Neural mechanism underlying depressive-like state associated with social status loss.

Downward social mobility is a well-known mental risk factor for depression, but its neural mechanism remains elusive. Here, by forcing mice to lose against their subordinates in a non-violent social contest, we lower their social ranks stably and induce depressive-like behaviors. These rank-decline-associated depressive-like behaviors can be reversed by regaining social status. In vivo fiber photometry and single-unit electrophysiological recording show that forced loss, but not natural loss, generates negative reward prediction error (RPE). Through the lateral hypothalamus, the RPE strongly activates the brain's anti-reward center, the lateral habenula (LHb). LHb activation inhibits the medial prefrontal cortex (mPFC) that controls social competitiveness and reinforces retreats in contests. These results reveal the core neural mechanisms mutually promoting social status loss and depressive behaviors. The intertwined neuronal signaling controlling mPFC and LHb activities provides a mechanistic foundation for the crosstalk between social mobility and psychological disorder, unveiling a promising target for intervention.

TBK1 Suppresses RIPK1-Driven Apoptosis and Inflammation during Development and in Aging.

Aging is a major risk factor for both genetic and sporadic neurodegenerative disorders. However, it is unclear how aging interacts with genetic predispositions to promote neurodegeneration. Here, we investigate how partial loss of function of TBK1, a major genetic cause for amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) comorbidity, leads to age-dependent neurodegeneration. We show that TBK1 is an endogenous inhibitor of RIPK1 and the embryonic lethality of Tbk1-/- mice is dependent on RIPK1 kinase activity. In aging human brains, another endogenous RIPK1 inhibitor, TAK1, exhibits a marked decrease in expression. We show that in Tbk1+/- mice, the reduced myeloid TAK1 expression promotes all the key hallmarks of ALS/FTD, including neuroinflammation, TDP-43 aggregation, axonal degeneration, neuronal loss, and behavior deficits, which are blocked upon inhibition of RIPK1. Thus, aging facilitates RIPK1 activation by reducing TAK1 expression, which cooperates with genetic risk factors to promote the onset of ALS/FTD.

Maternal inheritance of glucose intolerance via oocyte TET3 insufficiency.

Diabetes mellitus is prevalent among women of reproductive age, and many women are left undiagnosed or untreated1. Gestational diabetes has profound and enduring effects on the long-term health of the offspring2,3. However, the link between pregestational diabetes and disease risk into adulthood in the next generation has not been sufficiently investigated. Here we show that pregestational hyperglycaemia renders the offspring more vulnerable to glucose intolerance. The expression of TET3 dioxygenase, responsible for 5-methylcytosine oxidation and DNA demethylation in the zygote4, is reduced in oocytes from a mouse model of hyperglycaemia (HG mice) and humans with diabetes. Insufficient demethylation by oocyte TET3 contributes to hypermethylation at the paternal alleles of several insulin secretion genes, including the glucokinase gene (Gck), that persists from zygote to adult, promoting impaired glucose homeostasis largely owing to the defect in glucose-stimulated insulin secretion. Consistent with these findings, mouse progenies derived from the oocytes of maternal heterozygous and homozygous Tet3 deletion display glucose intolerance and epigenetic abnormalities similar to those from the oocytes of HG mice. Moreover, the expression of exogenous Tet3 mRNA in oocytes from HG mice ameliorates the maternal effect in offspring. Thus, our observations suggest an environment-sensitive window in oocyte development that confers predisposition to glucose intolerance in the next generation through TET3 insufficiency rather than through a direct perturbation of the oocyte epigenome. This finding suggests a potential benefit of pre-conception interventions in mothers to protect the health of offspring.

The genomic origins of the Bronze Age Tarim Basin mummies.

The identity of the earliest inhabitants of Xinjiang, in the heart of Inner Asia, and the languages that they spoke have long been debated and remain contentious1. Here we present genomic data from 5 individuals dating to around 3000-2800 BC from the Dzungarian Basin and 13 individuals dating to around 2100-1700 BC from the Tarim Basin, representing the earliest yet discovered human remains from North and South Xinjiang, respectively. We find that the Early Bronze Age Dzungarian individuals exhibit a predominantly Afanasievo ancestry with an additional local contribution, and the Early-Middle Bronze Age Tarim individuals contain only a local ancestry. The Tarim individuals from the site of Xiaohe further exhibit strong evidence of milk proteins in their dental calculus, indicating a reliance on dairy pastoralism at the site since its founding. Our results do not support previous hypotheses for the origin of the Tarim mummies, who were argued to be Proto-Tocharian-speaking pastoralists descended from the Afanasievo1,2 or to have originated among the Bactria-Margiana Archaeological Complex3 or Inner Asian Mountain Corridor cultures4. Instead, although Tocharian may have been plausibly introduced to the Dzungarian Basin by Afanasievo migrants during the Early Bronze Age, we find that the earliest Tarim Basin cultures appear to have arisen from a genetically isolated local population that adopted neighbouring pastoralist and agriculturalist practices, which allowed them to settle and thrive along the shifting riverine oases of the Taklamakan Desert.

Aging and comprehensive molecular profiling in acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aging-related and heterogeneous hematopoietic malignancy. In this study, a total of 1,474 newly diagnosed AML patients with RNA sequencing data were enrolled, and targeted or whole exome sequencing data were obtained in 94% cases. The correlation of aging-related factors including age and clonal hematopoiesis (CH), gender, and genomic/transcriptomic profiles (gene fusions, genetic mutations, and gene expression networks or pathways) was systematically analyzed. Overall, AML patients aged 60 y and older showed an apparently dismal prognosis. Alongside age, the frequency of gene fusions defined in the World Health Organization classification decreased, while the positive rate of gene mutations, especially CH-related ones, increased. Additionally, the number of genetic mutations was higher in gene fusion-negative (GF-) patients than those with GF. Based on the status of CH- and myelodysplastic syndromes (MDS)-related mutations, three mutant subgroups were identified among the GF- AML cohort, namely, CH-AML, CH-MDS-AML, and other GF- AML. Notably, CH-MDS-AML demonstrated a predominance of elderly and male cases, cytopenia, and significantly adverse clinical outcomes. Besides, gene expression networks including HOXA/B, platelet factors, and inflammatory responses were most striking features associated with aging and poor prognosis in AML. Our work has thus unraveled the intricate regulatory circuitry of interactions among different age, gender, and molecular groups of AML.

Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations.

Connections between circular RNAs (circRNAs) and microRNAs (miRNAs) assume a pivotal position in the onset, evolution, diagnosis and treatment of diseases and tumors. Selecting the most potential circRNA-related miRNAs and taking advantage of them as the biological markers or drug targets could be conducive to dealing with complex human diseases through preventive strategies, diagnostic procedures and therapeutic approaches. Compared to traditional biological experiments, leveraging computational models to integrate diverse biological data in order to infer potential associations proves to be a more efficient and cost-effective approach. This paper developed a model of Convolutional Autoencoder for CircRNA-MiRNA Associations (CA-CMA) prediction. Initially, this model merged the natural language characteristics of the circRNA and miRNA sequence with the features of circRNA-miRNA interactions. Subsequently, it utilized all circRNA-miRNA pairs to construct a molecular association network, which was then fine-tuned by labeled samples to optimize the network parameters. Finally, the prediction outcome is obtained by utilizing the deep neural networks classifier. This model innovatively combines the likelihood objective that preserves the neighborhood through optimization, to learn the continuous feature representation of words and preserve the spatial information of two-dimensional signals. During the process of 5-fold cross-validation, CA-CMA exhibited exceptional performance compared to numerous prior computational approaches, as evidenced by its mean area under the receiver operating characteristic curve of 0.9138 and a minimal SD of 0.0024. Furthermore, recent literature has confirmed the accuracy of 25 out of the top 30 circRNA-miRNA pairs identified with the highest CA-CMA scores during case studies. The results of these experiments highlight the robustness and versatility of our model.

Biolinguistic graph fusion model for circRNA-miRNA association prediction.

Emerging clinical evidence suggests that sophisticated associations with circular ribonucleic acids (RNAs) (circRNAs) and microRNAs (miRNAs) are a critical regulatory factor of various pathological processes and play a critical role in most intricate human diseases. Nonetheless, the above correlations via wet experiments are error-prone and labor-intensive, and the underlying novel circRNA-miRNA association (CMA) has been validated by numerous existing computational methods that rely only on single correlation data. Considering the inadequacy of existing machine learning models, we propose a new model named BGF-CMAP, which combines the gradient boosting decision tree with natural language processing and graph embedding methods to infer associations between circRNAs and miRNAs. Specifically, BGF-CMAP extracts sequence attribute features and interaction behavior features by Word2vec and two homogeneous graph embedding algorithms, large-scale information network embedding and graph factorization, respectively. Multitudinous comprehensive experimental analysis revealed that BGF-CMAP successfully predicted the complex relationship between circRNAs and miRNAs with an accuracy of 82.90% and an area under receiver operating characteristic of 0.9075. Furthermore, 23 of the top 30 miRNA-associated circRNAs of the studies on data were confirmed in relevant experiences, showing that the BGF-CMAP model is superior to others. BGF-CMAP can serve as a helpful model to provide a scientific theoretical basis for the study of CMA prediction.

Modulating TRADD to restore cellular homeostasis and inhibit apoptosis.

Cell death in human diseases is often a consequence of disrupted cellular homeostasis. If cell death is prevented without restoring cellular homeostasis, it may lead to a persistent dysfunctional and pathological state. Although mechanisms of cell death have been thoroughly investigated1-3, it remains unclear how homeostasis can be restored after inhibition of cell death. Here we identify TRADD4-6, an adaptor protein, as a direct regulator of both cellular homeostasis and apoptosis. TRADD modulates cellular homeostasis by inhibiting K63-linked ubiquitination of beclin 1 mediated by TRAF2, cIAP1 and cIAP2, thereby reducing autophagy. TRADD deficiency inhibits RIPK1-dependent extrinsic apoptosis and proteasomal stress-induced intrinsic apoptosis. We also show that the small molecules ICCB-19 and Apt-1 bind to a pocket on the N-terminal TRAF2-binding domain of TRADD (TRADD-N), which interacts with the C-terminal domain (TRADD-C) and TRAF2 to modulate the ubiquitination of RIPK1 and beclin 1. Inhibition of TRADD by ICCB-19 or Apt-1 blocks apoptosis and restores cellular homeostasis by activating autophagy in cells with accumulated mutant tau, α-synuclein, or huntingtin. Treatment with Apt-1 restored proteostasis and inhibited cell death in a mouse model of proteinopathy induced by mutant tau(P301S). We conclude that pharmacological targeting of TRADD may represent a promising strategy for inhibiting cell death and restoring homeostasis to treat human diseases.

Gibberellins regulate masculinization through the SpGAI-SpSTM module in dioecious spinach.

The sex of dioecious plants is mainly determined by genetic factors, but it can also be converted by environmental cues such as exogenous phytohormones. Gibberellic acids (GAs) are well-known inducers of flowering and sexual development, yet the pathway of gibberellin-induced sex conversion in dioecious spinach (Spinacia oleracea L.) remains elusive. Based on sex detection before and after GA3 application using T11A and SSR19 molecular markers, we confirmed and elevated the masculinization effect of GA on a single female plant through exogenous applications of GA3, showing complete conversion and functional stamens. Silencing of GIBBERELLIC ACID INSENSITIVE (SpGAI), a single DELLA family protein that is a central GA signaling repressor, results in similar masculinization. We also show that SpGAI can physically interact with the spinach KNOX transcription factor SHOOT MERISTEMLESS (SpSTM), which is a homolog of the flower meristem identity regulator STM in Arabidopsis. The silencing of SpSTM also masculinized female flowers in spinach. Furthermore, SpSTM could directly bind the intron of SpPI to repress SpPI expression in developing female flowers. Overall, our results suggest that GA induces a female masculinization process through the SpGAI-SpSTM-SpPI regulatory module in spinach. These insights may help to clarify the molecular mechanism underlying the sex conversion system in dioecious plants while also elucidating the physiological basis for the generation of unisexual flowers so as to establish dioecy in plants.

Deciphering PDH1's role in mung bean domestication: a genomic perspective on pod dehiscence.

Mung bean (Vigna radiata) stands as a crucial legume crop in Asia, contributing to food security. However, our understanding of the underlying genetic foundation governing domesticated agronomic traits, especially those linked to pod architecture, remains largely unexplored. In this study, we delved into the genomic divergence between wild and domesticated mung bean varieties, leveraging germplasm obtained from diverse sources. Our findings unveiled pronounced variation in promoter regions (35%) between the two mung bean subpopulations, suggesting substantial changes in gene expression patterns during domestication. Leveraging transcriptome analysis using distinct reproductive stage pods and subpopulations, we identified candidate genes responsible for pod and seed architecture development, along with Genome-Wide Association Studies (GWAS) and Quantitative Trait Locus (QTL) analysis. Notably, our research conclusively confirmed PDH1 as a parallel domesticated gene governing pod dehiscence in legumes. This study imparts valuable insights into the genetic underpinnings of domesticated agronomic traits in mung bean, and simultaneously highlighting the parallel domestication of pivotal traits within the realm of legume crops.

Pembrolizumab or placebo with chemoradiotherapy followed by pembrolizumab or placebo for newly diagnosed, high-risk, locally advanced cervical cancer (ENGOT-cx11/GOG-3047/KEYNOTE-A18): a randomised, double-blind, phase 3 clinical trial.

BACKGROUND: Pembrolizumab has shown efficacy in persistent, recurrent, or metastatic cervical cancer. The effect of chemoradiotherapy might be enhanced by immunotherapy. In this phase 3 trial, we assessed the efficacy and safety of adding pembrolizumab to chemoradiotherapy in locally advanced cervical cancer. METHODS: In this randomised, double-blind, placebo-controlled, phase 3 ENGOT-cx11/GOG-3047/KEYNOTE-A18 clinical trial, adults (age ≥18 years) at 176 medical centres in 30 countries with newly diagnosed, high-risk, locally advanced cervical cancer were randomly assigned (1:1) using an interactive voice-response system with integrated web response to receive 5 cycles of pembrolizumab (200 mg) or placebo every 3 weeks plus chemoradiotherapy, followed by 15 cycles of pembrolizumab (400 mg) or placebo every 6 weeks. Randomisation was stratified by planned external beam radiotherapy type (intensity-modulated radiotherapy or volumetric-modulated arc therapy vs non-intensity-modulated radiotherapy or non-volumetric-modulated arc therapy), cervical cancer stage at screening (International Federation of Gynecology and Obstetrics 2014 stage IB2-IIB node positive vs stage III-IVA), and planned total radiotherapy (external beam radiotherapy plus brachytherapy) dose (<70 Gy vs ≥70 Gy equivalent dose in 2 Gy fractions). Primary endpoints were progression-free survival per Response Evaluation Criteria in Solid Tumours version 1.1-by investigator or by histopathologic confirmation of suspected disease progression-and overall survival. Primary analysis was conducted in the intention-to-treat population, which included all randomly allocated participants. Safety was assessed in the as-treated population, which included all randomly allocated patients who received at least one dose of study treatment. This study is registered with ClinicalTrials.gov, NCT04221945, and is closed to new participants. FINDINGS: Between June 9, 2020, and Dec 15, 2022, 1060 participants were randomly assigned to treatment, with 529 assigned to the pembrolizumab-chemoradiotherapy group and 531 to the placebo-chemoradiotherapy group. At data cutoff (Jan 9, 2023), median follow-up was 17·9 months (IQR 11·3-22·3) in both treatment groups. Median progression-free survival was not reached in either group; rates at 24 months were 68% in the pembrolizumab-chemoradiotherapy group versus 57% in the placebo-chemoradiotherapy group. The hazard ratio (HR) for disease progression or death was 0·70 (95% CI 0·55-0·89, p=0·0020), meeting the protocol-specified primary objective. Overall survival at 24 months was 87% in the pembrolizumab-chemoradiotherapy group and 81% in the placebo-chemoradiotherapy group (information fraction 42·9%). The HR for death was 0·73 (0·49-1·07); these data have not crossed the boundary of statistical significance. Grade 3 or higher adverse event rates were 75% in the pembrolizumab-chemoradiotherapy group and 69% in the placebo-chemoradiotherapy group. INTERPRETATION: Pembrolizumab plus chemoradiotherapy significantly improved progression-free survival in patients with newly diagnosed, high-risk, locally advanced cervical cancer. FUNDING: Merck Sharp & Dohme, a subsidiary of Merck & Co (MSD).

SPRDA: a link prediction approach based on the structural perturbation to infer disease-associated Piwi-interacting RNAs.

piRNA and PIWI proteins have been confirmed for disease diagnosis and treatment as novel biomarkers due to its abnormal expression in various cancers. However, the current research is not strong enough to further clarify the functions of piRNA in cancer and its underlying mechanism. Therefore, how to provide large-scale and serious piRNA candidates for biological research has grown up to be a pressing issue. In this study, a novel computational model based on the structural perturbation method is proposed to predict potential disease-associated piRNAs, called SPRDA. Notably, SPRDA belongs to positive-unlabeled learning, which is unaffected by negative examples in contrast to previous approaches. In the 5-fold cross-validation, SPRDA shows high performance on the benchmark dataset piRDisease, with an AUC of 0.9529. Furthermore, the predictive performance of SPRDA for 10 diseases shows the robustness of the proposed method. Overall, the proposed approach can provide unique insights into the pathogenesis of the disease and will advance the field of oncology diagnosis and treatment.

A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks.

MOTIVATION: A large number of studies have shown that circular RNA (circRNA) affects biological processes by competitively binding miRNA, providing a new perspective for the diagnosis, and treatment of human diseases. Therefore, exploring the potential circRNA-miRNA interactions (CMIs) is an important and urgent task at present. Although some computational methods have been tried, their performance is limited by the incompleteness of feature extraction in sparse networks and the low computational efficiency of lengthy data. RESULTS: In this paper, we proposed JSNDCMI, which combines the multi-structure feature extraction framework and Denoising Autoencoder (DAE) to meet the challenge of CMI prediction in sparse networks. In detail, JSNDCMI integrates functional similarity and local topological structure similarity in the CMI network through the multi-structure feature extraction framework, then forces the neural network to learn the robust representation of features through DAE and finally uses the Gradient Boosting Decision Tree classifier to predict the potential CMIs. JSNDCMI produces the best performance in the 5-fold cross-validation of all data sets. In the case study, seven of the top 10 CMIs with the highest score were verified in PubMed. AVAILABILITY: The data and source code can be found at https://github.com/1axin/JSNDCMI.

N-Terminomic Changes in Neurons During Excitotoxicity Reveal Proteolytic Events Associated With Synaptic Dysfunctions and Potential Targets for Neuroprotection.

Excitotoxicity, a neuronal death process in neurological disorders such as stroke, is initiated by the overstimulation of ionotropic glutamate receptors. Although dysregulation of proteolytic signaling networks is critical for excitotoxicity, the identity of affected proteins and mechanisms by which they induce neuronal cell death remain unclear. To address this, we used quantitative N-terminomics to identify proteins modified by proteolysis in neurons undergoing excitotoxic cell death. We found that most proteolytically processed proteins in excitotoxic neurons are likely substrates of calpains, including key synaptic regulatory proteins such as CRMP2, doublecortin-like kinase I, Src tyrosine kinase and calmodulin-dependent protein kinase IIß (CaMKIIß). Critically, calpain-catalyzed proteolytic processing of these proteins generates stable truncated fragments with altered activities that potentially contribute to neuronal death by perturbing synaptic organization and function. Blocking calpain-mediated proteolysis of one of these proteins, Src, protected against neuronal loss in a rat model of neurotoxicity. Extrapolation of our N-terminomic results led to the discovery that CaMKIIα, an isoform of CaMKIIß, undergoes differential processing in mouse brains under physiological conditions and during ischemic stroke. In summary, by identifying the neuronal proteins undergoing proteolysis during excitotoxicity, our findings offer new insights into excitotoxic neuronal death mechanisms and reveal potential neuroprotective targets for neurological disorders.

Transcriptome-based molecular subtypes and differentiation hierarchies improve the classification framework of acute myeloid leukemia.

The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. Robust identification of clinically and biologically relevant molecular subtypes from nongenomic high-throughput sequencing data remains challenging. We established the largest multicenter AML cohort (n = 655) in China, with all patients subjected to RNA sequencing (RNA-Seq) and 619 (94.5%) to targeted or whole-exome sequencing (TES/WES). Based on an enhanced consensus clustering, eight stable gene expression subgroups (G1-G8) with unique clinical and biological significance were identified, including two unreported (G5 and G8) and three redefined ones (G4, G6, and G7). Apart from four well-known low-risk subgroups including PML::RARA (G1), CBFB::MYH11 (G2), RUNX1::RUNX1T1 (G3), biallelic CEBPA mutations or -like (G4), four meta-subgroups with poor outcomes were recognized. The G5 (myelodysplasia-related/-like) subgroup enriched clinical, cytogenetic and genetic features mimicking secondary AML, and hotspot mutations of IKZF1 (p.N159S) (n = 7). In contrast, most NPM1 mutations and KMT2A and NUP98 fusions clustered into G6-G8, showing high expression of HOXA/B genes and diverse differentiation stages, from hematopoietic stem/progenitor cell down to monocyte, namely HOX-primitive (G7), HOX-mixed (G8), and HOX-committed (G6). Through constructing prediction models, the eight gene expression subgroups could be reproduced in the Cancer Genome Atlas (TCGA) and Beat AML cohorts. Each subgroup was associated with distinct prognosis and drug sensitivities, supporting the clinical applicability of this transcriptome-based classification of AML. These molecular subgroups illuminate the complex molecular network of AML, which may promote systematic studies of disease pathogenesis and foster the screening of targeted agents based on omics.

SPATA2 regulates the activation of RIPK1 by modulating linear ubiquitination.

Stimulation of cells with TNFα leads to the formation of the TNF-R1 signaling complex (TNF-RSC) to mediate downstream cellular fate decision. Activation of the TNF-RSC is modulated by different types of ubiquitination and may lead to cell death, including apoptosis and necroptosis, in both RIPK1-dependent and RIPK1-independent manners. Spata2 (spermatogenesis-associated 2) is an adaptor protein recruited into the TNF-RSC to modulate the interaction between the linear ubiquitin chain assembly complex (LUBAC) and the deubiquitinase CYLD (cylindromatosis). However, the mechanism by which Spata2 regulates the activation of RIPK1 is unclear. Here, we report that Spata2-deficient cells show resistance to RIPK1-dependent apoptosis and necroptosis and are also partially protected against RIPK1-independent apoptosis. Spata2 deficiency promotes M1 ubiquitination of RIPK1 to inhibit RIPK1 kinase activity. Furthermore, we provide biochemical evidence for the USP domain of CYLD and the PUB domain of the SPATA2 complex preferentially deubiquitinating the M1 ubiquitin chain in vitro. Spata2 deficiency also promotes the activation of MKK4 and JNK and cytokine production independently of RIPK1 kinase activity. Spata2 deficiency sensitizes mice to systemic inflammatory response syndrome (SIRS) induced by TNFα, which can be suppressed by RIPK1 inhibitor Nec-1s. Thus, Spata2 can regulate inflammatory response and cell death in both RIPK1-dependent and RIPK1-independent manners.

MHESMMR: a multilevel model for predicting the regulation of miRNAs expression by small molecules.

According to the expression of miRNA in pathological processes, miRNAs can be divided into oncogenes or tumor suppressors. Prediction of the regulation relations between miRNAs and small molecules (SMs) becomes a vital goal for miRNA-target therapy. But traditional biological approaches are laborious and expensive. Thus, there is an urgent need to develop a computational model. In this study, we proposed a computational model to predict whether the regulatory relationship between miRNAs and SMs is up-regulated or down-regulated. Specifically, we first use the Large-scale Information Network Embedding (LINE) algorithm to construct the node features from the self-similarity networks, then use the General Attributed Multiplex Heterogeneous Network Embedding (GATNE) algorithm to extract the topological information from the attribute network, and finally utilize the Light Gradient Boosting Machine (LightGBM) algorithm to predict the regulatory relationship between miRNAs and SMs. In the fivefold cross-validation experiment, the average accuracies of the proposed model on the SM2miR dataset reached 79.59% and 80.37% for up-regulation pairs and down-regulation pairs, respectively. In addition, we compared our model with another published model. Moreover, in the case study for 5-FU, 7 of 10 candidate miRNAs are confirmed by related literature. Therefore, we believe that our model can promote the research of miRNA-targeted therapy.

The Zinc Finger Protein MaCCCH33-Like2 Positively Regulates Banana Fruit Ripening by Modulating Genes in Starch and Cell Wall Degradation.

As zinc finger protein transcription factors (TFs), the molecular mechanism of Cys-Cys-Cys-His (CCCH) TFs in regulating plant development, growth and stress response has been well studied. However, the roles of CCCH TFs in fruit ripening are still obscure. Herein, we report that MaCCCH33-like2 TF and its associated proteins modulate the fruit softening of 'Fenjiao' bananas. MaCCCH33-like2 interacts directly with the promoters of three genes: isoamylase2 (MaISA2), sugar transporter14-like (MaSUR14-like) and ß-d-xylosidase23 (MaXYL23), all of which are responsible for encoding proteins involved in the degradation of starch and cell wall components. Additionally, MaCCCH33-like2 forms interactions with abscisic acid-insensitive 5 (ABI5)-like and ethylene F-box protein 1 (MaEBF1), resulting in enhanced binding and activation of promoters of genes related to starch and cell wall degradation. When MaCCCH33-like2 is transiently and ectopically overexpressed in 'Fenjiao' banana and tomato fruit, it facilitates softening and ripening processes by promoting the degradation of cell wall components and starch and the production of ethylene. Conversely, the temporary silencing of MaCCCH33-like2 using virus-induced gene silencing (VIGS) inhibits softening and ripening in the 'Fenjiao' banana by suppressing ethylene synthesis, as well as starch and cell wall degradation. Furthermore, the promoter activity of MaCCCH33-like2 is regulated by MaABI5-like. Taken together, we have uncovered a novel MaCCCH33-like2/MaEBF1/MaABI5-like module that participates in fruit softening regulation in bananas.

Preclinical testing of CT1113, a novel USP28 inhibitor, for the treatment of T-cell acute lymphoblastic leukaemia.

T-cell acute lymphoblastic leukaemia (T-ALL) is a highly aggressive and heterogeneous lymphoid malignancy with poor prognosis in adult patients. Aberrant activation of the NOTCH1 signalling pathway is involved in the pathogenesis of over 60% of T-ALL cases. Ubiquitin-specific protease 28 (USP28) is a deubiquitinase known to regulate the stability of NOTCH1. Here, we report that genetic depletion of USP28 or using CT1113, a potent small molecule targeting USP28, can strongly destabilize NOTCH1 and inhibit the growth of T-ALL cells. Moreover, we show that USP28 also regulates the stability of sterol regulatory element binding protein 1 (SREBP1), which has been reported to mediate increased lipogenesis in tumour cells. As the most critical transcription factor involved in regulating lipogenesis, SREBP1 plays an important role in the metabolism of T-ALL. Therefore, USP28 may be a potential therapeutic target, and CT1113 may be a promising novel drug for T-ALL with or without mutant NOTCH1.

Genome-wide identification of the key kinesin genes during fiber and boll development in upland cotton (Gossypium hirsutum L.).

Kinesin is a kind of motor protein, which interacts with microtubule filaments and regulates cellulose synthesis. Cotton fiber is a natural model for studying the cellular development and cellulose synthesis. Therefore, a systematic research of kinesin gene family in cotton (Gossypium spp.) will be beneficial for both understanding the function of kinesin protein and assisting the fiber improvement. Here, we aimed to identify the key kinesin genes present in cotton by combining genome-wide expression profile data, association mapping, and public quantitative trait loci (QTLs) in upland cotton (G. hirsutum L.). Results showed that 159 kinesin genes, including 15 genes of the kinesin-13 gene subfamily, were identified in upland cotton; of which 157 kinesin genes can be traced back to the diploid ancestors, G. raimondii and G. arboreum. Using a combined analysis of public QTLs and genome-wide expression profile information, there were 29 QTLs co-localized together with 28 kinesin genes in upland cotton, including 10 kinesin-13 subfamily genes. Genome-wide expression profile data indicated that, among the 28 co-localized genes, seven kinesin genes were predominantly expressed in fibers or ovules. By association mapping analysis, 30 kinesin genes were significantly associated with three fiber traits, among which a kinesin-13 gene, Ghir_A11G028430, was found to be associated with both cotton boll length and lint weight, and one kinesin-7 gene, Ghir_D04G017880 (Gh_Kinesin7), was significantly associated with fiber strength. In addition, two missense mutations were identified in the motor domain of the Gh_Kinesin7 protein. Overall, the kinesin gene family seemingly plays an important role in cotton fiber and boll development. The exploited kinesin genes will be beneficial for the genetic improvement of fiber quality and yield.