Structural basis for transcription activation through cooperative recruitment of MntR.

The manganese transport regulator (MntR) from B. subtilis is a dual regulatory protein that responds to heightened Mn 2+ availability in the cell by both repressing the expression of uptake transporters and activating the expression of efflux proteins. Recent work indicates that, in its role as an activator, MntR binds several sites upstream of the genes encoding Mn 2+ exporters, leading to a cooperative response to manganese. Here, we use cryo-EM to explore the molecular basis of gene activation by MntR and report a structure of four MntR dimers bound to four 18-base pair sites across an 84-base pair regulatory region of the mneP promoter. Our structures, along with solution studies including mass photometry and in vivo transcription assays, reveal that MntR dimers employ polar and non-polar contacts to bind cooperatively to an array of low-affinity DNA-binding sites. These results reveal the molecular basis for cooperativity in the activation of manganese efflux.

Structural basis for transcription activation through cooperative recruitment of MntR.

The manganese transport regulator (MntR) from B. subtilis is a dual regulatory protein that responds to heightened Mn 2+ availability in the cell by both repressing the expression of uptake transporters and activating the expression of efflux proteins. Recent work indicates that, in its role as an activator, MntR binds several sites upstream of the genes encoding Mn 2+ exporters, leading to a cooperative response to manganese. Here, we use cryo-EM to explore the molecular basis of gene activation by MntR and report a structure of four MntR dimers bound to four 18-base pair sites across an 84-base pair regulatory region of the mneP promoter. Our structures, along with solution studies including mass photometry and in vivo transcription assays, reveal that MntR dimers employ polar and non-polar contacts to bind cooperatively to an array of low-affinity DNA-binding sites. These results reveal the molecular basis for cooperativity in the activation of manganese efflux.

Walnut-Derived Peptides Alleviate Learning and Memory Impairments in a Mice Model via Inhibition of Microglia Phagocytose Synapses.

Microglia phagocytose synapses have an important effect on the pathogenesis of neurological disorders. Here, we investigated the neuroprotective effects of the walnut-derived peptide, TWLPLPR(TW-7), against LPS-induced cognitive deficits in mice and explored the underlying C1q-mediated microglia phagocytose synapses mechanisms in LPS-treated HT22 cells. The MWM showed that TW-7 improved the learning and memory capacity of the LPS-injured mice. Both transmission electron microscopy and immunofluorescence analysis illustrated that synaptic density and morphology were increased while associated with the decreased colocalized synapses with C1q. Immunohistochemistry and immunofluorescence demonstrated that TW-7 effectively reduced the microglia phagocytosis of synapses. Subsequently, overexpression of C1q gene plasmid was used to verify the contribution of the TW-7 via the classical complement pathway-regulated mitochondrial function-mediated microglia phagocytose synapses in LPS-treated HT22 cells. These data suggested that TW-7 improved the learning and memory capability of LPS-induced cognitively impaired mice through a mechanism associated with the classical complement pathway-mediated microglia phagocytose synapse.

Bioinspired Genetic and Chemical Engineering of Protein Hydrogels for programable Multi-responsive Actuation.

Protein hydrogels with tailored stimuli-responsive features and tunable stiffness have garnered considerable attention due to the growing demand for biomedical soft robotics. However, integrating multiple responsive features toward intelligent yet biocompatible actuators remains challenging. Here, we report a facile approach that synergistically combines genetic and chemical engineering for the design of protein hydrogel actuators with programable complex spatial deformation. Genetically engineered silk-elastin-like proteins (SELPs) were encoded with stimuli-responsive motifs and enzymatic crosslinking sites via simulation-guided genetic engineering strategies. Chemical modifications of the recombinant proteins were also used as secondary control points to tailor material properties, responsive features, and anisotropy in SELP hydrogels. As a proof-of-concept example, diazonium coupling chemistry was exploited to incorporate sulfanilic acid groups onto the tyrosine residues in the elastin domains of SELPs to achieve patterned SELP hydrogels. These hydrogels can be programmed to perform various actuations, including controllable bending, buckling, and complex deformation under external stimuli, such as temperature, ionic strength, or pH. With the inspiration of genetic and chemical engineering in natural organisms, this work offers a predictable, tunable, and environmentally sustainable approach for the fabrication of programmed intelligent soft actuators, with implications for a variety of biomedical materials and bio-robotics needs. This article is protected by copyright. All rights reserved.

Effects of neonicotinoid residues on non-target soil animals: A case study of meta-analysis.

Neonicotinoids (NEOs) are currently the fastest-growing and most widely used insecticide class worldwide. Increasing evidence suggests that long-term NEO residues in the environment have toxic effects on non-target soil animals. However, few studies have conducted surveys on the effects of NEOs on soil animals, and only few have focused on global systematic reviews or meta-analysis to quantify the effects of NEOs on soil animals. Here, we present a meta-analysis of 2940 observations from 113 field and laboratory studies that investigated the effects of NEOs (at concentrations of 0.001-78,600.000 mg/kg) on different soil animals across five indicators (i.e., survival, growth, behavior, reproduction, and biochemical biomarkers). Furthermore, we quantify the effects of NEOs on different species of soil animals. Results show that NEOs inhibit the survival, growth rate, behavior, and reproduction of soil animals, and alter biochemical biomarkers. Both the survival rate and longevity of individuals decreased by 100 % with NEO residues. The mean values of juvenile survival, cocoon number, and egg hatchability were reduced by 97 %, 100 %, and 84 %, respectively. Both individual and cocoon weights were reduced by 82 %, while the growth rate decreased by 88 % with NEO residues. Our meta-analysis confirms that NEOs pose significant negative impacts on soil animals.

Exploring the S Protein of SARS-CoV-2 to Design a Novel Multi-Epitope Vaccine against COVID-19 Based on Immunoinformatics Approaches.

BACKGROUND: Developing a novel COVID-19 multi-epitope vaccine (CoVMEV) is essential to containing the SARS-CoV-2 pandemic. METHODS: The virus's immunodominant B and T cell epitopes from the S protein were found and joined to create the CoVMEV. Bioinformatics techniques were used to investigate the secondary and tertiary structures, as well as the physical and chemical properties of CoVMEV. RESULTS: CoVMEV exhibited high antigenicity and immunogenicity scores, together with good water solubility and stability. Toll-like receptor 2 (TLR2) and toll-like receptor4 (TLR4), which are critical in triggering immunological responses, were also strongly favoured by CoVMEV. Molecular dynamics simulation and immune stimulation studies revealed that CoVMEV effectively activated T and B lymphocytes, and increased the number of active CD8+ T cells than similar vaccines. CONCLUSION: CoVMEV holds promise as a potential vaccine candidate for COVID-19, given its robust immunogenicity, stability, antigenicity, and capacity to stimulate a strong immune response. This study presents a significant design concept for the development of peptidyl vaccines targeting SARS-CoV-2. Further investigation and clinical trials will be crucial in assessing the efficacy and safety of CoVMEV as a potential vaccine for COVID-19.

Biomimetic Nanovesicles as a Dual Gene Delivery System for the Synergistic Gene Therapy of Alzheimer's Disease.

The association between dysfunctional microglia and amyloid-ß (Aß) is a fundamental pathological event and increases the speed of Alzheimer's disease (AD). Additionally, the pathogenesis of AD is intricate and a single drug may not be enough to achieve a satisfactory therapeutic outcome. Herein, we reported a facile and effective gene therapy strategy for the modulation of microglia function and intervention of Aß anabolism by ROS-responsive biomimetic exosome-liposome hybrid nanovesicles (designated as TSEL). The biomimetic nanovesicles codelivery ß-site amyloid precursor protein cleaving enzyme-1 (BACE1) siRNA (siBACE1) and TREM2 plasmid (pTREM2) gene drug efficiently penetrate the blood-brain barrier and enhance the drug accumulation at AD lesions with the help of exosomes homing ability and angiopep-2 peptides. Specifically, an upregulation of TREM2 expression can reprogram microglia from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype while also restoring its capacity to phagocytose Aß and its nerve repair function. In addition, siRNA reduces the production of Aß plaques at the source by knocking out the BACE1 gene, which is expected to further enhance the therapeutic effect of AD. The in vivo study suggests that TSEL through the synergistic effect of two gene drugs can ameliorate APP/PS1 mice cognitive impairment by regulating the activated microglial phenotype, reducing the accumulation of Aß, and preventing the retriggering of neuroinflammation. This strategy employs biomimetic nanovesicles for the delivery of dual nucleic acids, achieving synergistic gene therapy for AD, thus offering more options for the treatment of AD.

T cells, NK cells, and tumor-associated macrophages in cancer immunotherapy and the current state of the art of drug delivery systems.

The immune system provides full protection for the body by specifically identifying 'self' and removing 'others'; thus protecting the body from diseases. The immune system includes innate immunity and adaptive immunity, which jointly coordinate the antitumor immune response. T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are the main tumor-killing immune cells active in three antitumor immune cycle. Cancer immunotherapy focusses on activating and strengthening immune response or eliminating suppression from tumor cells in each step of the cancer-immunity cycle; thus, it strengthens the body's immunity against tumors. In this review, the antitumor immune cycles of T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are discussed. Co-stimulatory and co-inhibitory molecules in the three activity cycles and the development of drugs and delivery systems targeting these molecules are emphasized, and the current state of the art of drug delivery systems for cancer immunotherapy are summarized.

A Reactive Oxygen Species-Responsive Targeted Nanoscavenger to Promote Mitophagy for the Treatment of Alzheimer's Disease.

Mitophagy modulators are proposed as potential therapeutic intervention that enhance neuronal health and brain homeostasis in Alzheimer's disease (AD). Nevertheless, the lack of specific mitophagy inducers, low efficacies, and the severe side effects of nonselective autophagy during AD treatment have hindered their application. In this study, the P@NB nanoscavenger is designed with a reactive-oxygen-species-responsive (ROS-responsive) poly(l-lactide-co-glycolide) core and a surface modified with the Beclin1 and angiopoietin-2 peptides. Notably, nicotinamide adenine dinucleotide (NAD+ ) and Beclin1, which act as mitophagy promoters, are quickly released from P@NB in the presence of high ROS levels in lesions to restore mitochondrial homeostasis and induce microglia polarization toward the M2-type, thereby enabling it to phagocytose amyloid-peptide (Aß). These studies demonstrate that P@NB accelerates Aß degradation and alleviates excessive inflammatory responses by restoring autophagic flux, which ameliorates cognitive impairment in AD mice. This multitarget strategy induces autophagy/mitophagy through synergy, thereby normalizing mitochondrial dysfunction. Therefore, the developed method provides a promising AD-therapy strategy.

Efficacy relevance of PD-L1 expression on circulating tumor cells in metastatic breast cancer patients treated with anti-PD-1 immunotherapy.

PURPOSE: Breast cancer has become the leading cause of cancer mortality in women. Although immune checkpoint inhibitors targeting programmed death-1 (PD-1) are promising, it remains unclear whether PD-L1 expression on circulating tumor cells (CTCs) has predictive and prognostic values in predicting and stratifying metastatic breast cancer (MBC) patients who can benefit from anti-PD-1 immunotherapy. METHODS: Twenty six MBC patients that received anti-PD-1 immunotherapy were enrolled in this study. The peptide-based Pep@MNPs method was used to isolate and enumerate CTCs from 2.0 ml of peripheral venous blood. The expression of PD-L1 on CTCs was evaluated by an established immunoscoring system categorizing into four classes (negative, low, medium, and high). RESULTS: Our data showed that 92.3% (24/26) of patients had CTCs, 83.3% (20/26) of patients had PD-L1-positive CTCs, and 65.4% (17/26) of patients had PD-L1-high CTCs. We revealed that the clinical benefit rate (CBR) of patients with a cut-off value of ≥ 35% PD-L1-high CTCs (66.6%) was higher than the others (29.4%). We indicated that PD-L1 expression on CTCs from MBC patients treated with anti-PD-1 monotherapy was dynamic. We demonstrated that MBC patients with a cut-off value of ≥ 35% PD-L1-high CTCs had longer PFS (P = 0.033) and OS (P = 0.00058) compared with patients with a cut-off value of < 35% PD-L1-high CTCs. CONCLUSION: Our findings suggested that PD-L1 expression on CTCs could predict the therapeutic response and clinical outcomes, providing a valuable predictive and prognostic biomarker for patients treated with anti-PD-1 immunotherapy.

GRA-GCN: Dense Granule Protein Prediction in Apicomplexa Protozoa Through Graph Convolutional Network.

Dense granule proteins (GRAs) are secreted by Apicomplexa protozoa, which are closely related to an extensive variety of farm animal diseases. Predicting GRAs is an integral part in prevention and treatment of parasitic diseases. Considering that biological experiment approach is time-consuming and labor-intensive, computational method is a superior choice. Hence, developing an effective computational method for GRAs prediction is of urgency. In this paper, we present a novel computational method named GRA-GCN through graph convolutional network. In terms of the graph theory, the GRAs prediction can be regarded as a node classification task. GRA-GCN leverages k-nearest neighbor algorithm to construct the feature graph for aggregating more informative representation. To our knowledge, this is the first attempt to utilize computational approach for GRAs prediction. Evaluated by 5-fold cross-validations, the GRA-GCN method achieves satisfactory performance, and is superior to four classic machine learning-based methods and three state-of-the-art models. The analysis of the comprehensive experiment results and a case study could offer valuable information for understanding complex mechanisms, and would contribute to accurate prediction of GRAs. Moreover, we also implement a web server at http://dgpd.tlds.cc/GRAGCN/index/, for facilitating the process of using our model.

Molecular Design and Preparation of Protein-Based Soft Ionic Conductors with Tunable Properties.

Protein-based soft ionic conductors have attracted considerable research interest in recent years with great potential in applications at the human-machine interfaces. However, a fundamental mechanistic understanding of the ionic conductivity of silk-based ionic conductors is still unclear. Here, we first developed an environmental-friendly and scalable method to fabricate silk-based soft ionic conductors using silk proteins and calcium chloride. The mechanistic understanding of the ion transport and molecular interactions between calcium ions and silk proteins at variable water contents was investigated in-depth by combining experimental and simulation approaches. The results show that calcium ions primarily interact with amide groups in proteins at a low water content. The ionic conductivity is low since the calcium ions are confined around silk proteins within 2.0-2.6 Å. As water content increases, the calcium ions are hydrated with the formation of water shells, leading to the increased distance between calcium ions and silk proteins (3.3-6.0 Å). As a result, the motion of the calcium ions increased to achieve a higher ionic conductivity. By optimizing the ratio of the silk proteins, calcium ions, and water, silk-based soft ionic conductors with good stretchability and self-healing properties can be obtained. Such protein-based soft ionic conductors can be further used to fabricate smart devices such as electrochromic devices.

Probing the alignment-dependent mechanical behaviors and time-evolutional aligning process of collagen scaffolds.

Efficiently manipulating and reproducing collagen (COL) alignment in vitro remains challenging because many of the fundamental mechanisms underlying and guiding the alignment process are not known. We reconcile experiments and coarse-grained molecular dynamics simulations to investigate the mechanical behaviors of a growing COL scaffold and assay how changes in fiber alignment and various cross-linking densities impact their alignment dynamics under shear flow. We find higher cross-link densities and alignment levels significantly enhance the apparent tensile/shear moduli and strength of a bulk COL system, suggesting potential measures to facilitate the design of stronger COL based materials. Since fibril alignment plays a key factor in scaffold mechanics, we next investigate the molecular mechanism behind fibril alignment with Couette flow by computationally investigating the effects of COL's structural properties such as chain lengths, number of chains, tethering conditions, and initial COL conformations on the COL's final alignment level. Our computations suggest that longer chain lengths, more chains, greater amounts of tethering, and initial anisotropic COL conformations benefit the final alignment, but the effect of chain lengths may be more dominant over other factors. These results provide important parameters for consideration in manufacturing COL-based scaffolds where alignment and cross-linking are necessary for regulating performance.

Thermo- and ion-responsive silk-elastin-like proteins and their multiscale mechanisms.

Silk-elastin-like protein (SELP) is an excellent biocompatible and biodegradable material for hydrogels with tunable properties that can respond to multiple external stimuli. By integrating fully atomistic, replica exchange molecular dynamics simulations with detailed experiments, we predict and measure structural responses to changes in temperature and ion concentration of a novel SELP sequence, as well as a diazonium-coupled version. A single SELP molecule shrinks at high temperatures, whereas diazonium coupling decreases this thermo-responsiveness. Diazonium coupling weakens electrostatic interactions, leading to an insignificant ionic response in the single chain, while also decreasing gelation rates by reducing the number of exposed dityrosine crosslink sites and their solvent-accessible surface areas. With further data from our coarse-grained crosslinked SELP model and our experiments, we find that three effects are critical for SELP cluster's physical response to external stimuli: (1) the structural transition of SELPs at high temperature, (2) the geometry restraints in hydrogel networks, and (3) the electrostatic interactions between molecules. This molecular understanding of the thermal and ion response in single molecules of SELPs and their crosslinked networks may further improve and help innovate SELP's stimuli-responsive properties, creating significant opportunities for applications in biomedical devices and other engineering applications.

Prognostic Relevance of Estrogen Receptor Status in Circulating Tumor Cells in Breast Cancer Patients Treated With Endocrine Therapy.

Recently, female breast cancer (BC) has surpassed lung cancer to occupy the first place of the most commonly diagnosed cancer. The unsatisfactory prognosis of endocrine therapy for breast cancer might be attributed to the discordance in estrogen receptor (ER) status between primary tumors and corresponding metastases, as well as temporal and spatial receptor status heterogeneity at point-in-time between biopsy and treatment. The purpose of this study was to evaluate the prognostic and predictive value of ER status in circulating tumor cells (CTCs) in BC patients. We analyzed ER expression on CTCs isolated using the Pep@MNPs method in 2.0 ml of blood samples from 70 patients with BC and 67 female controls. The predictive and prognostic value of ER expression in CTCs and immunohistochemistry results of biopsies for progression-free survival (PFS) and overall survival (OS) of patients in response to therapies were assessed. The detection rate for CTCs was 95.71% (67/70 patients), with a median of 8 CTCs within 2 ml of peripheral venous blood (PVB). A concordance of 76.56% in ER status between CTCs and corresponding primary tumor and 69.23% between CTCs and corresponding metastases was observed. We also found that patients with ER-positive CTCs (CTC ER+) had longer PFS and OS than those without ER-positive CTCs (CTC ER-). Our findings suggested that ER status in CTCs of BC patients may provide valuable predictive and prognostic insights into endocrine therapies, although further evaluation in larger prospective trials is required.

Engineering Natural and Recombinant Silks for Sustainable Biodevices.

Silk fibroin (SF) is a structural protein derived from natural silkworm silks. Materials fabricated based on SF usually inherit extraordinary physical and biological properties, including high mechanical strength, toughness, optical transparency, tailorable biodegradability, and biocompatibility. Therefore, SF has attracted interest in the development of sustainable biodevices, especially for emergent bio-electronic technologies. To expand the function of current silk devices, the SF characteristic sequence has been used to synthesize recombinant silk proteins that benefit from SF and other functional peptides, such as stimuli-responsive elastin peptides. In addition to genetic engineering methods, innovated chemistry modification approaches and improved material processing techniques have also been developed for fabricating advanced silk materials with tailored chemical features and nanostructures. Herein, this review summarizes various methods to synthesize functional silk-based materials from different perspectives. This review also highlights the recent advances in the applications of natural and recombinant silks in tissue regeneration, soft robotics, and biosensors, using B. mori SF and silk-elastin-like proteins (SELPs) as examples.

Fiber-Based Biopolymer Processing as a Route toward Sustainability.

Some of the most abundant biomass on earth is sequestered in fibrous biopolymers like cellulose, chitin, and silk. These types of natural materials offer unique and striking mechanical and functional features that have driven strong interest in their utility for a range of applications, while also matching environmental sustainability needs. However, these material systems are challenging to process in cost-competitive ways to compete with synthetic plastics due to the limited options for thermal processing. This results in the dominance of solution-based processing for fibrous biopolymers, which presents challenges for scaling, cost, and consistency in outcomes. However, new opportunities to utilize thermal processing with these types of biopolymers, as well as fibrillation approaches, can drive renewed opportunities to bridge this gap between synthetic plastic processing and fibrous biopolymers, while also holding sustainability goals as critical to long-term successful outcomes.

Specific osteogenesis imperfecta-related Gly substitutions in type I collagen induce distinct structural, mechanical, and dynamic characteristics.

The stiffnesses, ß-structures, hydrogen bonds, and vibrational modes of wild-type collagen triple helices are compared with osteogenesis imperfecta-related mutants using integrative structural and dynamic analysis via molecular dynamics simulations and Markov state models. Differences in these characteristics are strongly related to the unwound structural states in the mutated regions that are specific to each mutation.

Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence.

Materials chemistry is at the forefront of the global "Fourth Industrial Revolution", in part by establishing a "Materials 4.0" paradigm. A key aspect of this paradigm is developing methods to effectively integrate hardware, software, and biological systems. Towards this end, we must have intimate knowledge of the virtual space in materials design: materials omics (materiomics), materials informatics, computational modelling and simulations, artificial intelligence (AI), and big data. We focus on the discovery and design of next-generation bio-inspired materials because the design space is so huge as to be almost intractable. With nature providing researchers with specific guiding principles, this material design space may be probed most efficiently through digital, high-throughput methods. Therefore, to enhance awareness and adoption of digital approaches in soft polymeric bio-inspired materials discovery and design, we detail multiscale simulation techniques in soft matter from the molecular level to the macroscale. We also highlight the unique role that artificial intelligence and materials databases will play in molecular simulations as well as soft materials discovery. Finally, we showcase several case studies that concretely apply computational modelling and simulations for integrative soft bio-inspired materials design with experiments.