Alarming antibody evasion properties of rising SARS-CoV-2 BQ and XBB subvariants.

The BQ and XBB subvariants of SARS-CoV-2 Omicron are now rapidly expanding, possibly due to altered antibody evasion properties deriving from their additional spike mutations. Here, we report that neutralization of BQ.1, BQ.1.1, XBB, and XBB.1 by sera from vaccinees and infected persons was markedly impaired, including sera from individuals boosted with a WA1/BA.5 bivalent mRNA vaccine. Titers against BQ and XBB subvariants were lower by 13- to 81-fold and 66- to 155-fold, respectively, far beyond what had been observed to date. Monoclonal antibodies capable of neutralizing the original Omicron variant were largely inactive against these new subvariants, and the responsible individual spike mutations were identified. These subvariants were found to have similar ACE2-binding affinities as their predecessors. Together, our findings indicate that BQ and XBB subvariants present serious threats to current COVID-19 vaccines, render inactive all authorized antibodies, and may have gained dominance in the population because of their advantage in evading antibodies.

Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex.

Elucidating the cellular organization of the cerebral cortex is critical for understanding brain structure and function. Using large-scale single-nucleus RNA sequencing and spatial transcriptomic analysis of 143 macaque cortical regions, we obtained a comprehensive atlas of 264 transcriptome-defined cortical cell types and mapped their spatial distribution across the entire cortex. We characterized the cortical layer and region preferences of glutamatergic, GABAergic, and non-neuronal cell types, as well as regional differences in cell-type composition and neighborhood complexity. Notably, we discovered a relationship between the regional distribution of various cell types and the region's hierarchical level in the visual and somatosensory systems. Cross-species comparison of transcriptomic data from human, macaque, and mouse cortices further revealed primate-specific cell types that are enriched in layer 4, with their marker genes expressed in a region-dependent manner. Our data provide a cellular and molecular basis for understanding the evolution, development, aging, and pathogenesis of the primate brain.

Microbiota imbalance induced by dietary sugar disrupts immune-mediated protection from metabolic syndrome.

How intestinal microbes regulate metabolic syndrome is incompletely understood. We show that intestinal microbiota protects against development of obesity, metabolic syndrome, and pre-diabetic phenotypes by inducing commensal-specific Th17 cells. High-fat, high-sugar diet promoted metabolic disease by depleting Th17-inducing microbes, and recovery of commensal Th17 cells restored protection. Microbiota-induced Th17 cells afforded protection by regulating lipid absorption across intestinal epithelium in an IL-17-dependent manner. Diet-induced loss of protective Th17 cells was mediated by the presence of sugar. Eliminating sugar from high-fat diets protected mice from obesity and metabolic syndrome in a manner dependent on commensal-specific Th17 cells. Sugar and ILC3 promoted outgrowth of Faecalibaculum rodentium that displaced Th17-inducing microbiota. These results define dietary and microbiota factors posing risk for metabolic syndrome. They also define a microbiota-dependent mechanism for immuno-pathogenicity of dietary sugar and highlight an elaborate interaction between diet, microbiota, and intestinal immunity in regulation of metabolic disorders.

Intestinal microbiota-specific Th17 cells possess regulatory properties and suppress effector T cells via c-MAF and IL-10.

Commensal microbes induce cytokine-producing effector tissue-resident CD4+ T cells, but the function of these T cells in mucosal homeostasis is not well understood. Here, we report that commensal-specific intestinal Th17 cells possess an anti-inflammatory phenotype marked by expression of interleukin (IL)-10 and co-inhibitory receptors. The anti-inflammatory phenotype of gut-resident commensal-specific Th17 cells was driven by the transcription factor c-MAF. IL-10-producing commensal-specific Th17 cells were heterogeneous and derived from a TCF1+ gut-resident progenitor Th17 cell population. Th17 cells acquired IL-10 expression and anti-inflammatory phenotype in the small-intestinal lamina propria. IL-10 production by CD4+ T cells and IL-10 signaling in intestinal macrophages drove IL-10 expression by commensal-specific Th17 cells. Intestinal commensal-specific Th17 cells possessed immunoregulatory functions and curbed effector T cell activity in vitro and in vivo in an IL-10-dependent and c-MAF-dependent manner. Our results suggest that tissue-resident commensal-specific Th17 cells perform regulatory functions in mucosal homeostasis.

Antigenicity and receptor affinity of SARS-CoV-2 BA.2.86 spike.

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant, BA.2.86, has emerged and spread to numerous countries worldwide, raising alarm because its spike protein contains 34 additional mutations compared with its BA.2 predecessor1. We examined its antigenicity using human sera and monoclonal antibodies (mAbs). Reassuringly, BA.2.86 was no more resistant to human sera than the currently dominant XBB.1.5 and EG.5.1, indicating that the new subvariant would not have a growth advantage in this regard. Importantly, sera from people who had XBB breakthrough infection exhibited robust neutralizing activity against all viruses tested, suggesting that upcoming XBB.1.5 monovalent vaccines could confer added protection. Although BA.2.86 showed greater resistance to mAbs to subdomain 1 (SD1) and receptor-binding domain (RBD) class 2 and 3 epitopes, it was more sensitive to mAbs to class 1 and 4/1 epitopes in the 'inner face' of the RBD that is exposed only when this domain is in the 'up' position. We also identified six new spike mutations that mediate antibody resistance, including E554K that threatens SD1 mAbs in clinical development. The BA.2.86 spike also had a remarkably high receptor affinity. The ultimate trajectory of this new SARS-CoV-2 variant will soon be revealed by continuing surveillance, but its worldwide spread is worrisome.

Antibody evasion properties of SARS-CoV-2 Omicron sublineages.

The identification of the Omicron (B.1.1.529.1 or BA.1) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Botswana in November 20211 immediately caused concern owing to the number of alterations in the spike glycoprotein that could lead to antibody evasion. We2 and others3-6 recently reported results confirming such a concern. Continuing surveillance of the evolution of Omicron has since revealed the rise in prevalence of two sublineages, BA.1 with an R346K alteration (BA.1+R346K, also known as BA.1.1) and B.1.1.529.2 (BA.2), with the latter containing 8 unique spike alterations and lacking 13 spike alterations found in BA.1. Here we extended our studies to include antigenic characterization of these new sublineages. Polyclonal sera from patients infected by wild-type SARS-CoV-2 or recipients of current mRNA vaccines showed a substantial loss in neutralizing activity against both BA.1+R346K and BA.2, with drops comparable to that already reported for BA.1 (refs. 2,3,5,6). These findings indicate that these three sublineages of Omicron are antigenically equidistant from the wild-type SARS-CoV-2 and thus similarly threaten the efficacies of current vaccines. BA.2 also exhibited marked resistance to 17 of 19 neutralizing monoclonal antibodies tested, including S309 (sotrovimab)7, which had retained appreciable activity against BA.1 and BA.1+R346K (refs. 2-4,6). This finding shows that no authorized monoclonal antibody therapy could adequately cover all sublineages of the Omicron variant, except for the recently authorized LY-CoV1404 (bebtelovimab).

Striking antibody evasion manifested by the Omicron variant of SARS-CoV-2.

The B.1.1.529/Omicron variant of SARS-CoV-2 was only recently detected in southern Africa, but its subsequent spread has been extensive, both regionally and globally1. It is expected to become dominant in the coming weeks2, probably due to enhanced transmissibility. A striking feature of this variant is the large number of spike mutations3 that pose a threat to the efficacy of current COVID-19 vaccines and antibody therapies4. This concern is amplified by the findings of our study. Here we found that B.1.1.529 is markedly resistant to neutralization by serum not only from patients who recovered from COVID-19, but also from individuals who were vaccinated with one of the four widely used COVID-19 vaccines. Even serum from individuals who were vaccinated and received a booster dose of mRNA-based vaccines exhibited substantially diminished neutralizing activity against B.1.1.529. By evaluating a panel of monoclonal antibodies against all known epitope clusters on the spike protein, we noted that the activity of 17 out of the 19 antibodies tested were either abolished or impaired, including ones that are currently authorized or approved for use in patients. Moreover, we also identified four new spike mutations (S371L, N440K, G446S and Q493R) that confer greater antibody resistance on B.1.1.529. The Omicron variant presents a serious threat to many existing COVID-19 vaccines and therapies, compelling the development of new interventions that anticipate the evolutionary trajectory of SARS-CoV-2.

Fast and efficient template-mediated synthesis of genetic variants.

Efficient methods for the generation of specific mutations enable the study of functional variations in natural populations and lead to advances in genetic engineering applications. Here, we present a new approach, mutagenesis by template-guided amplicon assembly (MEGAA), for the rapid construction of kilobase-sized DNA variants. With this method, many mutations can be generated at a time to a DNA template at more than 90% efficiency per target in a predictable manner. We devised a robust and iterative protocol for an open-source laboratory automation robot that enables desktop production and long-read sequencing validation of variants. Using this system, we demonstrated the construction of 31 natural SARS-CoV2 spike gene variants and 10 recoded Escherichia coli genome fragments, with each 4 kb region containing up to 150 mutations. Furthermore, 125 defined combinatorial adeno-associated virus-2 cap gene variants were easily built using the system, which exhibited viral packaging enhancements of up to 10-fold compared with wild type. Thus, the MEGAA platform enables generation of multi-site sequence variants quickly, cheaply, and in a scalable manner for diverse applications in biotechnology.

SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding.

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

CottonMD: a multi-omics database for cotton biological study.

Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

Associations between liver function and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in non-demented adults: The CABLE study.

Liver function has been suggested as a possible factor in the progression of Alzheimer's disease (AD) development. However, the association between liver function and cerebrospinal fluid (CSF) levels of AD biomarkers remains unclear. In this study, we analyzed the data from 1687 adults without dementia from the Chinese Alzheimer's Biomarker and LifestylE study to investigate differences in liver function between pathological and clinical AD groups, as defined by the 2018 National Institute on Aging-Alzheimer's Association Research Framework. We also examined the linear relationship between liver function, CSF AD biomarkers, and cognition using linear regression models. Furthermore, mediation analyses were applied to explore the potential mediation effects of AD pathological biomarkers on cognition. Our findings indicated that, with AD pathological and clinical progression, the concentrations of total protein (TP), globulin (GLO), and aspartate aminotransferase/alanine transaminase (ALT) increased, while albumin/globulin (A/G), adenosine deaminase, alpha-L-fucosidase, albumin, prealbumin, ALT, and glutamate dehydrogenase (GLDH) concentrations decreased. Furthermore, we also identified significant relationships between TP (ß = -0.115, pFDR < 0.001), GLO (ß = -0.184, pFDR < 0.001), and A/G (ß = 0.182, pFDR < 0.001) and CSF ß-amyloid1-42 (Aß1-42 ) (and its related CSF AD biomarkers). Moreover, after 10 000 bootstrapped iterations, we identified a potential mechanism by which TP and GLDH may affect cognition by mediating CSF AD biomarkers, with mediation effect sizes ranging from 3.91% to 16.44%. Overall, our results suggested that abnormal liver function might be involved in the clinical and pathological progression of AD. Amyloid and tau pathologies also might partially mediate the relationship between liver function and cognition. Future research is needed to fully understand the underlying mechanisms and causality to develop an approach to AD prevention and treatment approach.

Conjugated Molecules Based Multi-Component Artificial Photosynthesis System for Producing Multi-Objective Products.

The development of artificial photosynthesis systems that mimics natural photosynthesis can help address the issue of energy scarcity by efficiently utilizing solar energy. Here, it presents liposomes-based artificial photosynthetic nanocapsules (PSNC) integrating photocatalytic, chemical catalytic, and biocatalytic systems through one-pot method. The PSNC contains 5,10,15,20-tetra(4-pyridyl) cobalt-porphyrin, tridipyridyl-ruthenium nitrate, oligo-pphenyl-ethylene-rhodium complex, and creatine kinase, efficiently generating oxygen, nicotinamide adenine dinucleotide (NADH), and adenosine triphosphate with remarkable enhancements of 231%, 30%, and 86%, compared with that of molecules mixing in aqueous solution. Additionally, the versatile PSNC enables simulation of light-independent reactions, achieving a controllable output of various target products. The regenerated NADH within PSNC further facilitates alcohol dehydrogenase, yielding methanol with a notable efficiency improvement of 37%. This work introduces a promising platform for sustainable solar energy conversion and the simultaneous synthesis of multiple valuable products in an ingenious and straightforward way.

Fly-scan high-throughput coded ptychographic microscopy via active micro-vibration and rolling-shutter distortion correction.

Recent advancements in ptychography have demonstrated the potential of coded ptychography (CP) for high-resolution optical imaging in a lensless configuration. However, CP suffers imaging throughput limitations due to scanning inefficiencies. To address this, we propose what we believe is a novel 'fly-scan' scanning strategy utilizing two eccentric rotating mass (ERM) vibration motors for high-throughput coded ptychographic microscopy. The intrinsic continuity of the 'fly-scan' technique effectively eliminates the scanning overhead typically encountered during data acquisition. Additionally, its randomized scanning trajectory considerably reduces periodic artifacts in image reconstruction. We also developed what we believe to be a novel rolling-shutter distortion correction algorithm to fix the rolling-shutter effects. We built up a low-cost, DIY-made prototype platform and validated our approach with various samples including a resolution target, a quantitative phase target, a thick potato sample and biospecimens. The reported platform may offer a cost-effective and turnkey solution for high-throughput bio-imaging.

Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains.

Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.

Bone mesenchymal stem cell-derived exosomal miR-26a-3p promotes autophagy to attenuate LPS-induced apoptosis and inflammation in pulmonary microvascular endothelial cells.

Acute lung injury (ALI) is a serious lung disease. The apoptosis and inflammation of pulmonary microvascular endothelial cells (PMVECs) are the primary reasons for ALI. This study aimed to explore the treatment effect and regulatory mechanism of bone mesenchymal stem cell-derived exosomes (BMSC-expos) on ALI. PMVECs were stimulated by Lipopolysaccharide (LPS) to imitate ALI environment. Cell viability was determined by CCK-8 assay. Cell apoptosis was evaluated by TUNEL and flow cytometry. ELISA was utilized for testing the contents of TNF-α, IL-1ß, IL-6, and IL-17. Western blot was applied for testing the levels of autophagy-related proteins LC3, p62, and Beclin-1. RNA interaction was determined by luciferase reporter assay. The ALI rat model was established by intratracheal injection of LPS. Evans blue staining was utilized for detecting pulmonary vascular permeability. Our results showed that LPS stimulation notably reduced cell viability, increased cell apoptosis rate, and enhanced the contents of inflammatory factors in PMVECs. However, BMSC-exo treatment significantly abolished the promoting effects of LPS on cell injury. In addition, we discovered that BMSC-exo treatment notably activated autophagy in LPS-induced PMVECs. Furthermore, BMSC-expos upregulated miR-26a-3p expression and downregulated PTEN in PMVECs. MiR-26a-3p was directly bound to PTEN. MiR-26a-3p overexpression reduced cell apoptosis, and inflammation and promoted autophagy by silencing PTEN. Animal experiments proved that miR-26a-3p overexpression effectively improved LPS-induced lung injury in rats. The results proved that BMSC-expos promotes autophagy to attenuate LPS-induced apoptosis and inflammation in pulmonary microvascular endothelial cells via miR-26a-3p/PTEN axis.

Utilizing microbial metabolite in catalytic cascade synthesis of conjugated oligomers for In-Situ regulation of biological activity.

Despite the advances of multistep enzymatic cascade reactions, their incorporation with abiotic reactions in living organisms remains challenging in synthetic biology. Herein, we combined microbial metabolic pathways and Pd-catalyzed processes for in-situ generation of bioactive conjugated oligomers. Our biocompatible one-pot coupling reaction utilized the fermentation process of engineered E. coli that converted glucose to styrene, which participated in the Pd-catalyzed Heck reaction for in-situ synthesis of conjugated oligomers. This process serves a great interest in understanding resistance evolution by utilizing the inhibitory activity of the synthesized conjugated oligomers. The approach allows for the in-situ combination of biological metabolism and CC coupling reactions, opening up new possibilities for the biosynthesis of unnatural molecules and enabling the in-situ regulation of the bioactivity of the obtained products.

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

Picea wilsonii NAC31 and DREB2A Cooperatively Activate ERD1 to Modulate Drought Resistance in Transgenic Arabidopsis.

The NAC family of transcription factors (TFs) regulate plant development and abiotic stress. However, the specific function and response mechanism of NAC TFs that increase drought resistance in Picea wilsonii remain largely unknown. In this study, we functionally characterized a member of the PwNAC family known as PwNAC31. PwNAC31 is a nuclear-localized protein with transcriptional activation activity and contains an NAC domain that shows extensive homology with ANAC072 in Arabidopsis. The expression level of PwNAC31 is significantly upregulated under drought and ABA treatments. The heterologous expression of PwNAC31 in atnac072 Arabidopsis mutants enhances the seed vigor and germination rates and restores the hypersensitive phenotype of atnac072 under drought stress, accompanied by the up-regulated expression of drought-responsive genes such as DREB2A (DEHYDRATION-RESPONSIVE ELEMENT BINDING PROTEIN 2A) and ERD1 (EARLY RESPONSIVE TO DEHYDRATION STRESS 1). Yeast two-hybrid and bimolecular fluorescence complementation assays confirmed that PwNAC31 interacts with DREB2A and ABF3 (ABSCISIC ACID-RESPONSIVE ELEMENT-BINDING FACTOR 3). Yeast one-hybrid and dual-luciferase assays showed that PwNAC31, together with its interaction protein DREB2A, directly regulated the expression of ERD1 by binding to the DRE element of the ERD1 promoter. Collectively, our study provides evidence that PwNAC31 activates ERD1 by interacting with DREB2A to enhance drought tolerance in transgenic Arabidopsis.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning. / 基于WGCNAå’Œæœºå™¨å­¦ä¹ ç­›é€‰å¸•é‡‘æ£®ç— å ç–«ç›¸å ³å ³é”®åŸºå› .

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. METHODS: This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. RESULTS: A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. CONCLUSIONS: This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Biosynthesis of Multifunctional Transformable Peptides for Inducing Tumor Cell Apoptosis.

Engineered nanomaterials hold great promise to improve the specificity of disease treatment. Herein, a fully protein-based material is obtained from nonpathogenic Escherichia coli (E. coli), which is capable of morphological transformation from globular to fibrous in situ for inducing tumor cell apoptosis. The protein-based material P1 is comprised of a ß-sheet-forming peptide KLVFF, pro-apoptotic protein BAK, and GFP along with targeting moieties. The self-assembled nanoparticles of P1 transform into nanofibers in situ in the presence of cathepsin B, and the generated nanofibrils favor the dimerization of functional BH3 domain of BAK on the mitochondrial outer membrane, leading to efficient anticancer activity both in vitro and in vivo via mitochondria-dependent apoptosis through Bcl-2 pathway. To precisely manipulate the morphological transformation of biosynthetic molecules in living cells, a spatiotemporally controllable anticancer system is constructed by coating P1-expressing E. coli with cationic conjugated polyelectrolytes to release the peptides in situ under light irradiation. The biosynthetic peptide-based enzyme-catalytic transformation strategy in vivo would offer a novel perspective for targeted delivery and shows great potential in precision disease therapeutics.