Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.

Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

Multi-omics analysis of innate and adaptive responses to BCG vaccination reveals epigenetic cell states that predict trained immunity.

Immune responses are tightly regulated yet highly variable between individuals. To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live-attenuated vaccine induces not only an adaptive immune response against tuberculosis but also triggers innate immune activation and memory that are indicative of trained immunity. We established personal immune profiles and chromatin accessibility maps over a 90-day time course of BCG vaccination in 323 individuals. Our analysis uncovered genetic and epigenetic predictors of baseline immunity and immune response. BCG vaccination enhanced the innate immune response specifically in individuals with a dormant immune state at baseline, rather than providing a general boost of innate immunity. This study advances our understanding of BCG's heterologous immune-stimulatory effects and trained immunity in humans. Furthermore, it highlights the value of epigenetic cell states for connecting immune function with genotype and the environment.

Construction of an artificial phosphoketolase pathway that efficiently catabolizes multiple carbon sources to acetyl-CoA.

The canonical glycolysis pathway is responsible for converting glucose into 2 molecules of acetyl-coenzyme A (acetyl-CoA) through a cascade of 11 biochemical reactions. Here, we have designed and constructed an artificial phosphoketolase (APK) pathway, which consists of only 3 types of biochemical reactions. The core enzyme in this pathway is phosphoketolase, while phosphatase and isomerase act as auxiliary enzymes. The APK pathway has the potential to achieve a 100% carbon yield to acetyl-CoA from any monosaccharide by integrating a one-carbon condensation reaction. We tested the APK pathway in vitro, demonstrating that it could efficiently catabolize typical C1-C6 carbohydrates to acetyl-CoA with yields ranging from 83% to 95%. Furthermore, we engineered Escherichia coli stain capable of growth utilizing APK pathway when glycerol act as a carbon source. This novel catabolic pathway holds promising route for future biomanufacturing and offering a stoichiometric production platform using multiple carbon sources.

Production of the antidepressant orcinol glucoside in Yarrowia lipolytica with yields over 6,400-fold higher than plant extraction.

Orcinol glucoside (OG), mainly found in the rhizome of the traditional Chinese herb Curculigo orchioides Gaertn, is noted for its antidepressant effects. In this study, an efficient screening pipeline was established for identifying the highly active orcinol synthase (ORS) and UDP-dependent glycosyltransferase (UGT) involved in the biosynthesis of OG by combining transcriptome analysis, structure-based virtual screening, and in vitro enzyme activity assays. By enhancing the downstream pathway, metabolic engineering and fermentation optimization, the OG production in Yarrowia lipolytica was improved 100-fold, resulting in a final yield of 43.46 g/L (0.84 g/g DCW), which is almost 6,400-fold higher than the extraction yield from C. orchioides roots. This study provides a reference for rapid identification of functional genes and high-yield production of natural products.

circNEIL3 inhibits tumor metastasis through recruiting the E3 ubiquitin ligase Nedd4L to degrade YBX1.

Distant metastasis is a major contributor to cancer-related mortality. However, the role of circRNAs in this process remains unclear. Herein, we profiled the circRNA expression in a cohort of 68 colorectal carcinoma (CRC) primary tumors and their paired liver metastatic lesions. By overlapping with the TGFß-responsive circRNAs, circNEIL3 (hsa_circ_0001460) was identified as a TGFß-repressive and metastasis-related circRNA. Functionally, circNEIL3 effectively inhibited tumor metastasis in both and in vivo and in vivo models of various cancer types. Mechanistically, circNEIL3 exerts its metastasis-repressive function through its direct interaction with oncogenic protein, Y-box-binding protein 1 (YBX1), which consequently promotes the Nedd4L-mediated proteasomal degradation of YBX1. Importantly, circNEIL3 expression was negatively correlated to YBX1 protein level and metastatic tendency in CRC patient samples. Collectively, our findings indicate the YBX1-dependent antimetastatic function of circNEIL3 and highlight the potential of circNEIL3 as a biomarker and therapeutic option in cancer treatment.

Visualization of the landscape of the read alignment shape of ATAC-seq data using Hellinger distance metric.

Assay for Transposase-Accessible Chromatin using high-throughput sequencing (ATAC-seq) is the popular technique using next-generation sequencing to measure chromatin accessibility and identify open chromatin regions. While read alignment shape information of next-generation sequencing data with intensity information has been used in various bioinformatics methods, few studies have focused on pure shape information alone. In this study, we investigated what types of ATAC-seq read alignment shapes are observed for the promoter region and whether the pure shape information was related or unrelated to other gene features. We introduced a novel concept and pipeline for handling the pure shape information of NGS data as probability distributions and quantifying their dissimilarities by information theory. Based on this concept, we demonstrate that the pure shape information of ATAC-seq data is correlated with chromatin openness and some gene characteristics. On the other hand, it is suggested that the pure information of ATAC-seq read alignment shape is unlikely to contain additional information to explain differences in RNA expression. Our study suggests that viewing the read alignment shape of NGS data as probability distributions enables us to capture the characteristics of the genome-wide landscape of such data in a non-parametric manner.

Plasma metabolome predicts trained immunity responses after antituberculosis BCG vaccination.

The antituberculosis vaccine Bacillus Calmette-Guérin (BCG) induces nonspecific protection against heterologous infections, at least partly through induction of innate immune memory (trained immunity). The amplitude of the response to BCG is variable, but the factors that influence this response are poorly understood. Metabolites, either released by cells or absorbed from the gut, are known to influence immune responses, but whether they impact BCG responses is not known. We vaccinated 325 healthy individuals with BCG, and collected blood before, 2 weeks and 3 months after vaccination, to assess the influence of circulating metabolites on the immune responses induced by BCG. Circulating metabolite concentrations after BCG vaccination were found to have a more pronounced impact on trained immunity responses, such as the increase in IL-1ß and TNF-α production upon Staphylococcus aureus stimulation, than on specific adaptive immune memory, assessed as IFN-γ production in response to Mycobacterium tuberculosis. Circulating metabolites at baseline were able to predict trained immunity responses at 3 months after vaccination and enrichment analysis based on the metabolites positively associated with trained immunity revealed enrichment of the tricarboxylic acid (TCA) cycle and glutamine metabolism, both of which were previously found to be important for trained immunity. Several new metabolic pathways that influence trained immunity were identified, among which taurine metabolism associated with BCG-induced trained immunity, a finding validated in functional experiments. In conclusion, circulating metabolites are important factors influencing BCG-induced trained immunity in humans. Modulation of metabolic pathways may be a novel strategy to improve vaccine and trained immunity responses.

Metabolomics meets systems immunology.

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Amino Acid Metabolism Subtypes in Neuroblastoma Identifying Distinct Prognosis and Therapeutic Vulnerabilities.

Although amino acid (AA) metabolism is linked to tumor progression and could serve as an attractive intervention target, its association with neuroblastoma (NB) is unknown. Based on AA metabolism-related genes, we established three NB subtypes associated with distinct prognoses and specific functions, with C1 and C2 having better outcomes. The C1 displayed enhanced metabolic activity and recruited metabolism-associated cells. The C2 exhibited an activated immune microenvironment and was more vulnerable to immunotherapy. The C3, characterized by cell cycle peculiarity, possessed a dismal prognosis and high frequency of gene mutations and was susceptible to chemotherapy. Furthermore, single-cell RNA sequencing analysis revealed that the C3-associated Scissor+ cell subpopulation was characterized by notorious functional states and orchestrated an immunosuppressive microenvironment. Additionally, we identified that ALK and BIRC5 contributed to the shorter lifespan of C3 and their corresponding inhibitors were potential interventions. In conclusion, we identified three distinct subtypes of NB, which help us foster individualized therapeutic strategies to improve the prognosis of NB.

Urban-rural disparities in the short-term effects of cold and heat on myocardial infarction mortality in Anhui Province, China.

Non-optimal ambient temperatures are risk factors for myocardial infarction (MI) and urban-rural temperature differences in the context of climate change may have caused and will lead to differential association between temperature and MI. We collected daily mean temperature and daily MI deaths from 1 January 2016 to 31 December 2020 in Anhui Province, China. A distributed lag nonlinear model was performed to estimate the area-specific association of heat and cold (defined as the 2.5th and 97.5th percentile of the daily mean temperature) with MI mortality; the random-effects meta-analysis was then used to pool the effects of cold and heat. We found the risk of MI death due to cold was higher in rural areas [relative risk (RR): 1.13, 95% confidence interval (CI): 1.02-1.26, lag0) than in urban areas (RR: 0.99, 95% CI: 0.80-1.21, lag0), whereas the risk of MI death associated with heat was higher in urban areas (RR: 1.14, 95% CI: 1.03-1.27, lag0) than in rural areas (RR: 1.04, 95% CI: 0.99-1.10, lag0). Our findings may help to develop targeted protective strategies to reduce the adverse effects of cold and heat on cardiovascular disease.

Disrupted pattern of rich-club organization in structural brain network from prediabetes to diabetes: A population-based study.

The network nature of the brain is gradually becoming a consensus in the neuroscience field. A set of highly connected regions in the brain network called "rich-club" are crucial high efficiency communication hubs in the brain. The abnormal rich-club organization can reflect underlying abnormal brain function and metabolism, which receives increasing attention. Diabetes is one of the risk factors for neurological diseases, and most individuals with prediabetes will develop overt diabetes within their lifetime. However, the gradual impact of hyperglycemia on brain structures, including rich-club organization, remains unclear. We hypothesized that the brain follows a special disrupted pattern of rich-club organization in prediabetes and diabetes. We used cross-sectional baseline data from the population-based PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study, which included 2218 participants with a mean age of 61.3 ± 6.6 years and 54.1% females comprising 1205 prediabetes, 504 diabetes, and 509 normal control subjects. The rich-club organization and network properties of the structural networks derived from diffusion tensor imaging data were investigated using a graph theory approach. Linear mixed models were used to assess associations between rich-club organization disruptions and the subjects' glucose status. Based on the graphical analysis methods, we observed the disrupted pattern of rich-club organization was from peripheral regions mainly located in frontal areas to rich-club regions mainly located in subcortical areas from prediabetes to diabetes. The rich-club organization disruptions were associated with elevated glucose levels. These findings provided more details of the process by which hyperglycemia affects the brain, contributing to a better understanding of the potential neurological consequences. Furthermore, the disrupted pattern observed in rich-club organization may serve as a potential neuroimaging marker for early detection and monitoring of neurological disorders in individuals with prediabetes or diabetes.

Regulation of Charge Transfer Pathway in Ag-ZnIn2S4 Nanowires for Visible Photodynamic Therapy on Candida Albicans Infections.

Photodynamic therapy (PDT) is receiving extensive attention as an antimicrobial strategy that does not cause drug resistance by reactive oxygen species (ROS). Herein, hierarchical Ag-ZnIn2S4 (Ag-ZIS) core-shell nanowires are synthesized by in situ Metal-Organic Framework derived method for efficient PDT of Candida albicans (C. albicans). The core-shell structure enables spatial synergy strategy to regulate the charge transfer pathway under visible light excitation, in which the Ag nanowires are like the highway for the photogenerated electrons. The enhanced charge carrier separation efficiency greatly increased the chances for the generation of ROS. As expected, the optimized Ag-ZIS nanowires exhibit excellent performance for inactivation of C. albicans under visible light irradiation (λ ≥ 420 nm, 15 min), and the effective sterilization concentration is as high as 107CFU mL-1. Moreover, in vivo infection experiments suggested that the PDT effect of Ag-ZIS nanowires on the mouse wound healing is better than that of the clinical Ketoconazole drug. The PDT antifungal mechanism of Ag-ZIS nanowires is also investigated, and superoxide anion is found to be the predominant active species to causes C. albicans damage. This work provides a new perspective for designing novel interface structures to regulate charge transfer to achieve efficient PDT antifungal therapy.

SLEMM: million-scale genomic predictions with window-based SNP weighting.

MOTIVATION: The amount of genomic data is increasing exponentially. Using many genotyped and phenotyped individuals for genomic prediction is appealing yet challenging. RESULTS: We present SLEMM (short for Stochastic-Lanczos-Expedited Mixed Models), a new software tool, to address the computational challenge. SLEMM builds on an efficient implementation of the stochastic Lanczos algorithm for REML in a framework of mixed models. We further implement SNP weighting in SLEMM to improve its predictions. Extensive analyses on seven public datasets, covering 19 polygenic traits in three plant and three livestock species, showed that SLEMM with SNP weighting had overall the best predictive ability among a variety of genomic prediction methods including GCTA's empirical BLUP, BayesR, KAML, and LDAK's BOLT and BayesR models. We also compared the methods using nine dairy traits of ∼300k genotyped cows. All had overall similar prediction accuracies, except that KAML failed to process the data. Additional simulation analyses on up to 3 million individuals and 1 million SNPs showed that SLEMM was advantageous over counterparts as for computational performance. Overall, SLEMM can do million-scale genomic predictions with an accuracy comparable to BayesR. AVAILABILITY AND IMPLEMENTATION: The software is available at https://github.com/jiang18/slemm.

Two lysin motif extracellular (LysMe) proteins are deployed in rice to facilitate arbuscular mycorrhizal symbiosis.

During arbuscular mycorrhizal (AM) symbiosis, plant innate immunity is modulated to a prime state to allow for fungal colonization. The underlying mechanisms remain to be further explored. In this study, two rice genes encoding LysM extracellular (LysMe) proteins were investigated. By obtaining OsLysMepro:GUS transgenic plants and generating oslysme1, oslysme2 and oslysme1oslysme2 mutants via CRISPR/Cas9 technique, OsLysMe genes were revealed to be specifically induced in the arbusculated cells and mutations in either gene caused significantly reduced root colonization rate by AM fungus Rhizophagus irregularis. Overexpression of OsLysMe1 or OsLysMe2 dramatically increased the colonization rates in rice and Medicago truncatula. The electrophoretic mobility shift assay and dual-luciferase reporter assay supported that OsLysMe genes are regulated by OsWRI5a. Either OsLysMe1 or OsLysMe2 can efficiently rescue the impaired AM phenotype of the mtlysme2 mutant, supporting a conserved function of LysMe across monocotyledonous and dicotyledonous plants. The co-localization of OsLysMe proteins with the apoplast marker SP-OsRAmy3A implies their probable localization to the periarbuscular space (PAS) during symbiosis. Relative to the fungal biomass marker RiTEF, some defense-related genes showed disproportionately high expression levels in the oslysme mutants. These data support that rice plants deploy two OsLysMe proteins to facilitate AM symbiosis, likely by diminishing plant defense responses.

Efficient second harmonic generation in a high-Q Fabry-Perot microresonator on x-cut thin film lithium niobate.

Microresonators facilitate enhanced light-matter interactions within a limited space, showing great promise for nonlinear optics. Here, we demonstrate a high-quality (Q) factor Fabry-Perot microresonator (FPR) for second harmonic generation (SHG) on an x-cut thin film lithium niobate (TFLN) platform. The FPR exhibits Q factors of Qpump = 1.09 × 105 and QSH = 1.15 × 104 at the 1560 nm pump wavelength and 780 nm second harmonic wavelength, respectively. Under low pump power, a normalized SHG efficiency of 158.5 ± 18.5%/W is attained. We experimentally verify that increased temperatures mitigate photorefractive effects that degrade SHG performance. This work highlights the immense capabilities of one-dimensional planar optical waveguide resonators for efficient on-chip nonlinear wavelength conversion.

Robust and high-efficiency dynamical method of enantio-specific state transfer.

We propose a simple dynamical method to realize fast enantio-specific state transfer (ESST) of chiral molecules. Driven by three external electromagenetic fields, the chiral molecules are modeled as cyclic three-level systems, where the overall phase differs by π for the left- and right-handed chiral molecules. We unveil that the ESST is allowed when the amplitudes of three Rabi frequencies in the cyclic three-level systems are equal. Our method is robust and highly efficient in the sense that the external fields can have arbitrary waveforms. This thus provides the opportunity of simplifying the experimental implementations of ESST through pulse design.

Sr2[B5O8(OH)]2 ⋠[B(OH)3] ⋠H2O: A Strontium Borate That Shows Deep-Ultraviolet-Transparent Nonlinear Optical Properties.

A new noncentrosymmetric strontium borate, P1-Sr2[B5O8(OH)]2 ⋅ [B(OH)3] ⋅ H2O (1), has been synthesized under the hydrothermal condition. The P1-Sr2[B5O8(OH)]2 ⋅ [B(OH)3] ⋅ H2O shows a layered B-O network with 9-ring windows in the ab plane. Sr2+ cations, H3BO3, and H2O molecules are located in the voids of layers and interlayers, respectively. The P1-Sr2[B5O8(OH)]2 ⋅ [B(OH)3] ⋅ H2O is the first synthetic phase of veatchite, while the other three polymorphs are found in different natural minerals. This strontium borate is a potential deep-ultraviolet-transparent nonlinear-optical (NLO) crystal whose second-harmonic-generation (SHG) intensity is 1.7 times that of KH2PO4 (KDP) and is phase-matchable. The short wavelength cutoff edge of compound 1 is below 190 nm. Density functional theory (DFT) calculations show that the B-O units are responsible for the nonlinear optical property.

Survival benefit of adjuvant TACE for patients with hepatocellular carcinoma and child-pugh B7 or B8 after hepatectomy.

BACKGROUND & AIMS: The benefit of postoperative adjuvant transcatheter arterial chemoembolization (pTACE) for patients with hepatocellular carcinoma (HCC), especially those with Child-Pugh (CP) B, remains controversial. This study aimed to assess the survival benefit of pTACE for HCC patients with CP B. METHODS: Data from 297 HCC patients with CP B7 or B8 were analyzed, dividing them into groups with and without pTACE (70, 23.6% vs. 227, 76.4%). Propensity score matching (PSM) was used to control for confounding bias, and competing-risk regression was applied to address bias from non-cancer-specific death (NCSD). RESULTS: Preliminary findings suggest that pTACE did not increase the incidence of severe complications in HCC patients with CP B7 or B8. Survival analysis indicated that the group receiving pTACE had better overall survival and recurrence-free survival than the group without pTACE after PSM. Furthermore, competitive risk analysis revealed that pTACE was an independent prognostic factor associated with reduced cancer-specific death incidence (subdistribution hazard ratio [SHR] 0.644, 95%CI: 0.378-0.784, P = 0.011) and recurrence (SHR 0.635, 95% CI: 0.379-0.855, P = 0.001). Importantly, pTACE did not increase NCSD. Subgroup analysis corroborated these results. CONCLUSION: Adjuvant TACE demonstrates the potential to significantly enhance the long-term prognosis of HCC patients with CP B7 or B8 following hepatectomy, particularly those with multiple tumors, large tumor size, macrovascular or microvascular invasion, and narrow resection margin. Hence, pTACE should be considered for patients at high risk of recurrence following thorough evaluation.

Comparison of percutaneous microwave/radiofrequency ablation liver partition and portal vein embolization versus transarterial chemoembolization and portal vein embolization for planned hepatectomy with insufficient future liver remnant.

BACKGROUND: In China, both percutaneous microwave/radiofrequency ablation liver partition plus portal vein embolization (PALPP) and transarterial chemoembolization (TACE) plus portal vein embolization (PVE) have been utilized in planned hepatectomy. However, there is a lack of comparative studies on the effectiveness of these two techniques for cases with insufficient future liver remnant (FLR). METHODS: Patients were categorized into either the PALPP group or the TACE + PVE group. Clinical data, including FLR growth rate, complications, secondary resection rate, and overall survival rate, were compared and analyzed for both groups retrospectively. RESULTS: Between December 2014 and October 2021, a total of 29 patients underwent TACE + PVE (n = 12) and PALPP (n = 17). In the TACE + PVE group, 7 patients successfully underwent two-stage hepatectomy, while in the PALPP group, 13 patients underwent the procedure (two-stage resection rate: 58.3% vs. 76.5%, P = 0.42). There were no significant differences in postoperative complications of one-stage procedures (11.8% vs. 8.3%, P > 0.05) and second-stage resection complication (0% vs. 46.2%, P = 0.05) between the TACE + PVE and PALPP groups. However, the PALPP group demonstrated a shorter time to FLR volume growth for second-stage resection (18.5 days vs. 66 days, P = 0.001) and KGR (58.5 ml/week vs. 7.7 ml/week, P = 0.001). CONCLUSIONS: Compared with TACE + PVE, PALPP results in a more significant increase in FLR volume and a higher rate of two-stage resection without increasing postoperative complications.

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.

BACKGROUND: Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown. RESULT: We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age. CONCLUSION: DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.