Mucus-degrading Bacteroides link carbapenems to aggravated graft-versus-host disease.

The intestinal microbiota is an important modulator of graft-versus-host disease (GVHD), which often complicates allogeneic hematopoietic stem cell transplantation (allo-HSCT). Broad-spectrum antibiotics such as carbapenems increase the risk for intestinal GVHD, but mechanisms are not well understood. In this study, we found that treatment with meropenem, a commonly used carbapenem, aggravates colonic GVHD in mice via the expansion of Bacteroides thetaiotaomicron (BT). BT has a broad ability to degrade dietary polysaccharides and host mucin glycans. BT in meropenem-treated allogeneic mice demonstrated upregulated expression of enzymes involved in the degradation of mucin glycans. These mice also had thinning of the colonic mucus layer and decreased levels of xylose in colonic luminal contents. Interestingly, oral xylose supplementation significantly prevented thinning of the colonic mucus layer in meropenem-treated mice. Specific nutritional supplementation strategies, including xylose supplementation, may combat antibiotic-mediated microbiome injury to reduce the risk for intestinal GVHD in allo-HSCT patients.

Large-Scale Comparative Analyses of Tick Genomes Elucidate Their Genetic Diversity and Vector Capacities.

Among arthropod vectors, ticks transmit the most diverse human and animal pathogens, leading to an increasing number of new challenges worldwide. Here we sequenced and assembled high-quality genomes of six ixodid tick species and further resequenced 678 tick specimens to understand three key aspects of ticks: genetic diversity, population structure, and pathogen distribution. We explored the genetic basis common to ticks, including heme and hemoglobin digestion, iron metabolism, and reactive oxygen species, and unveiled for the first time that genetic structure and pathogen composition in different tick species are mainly shaped by ecological and geographic factors. We further identified species-specific determinants associated with different host ranges, life cycles, and distributions. The findings of this study are an invaluable resource for research and control of ticks and tick-borne diseases.

Earth's early continental crust formed from wet and oxidizing arc magmas.

Formation of continental crust has shaped the surface and interior of our planet and generated the land and mineral resources on which we rely. However, how the early continental crust of Earth formed is still debated1-7. Modern continental crust is largely formed from wet and oxidizing arc magmas at subduction zones, in which oceanic lithosphere and water recycle into the mantle8-10. The magmatic H2O content and redox state of ancient rocks that constitute the early continental crust, however, are difficult to quantify owing to ubiquitous metamorphism. Here we combine two zircon oxybarometers11,12 to simultaneously determine magmatic oxygen fugacity (fO2) and H2O content of Archaean (4.0-2.5 billion years ago) granitoids that dominate the early continental crust. We show that most Archaean granitoid magmas were ≥1 log unit more oxidizing than Archaean ambient mantle-derived magmas13,14 and had high magmatic H2O contents (6-10 wt%) and high H2O/Ce ratios (>1,000), similar to modern arc magmas. We find that magmatic fO2, H2O contents and H2O/Ce ratios of Archaean granitoids positively correlate with depth of magma formation, requiring transport of large amounts of H2O to the lower crust and mantle. These observations can be readily explained by subduction but are difficult to reconcile with non-subduction models of crustal formation3-7. We note an increase in magmatic fO2 and H2O content between 4.0 and 3.6 billion years ago, probably indicating the onset of subduction during this period.

Electrifying HCOOH synthesis from CO2 building blocks over Cu-Bi nanorod arrays.

Precise electrochemical synthesis of commodity chemicals and fuels from CO2 building blocks provides a promising route to close the anthropogenic carbon cycle, in which renewable but intermittent electricity could be stored within the greenhouse gas molecules. Here, we report state-of-the-art CO2-to-HCOOH valorization performance over a multiscale optimized Cu-Bi cathodic architecture, delivering a formate Faradaic efficiency exceeding 95% within an aqueous electrolyzer, a C-basis HCOOH purity above 99.8% within a solid-state electrolyzer operated at 100 mA cm-2 for 200 h and an energy efficiency of 39.2%, as well as a tunable aqueous HCOOH concentration ranging from 2.7 to 92.1 wt%. Via a combined two-dimensional reaction phase diagram and finite element analysis, we highlight the role of local geometries of Cu and Bi in branching the adsorption strength for key intermediates like *COOH and *OCHO for CO2 reduction, while the crystal orbital Hamiltonian population analysis rationalizes the vital contribution from moderate binding strength of η2(O,O)-OCHO on Cu-doped Bi surface in promoting HCOOH electrosynthesis. The findings of this study not only shed light on the tuning knobs for precise CO2 valorization, but also provide a different research paradigm for advancing the activity and selectivity optimization in a broad range of electrosynthetic systems.

The Role of Fc Receptors in the Innate Immune System of Flounders Purported to Be Homologs of FcγRII and FcγRIII.

FcγR is a significant opsonin receptor located on the surface of immune cells, playing a crucial role in Ab-dependent cell-mediated immunity. Our previous work revealed opposite expression trends of FcγRII and FcγRIII in flounder mIgM+ B lymphocytes after phagocytosis of antiserum-opsonized Edwardsiella tarda. This observation suggests that FcγRII and FcγRIII might serve distinct functions in Ig-opsonized immune responses. In this study, we prepared rFcγRIII as well as its corresponding Abs to investigate the potential roles of FcγRII and FcγRIII in the Ab-dependent immune response of IgM+ B cells. Our findings indicate that, unlike FcγRII, FcγRIII does not participate in Ab-dependent cellular phagocytosis. Instead, it is involved in cytokine production and bacterial killing in mIgM+ B lymphocytes. Additionally, we identified platelet-derived ADAM17 as a key factor in regulating FcγRIII shedding and cytokine release in mIgM+ B lymphocytes. These results elucidate the functions of FcγRII and FcγRIII in the innate immunology of mIgM+ B lymphocytes and contribute to an improved understanding of the regulatory roles of FcγRs in the phagocytosis of teleost B lymphocytes.

PROSE: phenotype-specific network signatures from individual proteomic samples.

Proteomic studies characterize the protein composition of complex biological samples. Despite recent advancements in mass spectrometry instrumentation and computational tools, low proteome coverage and interpretability remains a challenge. To address this, we developed Proteome Support Vector Enrichment (PROSE), a fast, scalable and lightweight pipeline for scoring proteins based on orthogonal gene co-expression network matrices. PROSE utilizes simple protein lists as input, generating a standard enrichment score for all proteins, including undetected ones. In our benchmark with 7 other candidate prioritization techniques, PROSE shows high accuracy in missing protein prediction, with scores correlating strongly to corresponding gene expression data. As a further proof-of-concept, we applied PROSE to a reanalysis of the Cancer Cell Line Encyclopedia proteomics dataset, where it captures key phenotypic features, including gene dependency. We lastly demonstrated its applicability on a breast cancer clinical dataset, showing clustering by annotated molecular subtype and identification of putative drivers of triple-negative breast cancer. PROSE is available as a user-friendly Python module from https://github.com/bwbio/PROSE.

ProJect: a powerful mixed-model missing value imputation method.

Missing values (MVs) can adversely impact data analysis and machine-learning model development. We propose a novel mixed-model method for missing value imputation (MVI). This method, ProJect (short for Protein inJection), is a powerful and meaningful improvement over existing MVI methods such as Bayesian principal component analysis (PCA), probabilistic PCA, local least squares and quantile regression imputation of left-censored data. We rigorously tested ProJect on various high-throughput data types, including genomics and mass spectrometry (MS)-based proteomics. Specifically, we utilized renal cancer (RC) data acquired using DIA-SWATH, ovarian cancer (OC) data acquired using DIA-MS, bladder (BladderBatch) and glioblastoma (GBM) microarray gene expression dataset. Our results demonstrate that ProJect consistently performs better than other referenced MVI methods. It achieves the lowest normalized root mean square error (on average, scoring 45.92% less error in RC_C, 27.37% in RC_full, 29.22% in OC, 23.65% in BladderBatch and 20.20% in GBM relative to the closest competing method) and the Procrustes sum of squared error (Procrustes SS) (exhibits 79.71% less error in RC_C, 38.36% in RC full, 18.13% in OC, 74.74% in BladderBatch and 30.79% in GBM compared to the next best method). ProJect also leads with the highest correlation coefficient among all types of MV combinations (0.64% higher in RC_C, 0.24% in RC full, 0.55% in OC, 0.39% in BladderBatch and 0.27% in GBM versus the second-best performing method). ProJect's key strength is its ability to handle different types of MVs commonly found in real-world data. Unlike most MVI methods that are designed to handle only one type of MV, ProJect employs a decision-making algorithm that first determines if an MV is missing at random or missing not at random. It then employs targeted imputation strategies for each MV type, resulting in more accurate and reliable imputation outcomes. An R implementation of ProJect is available at https://github.com/miaomiao6606/ProJect.

OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs.

MOTIVATION: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models have been developed to enhance ligand bioactivity prediction in the presence of ACs. Yet, there remains a largely unexplored opportunity within ACs for optimizing ligand bioactivity, making it an area ripe for further investigation. RESULTS: We present a novel approach to simultaneously predict and optimize ligand bioactivities through DGL and ACs (OLB-AC). OLB-AC possesses the capability to optimize ligand molecules located near ACs, providing a direct reference for optimizing ligand bioactivities with the matching of original ligands. To accomplish this, a novel attentive graph reconstruction neural network and ligand optimization scheme are proposed. Attentive graph reconstruction neural network reconstructs original ligands and optimizes them through adversarial representations derived from their bioactivity prediction process. Experimental results on nine drug targets reveal that out of the 667 molecules generated through OLB-AC optimization on datasets comprising 974 low-activity, noninhibitor, or highly toxic ligands, 49 are recognized as known highly active, inhibitor, or nontoxic ligands beyond the datasets' scope. The 27 out of 49 matched molecular pairs generated by OLB-AC reveal novel transformations not present in their training sets. The adversarial representations employed for ligand optimization originate from the gradients of bioactivity predictions. Therefore, we also assess OLB-AC's prediction accuracy across 33 different bioactivity datasets. Results show that OLB-AC achieves the best Pearson correlation coefficient (r2) on 27/33 datasets, with an average improvement of 7.2%-22.9% against the state-of-the-art bioactivity prediction methods. AVAILABILITY AND IMPLEMENTATION: The code and dataset developed in this work are available at github.com/Yueming-Yin/OLB-AC.

GLK transcription factors accompany ELONGATED HYPOCOTYL5 to orchestrate light-induced seedling development in Arabidopsis.

Light-induced de-etiolation is an important aspect of seedling photomorphogenesis. GOLDEN2 LIKE (GLK) transcriptional regulators are involved in chloroplast development, but to what extent they participate in photomorphogenesis is not clear. Here, we show that ELONGATED HYPOCOTYL5 (HY5) binds to GLK promoters to activate their expression, and also interacts with GLK proteins in Arabidopsis (Arabidopsis thaliana). The chlorophyll content in the de-etiolating Arabidopsis seedlings of the hy5 glk2 double mutants was lower than that in the hy5 single mutant. GLKs inhibited hypocotyl elongation, and the phenotype could superimpose on the hy5 phenotype. Correspondingly, GLK2 regulated the expression of photosynthesis and cell elongation genes partially independent of HY5. Before exposure to light, DE-ETIOLATED 1 (DET1) affected accumulation of GLK proteins. The enhanced etioplast development and photosystem gene expression observed in the det1 mutant were attenuated in the det1 glk2 double mutant. Our study reveals that GLKs act downstream of HY5, or additive to HY5, and are likely quantitatively adjusted by DET1, to orchestrate multiple developmental traits during the light-induced skotomorphogenesis-to-photomorphogenesis transition in Arabidopsis.

Combining full-length gene assay and SpliceAI to interpret the splicing impact of all possible SPINK1 coding variants.

BACKGROUND: Single-nucleotide variants (SNVs) within gene coding sequences can significantly impact pre-mRNA splicing, bearing profound implications for pathogenic mechanisms and precision medicine. In this study, we aim to harness the well-established full-length gene splicing assay (FLGSA) in conjunction with SpliceAI to prospectively interpret the splicing effects of all potential coding SNVs within the four-exon SPINK1 gene, a gene associated with chronic pancreatitis. RESULTS: Our study began with a retrospective analysis of 27 SPINK1 coding SNVs previously assessed using FLGSA, proceeded with a prospective analysis of 35 new FLGSA-tested SPINK1 coding SNVs, followed by data extrapolation, and ended with further validation. In total, we analyzed 67 SPINK1 coding SNVs, which account for 9.3% of the 720 possible coding SNVs. Among these 67 FLGSA-analyzed SNVs, 12 were found to impact splicing. Through detailed comparison of FLGSA results and SpliceAI predictions, we inferred that the remaining 653 untested coding SNVs in the SPINK1 gene are unlikely to significantly affect splicing. Of the 12 splice-altering events, nine produced both normally spliced and aberrantly spliced transcripts, while the remaining three only generated aberrantly spliced transcripts. These splice-impacting SNVs were found solely in exons 1 and 2, notably at the first and/or last coding nucleotides of these exons. Among the 12 splice-altering events, 11 were missense variants (2.17% of 506 potential missense variants), and one was synonymous (0.61% of 164 potential synonymous variants). Notably, adjusting the SpliceAI cut-off to 0.30 instead of the conventional 0.20 would improve specificity without reducing sensitivity. CONCLUSIONS: By integrating FLGSA with SpliceAI, we have determined that less than 2% (1.67%) of all possible coding SNVs in SPINK1 significantly influence splicing outcomes. Our findings emphasize the critical importance of conducting splicing analysis within the broader genomic sequence context of the study gene and highlight the inherent uncertainties associated with intermediate SpliceAI scores (0.20 to 0.80). This study contributes to the field by being the first to prospectively interpret all potential coding SNVs in a disease-associated gene with a high degree of accuracy, representing a meaningful attempt at shifting from retrospective to prospective variant analysis in the era of exome and genome sequencing.

Ten quick tips for ensuring machine learning model validity.

Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips described here discuss useful practices on how to check AI/ML models from 2 perspectives-the user and the developer.

Heterozygous variants in USP25 cause genetic generalized epilepsy.

USP25 encodes ubiquitin-specific protease 25, a key member of the deubiquitinating enzyme family that is involved in neural fate determination. Although abnormal expression in Down's syndrome was reported previously, the specific role of USP25 in human diseases has not been defined. In this study, we performed trio-based whole exome sequencing in a cohort of 319 cases (families) with generalized epilepsy of unknown aetiology. Five heterozygous USP25 variants, including two de novo and three co-segregated variants, were determined in eight individuals affected by generalized seizures and/or febrile seizures from five unrelated families. The frequency of USP25 variants showed a significantly high aggregation in this cohort compared with the East Asian population and all populations in the gnomAD database. The mean age at onset of febrile and afebrile seizures were 10 months (infancy) and 11.8 years (juvenile), respectively. The patients achieved seizure freedom, except that one had occasional nocturnal seizures at the last follow-up. Two patients exhibited intellectual disability. Usp25 was expressed ubiquitously in mouse brain with two peaks, on embryonic Days 14-16 and postnatal Day 21, respectively. In human brain, likewise, USP25 is expressed in the fetus/early childhood stage and with a second peak at ∼12-20 years old, consistent with the seizure onset age in patients during infancy and in juveniles. To investigate the functional impact of USP25 deficiency in vivo, we established Usp25 knockout mice, which showed increased seizure susceptibility compared with wild-type mice in a pentylenetetrazol-induced seizure test. To explore the impact of USP25 variants, we used multiple functional detections. In HEK293 T cells, the variant associated with a severe phenotype (p.Gln889Ter) led to a significant reduction of mRNA and protein expressions but formed stable truncated dimers with an increment of deubiquitinating enzyme activities and abnormal cellular aggregations, indicating a gain-of-function effect. The p.Gln889Ter and p.Leu1045del variants increased neuronal excitability in mouse brain, with a higher firing ability in p.Gln889Ter. These functional impairments align with the severity of the observed phenotypes, suggesting a genotype-phenotype correlation. Hence, a moderate association between USP25 and epilepsy was noted, indicating that USP25 is potentially a predisposing gene for epilepsy. Our results from Usp25 null mice and the patient-derived variants indicated that USP25 would play an epileptogenic role via loss-of-function or gain-of-function effects. The truncated variant p.Gln889Ter would have a profoundly different effect on epilepsy. Together, our results underscore the significance of USP25 heterozygous variants in epilepsy, thereby highlighting the critical role of USP25 in the brain.

Superantigen-fused T cell engagers for tumor antigen-mediated robust T cell activation and tumor cell killing.

Inadequate T cell activation has severely limited the success of T cell engager (TCE) therapy, especially in solid tumors. Enhancing T cell activity while maintaining the tumor specificity of TCEs is the key to improving their clinical efficacy. However, currently, there needs to be more effective strategies in clinical practice. Here, we design novel superantigen-fused TCEs that display robust tumor antigen-mediated T cell activation effects. These innovative drugs are not only armed with the powerful T cell activation ability of superantigens but also retain the dependence of TCEs on tumor antigens, realizing the ingenious combination of the advantages of two existing drugs. Superantigen-fused TCEs have been preliminarily proven to have good (>30-fold more potent) and specific (>25-fold more potent) antitumor activity in vitro and in vivo. Surprisingly, they can also induce the activation of T cell chemotaxis signals, which may promote T cell infiltration and further provide an additional guarantee for improving TCE efficacy in solid tumors. Overall, this proof-of-concept provides a potential strategy for improving the clinical efficacy of TCEs.

Gene delivery available in molluscan cells by strong promoter discovered from bivalve-infectious virus.

Understanding gene functions in marine invertebrates has been limited, largely due to the lack of suitable assay systems. Such a system requires investigative methods that are reproducible and can be quantitatively evaluated, such as a cell line, and a strong promoter that can drive high expression of a transgene. In this study, we established primary cell culture from a marine bivalve mollusc, Mizuhopecten yessoensis. Using scallop primary cells, we optimized electroporation conditions for transfection and carried out a luciferase-based promoter activity assay to identify strong promoter sequences that can drive expression of a gene of interest. We evaluated potential promoter sequences from genes of endogenous and exogenous origin and discovered a strong viral promoter derived from a bivalve-infectious virus, ostreid herpesvirus-1 (OsHV-1). This promoter, we termed OsHV-1 promoter, showed 24.7-fold and 16.1-fold higher activity than the cytomegalovirus immediate early (CMV IE) promoter and the endogenous EF1α promoter, the two most commonly used promoters in bivalves so far. Our GFP assays showed that the OsHV-1 promoter is active not only in scallop cells but also in HEK293 cells and zebrafish embryos. The OsHV-1 promoter practically enables functional analysis of marine molluscan genes, which can contribute to unveiling gene-regulatory networks underlying astonishing regeneration, adaptation, reproduction, and aging in marine invertebrates.

What can molecular assembly learn from catalysed assembly in living organisms?

Molecular assembly is the process of organizing individual molecules into larger structures and complex systems. The self-assembly approach is predominantly utilized in creating artificial molecular assemblies, and was believed to be the primary mode of molecular assembly in living organisms as well. However, it has been shown that the assembly of many biological complexes is "catalysed" by other molecules, rather than relying solely on self-assembly. In this review, we summarize these catalysed-assembly (catassembly) phenomena in living organisms and systematically analyse their mechanisms. We then expand on these phenomena and discuss related concepts, including catalysed-disassembly and catalysed-reassembly. Catassembly proves to be an efficient and highly selective strategy for synergistically controlling and manipulating various noncovalent interactions, especially in hierarchical molecular assemblies. Overreliance on self-assembly may, to some extent, hinder the advancement of artificial molecular assembly with powerful features. Furthermore, inspired by the biological catassembly phenomena, we propose guidelines for designing artificial catassembly systems and developing characterization and theoretical methods, and review pioneering works along this new direction. Overall, this approach may broaden and deepen our understanding of molecular assembly, enabling the construction and control of intelligent assembly systems with advanced functionality.

A Bioinspired Gradient Design Strategy for Cellulose-Based Electromagnetic Wave Absorbing Structural Materials.

Cellulose nanofiber (CNF) possesses excellent intrinsic properties, and many CNF-based high-performance structural and functional materials have been developed recently. However, the coordination of the mechanical properties and functionality is still a considerable challenge. Here, a CNF-based structural material is developed by a bioinspired gradient structure design using hollow magnetite nanoparticles and the phosphorylation-modified CNF as building blocks, which simultaneously achieves a superior mechanical performance and electromagnetic wave absorption (EMA) ability. Benefiting from the gradient design, the flexural strength of the structural material reached ∼205 MPa. Meanwhile, gradient design improves impedance matching, contributing to the high EMA ability (-59.5 dB) and wide effective absorption width (5.20 GHz). Besides, a low coefficient of thermal expansion and stable storage modulus was demonstrated as the temperature changes. The excellent mechanical, thermal, and EMA performance exhibited great potential for application in stealth equipment and electromagnetic interference protecting electronic packaging materials.

Pancreas-directed AAV8-hSPINK1 gene therapy safely and effectively protects against pancreatitis in mice.

OBJECTIVE: Currently, there is no cure for chronic pancreatitis (CP). Germline loss-of-function variants in SPINK1 (encoding trypsin inhibitor) are common in patients with CP and are associated with acute attacks and progression of the disease. This preclinical study was conducted to explore the potential of adeno-associated virus type 8 (AAV8)-mediated overexpression of human SPINK1 (hSPINK1) for pancreatitis therapy in mice. DESIGN: A capsid-optimised AAV8-mediated hSPINK1 expression vector (AAV8-hSPINK1) to target the pancreas was constructed. Mice were treated with AAV8-hSPINK1 by intraperitoneal injection. Pancreatic transduction efficiency and safety of AAV8-hSPINK1 were dynamically evaluated in infected mice. The effectiveness of AAV8-hSPINK1 on pancreatitis prevention and treatment was studied in three mouse models (caerulein-induced pancreatitis, pancreatic duct ligation and Spink1 c.194+2T>C mouse models). RESULTS: The constructed AAV8-hSPINK1 vector specifically and safely targeted the pancreas, had low organ tropism for the heart, lungs, spleen, liver and kidneys and had a high transduction efficiency (the optimal expression dose was 2×1011 vg/animal). The expression and efficacy of hSPINK1 peaked at 4 weeks after injection and remained at significant level for up to at least 8 weeks. In all three mouse models, a single dose of AAV8-hSPINK1 before disease onset significantly alleviated the severity of pancreatitis, reduced the progression of fibrosis, decreased the levels of apoptosis and autophagy in the pancreas and accelerated the pancreatitis recovery process. CONCLUSION: One-time injection of AAV8-hSPINK1 safely targets the pancreas with high transduction efficiency and effectively ameliorates pancreatitis phenotypes in mice. This approach is promising for the prevention and treatment of CP.

Optimizing the PROTREC network-based missing protein prediction algorithm.

This article summarizes the PROTREC method and investigates the impact that the different hyper-parameters have on the task of missing protein prediction using PROTREC. We evaluate missing protein recovery rates using different PROTREC score selection approaches (MAX, MIN, MEDIAN, and MEAN), different PROTREC score thresholds, as well as different complex size thresholds. In addition, we included two additional cancer datasets in our analysis and introduced a new validation method to check both the robustness of the PROTREC method as well as the correctness of our analysis. Our analysis showed that the missing protein recovery rate can be improved by adopting PROTREC score selection operations of MIN, MEDIAN, and MEAN instead of the default MAX. However, this may come at a cost of reduced numbers of proteins predicted and validated. The users should therefore choose their hyper-parameters carefully to find a balance in the accuracy-quantity trade-off. We also explored the possibility of combining PROTREC with a p-value-based method (FCS) and demonstrated that PROTREC is able to perform well independently without any help from a p-value-based method. Furthermore, we conducted a downstream enrichment analysis to understand the biological pathways and protein networks within the cancerous tissues using the recovered proteins. Missing protein recovery rate using PROTREC can be improved by selecting a different PROTREC score selection method. Different PROTREC score selection methods and other hyper-parameters such as PROTREC score threshold and complex size threshold introduce accuracy-quantity trade-off. PROTREC is able to perform well independently of any filtering using a p-value-based method. Verification of the PROTREC method on additional cancer datasets. Downstream Enrichment Analysis to understand the biological pathways and protein networks in cancerous tissues.

The novel thromboxane prostanoid receptor mediates CTGF production to drive human nasal fibroblast self-migration through NF-κB and PKCδ-CREB signaling pathways.

Chronic rhinosinusitis without nasal polyp (CRSsNP) is characterized by tissue repair/remodeling and the subepithelial stroma region in whose nasal mucosa has been reported by us to have thromboxane A2 (TXA2) prostanoid (TP) receptor and overexpress connective tissue growth factor (CTGF). Therefore, this study aimed to investigate the relationship between TP receptor activation and CTGF production/function in human CRSsNP nasal mucosa stromal fibroblasts. We found that TP agonists including U46619 and IBOP ([1S-[1α,2α(Z),3ß(1E,3 S*),4α]]-7-[3-[3-hydroxy-4-(4-iodophenoxy)-1-butenyl]-7-oxabicyclo[2.2.1]hept-2-yl]-5-heptenoic acid) could promote CTGF protein/messenger RNA expression and secretion. The pharmacological intervention and TP activation assay with U46619 identified the possible participation of PKCµ, PKCδ, nuclear factor-κB (NF-κB), and cyclic AMP response element-binding protein (CREB) phosphorylation/activation in the CTGF induction. Moreover, a phorbol ester-phorbol-12-myristate 13-acetate (PMA) exhibited a similar cellular signaling and CTGF production profile to that elicited by TP activation. However, further small interfering RNA interference analysis revealed that only NF-κB and PKCδ-CREB pathways were necessarily required for TP-mediated CTGF production, which could not be completely supported by those findings from PMA. Finally, in a functional assay, although CTGF did not affect fibroblast proliferation, TP-mediated CTGF could drive novel self-migration in fibroblasts both in the scratch/wound healing and transwell apparatus assays. Meanwhile, the overall staining for stress fibers and formation of the lamellipodia and filopodia-like structures was concomitantly increased in the treated migrating cells. Collectively, we provided here that novel TP mediates CTGF production and self-migration in human nasal fibroblasts through NF-κB and PKCδ-CREB signaling pathways. More importantly, we also demonstrated that thromboxane, TP receptor, CTGF, and stromal fibroblasts may act in concert in the tissue remodeling/repair process during CRSsNP development and progression.

Variations and reduction of plastome are associated with the evolution of parasitism in Convolvulaceae.

Parasitic lifestyle can often relax the constraint on the plastome, leading to gene pseudogenization and loss, and resulting in diverse genomic structures and rampant genome degradation. Although several plastomes of parasitic Cuscuta have  been reported, the evolution of parasitism in the family Convolvulaceae which is linked to structural variations and reduction of plastome has not been well investigated. In this study, we assembled and collected 40 plastid genomes belonging to 23 species representing four subgenera of Cuscuta and ten species of autotrophic Convolvulaceae. Our findings revealed nine types of structural variations and six types of inverted repeat (IR) boundary variations in the plastome of Convolvulaceae spp. These structural variations were associated with the shift of parasitic lifestyle, and IR boundary shift, as well as the abundance of long repeats. Overall, the degradation of Cuscuta plastome proceeded gradually, with one clade exhibiting an accelerated degradation rate. We observed five stages of gene loss in Cuscuta, including NAD(P)H complex → PEP complex → Photosynthesis-related → Ribosomal protein subunits → ATP synthase complex. Based on our results, we speculated that the shift of parasitic lifestyle in early divergent time promoted relaxed selection on plastomes, leading to the accumulation of microvariations, which ultimately resulted in the plastome reduction. This study provides new evidence towards a better understanding of plastomic evolution, variation, and reduction in the genus Cuscuta.