Lipid nephrotoxicity mediated by HIF-1α activation accelerates tubular injury in diabetic nephropathy

This study is intended to explore the effect of hypoxia-inducible factor-1α (HIF-1α) activation on lipid accumulation in the diabetic kidney. A type 1 diabetic rat model was established by STZ intraperitoneal injection. Cobalt chloride (CoCl2) and YC-1 were used as the HIF-1α activator and antagonist, respectively. CoCl2 treatment significantly increased HIF-1α expression, accelerated lipid deposition, and accelerated tubular injury in diabetic kidneys. In vitro, CoCl2 effectively stabilized HIF-1α and increased its transportation from the cytoplasm to the nucleus, which was accompanied by significantly increased lipid accumulation in HK-2 cells. Furthermore, results obtained in vivo showed that HIF-1α protein expression in the renal tubules of diabetic rats was significantly downregulated by YC-1 treatment. Meanwhile, lipid accumulation in the tubules of the DM + YC-1 group was markedly decreased in comparison to the DM + DMSO group. Accordingly, PAS staining revealed that the pathological injury caused to the tubular epithelial cells was alleviated by YC-1 treatment. Furthermore, the blood glucose level, urine albumin creatinine ratio, and NAG creatinine ratio in the DM + YC-1 group were significantly decreased compared to the DM + DMSO group. Moreover, the protein expression levels of transforming growth factor β1 (TGF-β1) and connective tissue growth factor (CTGF) in diabetic kidneys were decreased by YC-1 treatment. Our findings demonstrate that the activation of HIF-1α contributed to interstitial injury in a rat model of diabetic nephropathy and that the underlying mechanism involved the induction of lipid accumulation.

Liver bioprinting within a novel support medium with functionalized spheroids, hepatic vein structures, and enhanced post-transplantation vascularization

Cell-laden bioprinting is a promising biofabrication strategy for regenerating bioactive transplants to address organ donor shortages. However, there has been little success in reproducing transplantable artificial organs with multiple distinctive cell types and physiologically relevant architecture. In this study, an omnidirectional printing embedded network (OPEN) is presented as a support medium for embedded 3D printing. The medium is state-of-the-art due to its one-step preparation, fast removal, and versatile ink compatibility. To test the feasibility of OPEN, exceptional primary mouse hepatocytes (PMHs) and endothelial cell line-C166, were used to print hepatospheroid-encapsulated-artificial livers (HEALs) with vein structures following predesigned anatomy-based printing paths in OPEN. PMHs self-organized into hepatocyte spheroids within the ink matrix, whereas the entire cross-linked structure remained intact for a minimum of ten days of cultivation. Cultivated HEALs maintained mature hepatic functions and marker gene expression at a higher level than conventional 2D and 3D conditions in vitro. HEALs with C166-laden vein structures promoted endogenous neovascularization in vivo compared with hepatospheroid-only liver prints within two weeks of transplantation. Collectively, the proposed platform enables the manufacture of bioactive tissues or organs resembling anatomical architecture, and has broad implications for liver function replacement in clinical applications.

Machine learning in infectious diseases: potential applications and limitations

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. It explores challenges in key areas such as outbreak prediction, pathogen identification, drug discovery, and personalized medicine. We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.

Prediction of deleterious non-synonymous SNPs of human MDC1 gene: an in silico approach

MDC1 (Mediator of DNA damage Checkpoint protein 1) functions to facilitate the localization of numerous DNA damage response (DDR) components to DNA double-strand break sites. MDC1 is an integral component in preserving genomic stability and appropriate DDR regulation. There haven't been systematic investigations of MDC1 mutations that induce cancer and genomic instability. Variations in nsSNPs have the potential to modify the protein chemistry and their function. Describing functional SNPs in disease-associated genes presents a significant conundrum for investigators, it is possible to assess potential functional SNPs before conducting larger population examinations. Multiple sequences and structure-based bioinformatics strategies were implemented in the current in-silico investigation to discern potential nsSNPs of the MDC1 genes. The nsSNPs were identified with SIFT, SNAP2, Align GVGD, PolyPhen-2, and PANTHER, and their stability was determined with MUpro. The conservation, solvent accessibility, and structural effects of the mutations were identified with ConSurf, NetSurfP-2.0, and SAAFEC-SEQ respectively. Cancer-related analysis of the nsSNPs was conducted using cBioPortal and TCGA web servers. The present study appraised five nsSNPs (P1426T, P69S, P194R, P203L, and H131Y) as probably mutilating due to their existence in highly conserved regions and propensity to deplete protein stability. The nsSNPs P194R, P203L, and H131Y were concluded as deleterious and possibly damaging from the 5 prediction tools. The functional nsSNP P194R mutation is associated with skin cutaneous melanoma while no significant records were found for other nsSNPs. The present study concludes that the highly deleterious P194R mutations can potentially induce genomic instability and contribute to various cancers' pathogenesis. Developing drugs targeting these mutations can undoubtedly be advantageous in large population-based studies, particularly in the development of precision medicine.

Biological characteristics of Muse cells derived from MenSCs and their application in acute liver injury and intracerebral hemorrhage diseases

The increasing interest in multilineage differentiating stress-enduring (Muse) cells within the field of regenerative medicine is attributed to their exceptional homing capabilities, prolonged viability in adverse conditions, and enhanced three-germ-layer differentiate ability, surpassing their parent mesenchymal stem cells. Given their abundant sources, non-invasive collection procedure, and periodic availability, human menstrual blood-derived endometrium stem cells (MenSCs) have been extensively investigated as a potential resource for stem cell-based therapies. However, there is no established modality to isolate Muse cells from MenSCs and disparity in gene expression profiles between Muse cells and MenSCs remain unknown. In this study, Muse cells were isolated from MenSCs by long-time trypsin incubation method. Muse cells expressed pluripotency markers and could realize multilineage differentiation in vitro. Compared with MenSCs, Muse cells showed enhanced homing ability and superior therapeutic efficacy in animal models of acute liver injury (ALI) and intracerebral hemorrhage (ICH). Furthermore, the RNA-seq analysis offers insights into the mechanism underlying the disparity in trypsin resistance and migration ability between Muse and MenSCs cells. This research offers a significant foundation for further exploration of cell-based therapies using MenSCs-derived Muse cells in the context of various human diseases, highlighting their promising application in the field of regenerative medicine.

The limits of prediction: Why intrinsically disordered regions challenge our understanding of antimicrobial peptides

Antimicrobial peptides (AMPs) are molecules found in most organisms, playing a vital role in innate immune defense against pathogens. Their mechanism of action involves the disruption of bacterial cell membranes, causing leakage of cellular contents and ultimately leading to cell death. While AMPs typically lack a defined structure in solution, they often assume a defined conformation when interacting with bacterial membranes. Given this structural flexibility, we investigated whether intrinsically disordered regions (IDRs) with AMP-like properties could exhibit antimicrobial activity. We tested 14 peptides from different IDRs predicted to have antimicrobial activity and found that nearly all of them did not display the anticipated effects. These peptides failed to adopt a defined secondary structure and had compromised membrane interactions, resulting in a lack of antimicrobial activity. We hypothesize that evolutionary constraints may prevent IDRs from folding, even in membrane-like environments, limiting their antimicrobial potential. Moreover, our research reveals that current antimicrobial predictors fail to accurately capture the structural features of peptides when dealing with intrinsically unstructured sequences. Hence, the results presented here may have far-reaching implications for designing and improving antimicrobial strategies and therapies against infectious diseases.

Mycobacterium tuberculosis hijacks host macrophages-derived interleukin 16 to block phagolysosome maturation for enhancing intracellular growth

The discovery of promising cytokines and clarification of their immunological mechanisms in controlling the intracellular fate of Mycobacterium tuberculosis (Mtb) are necessary to identify effective diagnostic biomarkers and therapeutic targets. To escape immune clearance, Mtb can manipulate and inhibit the normal host process of phagosome maturation. Phagosome maturation arrest by Mtb involves multiple effectors and much remains unknown about this important aspect of Mtb pathogenesis. In this study, we found that interleukin 16 (IL-16) is elevated in the serum samples of Tuberculosis (TB) patients and can serve as a specific target for treatment TB. There was a significant difference in IL-16 levels among active TB, latent TB infection (LTBI), and non-TB patients. This study first revealed that macrophages are the major source of IL-16 production in response to Mtb infection, and elucidated that IL-16 can promote Mtb intracellular survival by inhibiting phagosome maturation and suppressing the expression of Rev-erbα which can inhibit IL-10 secretion. The experiments using zebrafish larvae infected with M. marinum and mice challenged with H37Rv demonstrated that reducing IL-16 levels resulted in less severe pathology and improved survival, respectively. In conclusion, this study provided direct evidence that Mtb hijacks the host macrophages-derived interleukin 16 to enhance intracellular growth. It is suggesting the immunosuppressive role of IL-16 during Mtb infection, supporting IL-16 as a promising therapeutic target.

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Genes controlling hydrolysate toxin tolerance identified by QTL analysis of the natural Saccharomyces cerevisiae BCC39850

Lignocellulosic material can be converted to valorized products such as fuels. Pretreatment is an essential step in conversion, which is needed to increase the digestibility of the raw material for microbial fermentation. However, pretreatment generates by-products (hydrolysate toxins) that are detrimental to microbial growth. In this study, natural Saccharomyces strains isolated from habitats in Thailand were screened for their tolerance to synthetic hydrolysate toxins (synHTs). The Saccharomyces cerevisiae natural strain BCC39850 (toxin-tolerant) was crossed with the laboratory strain CEN.PK2-1C (toxin-sensitive), and quantitative trait locus (QTL) analysis was performed on the segregants using phenotypic scores of growth (OD600) and glucose consumption. VMS1, DET1, KCS1, MRH1, YOS9, SYO1, and YDR042C were identified from QTLs as candidate genes associated with the tolerance trait. CEN.PK2-1C knockouts of the VMS1, YOS9, KCS1, and MRH1 genes exhibited significantly greater hydrolysate toxin sensitivity to growth, whereas CEN.PK2-1C knock-ins with replacement of VMS1 and MRH1 genes from the BCC39850 alleles showed significant increased ethanol production titers compared with the CEN.PK2-1C parental strain in the presence of synHTs. The discovery of VMS1, YOS9, MRH1, and KCS1 genes associated with hydrolysate toxin tolerance in S. cerevisiae indicates the roles of the endoplasmic-reticulum-associated protein degradation pathway, plasma membrane protein association, and the phosphatidylinositol signaling system in this trait. KEY POINTS: • QTL analysis was conducted using a hydrolysate toxin-tolerant S. cerevisiae natural strain • Deletion of VMS1, YOS9, MRH1, and KCS1 genes associated with hydrolysate toxin-sensitivity • Replacement of VMS1 and MRH1 with natural strain alleles increased ethanol production titers in the presence of hydrolysate toxins.

Testacosides A-D, glycoglycerolipids produced by Microbacterium testaceum isolated from Tedania brasiliensis

Marine bacteria living in association with marine sponges have proven to be a reliable source of biologically active secondary metabolites. However, no studies have yet reported natural products from Microbacterium testaceum spp. We herein report the isolation of a M. testaceum strain from the sponge Tedania brasiliensis. Molecular networking analysis of bioactive pre-fractionated extracts from culture media of M. testaceum enabled the discovery of testacosides A-D. Analysis of spectroscopic data and chemical derivatizations allowed the identification of testacosides A-D as glycoglycerolipids bearing a 1-[α-glucopyranosyl-(1 → 3)-(α-mannopyranosyl)]-glycerol moiety connected to 12-methyltetradecanoic acid for testacoside A (1), 14-methylpentadecanoic acid for testacoside B (2), and 14-methylhexadecanoic acid for testacosides C (3) and D (4). The absolute configuration of the monosaccharide residues was determined by 1H-NMR analysis of the respective diastereomeric thiazolidine derivatives. This is the first report of natural products isolated from cultures of M. testaceum. KEY POINTS: • The first report of metabolites produced by Microbacterium testaceum. • 1-[α-Glucopyranosyl-(1 → 3)-(α-mannopyranosyl)]-glycerol lipids isolated and identified. • Microbacterium testaceum strain isolated from the sponge Tedania brasiliensis.

Deciphering and designing microbial communities by genome-scale metabolic modelling

Microbial communities are shaped by the complex interactions among organisms and the environment. Genome-scale metabolic models (GEMs) can provide deeper insights into the complexity and ecological properties of various microbial communities, revealing their intricate interactions. Many researchers have modified GEMs for the microbial communities based on specific needs. Thus, GEMs need to be comprehensively summarized to better understand the trends in their development. In this review, we summarized the key developments in deciphering and designing microbial communities using different GEMs. A timeline of selected highlights in GEMs indicated that this area is evolving from the single-strain level to the microbial community level. Then, we outlined a framework for constructing GEMs of microbial communities. We also summarized the models and resources of static and dynamic community-level GEMs. We focused on the role of external environmental and intracellular resources in shaping the assembly of microbial communities. Finally, we discussed the key challenges and future directions of GEMs, focusing on the integration of GEMs with quorum sensing mechanisms, microbial ecology interactions, machine learning algorithms, and automatic modeling, all of which contribute to consortia-based applications in different fields.

Inhibition of prefrontal cortex parvalbumin interneurons mitigates behavioral and physiological sequelae of chronic stress in male mice

Chronic stress leads to hypofunction of the medial prefrontal cortex (mPFC), mechanisms of which remain to be determined. Enhanced activation of GABAergic of parvalbumin (PV) expressing interneurons (INs) is thought to play a role in stress-induced prefrontal inhibition. In this study, we tested whether chemogenetic inhibition of mPFC PV INs after chronic stress can rescue chronic stress-related behavioral and physiological phenotypes. Mice underwent 2 weeks of chronic variable stress (CVS) followed by a battery of behavioral tests known to be affected by chronic stress exposure, e.g. an open field (OF), novel object recognition (NOR), tail suspension test (TST), sucrose preference test (SPT), and light dark (LD) box. Inhibitory DREADDs were actuated by 3 mg/kg CNO administered 30 min prior to each behavioral test. CVS caused hyperactivity in the OF, reduced sucrose preference in the SPT (indicative of enhanced anhedonia), and increased anxiety-like behavior in the LD box. Inhibition of PV IN after stress mitigated these effects. In addition, CVS also resulted in reduced thymus weight and body weight loss, which were also mitigated by PV IN inhibition. Our results indicate that chronic stress leads to plastic changes in PV INs that may be mitigated by chemogenetic inhibition. Our findings implicate cortical GABAergic INs as a therapeutic target in stress-related diseases.

Analysis of the spatial and morphological characteristics of oligodendrocytes from images of in vitro culture

Oligodendrocytes (OLs) are glial cells responsible for the formation of myelin sheaths in the central nervous system. The characteristic features of the oligodendrocyte lineage, ranging from proliferative and migratory oligodendrocyte progenitor cells (OPC) to myelinating mature OLs, can be observed in vitro cultures of OL lineage cells. Here, we introduce a method for analyzing the spatial distribution of OPCs, which reflects their capacity for proliferation and migration, and the morphological complexity of mature OLs, which reflects their capacity for myelin formation, from immunostaining images of in vitro OL cultures. Through the methods described, we have demonstrated the tendency for OPCs to cluster in an environment with epidermal growth factor (EGF), and the differing morphological complexity of mature OLs according to culture medium and duration of differentiation.•The proliferative and migratory characteristics of OPCs can be evaluated by analyzing their spatial distribution.•The myelin-forming capacity of mature OLs can be measured by analyzing their morphological complexity.•Image-based analyses may be a substitute for more convoluted experiments to assess OL function.

Integration of single-nucleus and exosome RNA sequencing dissected inter-cellular communication and biomarkers in pancreatic ductal adenocarcinoma

Background

Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication.

Method

We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network.

Results

We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes.

Conclusion

Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

Optimized extraction methodology for phenolic compounds in soil and plant tissues: Their implications in plant growth and gall formation

Phenolic compounds, abundant secondary metabolites in plants, profoundly influence soil ecosystems, plant growth, and interactions with herbivores. Phenolic in soil microorganisms have the potential to impact a wide range of activities in plant-soil interactions. However, the existing methods for measuring microbial activity are typically time-consuming, intricate, and expensive. In this study, we propose modifications to the method used for the extraction and quantification of various types of phenolics in soil and plant tissues. There have been substantial advancements in research aimed at extracting, identifying, and quantifying phenolic compounds in the plant and soil samples. This study discusses the use of different methodologies in the analysis of phenolic compounds. In addition, we investigated the effect of phenolics on plant growth and cues in gall-forming under environmental disturbances.•This method is the optimum way to extract phenolic from soil and microbial activity in bulk and rhizosphere soil.•It can be used on any soil type and plant tissue, metabolites extracted from living organisms.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Integrated omics analysis reveals the alteration of gut microbiota and fecal metabolites in Cervus elaphus kansuensis

The gut microbiota is the largest and most complex microecosystem in animals. It is influenced by the host's dietary habits and living environment, and its composition and diversity play irreplaceable roles in animal nutrient metabolism, immunity, and adaptation to the environment. Although the gut microbiota of red deer has been studied, the composition and function of the gut microbiota in Gansu red deer (Cervus elaphus kansuensis), an endemic subspecies of red deer in China, has not been reported. In this study, the composition and diversity of the gut microbiome and fecal metabolomics of C. elaphus kansuensis were identified and compared for the first time by using 16S rDNA sequencing, metagenomic sequencing, and LC-MS/MS. There were significant differences in gut microbiota structure and diversity between wild and farmed C. elaphus kansuensis. The 16S rDNA sequencing results showed that the genus UCRD-005 was dominant in both captive red deer (CRD) and wild red deer (WRD). Metagenomic sequencing showed similar results to those of 16S rDNA sequencing for gut microbiota in CRD and WRD at the phylum and genus levels. 16S rDNA and metagenomics sequencing data suggested that Bacteroides and Bacillus might serve as marker genera for CRD and WRD, respectively. Fecal metabolomics results showed that 520 metabolites with significant differences were detected between CRD and WRD and most differential metabolites were involved in lipid metabolism. The results suggested that large differences in gut microbiota composition and fecal metabolites between CRD and WRD, indicating that different dietary habits and living environments over time have led to the development of stable gut microbiome characteristics for CRD and WRD to meet their respective survival and reproduction needs. KEY POINTS: • Environment and food affected the gut microbiota and fecal metabolites in red deer • Genera Bacteroides and Bacillus may play important roles in CRD and WRD, respectively • Flavonoids and ascorbic acid in fecal metabolites may influence health of red deer.

Exploring metabolic effects of dipeptide feed media on CHO cell cultures by in silico model-guided flux analysis

There is a growing interest in perfusion or continuous processes to achieve higher productivity of biopharmaceuticals in mammalian cell culture, specifically Chinese hamster ovary (CHO) cells, towards advanced biomanufacturing. These intensified bioprocesses highly require concentrated feed media in order to counteract their dilution effects. However, designing such condensed media formulation poses several challenges, particularly regarding the stability and solubility of specific amino acids. To address the difficulty and complexity in relevant media development, the biopharmaceutical industry has recently suggested forming dipeptides by combining one from problematic amino acids with selected pairs to compensate for limitations. In this study, we combined one of the lead amino acids, L-tyrosine, which is known for its poor solubility in water due to its aromatic ring and hydroxyl group, with glycine as the partner, thus forming glycyl-L-tyrosine (GY) dipeptide. Subsequently, we investigated the utilization of GY dipeptide during fed-batch cultures of IgG-producing CHO cells, by changing its concentrations (0.125 × , 0.25 × , 0.5 × , 1.0 × , and 2.0 ×). Multivariate statistical analysis of culture profiles was then conducted to identify and correlate the most significant nutrients with the production, followed by in silico model-guided analysis to systematically evaluate their effects on the culture performance, and elucidate metabolic states and cellular behaviors. As such, it allowed us to explain how the cells can more efficiently utilize GY dipeptide with respect to the balance of cofactor regeneration and energy distribution for the required biomass and protein synthesis. For example, our analysis results uncovered specific amino acids (Asn and Gln) and the 0.5 × GY dipeptide in the feed medium synergistically alleviated the metabolic bottleneck, resulting in enhanced IgG titer and productivity. In the validation experiments, we tested and observed that lower levels of Asn and Gln led to decreased secretion of toxic metabolites, enhanced longevity, and elevated specific cell growth and titer. KEY POINTS: • Explored the optimal Tyr dipeptide for the enhanced CHO cell culture performance • Systematically analyzed effects of dipeptide media by model-guided approach • Uncovered synergistic metabolic utilization of amino acids with dipeptide.

Genetic variant classification by predicted protein structure: A case study on IRF6

Next-generation genome sequencing has revolutionized genetic testing, identifying numerous rare disease-associated gene variants. However, to impute pathogenicity, computational approaches remain inadequate and functional testing of gene variant is required to provide the highest level of evidence. The emergence of AlphaFold2 has transformed the field of protein structure determination, and here we outline a strategy that leverages predicted protein structure to enhance genetic variant classification. We used the gene IRF6 as a case study due to its clinical relevance, its critical role in cleft lip/palate malformation, and the availability of experimental data on the pathogenicity of IRF6 gene variants through phenotype rescue experiments in irf6-/- zebrafish. We compared results from over 30 pathogenicity prediction tools on 37 IRF6 missense variants. IRF6 lacks an experimentally derived structure, so we used predicted structures to explore associations between mutational clustering and pathogenicity. We found that among these variants, 19 of 37 were unanimously predicted as deleterious by computational tools. Comparing in silico predictions with experimental findings, 12 variants predicted as pathogenic were experimentally determined as benign. Even with the recently published AlphaMissense model, 15/18 (83%) of the predicted pathogenic variants were experimentally determined as benign. In comparison, mapping variants to the protein revealed deleterious mutation clusters around the protein binding domain, whereas N-terminal variants tend to be benign, suggesting the importance of structural information in determining pathogenicity of mutations in this gene. In conclusion, incorporating gene-specific structural features of known pathogenic/benign mutations may provide meaningful insights into pathogenicity predictions in a gene-specific manner and facilitate the interpretation of variant pathogenicity.

Cut&tag: a powerful epigenetic tool for chromatin profiling

Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, Cleavage Under Targets and Tagmentation (CUT&Tag) is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Tracing the evolution of the chikungunya virus in Argentina, 2016-2023: independent introductions and prominence of Latin American lineages

Chikungunya virus (CHIKV) has emerged as a significant public health concern due to its rapid spread and potential for causing debilitating epidemics. In Argentina, the virus has garnered attention since its introduction to the Americas in 2013, due to its growing incidence and impact in neighbouring countries. Here we present a comprehensive analysis of the spatiotemporal dynamics of CHIKV in Argentina, focusing on the evolutionary trajectory of its genetic variants. Through a combination of active surveillance, screening of historical and recent samples, and whole-genome sequencing, we traced the evolutionary history of CHIKV lineages circulating within the country. Our results reveal that two distinct genotypes circulated in Argentina: The Asian lineage during the 2016 epidemic and the ECSA lineage in 2023. This distribution reflects the dominance of particular variants across Latin America. Since 2023, the ECSA lineage has led to a surge in cases throughout the Americas, marking a significant shift. The replacement of lineages in the American region constitutes a major epidemiological event, potentially affecting the dynamics of virus transmission and the clinical outcomes in impacted populations. The spatiotemporal analysis highlights CHIKV's distribution across Argentina and underscores the significant role of human mobility, especially when considering recent epidemics in neighbouring countries such as Paraguay and Uruguay, which have facilitated the spread and introduction of the viral strain into different districts. By integrating epidemiological data with genomic insights, we elucidate the patterns of virus dissemination, highlighting key areas of transmission and potential factors contributing to its spread.

Efficacy of quercetin-like compounds from the mistletoe plant of Dendrophthoe pentandra L. Miq, as oral random blood sugar lowering treatment in diabetic rats

Background: Mistletoe is an herb that grows on duku plants (Lancium demosticum) and is known as benalu duku (BD) in Indonesia. It is predicted to have benefits such as anticancer or antiviral properties, and it is also thought to have anti-diabetic pharmacological activity. Quercetin-like compounds (QLCs) are secondary metabolites with antidiabetic activity that are expected to lower blood sugar levels in animals after oral administration.

Objective: This study aimed to analyze the ability of QLCs to reduce random blood sugar levels using experimental animals as clinical models.

Material and methods: The research method used was exploratory, which used a before-after test model, and observations were made on the random blood sugar levels after treatment. Secondary metabolites were extracted from BD leaves, which were then screened. Diabetes was induced in 30 rats (Rattus norvegicus) by the administration of streptozotocin at 0.045 mg/g body weight daily for 2 days. The antidiabetic effects of the secondary metabolite at doses of 0.5 mg/kg body weight (twice a day) when administered orally for up to 5 days were tested in diabetic rats. The random sugar levels (mg/dL) were measured using a One Touch Ultra Plus medical device for observation of randomized blood sugar levels. Results and novelty: The results revealed that the secondary metabolite, as an analyte from the BD leaf extract, can significantly reduce random blood sugar levels.

Conclusion: The secondary metabolite extracted from BD, could be used to treat diabetes in rats.

Qing Hua Chang Yin ameliorates chronic colitis in mice by inhibiting PERK-ATF4-CHOP pathway of ER stress and the NF-κB signalling pathway

CONTEXT

Ulcerative colitis has been clinically treated with Qing Hua Chang Yin (QHCY), a traditional Chinese medicine formula. However, its precise mechanisms in mitigating chronic colitis are largely uncharted.

OBJECTIVE

To elucidate the therapeutic efficiency of QHCY on chronic colitis and explore its underlying molecular mechanisms.

MATERIALS AND METHODS

A total ion chromatogram fingerprint of QHCY was analysed. Chronic colitis was induced in male C57BL/6 mice using 2% dextran sodium sulphate (DSS) over 49 days. Mice were divided into control, DSS, DSS + QHCY (0.8, 1.6 and 3.2 g/kg/d dose, respectively) and DSS + mesalazine (0.2 g/kg/d) groups (n = 6). Mice were intragastrically administered QHCY or mesalazine for 49 days. The changes of disease activity index (DAI), colon length, colon histomorphology and serum pro-inflammatory factors in mice were observed. RNA sequencing was utilized to identify the differentially expressed transcripts (DETs) in colonic tissues and the associated signalling pathways. The expression of endoplasmic reticulum (ER) stress-related protein and NF-κB signalling pathway-related proteins in colonic tissues was detected by immunohistochemistry staining.

RESULTS

Forty-seven compounds were identified in QHCY. Compared with the DSS group, QHCY significantly improved symptoms of chronic colitis like DAI increase, weight loss, colon shortening and histological damage. It notably reduced serum levels of IL-6, IL-1β and TNF-α. QHCY suppressed the activation of PERK-ATF4-CHOP pathway of ER stress and NF-κB signalling pathways in colonic tissues.

DISCUSSION AND CONCLUSIONS

The findings in this study provide novel insights into the potential of QHCY in treating chronic colitis patients.

Structural and functional prediction, evaluation, and validation in the post-sequencing era

The surge of genome sequencing data has underlined substantial genetic variants of uncertain significance (VUS). The decryption of VUS discovered by sequencing poses a major challenge in the post-sequencing era. Although experimental assays have progressed in classifying VUS, only a tiny fraction of the human genes have been explored experimentally. Thus, it is urgently needed to generate state-of-the-art functional predictors of VUS in silico. Artificial intelligence (AI) is an invaluable tool to assist in the identification of VUS with high efficiency and accuracy. An increasing number of studies indicate that AI has brought an exciting acceleration in the interpretation of VUS, and our group has already used AI to develop protein structure-based prediction models. In this review, we provide an overview of the previous research on AI-based prediction of missense variants, and elucidate the challenges and opportunities for protein structure-based variant prediction in the post-sequencing era.

An extracellular humanized IFNAR immunocompetent mouse model for analyses of human interferon alpha and subtypes

Type I interferons (IFN-Is) have key roles in immune defense and treatments for various diseases, including chronic hepatitis B virus (HBV) infection. All IFN-Is signal through a shared IFN-I heterodimeric receptor complex comprising IFN-α receptor 1 (IFNAR1) and IFNAR2 subunits, but differences in antiviral and immunomodulatory responses among IFN-I subtypes remain largely unknown. Because the IFN-IFNAR interactions are species-specific, mice exhibit weak responses to human IFN-I. To more fully characterize the actions of human IFN-α and its subtypes in vivo, a gene targeting strategy was employed to generate gene knock-in mice with extracellular-humanized IFNAR1/2 (IFNAR-hEC) in the C57BL/6N strain. IFNAR-hEC mice actively responded to human IFN-I, and endogenous mouse IFN-I signalling remained active in heterozygous mice (IfnarhEC/+). Analyses of IFNAR-hEC mice and isolated cells showed that human IFN-α2 and α14 subtypes exerted differential effect on the activation of JAK-STAT signalling and immune responses. Compared with IFN-α2, IFN-α14 induced greater activation of STAT1/2 and IFN-stimulated genes, synergistically elicited IFN-α and -γ signalling, and induced higher numbers of antigen-specific CD8+ T cells. Moreover, IFNAR-hEC mice with HBV replication displayed long-term viral suppression upon treatment with the clinically-used PEGylated hIFN-α2. These results indicate that IFNAR-hEC mice may be useful for elucidating antiviral and immunomodulatory functions of human IFN-Is and for conducting preclinical studies. A better understanding of the distinct activities of IFN-α subtypes can provide insights concerning the development of improved IFN-based therapy.

The dynamics of biofilm development and dispersal should be taken into account when quantifying biofilm via the crystal violet microtiter plate assay

The crystal violet microtiter plate biofilm assay is often used to compare the amount of biofilm formed by a mutant versus wild-type or a compound-treated biofilm versus the non-treatment control. In many of these studies the amount of biofilm is assessed only at one single time point. However, if the dynamics of biofilm development of the mutant (or compound-treated biofilm) is different than that of the wild-type (or non-treatment control), then biofilm quantification at a single time point may give misleading results. To overcome this shortcoming of the common biofilm quantification technique, we recommend to use a serial dilution-based crystal violet microtiter plate biofilm assay for easy assessment of the dynamics of biofilm development and dispersal. We demonstrate that the dilution-resolved crystal violet assay displays the dynamics of Pseudomonas aeruginosa biofilm development and dispersal as efficient as a time-resolved crystal violet assay. In addition, focusing on mutants of different parts of the c-di-GMP signaling system in P. aeruginosa, we provide an example illustrating the need to assess biofilm dynamics instead of quantifying biofilm biomass at a single time point.

Decoding phenotypic screening: A comparative analysis of image representations

Biomedical imaging techniques such as high content screening (HCS) are valuable for drug discovery, but high costs limit their use to pharmaceutical companies. To address this issue, The JUMP-CP consortium released a massive open image dataset of chemical and genetic perturbations, providing a valuable resource for deep learning research. In this work, we aim to utilize the JUMP-CP dataset to develop a universal representation model for HCS data, mainly data generated using U2OS cells and CellPainting protocol, using supervised and self-supervised learning approaches. We propose an evaluation protocol that assesses their performance on mode of action and property prediction tasks using a popular phenotypic screening dataset. Results show that the self-supervised approach that uses data from multiple consortium partners provides representation that is more robust to batch effects whilst simultaneously achieving performance on par with standard approaches. Together with other conclusions, it provides recommendations on the training strategy of a representation model for HCS images.

A novel NIR-II albumin-escaping probe for cerebral arteries and perfusion imaging in stroke mice model

In order to guide the formulation of post-stroke treatment strategy in time, it is necessary to have real-time feedback on collateral circulation and revascularization. Currently used near-infrared II (NIR-II) probes have inherent binding with endogenous albumin, resulting in significant background signals and uncontrollable pharmacokinetics. Therefore, the albumin-escaping properties of the new probe, IR-808AC, was designed, which achieved timely excretion and low background signal, enabling the short-term repeatable injection for visualization of cerebral vessels and perfusion. We further achieved continuous observation of changes in collateral vessels and perfusion during the 7-d period in middle cerebral artery occlusion mice using IR-808AC in vivo. Furthermore, using IR-808AC, we confirmed that remote ischemic conditioning could promote collateral vessels and perfusion. Finally, we evaluated the revascularization after thrombolysis on time in embolic stroke mice using IR-808AC. Overall, our study introduces a novel methodology for safe, non-invasive, and repeatable assessment of collateral circulation and revascularization in real-time that is crucial for the optimization of treatment strategies.

Node features of chromosome structure networks and their connections to genome annotation

The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.

A method for chromatin domain partitioning based on hypergraph clustering

For many years, multi-scale models of chromatin domains, such as A/B compartments, sub-compartments, topologically associated domains (TADs), sub-TADs, and loops have been popular. However, existing methods can only identify structures at a single scale and cannot partition multi-scale structures. In this paper, we proposed a method (TORNADOES) for chromatin domain partitioning based on hypergraph clustering. First, we use a density clustering algorithm to identify TADs at different scales based on Hi-C data with different resolutions. Then, by combining ChIP-seq data features and TAD results at different scales, we generate a hypergraph based on these TADs. Finally, we partition the chromatin domain structure at different scales, including A/B, A1, A2, B1, B2, and B3 based on the Laplacian matrix feature of the hypergraph. Similarity comparison experiments and ChIP-seq signal enrichment analysis are performed on the A/B region and sub-TAD levels, respectively, demonstrating that our method can identify chromatin domains with distinct features and provide a deeper understanding of the organizational patterns and functional differences in TADs at the genomic hierarchical structure. Comparative analysis of multiple cell line data shows that TORNADOES can better classify different numbers and types of compartments by changing the factors ChIP-seq data and clustering number used to characterize TAD compared to other methods. Source code for the TORNADOES method can be found at https://github.com/ghaiyan/TORNADOES.

Unmet needs of biochemical biomarkers for human prion diseases

Although the development of aggregation assays has noticeably improved the accuracy of the clinical diagnosis of prion diseases, research on biomarkers remains vital. The major challenges to overcome are non-invasive sampling and the exploration of new biomarkers that may predict the onset or reflect disease progression. This will become extremely important in the near future, when new therapeutics are clinically evaluated and eventually become available for treatment. This article aims to provide an overview of the achievements of biomarker research in human prion diseases, addresses unmet needs in the field, and points out future perspectives.

Usp9x contributes to the development of sepsis-induced acute kidney injury by promoting inflammation and apoptosis in renal tubular epithelial cells via activation of the TLR4/nf-κb pathway

As a pattern recognition receptor, Toll-like receptor 4 (TLR4) is crucial for the development and progression of acute kidney injury (AKI). This study aims to explore whether the deubiquitinase Usp9x influences the TLR4/NF-B pathway to cause sepsis-induced acute kidney injury (S-AKI). The model of AKI was established in Sprague-Dawley rats using the cecal ligation and puncture (CLP) method, while renal tubular epithelial cell NRK-52E was stimulated with lipopolysaccharide (LPS) in vitro. All plasmids were transfected into NRK-52E cells according to the indicated group. The deubiquitinase of TLR4 was predicted by the online prediction software Ubibrowser. Subsequently, Western blot and Pearson correlation analysis identified Usp9x protein as a potential candidate. Co-IP analysis verified the interaction between TLR4 and Usp9x. Further research revealed that overexpression of Usp9x inhibited degradation of TLR4 protein by downregulating its ubiquitination modification levels. Both in vivo and in vitro experiments observed that interference with Usp9x effectively alleviated the inflammatory response and apoptosis of renal tubular epithelial cells (RTECs) induced by CLP or LPS, whereas overexpression of TLR4 reversed this situation. Transfection with sh-Usp9x in NRK-52E cells suppressed the expression of proteins associated with the TLR4/NF-κB pathway induced by LPS. Moreover, the overexpression of TLR4 reversed the effect of sh-Usp9x transfection. Therefore, the deubiquitinase Usp9x interacts with TLR4, leading to the upregulation of its expression through deubiquitination modification, and the activation of the TLR4/NF-κB signaling pathway, thereby promoting inflammation and apoptosis in renal tubular epithelial cells and contributing to sepsis-induced acute kidney injury.

Sigma-1 receptor exerts protective effects on ameliorating nephrolithiasis by modulating endoplasmic reticulum-mitochondrion association and inhibiting endoplasmic reticulum stress-induced apoptosis in renal tubular epithelial cells

Oxalate-induced damage to renal tubular epithelial cells (RTECs) is an essential factor in the incident kidney stone, but the specific mechanism is unclear. Recent research has pinpointed interacting areas within the endoplasmic reticulum and mitochondria, called mitochondria-associated membranes (MAMs). These studies have linked endoplasmic reticulum stress (ERS) and oxidative imbalance to kidney disease development. The sigma-1 receptor (S1R), a specific protein found in MAMs, is involved in various physiological processes, but its role in oxalate-induced kidney stone formation remains unclear. In this study, we established cellular and rat models of oxalate-induced kidney stone formation to elucidate the S1R's effects against ERS and apoptosis and its mechanism in oxalate-induced RTEC injury. We found that oxalate downregulated S1R expression in RTECs and escalated oxidative stress and ERS, culminating in increased apoptosis. The S1R agonist dimemorfan up-regulated S1R expression and mitigated ERS and oxidative stress, thereby reducing apoptosis. This protective effect was mediated through S1R inhibition of the CHOP pathway. Animal experiments demonstrated that S1R's activation attenuated oxalate-induced kidney injury and alleviated kidney stone formation. This is the first study to establish the connection between S1R and kidney stones, suggesting S1R's protective role in inhibiting ERS-mediated apoptosis to ameliorate kidney stone formation.

Hesperetin-7-O-rhamnoglucoside ameliorates dichlorvos-facilitated cardiotoxicity in rats by counteracting ionoregulatory, ion pumps, redox, and lipid homeostasis disruptions

The contamination of edible agricultural goods with pesticides, including dichlorvos (DVDP), poses a substantial public health risk, promoting severe morbidity and mortality, especially in developing countries. It has been shown that hesperidin (hesperetin-7-O-rhamnoglucoside or Hes-7-RGlc) preserves cytomembrane, redox, and lipid homeostasis; unfortunately, its function on dichlorvos-incited heart damage has not been investigated. This work explored the ameliorative influence of Hes-7-RGlc on DVDP-activated cardiotoxicity. For this end, forty-two rats were randomly appropriated into seven groups (6 rats/group): Control, DVDP alone (8 mg.kg⁻¹day⁻¹), DVDP supplied with either Hes-7-RGlc (50 and 100 mg.kg⁻¹day⁻¹) or the reference medication atropine (0.2 mg.kg⁻¹day⁻¹), and Hes-7-RGlc alone (50 and 10 mg.kg⁻¹day⁻¹) were the seven groups investigated. DVDP was administered orally for seven days, followed by fourteen days of Hes-7-RGlc therapy. Then the rats were euthanized, and their blood and hearts were removed. Hes-7-RGlc chemotherapy substantially (p<0.05) restored DVDP-elicited dynamics in plasma and cardiac/myocardium creatine kinase isoenzyme (CK-MB), major lipids (cholesterol, triacylglycerol, and phospholipids), electrolytes (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻), and total protein. Hes-7-RGlc remedy decidedly (p<0.05) abolished DDVP-stimulated amplification in the cardiac concentration of H₂O₂, NO and malondialdehyde; annulled DVDP-educed decreases in heart GSH levels, activities of GST, SOD, catalase, and glutathione peroxidase, ion transporters (Na⁺/K⁺-ATPase and Ca²⁺/Mg²⁺-ATPase), ALT, AST, ALP, and LDH-1. Collectively, Hes-7-RGlc can be advocated as a natural supplementary candidate and blocker of DVDP-provoked heart deficits via its capacity to reverse disruptions of electrolytes, ion pumps, redox status, and lipid homeostasis.

The activation thresholds and inactivation kinetics of poking-evoked PIEZO1 and PIEZO2 currents are sensitive to subtle variations in mechanical stimulation parameters

PIEZO1 and PIEZO2 are mechanically activated ion channels that confer mechanosensitivity to various cell types. PIEZO channels are commonly examined using the so-called poking technique, where currents are recorded in the whole-cell configuration of the patch-clamp technique, while the cell surface is mechanically stimulated with a small fire-polished patch pipette. Currently, there is no gold standard for mechanical stimulation, and therefore, stimulation protocols differ significantly between laboratories with regard to stimulation velocity, angle, and size of the stimulation probe. Here, we systematically examined the impact of variations in these three stimulation parameters on the outcomes of patch-clamp recordings of PIEZO1 and PIEZO2. We show that the inactivation kinetics of PIEZO1 and, to a lesser extent, of PIEZO2 change with the angle at which the probe that is used for mechanical stimulation is positioned and, even more prominently, with the size of its tip. Moreover, we found that the mechanical activation threshold of PIEZO2, but not PIEZO1, decreased with increasing stimulation speeds. Thus, our data show that two key outcome parameters of PIEZO-related patch-clamp studies are significantly affected by common variations in the mechanical stimulation protocols, which calls for caution when comparing data from different laboratories and highlights the need to establish a gold standard for mechanical stimulation to improve comparability and reproducibility of data obtained with the poking technique.

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.

The activity of pyrazolo[4,3-e][1,2,4]triazine and pyrazolo[4,3-e]tetrazolo[1,5-b][1,2,4]triazine sulphonamide derivatives in monolayer and spheroid breast cancer cell cultures

In the last decade, an increasing interest in compounds containing pyrazolo[4,3-e][1,2,4]triazine moiety is observed. Therefore, the aim of the research was to synthesise a novel sulphonyl pyrazolo[4,3-e][1,2,4]triazines (2a, 2b) and pyrazolo[4,3-e]tetrazolo[1,5-b][1,2,4]triazine sulphonamide derivatives (3a, 3b) to assess their anticancer activity. The MTT assay showed that 2a, 2b, 3a, 3b have stronger cytotoxic activity than cisplatin in both breast cancer cells (MCF-7 and MDA-MB-231) and exhibited weaker effect on normal breast cells (MCF-10A). The obtained results showed that the most active compound 3b increased apoptosis via caspase 9, caspase 8, and caspase 3/7. It is worth to note that compound 3b suppressed NF-κB expression and promoted p53, Bax, and ROS which play important role in activation of apoptosis. Moreover, our results confirmed that compound 3b triggers autophagy through increased formation of autophagosomes, expression of beclin-1 and mTOR inhibition. Thus, our study defines a possible mechanism underlying 3b-induced anti-cancer activity against breast cancer cell lines.

Cat-E: A comprehensive web tool for exploring cancer targeting strategies

Identifying potential cancer-associated genes and drug targets from omics data is challenging due to its diverse sources and analyses, requiring advanced skills and large amounts of time. To facilitate such analysis, we developed Cat-E (Cancer Target Explorer), a novel R/Shiny web tool designed for comprehensive analysis with evaluation according to cancer-related omics data. Cat-E is accessible at https://cat-e.bioinfo-wuerz.eu/. Cat-E compiles information on oncolytic viruses, cell lines, gene markers, and clinical studies by integrating molecular datasets from key databases such as OvirusTB, TCGA, DrugBANK, and PubChem. Users can use all datasets and upload their data to perform multiple analyses, such as differential gene expression analysis, metabolic pathway exploration, metabolic flux analysis, GO and KEGG enrichment analysis, survival analysis, immune signature analysis, single nucleotide variation analysis, dynamic analysis of gene expression changes and gene regulatory network changes, and protein structure prediction. Cancer target evaluation by Cat-E is demonstrated here on lung adenocarcinoma (LUAD) datasets. By offering a user-friendly interface and detailed user manual, Cat-E eliminates the need for advanced computational expertise, making it accessible to experimental biologists, undergraduate and graduate students, and oncology clinicians. It serves as a valuable tool for investigating genetic variations across diverse cancer types, facilitating the identification of novel diagnostic markers and potential therapeutic targets.

The molecular subtypes of autoimmune diseases

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Resistance and aerobic training increases genome-wide DNA methylation in women with polycystic ovary syndrome

Physical activity is a first-line treatment for polycystic ovary syndrome (PCOS). Resistance or aerobic exercise improves metabolic complications, reproductive outcomes, and quality of life in PCOS. DNA methylation reprogramming during exercise may be the major modifier behind these changes. We sought to evaluate genome-wide DNA methylation changes after supervised resistance and aerobic exercise in women with PCOS. Exercises were performed in 56 women with PCOS (resistance, n = 30; aerobic, n = 26), for 16 weeks (wks), three times per week, in 50-minute to one-hour sessions. Anthropometric indices and hormonal and metabolic parameters were measured before and after training. Genome-wide leukocyte DNA methylation was analysed by Infinium Human MethylationEPIC 850K BeadChip microarrays (Illumina). Both resistance and aerobic exercise improved anthropometric indices, metabolic dysfunction, and hyperandrogenism in PCOS after the training programme, but no differences were observed between the two exercises. Resistance and aerobic exercise increased genome-wide DNA methylation, although resistance changed every category in the CpG island context (islands, shores, shelve, and open sea), whereas aerobic exercise altered CpG shores and the open sea. Using a stringent FDR (>40), 6 significantly differentially methylated regions (DMRs) were observed in the resistance exercise cohort and 14 DRMs in the aerobic cohort, all of which were hypermethylated. The increase in genome-wide DNA methylation may be related to the metabolic and hormonal changes observed in PCOS after resistance and aerobic exercise. Since the mammalian genome is hypermethylated globally to prevent genomic instability and ageing, resistance and aerobic exercise may promote health and longevity through environmentally induced epigenetic changes.

Endolysin EN572-5 as an alternative to treat urinary tract infection caused by Streptococcus agalactiae

Streptococcus agalactiae (Group B Streptococcus, GBS) is an opportunistic pathogen causing urinary tract infection (UTI). Endolysin EN572-5 was identified in prophage KMB-572-E of the human isolate Streptococcus agalactiae KMB-572. The entire EN572-5 gene was cloned into an expression vector and the corresponding recombinant protein EN572-5 was expressed in Escherichia coli in a soluble form, isolated by affinity chromatography, and characterized. The isolated protein was highly active after 30 min incubation in a temperature range of - 20 °C to 37 °C and in a pH range of 5.5-8.0. The endolysin EN572-5 lytic activity was tested on different Streptococcus spp. and Lactobacillus spp. The enzyme lysed clinical GBS (n = 31/31) and different streptococci (n = 6/8), and also exhibited moderate lytic activity against UPEC (n = 4/4), but no lysis of beneficial vaginal lactobacilli (n = 4) was observed. The ability of EN572-5 to eliminate GBS during UTI was investigated using an in vitro model of UPSA. After the administration of 3 μM EN572-5, a nearly 3-log decrease of urine bacterial burden was detected within 3 h. To date, no studies have been published on the use of endolysins against S. agalactiae during UTI. KEY POINTS: • A lytic protein, EN572-5, from a prophage of a human GBS isolate has been identified. • This protein is easily produced, simple to prepare, and stable after lyophilization. • The bacteriolytic activity of EN572-5 was demonstrated for the first time in human urine.

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.

Safety and immunogenicity of heterologous boosting with orally administered aerosolized bivalent adenovirus type-5 vectored COVID-19 vaccine and B.1.1.529 variant adenovirus type-5 vectored COVID-19 vaccine in adults 18 years and older: a randomized, double blinded, parallel controlled trial

Vaccination strategies that can induce a broad spectrum immune response are important to enhance protection against SARS-CoV-2 variants. We conducted a randomized, double-blind and parallel controlled trial to evaluate the safety and immunogenicity of the bivalent (5×1010viral particles) and B.1.1.529 variant (5×1010viral particles) adenovirus type-5 (Ad5) vectored COVID-19 vaccines administrated via inhalation. 451 eligible subjects aged 18 years and older who had been vaccinated with three doses inactivated COVID-19 vaccines were randomly assigned to inhale one dose of either B.1.1.529 variant Ad5 vectored COVID-19 vaccine (Ad5-nCoVO-IH group, N=150), bivalent Ad5 vectored COVID-19 vaccine (Ad5-nCoV/O-IH group, N=151), or Ad5 vectored COVID-19 vaccine (5×1010viral particles; Ad5-nCoV-IH group, N=150). Adverse reactions reported by 37 (24.67%) participants in the Ad5-nCoVO-IH group, 28 (18.54%) in the Ad5-nCoV/O-IH group, and 26 (17.33%) in the Ad5-nCoV-IH group with mainly mild to moderate dry mouth, oropharyngeal pain, headache, myalgia, cough, fever and fatigue. No serious adverse events related to the vaccine were reported. Investigational vaccines were immunogenic, with significant difference in the GMTs of neutralizing antibodies against Omicron BA.1 between Ad5-nCoV/O-IH (43.70) and Ad5-nCoV-IH (29.25) at 28 days after vaccination (P=0.0238). The seroconversion rates of neutralizing antibodies against BA.1 in Ad5-nCoVO-IH, Ad5-nCoV/O-IH, and Ad5-nCoV-IH groups were 56.00%, 59.60% and 48.67% with no significant difference among the groups. Overall, the investigational vaccines were demonstrated to be safe and well tolerated in adults, and was highly effective in inducing mucosal immunities in addition to humoral and cellular immune responses defending against SARS-CoV-2 variants.Trial registration: Chictr.org identifier: ChiCTR2200063996.

Effects of different exercise regimens on prognosis of patients with chronic obstructive pulmonary disease: a systematic reviews and meta-analysis

INTRODUCTION

Skeletal muscle dysfunction is a significant factor contributing to exercise limitation in patients with chronic obstructive pulmonary disease (COPD). Although exercise training is often recommended to enhance patient outcomes, there continues to be ongoing debate regarding its exact effects.

OBJECTIVE

The aim of this study is to evaluate the effectiveness of endurance exercise, strength training and combined exercise on cardiorespiratory fitness (including maximal oxygen uptake, maximal minute ventilation, and the 6-minute walk test), strength of lower limbs (measured by leg press), and quality of life (using the COPD Assessment Test) in patients with COPD. By conducting a systematic review and meta-analysis of randomized controlled trials (RCTs), our objective is to provide tailored training methods and intensity recommendations for patients with COPD in order to improve their quality of life.

METHODS

The meta-analysis included 10 randomized controlled trials (RCTs) of exercise rehabilitation programs involving 180 patients with COPD that were retrieved from electronic databases (PubMed, Cochrane Library, and Embase). Two reviewers independently assessed the topical relevance, trial quality, and extracted data for the meta-analysis.

RESULTS

Meta-analysis showed that primary outcomes representing exercise endurance were elevated under different exercise interventions compared to pre-test, such as maximal oxygen uptake (VO2max (ml/kg/min)) [SMD = 0.40, 95% CI (0.15, 0.64)] and the 6-min walk test (6MWT) [MD = 33.90, 95% CI (25.25, 42.55)], and primary outcomes representing strength also increased, such as leg press (1RM) [MD = 24.59, 95% CI (16.08, 33.11)], while secondary outcomes such as assessments of life such as the COPD Assessment Test (CAT) recovered [MD = 2.51, 95% CI (2.01, 3.00)], with all differences being statistically significant (p < 0.05). However, Maximum minute ventilation (VEmax (L)) [MD = 0.91, 95%CI (3.61, 5.43)] was not statistically significant (p > 0.05) when compared with the post-test data. The sensitivity test data were stable, and the results were reliable. We subgrouped the data from different types of exercise interventions and found that different types of exercise affected the experimental results.

CONCLUSION

Exercise interventions have a positive effect on the treatment of patients with COPD, significantly improving functional capacity, aerobic capacity, and exercise tolerance, but they should be individualized and developed according to the patient's condition to achieve the best therapeutic effect.

A novel heuristic of rigid docking scores positively correlates with full-length nuclear receptor LRH-1 regulation

The nuclear receptor Liver Receptor Homolog-1 (LRH-1, NR5A2) is a ligand-regulated transcription factor and validated drug target for several human diseases. LRH-1 activation is regulated by small molecule ligands, which bind to the ligand binding domain (LBD) within the full-length LRH-1. We recently identified 57 compounds that bind LRH-1, and unexpectedly found these compounds regulated either the isolated LBD, or the full-length LRH-1 in cells, with little overlap. Here, we correlated compound binding energy from a single rigid-body scoring function with full-length LRH-1 activity in cells. Although docking scores of the 57 hit compounds did not correlate with LRH-1 regulation in wet lab assays, a subset of the compounds had large differences in binding energy docked to the isolated LBD vs. full-length LRH-1, which we used to empirically derive a new metric of the docking scores we call "ΔΔG". Initial regressions, correlations and contingency analyses all suggest compounds with high ΔΔG values more frequently regulated LRH-1 in wet lab assays. We then docked all 57 compounds to 18 separate crystal structures of LRH-1 to obtain averaged ΔΔG values for each compound, which robustly and reproducibly associated with full-length LRH-1 activity in cells. Network analyses on the 18 crystal structures of LRH-1 suggest unique communication paths exist between the subsets of LRH-1 crystal structures that produced high vs. low ΔΔG values, identifying a structural relationship between ΔΔG and the position of Helix 6, a previously established regulatory helix important for LRH-1 regulation. Together, these data suggest rigid-body computational docking can be used to quickly calculate ΔΔG, which positively correlated with the ability of these 57 hit compounds to regulate full-length LRH-1 in cell-based assays. We propose ΔΔG as a novel computational tool that can be applied to LRH-1 drug screens to prioritize compounds for resource-intense secondary screening.

Integrating bulk RNA-seq and scRNA-seq analyses revealed the function and clinical value of thrombospondins in colon cancer

Background

Acting as mediators in cell-matrix and cell-cell communication, matricellular proteins play a crucial role in cancer progression. Thrombospondins (TSPs), a type of matricellular glycoproteins, are key regulators in cancer biology with multifaceted roles. Although TSPs have been implicated in anti-tumor immunity and epithelial-mesenchymal transition (EMT) in several malignancies, their specific roles to colon cancer remain elusive. Addressing this knowledge gap is essential, as understanding the function of TSPs in colon cancer could identify new therapeutic targets and prognostic markers.

Methods

Analyzing 1981 samples from 10 high-throughput datasets, including six bulk RNA-seq, three scRNA-seq, and one spatial transcriptome dataset, our study investigated the prognostic relevance, risk stratification value, immune heterogeneity, and cellular origin of TSPs, as well as their influence on cancer-associated fibroblasts (CAFs). Utilizing survival analysis, unsupervised clustering, and functional enrichment, along with multiple correlation analyses of the tumor-microenvironment (TME) via Gene Set Variation Analysis (GSVA), spatial localization, Monocle2, and CellPhoneDB, we provided insights into the clinical and cellular implications of TSPs.

Results

First, we observed significant upregulation of THBS2 and COMP in colon cancer, both of which displayed significant prognostic value. Additionally, we detected a significant positive correlation between TSPs and immune cells, as well as marker genes of EMT. Second, based on TSPs expression, patients were divided into two clusters with distinct prognoses: the high TSPs expression group (TSPs-H) was characterized by pronounced immune and stromal cell infiltration, and notably elevated T-cell exhaustion scores. Subsequently, we found that THBS2 and COMP may be associated with the differentiation of CAFs into pan-iCAFs and pan-dCAFs, which are known for their heightened matrix remodeling activities. Moreover, THBS2 enhanced CAFs communication with vascular endothelial cells and monocyte-macrophages. CAFs expressing THBS2 (THBS2+ CAFs) demonstrated higher scores across multiple signaling pathways, including angiogenic, EMT, Hedgehog, Notch, Wnt, and TGF-β, when compared to THBS2- CAFs. These observations suggest that THBS2 may be associated with stronger pro-carcinogenic activity in CAFs.

Conclusions

This study revealed the crucial role of TSPs and the significant correlation between THBS2 and CAFs interactions in colon cancer progression, providing valuable insights for targeting TSPs to mitigate cancer progression.

Context-dependent genomic locus effects on antibody production in recombinant Chinese hamster ovary cells generated through random integration

High-yield production of therapeutic protein using Chinese hamster ovary (CHO) cells requires stable cell line development (CLD). CLD typically uses random integration of transgenes; however, this results in clonal variation and subsequent laborious clone screening. Therefore, site-specific integration of a protein expression cassette into a desired chromosomal locus showing high transcriptional activity and stability, referred to as a hot spot, is emerging. Although positional effects are important for therapeutic protein expression, the sequence-specific mechanisms by which hotspots work are not well understood. In this study, we performed whole-genome sequencing (WGS) to locate randomly inserted vectors in the genome of recombinant CHO cells expressing high levels of monoclonal antibodies (mAbs) and experimentally validated these locations and vector compositions. The integration site was characterized by active histone marks and potential enhancer activities, and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) mediated indel mutations in the region upstream of the integration site led to a significant reduction in specific antibody productivity by up to 30%. Notably, the integration site and its core region did not function equivalently outside the native genomic context, showing a minimal effect on the increase in exogenous protein expression in the host cell line. We also observed a superior production capacity of the mAb expressing cell line compared to that of the host cell line. Collectively, this study demonstrates that developing recombinant CHO cell lines to produce therapeutic proteins at high levels requires a balance of factors including transgene configuration, genomic locus landscape, and host cell properties.

Promotive effect of skin precursor-derived Schwann cells on brachial plexus neurotomy and motor neuron damage repair through milieu-regulating secretome

Brachial plexus injury (BPI) with motor neurons (MNs) damage still remain poor recovery in preclinical research and clinical therapy, while cell-based therapy approaches emerged as novel strategies. Previous work of rat skin precursor-derived Schwann cells (SKP-SCs) provided substantial foundation for repairing peripheral nerve injury (PNI). Given that, our present work focused on exploring the repair efficacy and possible mechanisms of SKP-SCs implantation on rat BPI combined with neurorrhaphy post-neurotomy. Results indicated the significant locomotive and sensory function recovery, with improved morphological remodeling of regenerated nerves and angiogenesis, as well as amelioration of target muscles atrophy and motor endplate degeneration. Besides, MNs could restore from oxygen-glucose-deprivation (OGD) injury upon SKP-SCs-sourced secretome treatment, implying the underlying paracrine mechanisms. Moreover, rat cytokine array assay detected 67 cytokines from SKP-SC-secretome, and bioinformatic analyses of screened 32 cytokines presented multiple functional clusters covering diverse cell types, including inflammatory cells, Schwann cells, vascular endothelial cells (VECs), neurons, and SKP-SCs themselves, relating distinct biological processes to nerve regeneration. Especially, a panel of hypoxia-responsive cytokines (HRCK), can participate into multicellular biological process regulation for permissive regeneration milieu, which underscored the benefits of SKP-SCs and sourced secretome, facilitating the chorus of nerve regenerative microenvironment. Furthermore, platelet-derived growth factor-AA (PDGF-AA) and vascular endothelial growth factor-A (VEGF-A) were outstanding cytokines involved with nerve regenerative microenvironment regulating, with significantly elevated mRNA expression level in hypoxia-responsive SKP-SCs. Altogether, through recapitulating the implanted SKP-SCs and derived secretome as niche sensor and paracrine transmitters respectively, HRCK would be further excavated as molecular underpinning of the neural recuperative mechanizations for efficient cell therapy; meanwhile, the analysis paradigm in this study validated and anticipated the actions and mechanisms of SKP-SCs on traumatic BPI repair, and was beneficial to identify promising bioactive molecule cocktail and signaling targets for cell-free therapy strategy on neural repair and regeneration.

Mikania micrantha silver nanoparticles exhibit anticancer activities against human lung adenocarcinoma via caspase-mediated apoptotic cell death

Green-mediated synthesis of nanoparticles has earned a promising role in the area of nanotechnology due to their biomedical applications. This study describes the synthesis of silver nanoparticles (AgNPs) using Mikania micrantha leaf extract and its functional activities against cancer. The synthesis of AgNPs was confirmed using Ultraviolet-Visible (UV-Vis) spectrum that exhibited an absorption band at 459 nm. The bioactive compounds of M. micrantha leaf extract that functioned as reducing and capping agents were confirmed by a shift in the absorption bands in Fourier Transform Infra-red Spectroscopy (FT-IR). Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) studies validated the spherical shape and size of AgNPs, respectively. Energy Dispersive Spectroscopy (EDS) analysis revealed the presence of elemental silver. The crystalline nature of AgNPs was confirmed by the X-ray Diffraction Analysis (XRD). AgNPs effectively induced cytotoxicity and prevented A549 cell colony formation in a dose-dependent manner. Treatment of A549 cells with AgNPs also increased DNA damage, which was coupled with elevated lipid peroxidation and decreased antioxidant enzymes such as glutathione (GSH), glutathione-s-transferase (GST), and superoxide dismutase (SOD). Following AgNPs treatment, the mRNA expression levels of the pro-apoptotic genes as well as the activities of caspases were significantly elevated in A549 cells while the expression levels of anti-apoptotic genes were downregulated. Our study demonstrates the potential of the synthesised AgNPs for cancer therapy possibly targeting the apoptotic pathway.