Reactivation of Dormant Relay Pathways in Injured Spinal Cord by KCC2 Manipulations.

Many human spinal cord injuries are anatomically incomplete but exhibit complete paralysis. It is unknown why spared axons fail to mediate functional recovery in these cases. To investigate this, we undertook a small-molecule screen in mice with staggered bilateral hemisections in which the lumbar spinal cord is deprived of all direct brain-derived innervation, but dormant relay circuits remain. We discovered that a KCC2 agonist restored stepping ability, which could be mimicked by selective expression of KCC2, or hyperpolarizing DREADDs, in the inhibitory interneurons between and around the staggered spinal lesions. Mechanistically, these treatments transformed this injury-induced dysfunctional spinal circuit to a functional state, facilitating the relay of brain-derived commands toward the lumbar spinal cord. Thus, our results identify spinal inhibitory interneurons as a roadblock limiting the integration of descending inputs into relay circuits after injury and suggest KCC2 agonists as promising treatments for promoting functional recovery after spinal cord injury.

Deconstruction of Corticospinal Circuits for Goal-Directed Motor Skills.

Corticospinal neurons (CSNs) represent the direct cortical outputs to the spinal cord and play important roles in motor control across different species. However, their organizational principle remains unclear. By using a retrograde labeling system, we defined the requirement of CSNs in the execution of a skilled forelimb food-pellet retrieval task in mice. In vivo imaging of CSN activity during performance revealed the sequential activation of topographically ordered functional ensembles with moderate local mixing. Region-specific manipulations indicate that CSNs from caudal or rostral forelimb area control reaching or grasping, respectively, and both are required in the transitional pronation step. These region-specific CSNs terminate in different spinal levels and locations, therefore preferentially connecting with the premotor neurons of muscles engaged in different steps of the task. Together, our findings suggest that spatially defined groups of CSNs encode different movement modules, providing a logic for parallel-ordered corticospinal circuits to orchestrate multistep motor skills.

FACS-based genome-wide CRISPR screens define key regulators of DNA damage signaling pathways.

DNA damage-activated signaling pathways are critical for coordinating multiple cellular processes, which must be tightly regulated to maintain genome stability. To provide a comprehensive and unbiased perspective of DNA damage response (DDR) signaling pathways, we performed 30 fluorescence-activated cell sorting (FACS)-based genome-wide CRISPR screens in human cell lines with antibodies recognizing distinct endogenous DNA damage signaling proteins to identify critical regulators involved in DDR. We discovered that proteasome-mediated processing is an early and prerequisite event for cells to trigger camptothecin- and etoposide-induced DDR signaling. Furthermore, we identified PRMT1 and PRMT5 as modulators that regulate ATM protein level. Moreover, we discovered that GNB1L is a key regulator of DDR signaling via its role as a co-chaperone specifically regulating PIKK proteins. Collectively, these screens offer a rich resource for further investigation of DDR, which may provide insight into strategies of targeting these DDR pathways to improve therapeutic outcomes.

The eEF2 kinase confers resistance to nutrient deprivation by blocking translation elongation.

Metabolic adaptation is essential for cell survival during nutrient deprivation. We report that eukaryotic elongation factor 2 kinase (eEF2K), which is activated by AMP-kinase (AMPK), confers cell survival under acute nutrient depletion by blocking translation elongation. Tumor cells exploit this pathway to adapt to nutrient deprivation by reactivating the AMPK-eEF2K axis. Adaptation of transformed cells to nutrient withdrawal is severely compromised in cells lacking eEF2K. Moreover, eEF2K knockdown restored sensitivity to acute nutrient deprivation in highly resistant human tumor cell lines. In vivo, overexpression of eEF2K rendered murine tumors remarkably resistant to caloric restriction. Expression of eEF2K strongly correlated with overall survival in human medulloblastoma and glioblastoma multiforme. Finally, C. elegans strains deficient in efk-1, the eEF2K ortholog, were severely compromised in their response to nutrient depletion. Our data highlight a conserved role for eEF2K in protecting cells from nutrient deprivation and in conferring tumor cell adaptation to metabolic stress. PAPERCLIP:

Author Correction: A new coronavirus associated with human respiratory disease in China.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A new coronavirus associated with human respiratory disease in China.

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health1-3. Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here 'WH-Human 1' coronavirus (and has also been referred to as '2019-nCoV'). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China5. This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.

JANUS, a spliceosome-associated protein, promotes miRNA biogenesis in Arabidopsis.

MicroRNAs (miRNAs) are important regulators of genes expression. Their levels are precisely controlled through modulating the activity of the microprocesser complex (MC). Here, we report that JANUS, a homology of the conserved U2 snRNP assembly factor in yeast and human, is required for miRNA accumulation. JANUS associates with MC components Dicer-like 1 (DCL1) and SERRATE (SE) and directly binds the stem-loop of pri-miRNAs. In a hypomorphic janus mutant, the activity of DCL1, the numbers of MC, and the interaction of primary miRNA transcript (pri-miRNAs) with MC are reduced. These data suggest that JANUS promotes the assembly and activity of MC through its interaction with MC and/or pri-miRNAs. In addition, JANUS modulates the transcription of some pri-miRNAs as it binds the promoter of pri-miRNAs and facilitates Pol II occupancy of at their promoters. Moreover, global splicing defects are detected in janus. Taken together, our study reveals a novel role of a conserved splicing factor in miRNA biogenesis.

Cooperation of local features and global representations by a dual-branch network for transcription factor binding sites prediction.

Interactions between DNA and transcription factors (TFs) play an essential role in understanding transcriptional regulation mechanisms and gene expression. Due to the large accumulation of training data and low expense, deep learning methods have shown huge potential in determining the specificity of TFs-DNA interactions. Convolutional network-based and self-attention network-based methods have been proposed for transcription factor binding sites (TFBSs) prediction. Convolutional operations are efficient to extract local features but easy to ignore global information, while self-attention mechanisms are expert in capturing long-distance dependencies but difficult to pay attention to local feature details. To discover comprehensive features for a given sequence as far as possible, we propose a Dual-branch model combining Self-Attention and Convolution, dubbed as DSAC, which fuses local features and global representations in an interactive way. In terms of features, convolution and self-attention contribute to feature extraction collaboratively, enhancing the representation learning. In terms of structure, a lightweight but efficient architecture of network is designed for the prediction, in particular, the dual-branch structure makes the convolution and the self-attention mechanism can be fully utilized to improve the predictive ability of our model. The experiment results on 165 ChIP-seq datasets show that DSAC obviously outperforms other five deep learning based methods and demonstrate that our model can effectively predict TFBSs based on sequence feature alone. The source code of DSAC is available at https://github.com/YuBinLab-QUST/DSAC/.

DBGRU-SE: predicting drug-drug interactions based on double BiGRU and squeeze-and-excitation attention mechanism.

The prediction of drug-drug interactions (DDIs) is essential for the development and repositioning of new drugs. Meanwhile, they play a vital role in the fields of biopharmaceuticals, disease diagnosis and pharmacological treatment. This article proposes a new method called DBGRU-SE for predicting DDIs. Firstly, FP3 fingerprints, MACCS fingerprints, Pubchem fingerprints and 1D and 2D molecular descriptors are used to extract the feature information of the drugs. Secondly, Group Lasso is used to remove redundant features. Then, SMOTE-ENN is applied to balance the data to obtain the best feature vectors. Finally, the best feature vectors are fed into the classifier combining BiGRU and squeeze-and-excitation (SE) attention mechanisms to predict DDIs. After applying five-fold cross-validation, The ACC values of DBGRU-SE model on the two datasets are 97.51 and 94.98%, and the AUC are 99.60 and 98.85%, respectively. The results showed that DBGRU-SE had good predictive performance for drug-drug interactions.

DeepSTF: predicting transcription factor binding sites by interpretable deep neural networks combining sequence and shape.

Precise targeting of transcription factor binding sites (TFBSs) is essential to comprehending transcriptional regulatory processes and investigating cellular function. Although several deep learning algorithms have been created to predict TFBSs, the models' intrinsic mechanisms and prediction results are difficult to explain. There is still room for improvement in prediction performance. We present DeepSTF, a unique deep-learning architecture for predicting TFBSs by integrating DNA sequence and shape profiles. We use the improved transformer encoder structure for the first time in the TFBSs prediction approach. DeepSTF extracts DNA higher-order sequence features using stacked convolutional neural networks (CNNs), whereas rich DNA shape profiles are extracted by combining improved transformer encoder structure and bidirectional long short-term memory (Bi-LSTM), and, finally, the derived higher-order sequence features and representative shape profiles are integrated into the channel dimension to achieve accurate TFBSs prediction. Experiments on 165 ENCODE chromatin immunoprecipitation sequencing (ChIP-seq) datasets show that DeepSTF considerably outperforms several state-of-the-art algorithms in predicting TFBSs, and we explain the usefulness of the transformer encoder structure and the combined strategy using sequence features and shape profiles in capturing multiple dependencies and learning essential features. In addition, this paper examines the significance of DNA shape features predicting TFBSs. The source code of DeepSTF is available at https://github.com/YuBinLab-QUST/DeepSTF/.

A universal framework for single-cell multi-omics data integration with graph convolutional networks.

Single-cell omics data are growing at an unprecedented rate, whereas effective integration of them remains challenging due to different sequencing methods, quality, and expression pattern of each omics data. In this study, we propose a universal framework for the integration of single-cell multi-omics data based on graph convolutional network (GCN-SC). Among the multiple single-cell data, GCN-SC usually selects one data with the largest number of cells as the reference and the rest as the query dataset. It utilizes mutual nearest neighbor algorithm to identify cell-pairs, which provide connections between cells both within and across the reference and query datasets. A GCN algorithm further takes the mixed graph constructed from these cell-pairs to adjust count matrices from the query datasets. Finally, dimension reduction is performed by using non-negative matrix factorization before visualization. By applying GCN-SC on six datasets, we show that GCN-SC can effectively integrate sequencing data from multiple single-cell sequencing technologies, species or different omics, which outperforms the state-of-the-art methods, including Seurat, LIGER, GLUER and Pamona.

Microsporidian Nosema bombycis hijacks host vitellogenin and restructures ovariole cells for transovarial transmission.

Microsporidia are a group of obligate intracellular parasites that infect almost all animals, causing serious human diseases and major economic losses to the farming industry. Nosema bombycis is a typical microsporidium that infects multiple lepidopteran insects via fecal-oral and transovarial transmission (TOT); however, the underlying TOT processes and mechanisms remain unknown. Here, we characterized the TOT process and identified key factors enabling N. bombycis to invade the ovariole and oocyte of silkworm Bombyx mori. We found that the parasites commenced with TOT at the early pupal stage when ovarioles penetrated the ovary wall and were exposed to the hemolymph. Subsequently, the parasites in hemolymph and hemolymph cells firstly infiltrated the ovariole sheath, from where they invaded the oocyte via two routes: (I) infecting follicular cells, thereby penetrating oocytes after proliferation, and (II) infecting nurse cells, thus entering oocytes following replication. In follicle and nurse cells, the parasites restructured and built large vacuoles to deliver themselves into the oocyte. In the whole process, the parasites were coated with B. mori vitellogenin (BmVg) on their surfaces. To investigate the BmVg effects on TOT, we suppressed its expression and found a dramatic decrease of pathogen load in both ovarioles and eggs, suggesting that BmVg plays a crucial role in the TOT. Thereby, we identified the BmVg domains and parasite spore wall proteins (SWPs) mediating the interaction, and demonstrated that the von Willebrand domain (VWD) interacted with SWP12, SWP26 and SWP30, and the unknown function domain (DUF1943) bound with the SWP30. When disrupting these interactions, we found significant reductions of the pathogen load in both ovarioles and eggs, suggesting that the interplays between BmVg and SWPs were vital for the TOT. In conclusion, our study has elucidated key aspects about the microsporidian TOT and revealed the key factors for understanding the molecular mechanisms underlying this transmission.

G protein-coupled receptor-mediated signaling of immunomodulation in tumor progression.

G protein-coupled receptors (GPCRs) are essential contributors to tumor growth and metastasis due to their roles in immune cell regulation. Therefore, GPCRs are potential targets for cancer immunotherapy. Here, we discuss the current understanding of the roles of GPCRs and their signaling pathways in tumor progression from an immunocellular perspective. Additionally, we focus on the roles of GPCRs in regulating immune checkpoint proteins involved in immune evasion. Finally, we review the progress of clinical trials of GPCR-targeted drugs for cancer treatment, which may be combined with immunotherapy to improve treatment efficacy. This expanded understanding of the role of GPCRs may shed light on the mechanisms underlying tumor progression and provide a novel perspective on cancer immunotherapy.

Evaluating the role of DNA methyltransferases in trophoblast fusion and preeclampsia development: Insights from methylation-regulated genes.

The etiology of preeclampsia (PE), a complex and multifactorial condition, remains incompletely understood. DNA methylation, which is primarily regulated by three DNA methyltransferases (DNMTs), DNMT1, DNMT3A, and DNMT3B, plays a vital role in early embryonic development and trophectoderm differentiation. Yet, how DNMTs modulate trophoblast fusion and PE development remains unclear. In this study, we found that the DNMTs expression was downregulated during trophoblast cells fusion. Downregulation of DNMTs was observed during the reconstruction of the denuded syncytiotrophoblast (STB) layer of placental explants. Additionally, overexpression of DNMTs inhibited trophoblast fusion. Conversely, treatment with the DNA methylation inhibitor 5-aza-CdR decreased the expression of DNMTs and promoted trophoblast fusion. A combined analysis of DNA methylation data and gene transcriptome data obtained from the primary cytotrophoblasts (CTBs) fusion process identified 104 potential methylation-regulated differentially expressed genes (MeDEGs) with upregulated expression due to DNA demethylation, including CD59, TNFAIP3, SDC1, and CDK6. The transcription regulation region (TRR) of TNFAIP3 showed a hypomethylation with induction of 5-aza-CdR, which facilitated CREB recruitment and thereby participated in regulating trophoblast fusion. More importantly, clinical correlation analysis of PE showed that the abnormal increase in DNMTs may be involved in the development of PE. This study identified placental DNA methylation-regulated genes that may contribute to PE, offering a novel perspective on the role of epigenetics in trophoblast fusion and its implication in PE development.

RSK1 promotes mammalian axon regeneration by inducing the synthesis of regeneration-related proteins.

In contrast to the adult mammalian central nervous system (CNS), the neurons in the peripheral nervous system (PNS) can regenerate their axons. However, the underlying mechanism dictating the regeneration program after PNS injuries remains poorly understood. Combining chemical inhibitor screening with gain- and loss-of-function analyses, we identified p90 ribosomal S6 kinase 1 (RSK1) as a crucial regulator of axon regeneration in dorsal root ganglion (DRG) neurons after sciatic nerve injury (SNI). Mechanistically, RSK1 was found to preferentially regulate the synthesis of regeneration-related proteins using ribosomal profiling. Interestingly, RSK1 expression was up-regulated in injured DRG neurons, but not retinal ganglion cells (RGCs). Additionally, RSK1 overexpression enhanced phosphatase and tensin homolog (PTEN) deletion-induced axon regeneration in RGCs in the adult CNS. Our findings reveal a critical mechanism in inducing protein synthesis that promotes axon regeneration and further suggest RSK1 as a possible therapeutic target for neuronal injury repair.

UBR-1 ubiquitin ligase regulates the balance between GABAergic and glutamatergic signaling.

Excitation/inhibition (E/I) balance is carefully maintained by the nervous system. The neurotransmitter GABA has been reported to be co-released with its sole precursor, the neurotransmitter glutamate. The genetic and circuitry mechanisms to establish the balance between GABAergic and glutamatergic signaling have not been fully elucidated. Caenorhabditis elegans DVB is an excitatory GABAergic motoneuron that drives the expulsion step in the defecation motor program. We show here that in addition to UNC-47, the vesicular GABA transporter, DVB also expresses EAT-4, a vesicular glutamate transporter. UBR-1, a conserved ubiquitin ligase, regulates DVB activity by suppressing a bidirectional inhibitory glutamate signaling. Loss of UBR-1 impairs DVB Ca2+ activity and expulsion frequency. These impairments are fully compensated by the knockdown of EAT-4 in DVB. Further, glutamate-gated chloride channels GLC-3 and GLC-2/4 receive DVB's glutamate signals to inhibit DVB and enteric muscle activity, respectively. These results implicate an intrinsic cellular mechanism that promotes the inherent asymmetric neural activity. We propose that elevated glutamate in ubr-1 mutants, being the cause of the E/I shift, potentially contributes to Johanson Blizzard syndrome.

Prolonged myelin deficits contribute to neuron loss and functional impairments after ischaemic stroke.

Ischaemic stroke causes neuron loss and long-term functional deficits. Unfortunately, effective approaches to preserving neurons and promoting functional recovery remain unavailable. Oligodendrocytes, the myelinating cells in the CNS, are susceptible to oxygen and nutrition deprivation and undergo degeneration after ischaemic stroke. Technically, new oligodendrocytes and myelin can be generated by the differentiation of oligodendrocyte precursor cells (OPCs). However, myelin dynamics and their functional significance after ischaemic stroke remain poorly understood. Here, we report numerous denuded axons accompanied by decreased neuron density in sections from ischaemic stroke lesions in human brain, suggesting that neuron loss correlates with myelin deficits in these lesions. To investigate the longitudinal changes in myelin dynamics after stroke, we labelled and traced pre-existing and newly-formed myelin, respectively, using cell-specific genetic approaches. Our results indicated massive oligodendrocyte death and myelin loss 2 weeks after stroke in the transient middle cerebral artery occlusion (tMCAO) mouse model. In contrast, myelin regeneration remained insufficient 4 and 8 weeks post-stroke. Notably, neuronal loss and functional impairments worsened in aged brains, and new myelin generation was diminished. To analyse the causal relationship between remyelination and neuron survival, we manipulated myelinogenesis by conditional deletion of Olig2 (a positive regulator) or muscarinic receptor 1 (M1R, a negative regulator) in OPCs. Deleting Olig2 inhibited remyelination, reducing neuron survival and functional recovery after tMCAO. Conversely, enhancing remyelination by M1R conditional knockout or treatment with the pro-myelination drug clemastine after tMCAO preserved white matter integrity and neuronal survival, accelerating functional recovery. Together, our findings demonstrate that enhancing myelinogenesis is a promising strategy to preserve neurons and promote functional recovery after ischaemic stroke.

Age-related dysregulation of CXCL9/10 in monocytes is linked to impaired innate immune responses in a mouse model of Staphylococcus aureus osteomyelitis.

BACKGROUND: Age-associated impairments in innate immunity are believed to be a causative factor responsible for severe pathogenesis of Staphylococcus aureus (S. aureus) infection in the bone tissue. However, the basis for age-associated decline in innate immune response upon S. aureus infection remains poorly understood. RESULTS: Our transcriptional data (GEO: GSE166522) from a mouse model of S. aureus osteomyelitis show up-regulated CXCL9 and CXCL10 (CXCL9/10), which is further confirmed in vitro and in vivo by the present study. Notably, monocytes are a main source for CXCL9/10 production in bone marrow upon S. aureus challenge, but this response declines in middle-aged mice. Interestingly, conditional medium of bone marrow monocytes from middle-aged mice has a strikingly decreased effect on bactericidal functions of neutrophils and macrophages compares with that from young mice. We further show that activation of CXCL9/10-CXCR3 axis between monocytes and macrophages/neutrophils promotes the bactericidal function of the cells, whereas blocking the axis impairs such function. Importantly, treatment with either exogenous CXCL9 or CXCL10 in a middle-aged mice model enhances, while pharmacological inhibition of CXCR3 in young mice model impairs, bacterial clearance and bone marrow structure. CONCLUSIONS: These findings demonstrate that bone marrow monocytes act as a critical promotor of innate immune response via the CXLCL9/10-CXCR3 axis upon S. aureus infection, and that the increased susceptibility to S. aureus infection in skeleton in an aged host may be largely attributable to the declined induction of CXCR9/10 in monocytes.

Provable Boolean interaction recovery from tree ensemble obtained via random forests.

Random Forests (RFs) are at the cutting edge of supervised machine learning in terms of prediction performance, especially in genomics. Iterative RFs (iRFs) use a tree ensemble from iteratively modified RFs to obtain predictive and stable nonlinear or Boolean interactions of features. They have shown great promise for Boolean biological interaction discovery that is central to advancing functional genomics and precision medicine. However, theoretical studies into how tree-based methods discover Boolean feature interactions are missing. Inspired by the thresholding behavior in many biological processes, we first introduce a discontinuous nonlinear regression model, called the "Locally Spiky Sparse" (LSS) model. Specifically, the LSS model assumes that the regression function is a linear combination of piecewise constant Boolean interaction terms. Given an RF tree ensemble, we define a quantity called "Depth-Weighted Prevalence" (DWP) for a set of signed features S±. Intuitively speaking, DWP(S±) measures how frequently features in S± appear together in an RF tree ensemble. We prove that, with high probability, DWP(S±) attains a universal upper bound that does not involve any model coefficients, if and only if S± corresponds to a union of Boolean interactions under the LSS model. Consequentially, we show that a theoretically tractable version of the iRF procedure, called LSSFind, yields consistent interaction discovery under the LSS model as the sample size goes to infinity. Finally, simulation results show that LSSFind recovers the interactions under the LSS model, even when some assumptions are violated.