochar loaded foam nickel (Pd-SAC@Ni) was successfully fabricated using simple pyrolysis and solidification method, and exhibited remarkable electrocatalytic performance for 4-chlorophenol (4-CP) degradation. Furthermore, the morphology, element distribution and crystal composition were characterized by SEM, EDS, XPS and XRD. The Pd-SAC@Ni electrode exhibited superior electrocatalytic performance than Ni, SAC@Ni, Pd-Ni electrodes. The reduction rate of 98.9% was achieved at current density of 5 mA cm-2, 4-CP concentration of 0.8 mM and initial pH of 7.0. Also, Pd-SAC@Ni electrode showed desirable reusability and achieved 98% of 4-CP removal after multiple runs of experiments. Moreover, the active hydrogen species (H*) generation capacity of electrodes was determined using tert-butanol (TBA) as trapping agent. The mechanism analysis demonstrated that direct reduction process and indirect reduction process both involved in the 4-CP degradation process, and their contribution were 19.5% and 80.5%, respectively. Then, the intermediates formed in the electrochemical degradation of 4-CP were revealed by HPLC and the plausible degradation pathway was proposed. This study provides a cost-effective approach for preparing sludge biochar electrode, and explored a novel way to promote resourceful utilization of sludge for carbon neutrality.

Reversed graph embedding resolves complex single-cell trajectories.

Single-cell trajectories can unveil how gene regulation governs cell fate decisions. However, learning the structure of complex trajectories with multiple branches remains a challenging computational problem. We present Monocle 2, an algorithm that uses reversed graph embedding to describe multiple fate decisions in a fully unsupervised manner. We applied Monocle 2 to two studies of blood development and found that mutations in the genes encoding key lineage transcription factors divert cells to alternative fates.

Single-cell mRNA quantification and differential analysis with Census.

Single-cell gene expression studies promise to reveal rare cell types and cryptic states, but the high variability of single-cell RNA-seq measurements frustrates efforts to assay transcriptional differences between cells. We introduce the Census algorithm to convert relative RNA-seq expression levels into relative transcript counts without the need for experimental spike-in controls. Analyzing changes in relative transcript counts led to dramatic improvements in accuracy compared to normalized read counts and enabled new statistical tests for identifying developmentally regulated genes. Census counts can be analyzed with widely used regression techniques to reveal changes in cell-fate-dependent gene expression, splicing patterns and allelic imbalances. We reanalyzed single-cell data from several developmental and disease studies, and demonstrate that Census enabled robust analysis at multiple layers of gene regulation. Census is freely available through our updated single-cell analysis toolkit, Monocle 2.

Wavelength detection of model-sharing fiber Bragg grating sensor networks using long short-term memory neural network.

In this paper, an effective wavelength detection approach based on long short-term memory (LSTM) network is proposed for fiber Bragg grating (FBG) sensor networks. The FBG sensor network utilizes a model-sharing mechanism, where the whole spectral wavelength is divided into several shareable regions and spectral overlap is allowed in each region. LSTM, a representative recurrent neural network in deep learning, is applied to learn the features directly from the spectra of FBGs and build the wavelength detection model. By feeding the spectra sequentially into the well-trained model, the Bragg wavelengths of FBGs can be quickly determined under overlap. The obtained LSTM model can be repeatedly used without re-training to improve the multiplexing capability. The results demonstrate that the LSTM-based method can realize high-accuracy and high-speed wavelength detection in the spectral overlapping situations. The proposed approach offers a flexible tool to enhance the sensing capacity of FBG sensor networks.

Graphite-N reinforced sludge biochar electrode: A experimental and DFT theoretical analysis of efficient evolution and in-situ utilization of H2O2.

Rational reuse of municipal sludge to produce electro-Fenton electrode can not only save resources, but also produce superior peroxide and degradation pollutants simultaneously. Herein, a novel electro-Fenton electrode derived from sludge biochar loaded on Ni foam (SBC@Ni) was constructed via high temperature pyrolysis and chemical coating for efficient H2O2 evolution and pollutant degradation. Systematic experiments and density functional theory calculations (DFT calculation) explained that the production of graphite C and graphite N during high-temperature pyrolysis of municipal sludge can greatly enhance the oxygen reduction reaction of SBC@Ni electrode and promote the evolution of H2O2. And the hybrid heterojunctions, such as FeP, also played a key role in electrocatalytic processes. Notably, the electrode still exhibited excellent performance after 1000 linear scans and 12 h of continuous current stimulation, which demonstrated the excellent stability of the electrode. Moreover, SBC@Ni electrode can not only effectively oxidize 4-chlorophenol through the electro-Fenton effect, but also fully mineralize organic matter, indicating promising environmental application. The free radical quenching experiment also revealed that the ·OH is the main active species for 4-CP degradation in SBC@Ni electro-Fenton system.

Enhanced synergistic catalysis of bisphenol A in river water using an anti-aging photocatalytic membrane.

Bisphenol A (BPA), as an endocrine disruptor, poses a potential threat to ecosystems and human health in aquatic environments. Membrane catalytic systems can accelerate the degradation of BPA and facilitate its conversion into harmless compounds. Nevertheless, the complex nature of the water environments and the limited stability of catalysts often result in challenges such as catalyst aging and deactivation. Herein, an anti-aging multifunctional AgFeO2 catalytic material with electron transfer membrane support was prepared for synergistic catalysis of low-energy LED light (12 W) excitation and peroxydisulfate (PDS) activation. The anti-aging photocatalytic membrane completely degraded 10 ppm of BPA within 30 min, and did not show significant aging after the long-term synergistic catalytic process. In addition, actual river water was employed to assess the aging process and catalytic efficiency in a practical environment. A 60.79 cm2 photocatalytic membrane completely purified 10 L of BPA polluted river water, while the total organic carbon content decreased by 50 %. This was mainly due to the synergistic catalytic effect of the membrane, which boosted photoelectron transfer through electron transfer shortcuts, thereby enhancing persulfate activation. Overall, the multifunctional membrane provides an effective strategy for achieving a long-lasting catalytic effect and controlling photocatalyst aging in practice.

Resilient Model Free Adaptive Distributed LFC for Multi-Area Power Systems Against Jamming Attacks.

This article is concerned with distributed resilient load frequency control (LFC) for multi-area power interconnection systems against jamming attacks. First, considering uncertainties and high dimension nonlinearity, the model-free adaptive control (MFAC) model is adopted for the power system, in which only input and output (I/O) data are used. Second, jamming attacks are modeled in a stochastic process, and a multistep predictive compensation algorithm is developed to mitigate the impact of jamming attacks. Then, the distributed MFAC protocol with predictive compensation algorithm is designed such that the frequency tracking errors under the predictive compensation algorithm of multi-area power interconnection systems converge consensually into a small neighborhood of origin in the mean square sense. Simulation results show the effectiveness of the approach.

Competitive adsorption of sulfamethoxazole and bisphenol A on magnetic biochar: Mechanism and site energy distribution.

Competitive adsorption and complementary adsorption between emerging pollutants has been observed in multiple studies. Investigation of the preference of pollutants for different types of adsorption sites can provide a supplementary perspective for understanding complementary adsorption. In this study, the simultaneous adsorption of two typical emerging pollutants, sulfamethoxazole (SMX) and bisphenol A (BPA), on magnetic biochar (MBC-1) was investigated. The results showed that the modification with ferric chloride optimized the surface properties of biochar (aromaticity, hydrophobicity, and oxygen-containing functional groups, etc.), and helped to remove SMX and BPA through various interactions. The equilibrium adsorption capacity of the two adsorbents was inhibited by competitive adsorption in the mixed solute systems, which was due to the same adsorption mechanism. When pH = 7, the SMX and BPA adsorption mainly involved pore filling, hydrophobic effect, π-π EDA, and hydrogen bonding. In addition, electrostatic force, surface coordination, and ion exchange have also been proven to be related to the adsorption of SMX and BPA. In the co-adsorption system, BPA's competitive advantage might be due to its superior hydrophobicity, charge property, and molecular diameter. In the competitive adsorption experiment, the total adsorption capacity (Qi) of the competitive solute exceeded the adsorption inhibition (△Qi) of the main solute, indicating that the two solutes occupied their preferred adsorption sites, which confirmed the complementary adsorption phenomenon. Complementary adsorption can be explained by the preference of SMX and BPA for different types of adsorption sites. BPA preferentially occupied high-energy sites in the co-adsorption system, such as π-π EDA interaction, ion exchange, and surface coordination. At the same time, SMX tended to be removed by hydrophobic interaction and hydrogen bonding.