Circle-seq based method for eccDNA synthesis and its application as a canonical promoter independent vector for robust microRNA overexpression

Extrachromosomal circular DNA (eccDNA) has recently gained increasing attention due to its significant role in cancer and other pathophysiologic states. The majority of circular DNAs detected by Circle-seq are small-size eccDNAs with enigmatic functions. One major technical hurdle is to synthesize eccDNA for functional identification. Here, we describe CAES (Circle-seq based Artificial EccDNA Synthesis), a promising and reliable method for artificial eccDNA synthesis. Eight eccDNAs carrying different microRNA genes (eccMIR) found in gastric cancer tissues, ranging from 329 bp to 2189 bp in size, were created utilizing the CAES method. Exonuclease V and single restriction-endonuclease digestion identified the circular structure of synthetic eccDNAs. The DNA circularization efficiency afforded by CAES ranged from 15.6% to 31.1%, which was negatively correlated with the eccDNA length. In addition, we demonstrated that CAES-synthesized eccMIRs can express both miRNA-3p and - 5p molecules efficiently independent of a canonical promoter in human cell lines. Further assays proved that these eccMIRs were functional as they were able to repress the luciferase gene containing a miRNA-target sequence in the 3'UTR as well as the endogenous mRNA targets. Finally, kinetics study revealed that eccDNA exhibited a decay rate similar to the standard plasmids and linear DNA in cultured cells. Together, this study offers a rapid and convenient method for Circle-seq users to synthesize artificial eccDNAs. It also demonstrates the promising potential of eccMIR as a bacterial DNA-free vector for safe and robust miRNA overexpression in both basic research and therapeutic applications.

Core promoterome of barley embryo

Precise localization and dissection of gene promoters are key to understanding transcriptional gene regulation and to successful bioengineering applications. The core RNA polymerase II initiation machinery is highly conserved among eukaryotes, leading to a general expectation of equivalent underlying mechanisms. Still, less is known about promoters in the plant kingdom. In this study, we employed cap analysis of gene expression (CAGE) at three embryonic developmental stages in barley to accurately map, annotate, and quantify transcription initiation events. Unsupervised discovery of de novo sequence clusters grouped promoters based on characteristic initiator and position-specific core-promoter motifs. This grouping was complemented by the annotation of transcription factor binding site (TFBS) motifs. Integration with genome-wide epigenomic data sets and gene ontology (GO) enrichment analysis further delineated the chromatin environments and functional roles of genes associated with distinct promoter categories. The TATA-box presence governs all features explored, supporting the general model of two separate genomic regulatory environments. We describe the extent and implications of alternative transcription initiation events, including those that are specific to developmental stages, which can affect the protein sequence or the presence of regions that regulate translation. The generated promoterome dataset provides a valuable genomic resource for enhancing the functional annotation of the barley genome. It also offers insights into the transcriptional regulation of individual genes and presents opportunities for the informed manipulation of promoter architecture, with the aim of enhancing traits of agronomic importance.

Association of changes in expression of HDAC and SIRT genes after drug treatment with cancer cell line sensitivity to kinase inhibitors

Histone deacetylases (HDACs) and sirtuins (SIRTs) are important epigenetic regulators of cancer pathways. There is a limited understanding of how transcriptional regulation of their genes is affected by chemotherapeutic agents, and how such transcriptional changes affect tumour sensitivity to drug treatment. We investigated the concerted transcriptional response of HDAC and SIRT genes to 15 approved antitumor agents in the NCI-60 cancer cell line panel. Antitumor agents with diverse mechanisms of action induced upregulation or downregulation of multiple HDAC and SIRT genes. HDAC5 was upregulated by dasatinib and erlotinib in the majority of the cell lines. Tumour cell line sensitivity to kinase inhibitors was associated with upregulation of HDAC5, HDAC1, and several SIRT genes. We confirmed changes in HDAC and SIRT expression in independent datasets. We also experimentally validated the upregulation of HDAC5 mRNA and protein expression by dasatinib in the highly sensitive IGROV1 cell line. HDAC5 was not upregulated in the UACC-257 cell line resistant to dasatinib. The effects of cancer drug treatment on expression of HDAC and SIRT genes may influence chemosensitivity and may need to be considered during chemotherapy.

Dysfunction of synaptic endocytic trafficking in Parkinson's disease

Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum. The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive. Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease. Notably, several of these genes are linked to the synaptic vesicle recycling process, particularly the clathrin-mediated endocytosis pathway. This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease, followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a "dying back" mechanism. Recently, several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized. These models faithfully recapitulate certain Parkinson's disease-like features at the animal, circuit, and cellular levels, and exhibit defects in synaptic membrane trafficking, further supporting the findings from human genetics and clinical studies. In this review, we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins: auxilin (DNAJC6/PARK19) and synaptojanin 1 (SYNJ1/PARK20). The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect. Subsequently, we will delve into the involvement of several clathrin-mediated endocytosis-related proteins (GAK, endophilin A1, SAC2/INPP5F, synaptotagmin-11), identified as Parkinson's disease risk factors through genome-wide association studies, in Parkinson's disease pathogenesis. We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins (alpha-synuclein (PARK1/4), Parkin (PARK2), and LRRK2 (PARK8)) in synaptic endocytic trafficking. Additionally, we will discuss the emerging novel functions of these endocytic proteins in downstream membrane traffic pathways, particularly autophagy. Given that synaptic dysfunction is considered as an early event in Parkinson's disease, a deeper understanding of the cellular mechanisms underlying synaptic vesicle endocytic trafficking may unveil novel targets for early diagnosis and the development of interventional therapies for Parkinson's disease. Future research should aim to elucidate why generalized synaptic endocytic dysfunction leads to the selective degeneration of nigrostriatal dopamine neurons in Parkinson's disease.

WGBS of embryonic gonads revealed that long non-coding RNAs in the MHM region might be involved in cell autonomous sex identity and female gonadal development in chickens

DNA methylation plays a key role in sex determination and differentiation in vertebrates. However, there are few studies on DNA methylation involved in chicken gonad development, and most focused on male hypermethylated regions (MHM). It is unclear whether there are specific differentially methylated regions (DMRs) in chicken embryonic gonads regulating sex determination and differentiation. Here, the DNA methylation maps showed that the difference of DNA methylation level between sexes was much higher at embryonic day 10 (E10) than that at embryonic day 6 (E6), and the significant differentially methylated regions at both stages were mainly distributed on the Z chromosome, including MHM1 and MHM2. The results of bisulphite sequencing PCR (BSP) and qRT-PCR showed hypomethylation of female MHM and upregulation of long non-coding RNAs (lncRNAs) whose promoter in the MHM region was consistent with the sequencing results, and similar results were in brain and muscle. In female sex-reversed gonads, the methylation pattern of MHM remained unchanged, and the expression levels of the three candidate lncRNAs were significantly decreased compared with those in females, but were significantly increased compared to males. The fluorescence in situ hybridization (FISH) results also showed that these lncRNAs were highly expressed in female embryonic gonads. The results of methyltransferase inhibitor and dual-luciferase reporter assay suggest that lncRNA expression may be regulated by DNA methylation within their promoters. Therefore, we speculated that MHM may be involved in cell-autonomous sex identity in chickens, and that lncRNAs regulated by MHM may be involved in female sexual differentiation.

Within-host genomic evolution of methicillin-resistant Staphylococcus aureus in long-term carriers

Assessing the genomic evolution of Staphylococcus aureus can help us understand how the bacteria adapt to its environment. In this study, we aimed to assess the mutation rate within 144 methicillin-resistant Staphylococcus aureus (MRSA) carriers with a carriage time from 4 to 11 years, including some carriers who belonged to the same households. We found that 23 of the 144 individuals had completely different MRSA types over time and were therefore not long-term carriers of the same MRSA. From the remaining 121 individuals, we performed whole-genome sequencing (WGS) on 424 isolates and then compared these pairwise using core genome multilocus sequence typing (cgMLST) and single-nucleotide polymorphism (SNP) analyses. We found a median within-host mutation rate in long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year and 2.7 (1.8-4.2) allelic differences/genome/year, when excluding presumed recombination. Furthermore, we stratified the cohort into subgroups and found no significant difference between the median mutation rate of members of households, individuals with presumed continued exposure, e.g., from travel and persons without known continued exposure. Finally, we found that SNPs occurred at random within the genes in our cohort. KEY POINTS: • Median mutation rate within long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year • Similar median mutation rates in subgroups (households, travelers) • No hotspots for SNPs within the genome.

Predicting antimicrobial resistance in E. coli with discriminative position fused deep learning classifier

Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict E. coli AMR is a more efficient method than traditional laboratory testing. However, further improvement in the predictive performance of existing models remains challenging. In this study, we collected 1937 high-quality whole genome sequencing (WGS) data from public databases with an antimicrobial resistance phenotype and modified the existing workflow by adding an attention mechanism to enable the modified workflow to focus more on core single nucleotide polymorphisms (SNPs) that may significantly lead to the development of AMR in E. coli. While comparing the model performance before and after adding the attention mechanism, we also performed a cross-comparison among the published models using random forest (RF), support vector machine (SVM), logistic regression (LR), and convolutional neural network (CNN). Our study demonstrates that the discriminative positional colors of Chaos Game Representation (CGR) images can selectively influence and highlight genome regions without prior knowledge, enhancing prediction accuracy. Furthermore, we developed an online tool (https://github.com/tjiaa/E.coli-ML/tree/main) for assisting clinicians in the rapid prediction of the AMR phenotype of E. coli and accelerating clinical decision-making.

Sculpting nuclear envelope identity from the endoplasmic reticulum during the cell cycle

The nuclear envelope (NE) regulates nuclear functions, including transcription, nucleocytoplasmic transport, and protein quality control. While the outer membrane of the NE is directly continuous with the endoplasmic reticulum (ER), the NE has an overall distinct protein composition from the ER, which is crucial for its functions. During open mitosis in higher eukaryotes, the NE disassembles during mitotic entry and then reforms as a functional territory at the end of mitosis to reestablish nucleocytoplasmic compartmentalization. In this review, we examine the known mechanisms by which the functional NE reconstitutes from the mitotic ER in the continuous ER-NE endomembrane system during open mitosis. Furthermore, based on recent findings indicating that the NE possesses unique lipid metabolism and quality control mechanisms distinct from those of the ER, we explore the maintenance of NE identity and homeostasis during interphase. We also highlight the potential significance of membrane junctions between the ER and NE.

Non-coding 886 (nc886/vtRNA2-1), the epigenetic odd duck - implications for future studies

Non-coding 886 (nc886, vtRNA2-1) is the only human polymorphically imprinted gene, in which the methylation status is not determined by genetics. Existing literature regarding the establishment, stability and consequences of the methylation pattern, as well as the nature and function of the nc886 RNAs transcribed from the locus, are contradictory. For example, the methylation status of the locus has been reported to be stable through life and across somatic tissues, but also susceptible to environmental effects. The nature of the produced nc886 RNA(s) has been redefined multiple times, and in carcinogenesis, these RNAs have been reported to have conflicting roles. In addition, due to the bimodal methylation pattern of the nc886 locus, traditional genome-wide methylation analyses can lead to false-positive results, especially in smaller datasets. Herein, we aim to summarize the existing literature regarding nc886, discuss how the characteristics of nc886 give rise to contradictory results, as well as to reinterpret, reanalyse and, where possible, replicate the results presented in the current literature. We also introduce novel findings on how the distribution of the nc886 methylation pattern is associated with the geographical origins of the population and describe the methylation changes in a large variety of human tumours. Through the example of this one peculiar genetic locus and RNA, we aim to highlight issues in the analysis of DNA methylation and non-coding RNAs in general and offer our suggestions for what should be taken into consideration in future analyses.

Animal and plant protein intake during infancy and childhood DNA methylation: a meta-analysis in the NutriPROGRAM consortium

BACKGROUND

Higher early-life animal protein intake is associated with a higher childhood obesity risk compared to plant protein intake. Differential DNA methylation may represent an underlying mechanism.

METHODS

We analysed associations of infant animal and plant protein intakes with DNA methylation in early (2-6 years, N = 579) and late (7̄-12 years, N = 604) childhood in two studies. Study-specific robust linear regression models adjusted for relevant confounders were run, and then meta-analysed using a fixed-effects model. We also performed sex-stratified meta-analyses. Follow-up analyses included pathway analysis and eQTM look-up.

RESULTS

Infant animal protein intake was not associated with DNA methylation in early childhood, but was associated with late-childhood DNA methylation at cg21300373 (P = 4.27 × 10¯8, MARCHF1) and cg10633363 (P = 1.09 × 10¯7, HOXB9) after FDR correction. Infant plant protein intake was associated with early-childhood DNA methylation at cg25973293 (P = 2.26 × 10-7, C1orf159) and cg15407373 (P = 2.13 × 10-7, MBP) after FDR correction. There was no overlap between the findings from the animal and plant protein analyses. We did not find enriched functional pathways at either time point using CpGs associated with animal and plant protein. These CpGs were not previously associated with childhood gene expression. Sex-stratified meta-analyses showed sex-specific DNA methylation associations for both animal and plant protein intake.

CONCLUSION

Infant animal protein intake was associated with DNA methylation at two CpGs in late childhood. Infant plant protein intake was associated with DNA methylation in early childhood at two CpGs. A potential mediating role of DNA methylation at these CpGs between infant protein intake and health outcomes requires further investigation.

The role of NLRP3 inflammasome in type 2 inflammation related diseases

Type 2 inflammation related diseases, such as atopic dermatitis, asthma, and allergic rhinitis, are diverse and affect multiple systems in the human body. It is common for individuals to have multiple co-existing type 2 inflammation related diseases, which can impose a significant financial and living burden on patients. However, the exact pathogenesis of these diseases is still unclear. The NLRP3 inflammasome is a protein complex composed of the NLRP3 protein, ASC, and Caspase-1, and is activated through various mechanisms, including the NF-κB pathway, ion channels, and lysosomal damage. The NLRP3 inflammasome plays a role in the immune response to pathogens and cellular damage. Recent studies have indicated a strong correlation between the abnormal activation of NLRP3 inflammasome and the onset of type 2 inflammation. Additionally, it has been demonstrated that suppressing NLRP3 expression effectively diminishes the inflammatory response, highlighting its promising therapeutic applications. Therefore, this article reviews the role of NLRP3 inflammasome in the development and therapy of multiple type 2 inflammation related diseases.

GLP1R boosts survival, migration and invasion of endometrial cancer cells and protects against ferroptotic cell death

BACKGROUND

Despite the strong evidence concerning carcinogenic roles of glucagon-like peptide 1 receptor (GLP1R), the role of this gene in endometrial cancer (EC) remains elusive. This study investigated the properties of GLP1R on EC in vitro.

METHODS

The expression of GLP1R in EC was detected by RT-qPCR, immunohistochemistry, and western blotting. Cell viability, cell cycle, apoptosis, migration, invasion and ferroptosis were assessed through CCK-8, flow cytometry, wound healing, transwell, DCFH-DA and western blotting, respectively.

RESULTS

We found that GLP1R was up-regulated in EC than normal specimens. It had the highest expression in AN3CA cells. Cell viability, migration and invasion were significantly reduced, while cell cycle arrest and apoptosis were induced following GLP1R knockdown. The malignant biological behaviours of AN3CA cells were investigated when treated with exendin-4 (GLP1R agonist). Moreover, GLP1R lowered intracellular ROS level and expression of SLC7A11, and FTH1, but mitigated GPX4 expression in AN3CA cells.

CONCLUSION

In a word, GLP1R was up-regulated in EC and its up-regulation facilitated the proliferative and metastatic potentials, and protected cells from ferroptosis, thereby accelerating EC progression. These data emphasised the potency of GLP1R as a therapeutic agent against EC.

The genome in space and time comes of age

DNA sequencing is not enough to grasp the complexity of genome organization and function. The four-dimensional (three in space, one in time) configuration of the eukaryotic nucleus varies with cell types, during development and in diseased tissues, and has to be taken into account to decipher genome function. To study, discuss, and advance in such direction, the International Nucleome Consortium COST Action, funded by the European Union, held its concluding symposium 'The Genome in Space and Time' at the Ionian University in Corfu, Greece, on September 10-13, 2023.

Using methylation data to improve transcription factor binding prediction

Modelling the regulatory mechanisms that determine cell fate, response to external perturbation, and disease state depends on measuring many factors, a task made more difficult by the plasticity of the epigenome. Scanning the genome for the sequence patterns defined by Position Weight Matrices (PWM) can be used to estimate transcription factor (TF) binding locations. However, this approach does not incorporate information regarding the epigenetic context necessary for TF binding. CpG methylation is an epigenetic mark influenced by environmental factors that is commonly assayed in human cohort studies. We developed a framework to score inferred TF binding locations using methylation data. We intersected motif locations identified using PWMs with methylation information captured in both whole-genome bisulfite sequencing and Illumina EPIC array data for six cell lines, scored motif locations based on these data, and compared with experimental data characterizing TF binding (ChIP-seq). We found that for most TFs, binding prediction improves using methylation-based scoring compared to standard PWM-scores. We also illustrate that our approach can be generalized to infer TF binding when methylation information is only proximally available, i.e. measured for nearby CpGs that do not directly overlap with a motif location. Overall, our approach provides a framework for inferring context-specific TF binding using methylation data. Importantly, the availability of DNA methylation data in existing patient populations provides an opportunity to use our approach to understand the impact of methylation on gene regulatory processes in the context of human disease.

scQA: A dual-perspective cell type identification model for single cell transcriptome data

Single-cell RNA sequencing technologies have been pivotal in advancing the development of algorithms for clustering heterogeneous cell populations. Existing methods for utilizing scRNA-seq data to identify cell types tend to neglect the beneficial impact of dropout events and perform clustering focusing solely on quantitative perspective. Here, we introduce a novel method named scQA, notable for its ability to concurrently identify cell types and cell type-specific key genes from both qualitative and quantitative perspectives. In contrast to other methods, scQA not only identifies cell types but also extracts key genes associated with these cell types, enabling bidirectional clustering for scRNA-seq data. Through an iterative process, our approach aims to minimize the number of landmarks to approximately a dozen while maximizing the inclusion of quasi-trend-preserved genes with dropouts both qualitatively and quantitatively. It then clusters cells by employing an ingenious label propagation strategy, obviating the requirement for a predetermined number of cell types. Validated on 20 publicly available scRNA-seq datasets, scQA consistently outperforms other salient tools. Furthermore, we confirm the effectiveness and potential biological significance of the identified key genes through both external and internal validation. In conclusion, scQA emerges as a valuable tool for investigating cell heterogeneity due to its distinctive fusion of qualitative and quantitative facets, along with bidirectional clustering capabilities. Furthermore, it can be seamlessly integrated into border scRNA-seq analyses. The source codes are publicly available at https://github.com/LD-Lyndee/scQA.

Identification of common and specific fibrosis-related genes in three common chronic kidney diseases

BACKGROUND

Kidney fibrosis is the common final pathway of virtually all advanced forms of chronic kidney disease (CKD) including diabetic nephropathy (DN), IgA nephropathy (IgAN) and membranous nephropathy (MN), with complex mechanism. Comparative gene expression analysis among these types of CKD may shed light on its pathogenesis. Therefore, we conducted this study aiming at exploring the common and specific fibrosis-related genes involved in different types of CKD.

METHODS

Kidney biopsy specimens from patients with different types of CKD and normal control subjects were analyzed using the NanoString nCounter® Human Fibrosis V2 Panel. Genes differentially expressed in all fibrotic DN, IgAN and MN tissues compared to the normal controls were regarded as the common fibrosis-related genes in CKD, whereas genes exclusively differentially expressed in fibrotic DN, IgAN or MN samples were considered to be the specific genes related to fibrosis in DN, IgAN and MN respectively. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression of the selected genes.

RESULTS

Protein tyrosine phosphatase receptor type C (PTPRC), intercellular cell adhesion molecule-1 (ICAM1), vascular cell adhesion molecule-1 (VCAM1), interleukin 10 receptor alpha (IL10RA) and CC chemokine receptor 2 (CCR2) were identified as the potential common genes for kidney fibrosis in different types of CKD, while peroxisome proliferator-activated receptor alpha (PPARA), lactate oxidase (LOX), secreted phosphoprotein 1 (SPP1) were identified as the specific fibrosis-associated genes for DN, IgAN and MN respectively. qRT-PCR demonstrated that the expression levels of these selected genes were consistent with the NanoString analysis.

CONCLUSIONS

There were both commonalities and differences in the mechanisms of fibrosis in different types of CKD, the commonalities might be used as the common therapeutic targets for kidney fibrosis in CKD, while the differences might be used as the diagnostic markers for DN, IgAN and MN respectively. Inflammation was highly relevant to the pathogenesis of fibrosis. This study provides further insight into the pathophysiology and treatment of fibrotic kidney disease.

Association between circulating unsaturated fatty acid and preeclampsia: a two-sample Mendelian randomization study

OBJECTIVE

In recent years, several studies have reported an association between unsaturated fatty acids (UFAs) and the risk of developing preeclampsia; however, its exact causal effect is unclear. This study assessed the causal association between circulating UFAs and preeclampsia.

METHODS

A two-sample Mendelian randomization (MR) study using publicly available genome-wide association study (GWAS) summary data for circulating UFA s (N = 114,999) and preeclampsia (N = 118,291) was performed. Single nucleotide polymorphisms (SNPs) significantly associated with exposure was selected as instrumental variables (IVs). The inverse variance weighted (IVW) test was used as the primary method for estimating causality in MR analysis, while MR pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression methods were used to assess horizontal pleiotropy. Cochran's Q test was used to evaluate heterogeneity among SNPs, and leave-one-out sensitivity analysis was used to determine the effect of individual SNPs on the results of the MR analysis. Bonferroni correction was used as a correction for multiple corrections.

RESULTS

Two-sample MR analysis suggested that the ratio of monounsaturated fatty acids (MUFAs) to total fatty acids (OR 1.150, 95% CI 1.006-1.315, p = 0.041), the ratio of polyunsaturated fatty acids (PUFAs) to total fatty acids (OR 0.805, 95% CI 0.658-0.986, p = 0.036) and the ratio of PUFAs to MUFAs (OR 0.807, 95% CI 0.694-0.938, p = 0.005) were causally associated with preeclampsia. After Bonferroni correction, the causal association between the ratio of polyunsaturated to MUFAs and preeclampsia remained statistically different.

CONCLUSIONS

This MR analysis provides evidence for a genetic causal association between circulating UFAs and preeclampsia.

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Causal relationship between affect disorders and endometrial cancer: a Mendelian randomisation study

BACKGROUND

The aim was to assess the causal relationship between depression and anxiety disorders and endometrial cancer.

METHOD

We performed two-sample Mendelian randomisation analysis using summary statistics from genome-wide association studies to assess associations of major depressive disorder, anxiety and stress-related disorders with endometrial cancer. The genome-wide association studies(GWASs) data were derived from participants of predominantly European ancestry included in the Genome-wide Association Research Collaboration. Inverse variance-weighted, MR-Egger and weighted median MR analyses were performed, together with a range of sensitivity analyses.

RESULTS

Mendelian randomisation analysis showed no statistically significant genetic responsibility effect of anxiety and stress-related disorders on any pathological type of endometrial cancer. Only the effect of major depressive disorder under the inverse variance weighting method increasing the risk of endometrial endometrial cancer (effect 0.004 p = 0.047) and the effect of major depressive disorder under the MR-Egger method decreasing endometrial cancer of all pathology types (effect -0.691 p = 0.015) were statistically significant. Other Mendelian randomisation analyses did not show a statistically significant effect.

CONCLUSION

Major depressive disorder(MDD), anxiety and stress-related disorders(ASRD) are not genetically responsible for endometrial cancer. We consider that emotional disorders may affect endometrial cancer indirectly by affecting body mass index. This study provides us with new insights to better understand the aetiology of endometrial cancer and inform prevention strategies.

TET1 inhibits the migration and invasion of cervical cancer cells by regulating autophagy

Methylation modifications play pertinent roles in regulating gene expression and various biological processes. The silencing of the demethylase enzyme TET1 can affect the expressions of key oncogenes or tumour suppressor genes, thus contributing to tumour formation. Nonetheless, how TET1 affects the progression of cervical cancer is yet to be elucidated. In this study, we found that the expression of TET1 was significantly downregulated in cervical cancer tissues. Functionally, TET1 knockdown in cervical cancer cells can promote cell proliferation, migration, invasion, cervical xenograft tumour formation and EMT. On the contrary, its overexpression can reverse the aforementioned processes. Moreover, the autophagy level of cervical cancer cells can be enhanced after TET1 knockdown. Mechanistically, methylated DNA immunoprecipitation (MeDIP)-sequencing and MeDIP quantitative real-time PCR revealed that TET1 mediates the methylation of autophagy promoter regions. These findings suggest that TET1 affects the autophagy of cervical cancer cells by altering the methylation levels of NKRF or HIST1H2AK, but the specific mechanism needs to be investigated further.

Recent advances in the application of Mendelian randomization to chronic kidney disease

OBJECTIVE

Chronic kidney disease (CKD) is a condition influenced by both genetic and environmental factors and has been a focus of extensive research. Utilizing Mendelian randomization, researchers have begun to untangle the complex causal relationships underlying CKD. This review delves into the advances and challenges in the application of MR in the field of nephrology, shifting from a mere summary of its principles and limitations to a more nuanced exploration of its contributions to our understanding of CKD.

METHODS

Key findings from recent studies have been pivotal in reshaping our comprehension of CKD. Notably, evidence indicates that elevated testosterone levels may impair renal function, while higher sex hormone-binding globulin (SHBG) levels appear to be protective, predominantly in men. Surprisingly, variations in plasma glucose and glycated hemoglobin levels seem unaffected by genetically induced changes in the estimated glomerular filtration rate (eGFR), suggesting an independent pathway for renal function impairment.

RESULTS

Furthermore, lifestyle factors such as physical activity and socioeconomic status emerge as significant influencers of CKD risk and kidney health. The relationship between sleep duration and CKD is nuanced; short sleep duration is linked to increased risk, while long sleep duration does not exhibit a clear causal effect. Additionally, lifestyle factors, including diet, exercise, and mental wellness activities, play a crucial role in kidney health. New insights also reveal a substantial causal connection between both central and general obesity and CKD onset, while no significant links were found between genetically modified LDL cholesterol or triglyceride levels and kidney function.

CONCLUSION

This review not only presents the recent achievements of MR in CKD research but also illuminates the path forwards, underscoring critical unanswered questions and proposing future research directions in this dynamic field.

Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

Molecule interacting with CasL 1 (MICAL1) is a crucial protein involved in cell motility, axon guidance, cytoskeletal dynamics, and gene transcription. This pan-cancer study analyzed MICAL1 across 33 cancer types using bioinformatics and experiments. Dysregulated expression, diagnostic potential, and prognostic value were assessed. Associations with tumor characteristics, immune factors, and drug sensitivity were explored. Enrichment analysis revealed MICAL1's involvement in metastasis, angiogenesis, metabolism, and immune pathways. Functional experiments demonstrated its impact on renal carcinoma cells. These findings position MICAL1 as a potential biomarker and therapeutic target in specific cancers, warranting further investigation into its role in cancer pathogenesis.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Objective

Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements.

Methods

Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets.

Results

We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Study on chromatin regulation patterns of expression vectors in the PhiC31 integration site

The PhiC31 integration system allows for targeted and efficient transgene integration and expression by recognizing pseudo attP sites in mammalian cells and integrating the exogenous genes into the open chromatin regions of active chromatin. In order to investigate the regulatory patterns of efficient gene expression in the open chromatin region of PhiC31 integration, this study utilized Ubiquitous Chromatin Opening Element (UCOE) and activating RNA (saRNA) to modulate the chromatin structure in the promoter region of the PhiC31 integration vector. The study analysed the effects of DNA methylation and nucleosome occupancy changes in the integrated promoter on gene expression levels. The results showed that for the OCT4 promoter with moderate CG density, DNA methylation had a smaller impact on expression compared to changes in nucleosome positioning near the transcription start site, which was crucial for enhancing downstream gene expression. On the other hand, for the SOX2 promoter with high CG density, increased methylation in the CpG island upstream of the transcription start site played a key role in affecting high expression, but the positioning and clustering of nucleosomes also had an important influence. In conclusion, analysing the DNA methylation patterns, nucleosome positioning, and quantity distribution of different promoters can determine whether the PhiC31 integration site possesses the potential to further enhance expression or overcome transgene silencing effects by utilizing chromatin regulatory elements.

Running the gauntlet: challenges to genome integrity in spermiogenesis

Species' continuity depends on gametogenesis to produce the only cell types that can transmit genetic information across generations. Spermiogenesis, which encompasses post-meiotic, haploid stages of male gametogenesis, is a process that leads to the formation of sperm cells well-known for their motility. Spermiogenesis faces three major challenges. First, after two rounds of meiotic divisions, the genome lacks repair templates (no sister chromatids, no homologous chromosomes), making it incredibly vulnerable to any genomic insults over an extended time (typically days-weeks). Second, the sperm genome becomes transcriptionally silent, making it difficult to respond to new perturbations as spermiogenesis progresses. Third, the histone-to-protamine transition, which is essential to package the sperm genome, counterintuitively involves DNA break formation. How spermiogenesis handles these challenges remains poorly understood. In this review, we discuss each challenge and their intersection with the biology of protamines. Finally, we discuss the implication of protamines in the process of evolution.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

GETdb: A comprehensive database for genetic and evolutionary features of drug targets

The development of an innovative drug is complex and time-consuming, and the drug target identification is one of the critical steps in drug discovery process. Effective and accurate identification of drug targets can accelerate the drug development process. According to previous research, evolutionary and genetic information of genes has been found to facilitate the identification of approved drug targets. In addition, allosteric proteins have great potential as targets due to their structural diversity. However, this information that could facilitate target identification has not been collated in existing drug target databases. Here, we construct a comprehensive drug target database named Genetic and Evolutionary features of drug Targets database (GETdb, http://zhanglab.hzau.edu.cn/GETdb/page/index.jsp). This database not only integrates and standardizes data from dozens of commonly used drug and target databases, but also innovatively includes the genetic and evolutionary information of targets. Moreover, this database features an effective allosteric protein prediction model. GETdb contains approximately 4000 targets and over 29,000 drugs, and is a user-friendly database for searching, browsing and downloading data to facilitate the development of novel targets.

The transcription factor HMGB2 indirectly regulates APRIL expression and Gd-IgA1 production in patients with IgA nephropathy

BACKGROUND

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Proliferation-inducing ligand (APRIL) was identified as an important cause of glycosylation deficiency of IgA1 (Gd-IgA1), which can 'trigger' IgAN. Our previous study indicated that high migration group protein B2 (HMGB2) in peripheral blood mononuclear cells from patients with IgAN was associated with disease severity, but the underlying mechanism remains unclear.

MATERIALS AND METHODS

The location of HMGB2 was identified by immunofluorescence. qRT-PCR and Western blotting were used to measure HMGB2, HMGA1, and APRIL expression. Gd-IgA1 levels were detected by enzyme-linked immunosorbent assay (ELISA). In addition, we used DNA pull-down, protein profiling, and transcription factor prediction software to identify proteins bound to the promoter region of the APRIL gene. RNA interference and coimmunoprecipitation (Co-IP) were used to verify the relationships among HMGB2, high mobility group AT-hook protein 1 (HMGA1), and APRIL.

RESULTS

HMGB2 expression was greater in IgAN patients than in HCs and was positively associated with APRIL expression in B cells. DNA pull-down and protein profiling revealed that HMGB2 and HMGA1 bound to the promoter region of the APRIL gene. The expression levels of HMGA1, APRIL, and Gd-IgA1 were downregulated after HMGB2 knockdown. Co-IP indicated that HMGB2 binds to HMGA1. The Gd-IgA1 concentration in the supernatant was reduced after HMGA1 knockdown. HMGA1 binding sites were predicted in the promoter region of the APRIL gene.

CONCLUSION

HMGB2 expression is greater in IgAN patients than in healthy controls; it promotes APRIL expression by interacting with HMGA1, thereby inducing Gd-IgA1 overexpression and leading to IgAN.

Impact of folic acid supplementation on the epigenetic profile in healthy unfortified individuals - a randomized intervention trial

Folate is an essential mediator in one-carbon metabolism, which provides methyl groups for DNA synthesis and methylation. The availability of active methyl groups can be influenced by the uptake of folic acid. We conducted a randomized intervention trial to test the influence of folic acid supplementation on DNA methylation in an unfortified population in Germany. A total of 16 healthy male volunteers (age range 23-61 y) were randomized to receive either 400 μg (n = 9) or 800 μg (n = 7) folic acid supplements daily for 8 weeks. Infinium Human Methylation 450K BeadChip Microarrays were used to assay site-specific DNA methylation across the genome. Microarray analyses were conducted on PBL DNA. We estimated several epigenetic clocks and mean DNA methylation across all autosomal probes on the array. AgeAccel was estimated as the residual variation in each metric. In virtually all participants, both serum and red blood cell (RBC) folate increased successively throughout the trial period. Participants with a larger increase in RBC folate had a larger increase in DNAmAge AgeAccel (Spearman Rho: 0.56, p-value = 0.03). No notable changes in the methylome resulting from the folic acid supplementation emerged. In this population with adequate folate levels derived from diet, an increase in RBC folate had a modest impact on the epigenetic clock predicting chronologic age.

Extracellular vesicles from virulent P. brasiliensis induce TLR4 and dectin-1 expression in innate cells and promote enhanced Th1/Th17 response

Extracellular vesicles (EVs) are membrane-enclosed nanoparticles that transport several biomolecules and are involved in important mechanisms and functions related to the pathophysiology of fungal diseases. EVs from Paracoccidioides brasiliensis, the main causative agent of Paracoccidioidomycosis (PCM), modulate the immune response of macrophages. In this study, we assessed the EVs proteome from a virulent P. brasiliensis isolated from granulomatous lesions and compared their immunomodulatory ability with EVs isolated from the fungus before the animal passage (control EVs) when challenging macrophages and dendritic cells (DCs). Proteome showed that virulent EVs have a higher abundance of virulence factors such as GP43, protein 14-3-3, GAPDH, as well as virulence factors never described in PCM, such as aspartyl aminopeptidase and a SidJ analogue compared with control EVs. Virulent extracellular vesicles induced higher expression of TLR4 and Dectin-1 than control EVs in macrophages and dendritic cells (DCs). In opposition, a lower TLR2 expression was induced by virulent EVs. Additionally, virulent EVs induced lower expression of CD80, CD86 and TNF-α, but promoted a higher expression of IL-6 and IL-10, suggesting that EVs isolated from virulent P. brasiliensis-yeast promote a milder DCs and macrophage maturation. Herein, we showed that EVs from virulent fungi stimulated a higher frequency of Th1/Tc1, Th17, and Treg cells, which gives new insights into fungal extracellular vesicles. Taken together, our results suggest that P. brasiliensis utilizes its EVs as virulence bags that manipulate the immune system in its favour, creating a milder immune response and helping with fungal evasion from the immune system.

Vitamin C enhances co-localization of novel TET1 nuclear bodies with both Cajal and PML bodies in colorectal cancer cells

Deregulation of ten-eleven Translocation protein 1 (TET1) is commonly reported to induce imbalances in gene expression and subsequently to colorectal cancer development (CRC). On the other hand, vitamin C (VitC) improves the prognosis of colorectal cancer by reprogramming the cancer epigenome and limiting chemotherapeutic drug resistance events. In this study, we aimed to characterize TET1-specific subcellular compartments and evaluate the effect of VitC on TET1 compartmentalization in colonic tumour cells. We demonstrated that TET1 is concentrated in coarse nuclear bodies (NB) and 5-hydroxymethylcytosine (5hmC) in foci in colorectal cancer cells (HCT116, Caco-2, and HT-29). To our knowledge, this is the first report of a novel intracellular localization profile of TET1 and its demethylation marker, 5hmC, in CRC cells. Interestingly, we found that TET1-NBs frequently interacted with Cajal bodies, but not with promyelocytic leukaemia (PML) bodies. In addition, we report that VitC treatment of HCT116 cells induces 5hmC foci biogenesis and triggers 5hmC marks to form active complexes with nuclear body components, including both Cajal and PML proteins. Our data highlight novel NB-concentrating TET1 in CRC cells and demonstrate that VitC modulates TET1-NBs' interactions with other nuclear structures. These findings reveal novel TET1-dependent cellular functions and potentially provide new insights for CRC management.

A Mendelian randomization study: physical activities and chronic kidney disease

Increasing evidence has shown that physical activity is related to a lower risk of chronic kidney disease (CKD), thus indicating a potential target for prevention. However, the causality is not clear; specifically, physical activity may protect against CKD, and CKD may lead to a reduction in physical activity. Our study examined the potential bidirectional relationship between physical activity and CKD by using a genetically informed method. Genome-wide association studies from the UK Biobank baseline data were used for physical activity phenotypes and included 460,376 participants. For kidney function (estimated Glomerular Filtration Rate (eGFR) and CKD, with eGFR < 60 mL/min/1.73 m2), CKDGen Consortium data were used, which included 480,698 CKD participants of European ancestry. Mendelian randomization (MR) analysis was used to determine the causal relationship between physical activities and kidney function. Two-sample MR genetically predicted that heavy DIY (do it yourself) (e.g., weeding, lawn mowing, carpentry, and digging) decreased the risk of CKD (odds ratio [OR] = 0.287, 95% CI = 0.117-0.705, p = 0.0065) and improved the level of eGFR (β = 0.036, 95% CI = 0.005-0.067, p = 0.021). The bidirectional MR showed no reverse causality. It is worth noting that other physical activities, such as walking for pleasure, strenuous sports, light DIY (e.g., pruning and watering the lawn), and other exercises (e.g., swimming, cycling, keeping fit, and bowling), were not significantly correlated with CKD and eGFR. This study used genetic data to provide reliable and robust causal evidence that heavy physical activity (e.g., weeding, lawn mowing, carpentry, and digging) can protect kidney function and further lower the risk of CKD.

Establishment and characterization of a highly metastatic hepatocellular carcinoma cell line

The prevalence of alcohol-related hepatocellular carcinoma (HCC) has been increasing during the last decade. Cancer research requires cell lines suitable for both in vitro and in vivo assays. However, there is a lack of cell lines with a high in vivo metastatic capacity for this HCC subtype. Herein, a new HCC cell line was established, named HCC-ZJ, using cells from a patient diagnosed with alcohol-related HCC. The karyotype of HCC-ZJ was 46, XY, del (p11.2). Whole-exome sequencing identified several genetic variations in HCC-Z that occur frequently in alcohol-associated HCC, such as mutations in TERT, CTNNB1, ARID1A, CDKN2A, SMARCA2, and HGF. Cell counting kit-8 assays, colony formation assays, and Transwell assays were performed to evaluate the proliferation, migration, and sensitivity to sorafenib and lenvatinib of HCC-Z in vitro. HCC-ZJ showed a robust proliferation rate, a weak foci-forming ability, a strong migration capacity, and a moderate invasion tendency in vitro. Finally, the tumorigenicity and metastatic capacity of HCC-Z were evaluated using a subcutaneous xenograft model, an orthotopic xenograft model, and a tail-veil injection model. HCCZJ exhibited strong tumorigenicity in the subcutaneous xenograft and orthotopic tumor models. Moreover, HCC-ZJ spontaneously formed pulmonary metastases in the orthotopic tumor model. In summary, a new HCC cell line derived from a patient with alcohol-related HCC was established, which showed a high metastatic capacity and could be applied for in vitro and in vivo experiments during pre-clinical research.Highlights• An alcohol-related HCC cell line, HCC-ZJ, was established• HCC-ZJ was applicable for in vitro functional experiment and gene editing• HCC-ZJ was applicable for in vivo tumor growth and spontaneous metastasis models.

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome

Genomic imprinting is essential for mammalian growth and embryogenesis. High-throughput bisulfite sequencing accompanied with parental haplotype-specific information allows analysis of imprinted genes and imprinting control regions (ICRs) on a large scale. Currently, although several allelic methylated regions (AMRs) detection software were developed, methods for detecting imprinted AMRs is still limited. Here, we developed a SNP-independent statistical approach, AIMER, to detect imprinting-like AMRs. By using the mouse frontal cortex methylome as input, we demonstrated that AIMER performs very well in detecting known germline ICRs compared with other methods. Furthermore, we found the putative parental AMRs AIMER detected could be distinguished from sequence-dependent AMRs. Finally, we found a novel germline imprinting-like AMR using WGBS data from 17 distinct mouse tissue samples. The results indicate that AIMER is a good choice for detecting imprinting-like (parent-of-origin-dependent) AMRs. We hope this method will be helpful for future genomic imprinting studies. The Python source code for our project is now publicly available on both GitHub (https://github.com/ZhaoLab-TMU/AIMER) and Gitee (https://gitee.com/zhaolab_tmu/AIMER).

Novel dual-targeting inhibitors of NSD2 and HDAC2 for the treatment of liver cancer: structure-based virtual screening, molecular dynamics simulation, and in vitro and in vivo biological activity evaluations

Liver cancer exhibits a high degree of heterogeneity and involves intricate mechanisms. Recent research has revealed the significant role of histone lysine methylation and acetylation in the epigenetic regulation of liver cancer development. In this study, five inhibitors capable of targeting both histone lysine methyltransferase nuclear receptor-binding SET domain 2 (NSD2) and histone deacetylase 2 (HDAC2) were identified using a structure-based virtual screening approach. Notably, DT-NH-1 displayed a potent inhibition of NSD2 (IC50 = 0.08 ± 0.03 μM) and HDAC2 (IC50 = 5.24 ± 0.87 nM). DT-NH-1 also demonstrated a strong anti-proliferative activity against various liver cancer cell lines, particularly HepG2 cells, and exhibited a high level of biological safety. In an experimental xenograft model involving HepG2 cells, DT-NH-1 showed a significant reduction in tumour growth. Consequently, these findings indicate that DT-NH-1 will be a promising lead compound for the treatment of liver cancer with epigenetic dual-target inhibitors.

Nuclear pore dysfunction and disease: a complex opportunity

The separation of genetic material from bulk cytoplasm has enabled the evolution of increasingly complex organisms, allowing for the development of sophisticated forms of life. However, this complexity has created new categories of dysfunction, including those related to the movement of material between cellular compartments. In eukaryotic cells, nucleocytoplasmic trafficking is a fundamental biological process, and cumulative disruptions to nuclear integrity and nucleocytoplasmic transport are detrimental to cell survival. This is particularly true in post-mitotic neurons, where nuclear pore injury and errors to nucleocytoplasmic trafficking are strongly associated with neurodegenerative disease. In this review, we summarize the current understanding of nuclear pore biology in physiological and pathological contexts and discuss potential therapeutic approaches for addressing nuclear pore injury and dysfunctional nucleocytoplasmic transport.

Inflammatory response signature score model for predicting immunotherapy response and pan-cancer prognosis

Background

Inflammatory responses influence the outcome of immunotherapy and tumorigenesis by modulating host immunity. However, systematic inflammatory response assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers remain unexplored. Here, we investigated an inflammatory response score model to predict CIT responses and patient survival in a pan-cancer analysis.

Methods

We retrieved 12 CIT response gene expression datasets from the Gene Expression Omnibus database (GSE78220, GSE19423, GSE100797, GSE126044, GSE35640, GSE67501, GSE115821 and GSE168204), Tumor Immune Dysfunction and Exclusion database (PRJEB23709, PRJEB25780 and phs000452.v2.p1), European Genome-phenome Archive database (EGAD00001005738), and IMvigor210 cohort. The tumor samples from six cancers types: metastatic urothelial cancer, metastatic melanoma, gastric cancer, primary bladder cancer, renal cell carcinoma, and non-small cell lung cancer.We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm.

Findings

The model had high predictive accuracy in both the training and validation cohorts. During sub-group analysis, area under the curve (AUC) values of 0.82, 0.80, 0.71, 0.7, 0.67, and 0.64 were obtained for the non-small cell lung cancer, gastric cancer, metastatic urothelial cancer, primary bladder cancer, metastatic melanoma, and renal cell carcinoma cohorts, respectively. CIT response rates were higher in the high-scoring training cohort subjects (51%) than the low-scoring subjects (27%). The five-year survival rates in the high- and low score groups of the training cohorts were 62% and 21%, respectively, while those of the validation cohorts were 54% and 22%, respectively (P < 0·001 in all cases). Inflammatory response signature score derived from on-treatment tumor specimens are highly predictive of response to CIT in patients with metastatic melanoma. A significant correlation was observed between the inflammatory response scores and tumor purity. Regardless of the tumor purity, patients in the low score group had a significantly poorer prognosis than those in the high score group. Immune cell infiltration analysis indicated that in the high score cohort, tumor-infiltrating lymphocytes were significantly enriched, particularly effector and natural killer cells. Inflammatory response scores were positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may have benefited patients with high scores. Analysis of signature scores across different cancer types from The Cancer Genome Atlas revealed that the prognostic performance of inflammatory response scores for survival in patients who have not undergone immunotherapy can be affected by tumor purity. Interleukin 21 (IL21) had the highest weight in the inflammatory response model, suggesting its vital role in the prediction mode. Since the number of metastatic melanoma patients (n = 429) was relatively large among CIT cohorts, we further performed a co-culture experiment using a melanoma cell line and CD8 + T cell populations generated from peripheral blood monocytes. The results showed that IL21 therapy combined with anti-PD1 (programmed cell death 1) antibodies (trepril monoclonal antibodies) significantly enhanced the cytotoxic activity of CD8 + T cells against the melanoma cell line.

Conclusion

In this study, we developed an inflammatory response gene signature model that predicts patient survival and immunotherapy response in multiple malignancies. We further found that the predictive performance in the non-small cell lung cancer and gastric cancer group had the highest value among the six different malignancy subgroups. When compared with existing signatures, the inflammatory response gene signature scores for on-treatment samples were more robust predictors of the response to CIT in metastatic melanoma.

Human-specific epigenomic states in spermatogenesis

Infertility is becoming increasingly common, affecting one in six people globally. Half of these cases can be attributed to male factors, many driven by abnormalities in the process of sperm development. Emerging evidence from genome-wide association studies, genetic screening of patient cohorts, and animal models highlights an important genetic contribution to spermatogenic defects, but comprehensive identification and characterization of the genes critical for male fertility remain lacking. High divergence of gene regulation in spermatogenic cells across species poses challenges for delineating the genetic pathways required for human spermatogenesis using common model organisms. In this study, we leveraged post-translational histone modification and gene transcription data for 15,491 genes in four mammalian species (human, rhesus macaque, mouse, and opossum), to identify human-specific patterns of gene regulation during spermatogenesis. We combined H3K27me3 ChIP-seq, H3K4me3 ChIP-seq, and RNA-seq data to define epigenetic states for each gene at two stages of spermatogenesis, pachytene spermatocytes and round spermatids, in each species. We identified 239 genes that are uniquely active, poised, or dynamically regulated in human spermatogenic cells distinct from the other three species. While some of these genes have been implicated in reproductive functions, many more have not yet been associated with human infertility and may be candidates for further molecular and epidemiologic studies. Our analysis offers an example of the opportunities provided by evolutionary and epigenomic data for broadly screening candidate genes implicated in reproduction, which might lead to discoveries of novel genetic targets for diagnosis and management of male infertility and male contraception.

Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.

drexml: A command line tool and Python package for drug repurposing

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Resistance mechanism of Escherichia coli strains with different ampicillin resistance levels

Antibiotic resistance is an important problem that threatens medical treatment. Differences in the resistance levels of microorganisms cause great difficulties in understanding the mechanisms of antibiotic resistance. Therefore, the molecular reasons underlying the differences in the level of antibiotic resistance need to be clarified. For this purpose, genomic and transcriptomic analyses were performed on three Escherichia coli strains with varying degrees of adaptive resistance to ampicillin. Whole-genome sequencing of strains with different levels of resistance detected five mutations in strains with 10-fold resistance and two additional mutations in strains with 95-fold resistance. Overall, three of the seven mutations occurred as a single base change, while the other four occurred as insertions or deletions. While it was thought that 10-fold resistance was achieved by the effect of mutations in the ftsI, marAR, and rpoC genes, it was found that 95-fold resistance was achieved by the synergistic effect of five mutations and the ampC mutation. In addition, when the general transcriptomic profiles were examined, it was found that similar transcriptomic responses were elicited in strains with different levels of resistance. This study will improve our view of resistance mechanisms in bacteria with different levels of resistance and provide the basis for our understanding of the molecular mechanism of antibiotic resistance in ampicillin-resistant E. coli strains. KEY POINTS: •The mutation of the ampC promoter may act synergistically with other mutations and lead to higher resistance. •Similar transcriptomic responses to ampicillin are induced in strains with different levels of resistance. •Low antibiotic concentrations are the steps that allow rapid achievement of high antibiotic resistance.

Imprinted gene alterations in the kidneys of growth restricted offspring may be mediated by a long non-coding RNA

Altered epigenetic mechanisms have been previously reported in growth restricted offspring whose mothers experienced environmental insults during pregnancy in both human and rodent studies. We previously reported changes in the expression of the DNA methyltransferase Dnmt3a and the imprinted genes Cdkn1c (Cyclin-dependent kinase inhibitor 1C) and Kcnq1 (Potassium voltage-gated channel subfamily Q member 1) in the kidney tissue of growth restricted rats whose mothers had uteroplacental insufficiency induced on day 18 of gestation, at both embryonic day 20 (E20) and postnatal day 1 (PN1). To determine the mechanisms responsible for changes in the expression of these imprinted genes, we investigated DNA methylation of KvDMR1, an imprinting control region (ICR) that includes the promoter of the antisense long non-coding RNA Kcnq1ot1 (Kcnq1 opposite strand/antisense transcript 1). Kcnq1ot1 expression decreased by 51% in growth restricted offspring compared to sham at PN1. Interestingly, there was a negative correlation between Kcnq1ot1 and Kcnq1 in the E20 growth restricted group (Spearman's ρ = 0.014). No correlation was observed between Kcnq1ot1 and Cdkn1c expression in either group at any time point. Additionally, there was a 11.25% decrease in the methylation level at one CpG site within KvDMR1 ICR. This study, together with others in the literature, supports that long non-coding RNAs may mediate changes seen in tissues of growth restricted offspring.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

Co-expression of immune checkpoints in glioblastoma revealed by single-nucleus RNA sequencing and spatial transcriptomics

Glioblastoma (GBM) is one of the most malignant tumors of the central nervous system. The pattern of immune checkpoint expression in GBM remains largely unknown. We performed snRNA-Seq and spatial transcriptomic (ST) analyses on untreated GBM samples. 8 major cell types were found in both tumor and adjacent normal tissues, with variations in infiltration grade. Neoplastic cells_6 was identified in malignant cells with high expression of invasion and proliferator-related genes, and analyzed its interactions with microglia, MDM cells and T cells. Significant alterations in ligand-receptor interactions were observed, particularly between Neoplastic cells_6 and microglia, and found prominent expression of VISTA/VSIG3, suggesting a potential mechanism for evading immune system attacks. High expression of TIM-3, VISTA, PSGL-1 and VSIG-3 with similar expression patterns in GBM, may have potential as therapeutic targets. The prognostic value of VISTA expression was cross-validated in 180 glioma patients, and it was observed that patients with high VISTA expression had a poorer prognosis. In addition, multimodal cross analysis integrated SnRNA-seq and ST, revealing complex intracellular communication and mapping the GBM tumor microenvironment. This study reveals novel molecular characteristics of GBM, co-expression of immune checkpoints, and potential therapeutic targets, contributing to improving the understanding and treatment of GBM.

Techniques for assessing telomere length: A methodological review

Telomeres are located at the ends of chromosomes and have specific sequences with a distinctive structure that safeguards genes. They possess capping structures that protect chromosome ends from fusion events and ensure chromosome stability. Telomeres shorten in length during each cycle of cell division. When this length reaches a certain threshold, it can lead to genomic instability, thus being implicated in various diseases, including cancer and neurodegenerative disorders. The possibility of telomeres serving as a biomarker for aging and age-related disease is being explored, and their significance is still under study. This is because post-mitotic cells, which are mature cells that do not undergo mitosis, do not experience telomere shortening due to age. Instead, other causes, for example, exposure to oxidative stress, can directly damage the telomeres, causing genomic instability. Nonetheless, a general agreement has been established that measuring telomere length offers valuable insights and forms a crucial foundation for analyzing gene expression and epigenetic data. Numerous approaches have been developed to accurately measure telomere lengths. In this review, we summarize various methods and their advantages and limitations for assessing telomere length.

Large language models assisted multi-effect variants mining on cerebral cavernous malformation familial whole genome sequencing

Cerebral cavernous malformation (CCM) is a polygenic disease with intricate genetic interactions contributing to quantitative pathogenesis across multiple factors. The principal pathogenic genes of CCM, specifically KRIT1, CCM2, and PDCD10, have been reported, accompanied by a growing wealth of genetic data related to mutations. Furthermore, numerous other molecules associated with CCM have been unearthed. However, tackling such massive volumes of unstructured data remains challenging until the advent of advanced large language models. In this study, we developed an automated analytical pipeline specialized in single nucleotide variants (SNVs) related biomedical text analysis called BRLM. To facilitate this, BioBERT was employed to vectorize the rich information of SNVs, while a deep residue network was used to discriminate the classes of the SNVs. BRLM was initially constructed on mutations from 12 different types of TCGA cancers, achieving an accuracy exceeding 99%. It was further examined for CCM mutations in familial sequencing data analysis, highlighting an upstream master regulator gene fibroblast growth factor 1 (FGF1). With multi-omics characterization and validation in biological function, FGF1 demonstrated to play a significant role in the development of CCMs, which proved the effectiveness of our model. The BRLM web server is available at http://1.117.230.196.

Thousands of oscillating LncRNAs in the mouse testis

The long noncoding RNAs (lncRNAs) are involved in numerous fundamental biological processes, including circadian regulation. Although recent studies have revealed insights into the functions of lncRNAs, how the lncRNAs regulate circadian rhythms still requires a deeper investigation. In this study, we generate two datasets of RNA-seq profiles of the mouse (Mus musculus) testis under light-dark (LD) cycle. The first dataset included 18,613 unannotated transcripts measured at 12 time points, each with duplicate samples, under LD conditions; while the second dataset included 21,414 unannotated transcripts measured at six time points, each with three replicates, under desynchronized and control conditions. We identified 5964 testicular lncRNAs in each dataset by BLASTing these transcripts against the known mouse lncRNAs from the NONCODE database. MetaCycle analyses were performed to identify 519, 475, and 494 rhythmically expressed mouse testicular lncRNAs in the 12-time-point dataset, the six-time-point control dataset, and the six-time-point desynchronized dataset, respectively. A comparison of the expression profiles of the lncRNAs under desynchronized and control conditions revealed that 427 rhythmically expressed lncRNAs from the control condition became arrhythmic under the desynchronized condition, suggesting a possible loss of rhythmicity. In contrast, 446 arrhythmic lncRNAs from the control condition became rhythmic under the desynchronized condition, suggesting a possible gain of rhythmicity. Interestingly, 48 lncRNAs were rhythmically expressed under both desynchronized and control conditions. These oscillating lncRNAs were divided into morning lncRNAs, evening lncRNAs, and night lncRNAs based on their time-course expression patterns. We interrogated the promoter regions of these rhythmically expressed mouse testicular lncRNAs to predict their possible regulation by the E-box, D-box, or RORE promoter motifs. GO and KEGG analyses were performed to identify the possible biological functions of these rhythmically expressed mouse testicular lncRNAs. Further, we conducted conservation analyses of the rhythmically expressed mouse testicular lncRNAs with lncRNAs from humans, rats, and zebrafish, and uncovered three mouse testicular lncRNAs conserved across these four species. Finally, we computationally predicted the conserved lncRNA-encoded peptides and their 3D structures from each of the four species. Taken together, our study revealed thousands of rhythmically expressed lncRNAs in the mouse testis, setting the stage for further computational and experimental validations.

PML Nuclear bodies: the cancer connection and beyond

Promyelocytic leukemia (PML) nuclear bodies, membrane-less organelles in the nucleus, play a crucial role in cellular homeostasis. These dynamic structures result from the assembly of scaffolding PML proteins and various partners. Recent crystal structure analyses revealed essential self-interacting domains, while liquid-liquid phase separation contributes to their formation. PML bodies orchestrate post-translational modifications, particularly stress-induced SUMOylation, impacting target protein functions. Serving as hubs in multiple signaling pathways, they influence cellular processes like senescence. Dysregulation of PML expression contributes to diseases, including cancer, highlighting their significance. Therapeutically, PML bodies are promising targets, exemplified by successful acute promyelocytic leukemia treatment with arsenic trioxide and retinoic acid restoring PML bodies. Understanding their functions illuminates both normal and pathological cellular physiology, guiding potential therapies. This review explores recent advancements in PML body biogenesis, biochemical activity, and their evolving biological roles.