ColorCells: a database of expression, classification and functions of lncRNAs in single cells.

Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs' functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.

Fast location and segmentation of high-throughput damaged soybean seeds with invertible neural networks.

BACKGROUND: Fast identification of damaged soybean seeds has undeniable importance in seed sorting and food quality. Mechanical vibration is generally used in soybean seed sorting, but this can seriously damage soybean seeds. The convolutional neural network (CNN) is considered an effective method for location and segmentation tasks. However, a CNN requires a large amount of ground truth data and has high computational cost. RESULTS: First, we propose a self-supervision manner to automatically generate ground truths, which can theoretically create an almost unlimited number of labeled images. Second, instead of using popular CNNs, a novel invertible convolution (involution)-enabled scheme is proposed by using the bottleneck block of the residual networks. Third, a feature selection feature pyramid network (FS-FPN) based on involution is designed, which selects features more flexibly and adaptively. We further merge involution-based backbones and FS-FPN into a unified network, achieving an end-to-end seed location and segmentation model; the best mean average precision of location and segmentation achieved was 85.1% and 81% respectively. CONCLUSION: The experimental results demonstrate that the proposed method greatly improves the performance of the baseline network with faster speed and fewer parameters, enabling it to detect soybean seeds more effectively. © 2022 Society of Chemical Industry.

Mechanogenetics for the remote and noninvasive control of cancer immunotherapy.

While cell-based immunotherapy, especially chimeric antigen receptor (CAR)-expressing T cells, is becoming a paradigm-shifting therapeutic approach for cancer treatment, there is a lack of general methods to remotely and noninvasively regulate genetics in live mammalian cells and animals for cancer immunotherapy within confined local tissue space. To address this limitation, we have identified a mechanically sensitive Piezo1 ion channel (mechanosensor) that is activatable by ultrasound stimulation and integrated it with engineered genetic circuits (genetic transducer) in live HEK293T cells to convert the ultrasound-activated Piezo1 into transcriptional activities. We have further engineered the Jurkat T-cell line and primary T cells (peripheral blood mononuclear cells) to remotely sense the ultrasound wave and transduce it into transcriptional activation for the CAR expression to recognize and eradicate target tumor cells. This approach is modular and can be extended for remote-controlled activation of different cell types with high spatiotemporal precision for therapeutic applications.

Integrated Ultrafine Co0.85 Se in Carbon Nanofibers: An Efficient and Robust Bifunctional Catalyst for Oxygen Electrocatalysis.

Transition-metal selenides are emerging as alternative bifunctional catalysts for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR); however, their activity and stability are still less than desirable. Herein, ultrafine Co0.85 Se nanoparticles encapsulated into carbon nanofibers (CNFs), Co0.85 Se@CNFs, is reported as an integrated bifunctional catalyst for OER and ORR. This catalyst exhibits a low OER potential of 1.58 V vs. reversible hydrogen electrode (RHE) (EJ=10, OER ) to achieve a current density (J) of 10 mA cm-2 and a high ORR potential of 0.84 V vs. RHE (EJ=-1, ORR ) to reach -1 mA cm-2 . Thus, the potential between EJ=10, OER and EJ=-1, ORR is only 0.74 V, indicating considerable bifunctional activity. The excellent bifunctionality can be attributed to high electronic conduction, abundant electrochemically active sites, and the synergistic effect of Co0.85 Se and CNFs. Furthermore, this Co0.85 Se@CNFs catalyst displays good cycling stability for both OER and ORR. This study paves a new way for the rational design of hybrid catalysts composed of transition-metal selenides and carbon materials for efficiently catalyzing OER and ORR.

Construction of a linker library with widely controllable flexibility for fusion protein design.

Flexibility or rigidity of the linker between two fused proteins is an important parameter that affects the function of fusion proteins. In this study, we constructed a linker library with five elementary units based on the combination of the flexible (GGGGS) and the rigid (EAAAK) units. Molecular dynamics (MD) simulation showed that more rigid units in the linkers lead to more helical conformation and hydrogen bonds, and less distance fluctuation between the N- and C-termini of the linker. The diversity of linker flexibility of the linker library was then studied by fluorescence resonance energy transfer (FRET) of cyan fluorescent protein (CFP)-yellow fluorescent protein (YFP) fusion proteins, which showed that there is a wide range of distribution of the FRET efficiency. Dissipative particle dynamics (DPD) simulation of CFP-YFP with different linkers also gave identical results with that of FRET efficiency analysis, and we further found that the combination manner of the linker peptide had a remarkable effect on the orientation of CFP and YFP domains. Our studies demonstrated that the construction of the linker library with the widely controllable flexibility could provide appropriate linkers with the desirable characteristics to engineer the fusion proteins with the expected functions.

Discrimination of internal crack for rice seeds using near infrared spectroscopy.

It is an important thing to identify internal crack in seeds from normal seeds for evaluating the quality of rice seeds (Oryza sativa L.). In this study, non-destructive discrimination of internal crack in rice seeds using near infrared spectroscopy and chemometrics is proposed. Principal component analysis (PCA) was used to analyze the rice seeds spectra. Four supervised classification techniques(partial least squares discriminate analysis (PLS-DA), support vector machines (SVM), k-nearest neighbors (KNN) and random forest (RF)) with four different pre-processing techniques (standard normal variate (SNV), multiplicative scatter correction (MSC), first and second derivative with Savitzky-Golay (SG) smoothing) were applied. The best results (Sn = 0.8824, Sp = 0.9429, Acc = 0.913) were achieved by PLS-DA with the raw spectral data. The performance of the best SVM model was inferior to that of PLS-DA, but superior to that of RF and KNN. Except for PLS-DA, four different preprocessing techniques were improved the performance of the developed models. The important variables for discriminating internal cracks in rice seeds were related to the amylose. Overall, the all results demonstrated the feasibility of non-destructive discrimination of internal crack for rice seeds (Oryza sativa L.) using near infrared spectroscopy and chemometrics.

Abalone peptide increases stress resilience and cost-free longevity via SKN-1-governed transcriptional metabolic reprogramming in C. elegans.

A major goal of healthy aging is to prevent declining resilience and increasing frailty, which are associated with many chronic diseases and deterioration of stress response. Here, we propose a loss-or-gain survival model, represented by the ratio of cumulative stress span to life span, to quantify stress resilience at organismal level. As a proof of concept, this is demonstrated by reduced survival resilience in Caenorhabditis elegans exposed to exogenous oxidative stress induced by paraquat or with endogenous proteotoxic stress caused by polyglutamine or amyloid-ß aggregation. Based on this, we reveal that a hidden peptide ("cryptide")-AbaPep#07 (SETYELRK)-derived from abalone hemocyanin not only enhances survival resilience against paraquat-induced oxidative stress but also rescues proteotoxicity-mediated behavioral deficits in C. elegans, indicating its capacity against stress and neurodegeneration. Interestingly, AbaPep#07 is also found to increase cost-free longevity and age-related physical fitness in nematodes. We then demonstrate that AbaPep#07 can promote nuclear localization of SKN-1/Nrf, but not DAF-16/FOXO, transcription factor. In contrast to its effects in wild-type nematodes, AbaPep#07 cannot increase oxidative stress survival and physical motility in loss-of-function skn-1 mutant, suggesting an SKN-1/Nrf-dependent fashion of these effects. Further investigation reveals that AbaPep#07 can induce transcriptional activation of immune defense, lipid metabolism, and metabolic detoxification pathways, including many SKN-1/Nrf target genes. Together, our findings demonstrate that AbaPep#07 is able to boost stress resilience and reduce behavioral frailty via SKN-1/Nrf-governed transcriptional reprogramming, and provide an insight into the health-promoting potential of antioxidant cryptides as geroprotectors in aging and associated conditions.

GateView: A Multi-Omics Platform for Gene Feature Analysis of Virus Receptors within Human Normal Tissues and Tumors.

Viruses are obligate intracellular parasites that rely on cell surface receptor molecules to complete the first step of invading host cells. The experimental method for virus receptor screening is time-consuming, and receptor molecules have been identified for less than half of known viruses. This study collected known human viruses and their receptor molecules. Through bioinformatics analysis, common characteristics of virus receptor molecules (including sequence, expression, mutation, etc.) were obtained to study why these membrane proteins are more likely to become virus receptors. An in-depth analysis of the cataloged virus receptors revealed several noteworthy findings. Compared to other membrane proteins, human virus receptors generally exhibited higher expression levels and lower sequence conservation. These receptors were found in multiple tissues, with certain tissues and cell types displaying significantly higher expression levels. While most receptor molecules showed noticeable age-related variations in expression across different tissues, only a limited number of them exhibited gender-related differences in specific tissues. Interestingly, in contrast to normal tissues, virus receptors showed significant dysregulation in various types of tumors, particularly those associated with dsRNA and retrovirus receptors. Finally, GateView, a multi-omics platform, was established to analyze the gene features of virus receptors in human normal tissues and tumors. Serving as a valuable resource, it enables the exploration of common patterns among virus receptors and the investigation of virus tropism across different tissues, population preferences, virus pathogenicity, and oncolytic virus mechanisms.

Active inclusion bodies of acid phosphatase PhoC: aggregation induced by GFP fusion and activities modulated by linker flexibility.

BACKGROUND: Biologically active inclusion bodies (IBs) have gained much attention in recent years. Fusion with IB-inducing partner has been shown to be an efficient strategy for generating active IBs. To make full use of the advantages of active IBs, one of the key issues will be to improve the activity yield of IBs when expressed in cells, which would need more choices on IB-inducing fusion partners and approaches for engineering IBs. Green fluorescent protein (GFP) has been reported to aggregate when overexpressed, but GFP fusion has not been considered as an IB-inducing approach for these fusion proteins so far. In addition, the role of linker in fusion proteins has been shown to be important for protein characteristics, yet impact of linker on active IBs has never been reported. RESULTS: Here we report that by fusing GFP and acid phosphatase PhoC via a linker region, the resultant PhoC-GFPs were expressed largely as IBs. These IBs show high levels of specific fluorescence and specific PhoC activities (phosphatase and phosphotransferase), and can account for up to over 80% of the total PhoC activities in the cells. We further demonstrated that the aggregation of GFP moiety in the fusion protein plays an essential role in the formation of PhoC-GFP IBs. In addition, PhoC-GFP IBs with linkers of different flexibility were found to exhibit different levels of activities and ratios in the cells, suggesting that the linker region can be utilized to manipulate the characteristics of active IBs. CONCLUSIONS: Our results show that active IBs of PhoC can be generated by GFP fusion, demonstrating for the first time the potential of GFP fusion to induce active IB formation of another soluble protein. We also show that the linker sequence in PhoC-GFP fusion proteins plays an important role on the regulation of IB characteristics, providing an alternative and important approach for engineering of active IBs with the goal of obtaining high activity yield of IBs.

Combination of site-directed mutagenesis and calcium ion addition for enhanced production of thermostable MBP-fused heparinase I in recombinant Escherichia coli.

Heparinase I (HepI), which specifically cleaves heparin and heparan sulfate, is one of the most extensively studied glycosaminoglycan lyases. Low productivity of HepI has largely hindered its industrial and pharmaceutical applications. Loss of bacterial HepI enzyme activity through poor thermostability during its expression and purification process in production can be an important issue. In this study, using a thermostabilization strategy combining site-directed mutagenesis and calcium ion addition during its production markedly improved the yield of maltose-binding protein-fused HepI (MBP-HepI) from recombinant Escherichia coli. Substitution of Cys297 to serine in MBP-HepI offered a 30.6% increase in the recovered total enzyme activity due to a mutation-induced thermostabilizing effect. Furthermore, upon addition of Ca2+ as a stabilizer at optimized concentrations throughout its expression, extraction, and purification process, purified mutant MBP-HepI showed a specific activity of 56.3 IU/mg, 206% higher than that of the wild type obtained without Ca2+ addition, along with a 177% increase in the recovered total enzyme activity. The enzyme obtained through this novel approach also exhibited significantly enhanced thermostability, as indicated by both experimental data and the kinetic modeling. High-yield production of thermostable MBP-HepI using the present system will facilitate its applications in laboratory-scale heparin analysis as well as industrial-scale production of low molecular weight heparin as an improved anticoagulant substitute.

Single Genomic Loci Labeling and Manipulation Using SIMBA System.

The SIMBA (Simultaneous Imaging and Manipulation of genomic loci by Biomolecular Assemblies) system is an innovative CRISPR-based imaging technique that leverages dCas9-SunTag and FRB-mCherry-HP1α, with scFv-FKBP acting as a bridge. This powerful system enables simultaneous visualization and manipulation of genomic loci. The dCas9-SunTag fusion protein allows for precise targeting of specific genomic sites, and the FRB-mCherry-HP1α fusion protein facilitates the condensation of chromatin at the targeted loci. The scFv-FKBP bridge protein links dCas9-SunTag and FRB-mCherry-HP1α, ensuring efficient and specific recruitment of HP1α to the desired genomic loci. This integrated approach allows us to visualize and manipulate genomic regions of interest, opening up new avenues for studying genome organization, gene expression regulation, and chromatin dynamics in living cells. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Cloning of genetic constructs Basic Protocol 2: Transient transfection in mammalian cells and live-cell imaging Basic Protocol 3: Generation of SIMBA-expressing stable cell lines Basic Protocol 4: Manipulation of genomic loci using SIMBA.

Integrative profiling of extrachromosomal circular DNA in placenta and maternal plasma provides insights into the biology of fetal growth restriction and reveals potential biomarkers.

Introduction: Fetal growth restriction (FGR) is a placenta-mediated pregnancy complication that predisposes fetuses to perinatal complications. Maternal plasma cell-free DNA harbors DNA originating from placental trophoblasts, which is promising for the prenatal diagnosis and prediction of pregnancy complications. Extrachromosomal circular DNA (eccDNA) is emerging as an ideal biomarker and target for several diseases. Methods: We utilized eccDNA sequencing and bioinformatic pipeline to investigate the characteristics and associations of eccDNA in placenta and maternal plasma, the role of placental eccDNA in the pathogenesis of FGR, and potential plasma eccDNA biomarkers of FGR. Results: Using our bioinformatics pipelines, we identified multi-chromosomal-fragment and single-fragment eccDNA in placenta, but almost exclusively single-fragment eccDNA in maternal plasma. Relative to that in plasma, eccDNA in placenta was larger and substantially more abundant in exons, untranslated regions, promoters, repetitive elements [short interspersed nuclear elements (SINEs)/Alu, SINEs/mammalian-wide interspersed repeats, long terminal repeats/endogenous retrovirus-like elements, and single recognition particle RNA], and transcription factor binding motifs. Placental multi-chromosomal-fragment eccDNA was enriched in confident enhancer regions predicted to pertain to genes in apoptosis, energy, cell growth, and autophagy pathways. Placental eccDNA-associated genes whose abundance differed between the FGR and control groups were associated with immunity-related gene ontology (GO) terms. The combined analysis of plasma and placental eccDNA-associated genes in the FGR and control groups led to the identification of potential biomarkers that were assigned to the GO terms of the epigenetic regulation of gene expression and nutrient-related processes, respectively. Conclusion: Together, our results highlight links between placenta functions and multi-chromosomal-fragment and single-fragment eccDNA. The integrative analysis of placental and plasma eccDNA confirmed the potential of these molecules as disease-specific biomarkers of FGR.

Study on the Effect of Self-Made Lifei Dingchuan Decoction Combined with Western Medicine on Cough Variant Asthma.

Aims: To observe the clinical efficacy of self-made Lifei Dingchuan decoction combined with western medicine in the treatment of cough variant asthma (phlegm-heat accumulation in the lung syndrome). Materials and Methods: The clinical data of 90 patients with cough variant asthma who were hospitalized in the Department of Respiratory Medicine of our hospital from January 2020 to April 2022 were selected as the research objects, and they were equally divided into the observation group and the reference group according to different treatment methods, 45 cases in each group. The group was treated with traditional montelukast sodium chewable tablet and salmeterol fluticasone mixed powder inhalation, and the observation group was treated with self-made Lifei Dingchuan decoction on the basis of the control group, saturation, pH, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide, length of stay, and hospitalization costs. Results: After the patients underwent self-made Lifei Dingchuan decoction, there were significant differences between the observation group and the reference group in terms of heart rate, respiratory rate, blood oxygen saturation, pH value, arterial blood oxygen partial pressure, carbon dioxide partial pressure, and within the group. There was a statistical difference (P < 0.05). The adverse reactions in patients with cough variant asthma after treatment showed that the red throat, shortness of breath, chest tightness, and dry mouth in the observation group were significantly different from those in the control group (P < 0.05). After investigation, follow-up, and statistics, the hospitalization time, hospitalization cost, asthma exacerbation control time, effective rate, and recurrence rate were compared between the two groups, and the differences between the two groups were statistically significant (P < 0.05). Conclusion: The study on the clinical efficacy and low hospitalization cost of the self-prepared lung and asthma-restorative soup in patients with cough variant asthma significantly improved the patients' arterial oxygen saturation, acid-base value, arterial partial pressure of oxygen, and partial pressure of carbon dioxide and effectively controlled the heart rate and respiratory rate with high safety, which is worth further promotion.

ASP-Det: Toward Appearance-Similar Light-Trap Agricultural Pest Detection and Recognition.

Automatic pest detection and recognition using computer vision techniques are a hot topic in modern intelligent agriculture but suffer from a serious challenge: difficulty distinguishing the targets of similar pests in 2D images. The appearance-similarity problem could be summarized into two aspects: texture similarity and scale similarity. In this paper, we re-consider the pest similarity problem and state a new task for the specific agricultural pest detection, namely Appearance Similarity Pest Detection (ASPD) task. Specifically, we propose two novel metrics to define the texture-similarity and scale-similarity problems quantitatively, namely Multi-Texton Histogram (MTH) and Object Relative Size (ORS). Following the new definition of ASPD, we build a task-specific dataset named PestNet-AS that is collected and re-annotated from PestNet dataset and also present a corresponding method ASP-Det. In detail, our ASP-Det is designed to solve the texture-similarity by proposing a Pairwise Self-Attention (PSA) mechanism and Non-Local Modules to construct a domain adaptive balanced feature module that could provide high-quality feature descriptors for accurate pest classification. We also present a Skip-Calibrated Convolution (SCC) module that can balance the scale variation among the pest objects and re-calibrate the feature maps into the sizing equivalent of pests. Finally, ASP-Det integrates the PSA-Non Local and SCC modules into a one-stage anchor-free detection framework with a center-ness localization mechanism. Experiments on PestNet-AS show that our ASP-Det could serve as a strong baseline for the ASPD task.

TD-Det: A Tiny Size Dense Aphid Detection Network under In-Field Environment.

It is well recognized that aphid infestation severely reduces crop yield and further leads to significant economic loss. Therefore, accurately and efficiently detecting aphids is of vital importance in pest management. However, most existing detection methods suffer from unsatisfactory performance without fully considering the aphid characteristics, including tiny size, dense distribution, and multi-viewpoint data quality. In addition, existing clustered tiny-sized pest detection methods improve performance at the cost of time and do not meet the real-time requirements. To address the aforementioned issues, we propose a robust aphid detection method with two customized core designs: a Transformer feature pyramid network (T-FPN) and a multi-resolution training method (MTM). To be specific, the T-FPN is employed to improve the feature extraction capability by a feature-wise Transformer module (FTM) and a channel-wise feature recalibration module (CFRM), while the MTM aims at purifying the performance and lifting the efficiency simultaneously with a coarse-to-fine training pattern. To fully demonstrate the validity of our methods, abundant experiments are conducted on a densely clustered tiny pest dataset. Our method can achieve an average recall of 46.1% and an average precision of 74.2%, which outperforms other state-of-the-art methods, including ATSS, Cascade R-CNN, FCOS, FoveaBox, and CRA-Net. The efficiency comparison shows that our method can achieve the fastest training speed and obtain 0.045 s per image testing time, meeting the real-time detection. In general, our TD-Det can accurately and efficiently detect in-field aphids and lays a solid foundation for automated aphid detection and ranking.

Engineering CAR T cells for enhanced efficacy and safety.

Despite its success in treating hematologic malignancies, chimeric antigen receptor (CAR) T cell therapy faces two major challenges which hinder its broader applications: the limited effectiveness against solid tumors and the nonspecific toxicities. To address these concerns, researchers have used synthetic biology approaches to develop optimization strategies. In this review, we discuss recent improvements on the CAR and other non-CAR molecules aimed to enhance CAR T cell efficacy and safety. We also highlight the development of different types of inducible CAR T cells that can be controlled by environmental cues and/or external stimuli. These advancements are bringing CAR T therapy one step closer to safer and wider applications, especially for solid tumors.

A wheat spike detection method based on Transformer.

Wheat spike detection has important research significance for production estimation and crop field management. With the development of deep learning-based algorithms, researchers tend to solve the detection task by convolutional neural networks (CNNs). However, traditional CNNs equip with the inductive bias of locality and scale-invariance, which makes it hard to extract global and long-range dependency. In this paper, we propose a Transformer-based network named Multi-Window Swin Transformer (MW-Swin Transformer). Technically, MW-Swin Transformer introduces the ability of feature pyramid network to extract multi-scale features and inherits the characteristic of Swin Transformer that performs self-attention mechanism by window strategy. Moreover, bounding box regression is a crucial step in detection. We propose a Wheat Intersection over Union loss by incorporating the Euclidean distance, area overlapping, and aspect ratio, thereby leading to better detection accuracy. We merge the proposed network and regression loss into a popular detection architecture, fully convolutional one-stage object detection, and name the unified model WheatFormer. Finally, we construct a wheat spike detection dataset (WSD-2022) to evaluate the performance of the proposed methods. The experimental results show that the proposed network outperforms those state-of-the-art algorithms with 0.459 mAP (mean average precision) and 0.918 AP50. It has been proved that our Transformer-based method is effective to handle wheat spike detection under complex field conditions.

Integrated Analysis Reveals the Characteristics and Effects of SARS-CoV-2 Maternal-Fetal Transmission.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has caused a pandemic of coronavirus disease 2019 (COVID-19) and is threatening global health. SARS-CoV-2 spreads by air with a transmission rate of up to 15%, but the probability of its maternal-fetal transmission through the placenta is reported to be low at around 3.28%. However, it is still unclear that which tissues and developmental periods hold higher risks and what the underlying molecular mechanisms are. We conducted an integrated analysis of large-scale transcriptome and single-cell sequencing data to investigate the key factors that affect SARS-CoV-2 maternal-fetal transmission as well as the characteristics and effects of them. Our results showed that the abundance of cytomegalovirus (CMV) and Zika virus (ZIKV) infection-associated factors in the placenta were higher than their primarily infected tissues, while the expression levels of SARS-CoV-2 binding receptor angiotensin-converting enzyme II (ACE2) were similar between lung and placenta. By contrast, an important SARS-CoV-2 infection-associated factor, type II transmembrane serine protease (TMPRSS2), was poorly expressed in placenta. Further scRNA-Seq analysis revealed that ACE2 and TMPRSS2 were co-expressed in very few trophoblastic cells. Interestingly, during the embryonic development stages, the abundance of ACE2 and TMPRSS2 was much higher in multiple embryonic tissues than in the placenta. Based on our present analysis, the intestine in 20th week of embryonic development was at a high risk of SARS-CoV-2 infection. Additionally, we found that during the fetal development, ACE2 and TMPRSS2 were enriched in pathogen infection-associated pathways and may involve in the biological processes related to T-cell activation. In conclusion, our present study suggests that though the placenta provides a good physical barrier against SARS-CoV-2 infection for healthy fetal development, multiple embryonic tissues are under risks of the virus infection, which may be adversely affected once infected prenatally. Therefore, it is necessary to enhance maternal care to prevent the potential impact and harm of SARS-CoV-2 maternal-fetal transmission.

SARS-CoV-2 causes a significant stress response mediated by small RNAs in the blood of COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a serious impact on the world. In this study, small RNAs from the blood of COVID-19 patients with moderate or severe symptoms were extracted for high-throughput sequencing and analysis. Interestingly, the levels of a special group of tRNA-derived small RNAs (tsRNAs) were found to be dramatically upregulated after SARS-CoV-2 infection, particularly in coronavirus disease 2019 (COVID-19) patients with severe symptoms. In particular, the 3'CCA tsRNAs from tRNA-Gly were highly consistent with the inflammation indicator C-reactive protein (CRP). In addition, we found that the majority of significantly changed microRNAs (miRNAs) were associated with endoplasmic reticulum (ER)/unfolded protein response (UPR) sensors, which may lead to the induction of proinflammatory cytokine and immune responses. This study found that SARS-CoV-2 infection caused significant changes in the levels of stress-associated small RNAs in patient blood and their potential functions. Our research revealed that the cells of COVID-19 patients undergo tremendous stress and respond, which can be reflected or regulated by small non-coding RNA (sncRNAs), thus providing potential thought for therapeutic intervention in COVID-19 by modulating small RNA levels or activities.

Engineering inducible biomolecular assemblies for genome imaging and manipulation in living cells.

Genome architecture and organization play critical roles in cell life. However, it remains largely unknown how genomic loci are dynamically coordinated to regulate gene expression and determine cell fate at the single cell level. We have developed an inducible system which allows Simultaneous Imaging and Manipulation of genomic loci by Biomolecular Assemblies (SIMBA) in living cells. In SIMBA, the human heterochromatin protein 1α (HP1α) is fused to mCherry and FRB, which can be induced to form biomolecular assemblies (BAs) with FKBP-scFv, guided to specific genomic loci by a nuclease-defective Cas9 (dCas9) or a transcriptional factor (TF) carrying tandem repeats of SunTag. The induced BAs can not only enhance the imaging signals at target genomic loci using a single sgRNA, either at repetitive or non-repetitive sequences, but also recruit epigenetic modulators such as histone methyltransferase SUV39H1 to locally repress transcription. As such, SIMBA can be applied to simultaneously visualize and manipulate, in principle, any genomic locus with controllable timing in living cells.