Fluorescent chemosensors facilitate the visualization of plant health and their living environment in sustainable agriculture.

Globally, 91% of plant production encounters diverse environmental stresses that adversely affect their growth, leading to severe yield losses of 50-60%. In this case, monitoring the connection between the environment and plant health can balance population demands with environmental protection and resource distribution. Fluorescent chemosensors have shown great progress in monitoring the health and environment of plants due to their high sensitivity and biocompatibility. However, to date, no comprehensive analysis and systematic summary of fluorescent chemosensors used in monitoring the correlation between plant health and their environment have been reported. Thus, herein, we summarize the current fluorescent chemosensors ranging from their design strategies to applications in monitoring plant-environment interaction processes. First, we highlight the types of fluorescent chemosensors with design strategies to resolve the bottlenecks encountered in monitoring the health and living environment of plants. In addition, the applications of fluorescent small-molecule, nano and supramolecular chemosensors in the visualization of the health and living environment of plants are discussed. Finally, the major challenges and perspectives in this field are presented. This work will provide guidance for the design of efficient fluorescent chemosensors to monitor plant health, and then promote sustainable agricultural development.

GhHAM regulates GoPGF-dependent gland development and contributes to broad-spectrum pest resistance in cotton.

Cotton is a globally cultivated crop, producing 87% of the natural fiber used in the global textile industry. The pigment glands, unique to cotton and its relatives, serve as a defense structure against pests and pathogens. However, the molecular mechanism underlying gland formation and the specific role of pigment glands in cotton's pest defense are still not well understood. In this study, we cloned a gland-related transcription factor GhHAM and generated the GhHAM knockout mutant using CRISPR/Cas9. Phenotypic observations, transcriptome analysis, and promoter-binding experiments revealed that GhHAM binds to the promoter of GoPGF, regulating pigment gland formation in cotton's multiple organs via the GoPGF-GhJUB1 module. The knockout of GhHAM significantly reduced gossypol production and increased cotton's susceptibility to pests in the field. Feeding assays demonstrated that more than 80% of the cotton bollworm larvae preferred ghham over the wild type. Furthermore, the ghham mutants displayed shorter cell length and decreased gibberellins (GA) production in the stem. Exogenous application of GA3 restored stem cell elongation but not gland formation, thereby indicating that GhHAM controls gland morphogenesis independently of GA. Our study sheds light on the functional differentiation of HAM proteins among plant species, highlights the significant role of pigment glands in influencing pest feeding preference, and provides a theoretical basis for breeding pest-resistant cotton varieties to address the challenges posed by frequent outbreaks of pests.

Multi-level bioinformatics resources support drug target discovery of protein-protein interactions.

Drug discovery often begins with a new target. Protein-protein interactions (PPIs) are crucial to multitudinous cellular processes and offer a promising avenue for drug-target discovery. PPIs are characterized by multi-level complexity: at the protein level, interaction networks can be used to identify potential targets, whereas at the residue level, the details of the interactions of individual PPIs can be used to examine a target's druggability. Much great progress has been made in target discovery through multi-level PPI-related computational approaches, but these resources have not been fully discussed. Here, we systematically survey bioinformatics tools for identifying and assessing potential drug targets, examining their characteristics, limitations and applications. This work will aid the integration of the broader protein-to-network context with the analysis of detailed binding mechanisms to support the discovery of drug targets.

Transfer learning empowers accurate pharmacokinetics prediction of small samples.

Accurate assessment of pharmacokinetic (PK) properties is crucial for selecting optimal candidates and avoiding downstream failures. Transfer learning is an innovative machine learning approach enabling high-throughput prediction with limited data. Recently, transfer learning methods showed promise in predicting ADME/PK parameters. Given the prolific growth of research on transfer learning for PK prediction, a comprehensive review of its advantages and challenges is imperative. This study explores the fundamentals, classifications, toolkits and applications of various transfer learning techniques for PK prediction, demonstrating their utility through three practical case studies. This work will serve as a reference for drug design researchers.

Targeting Fks1 proteins for novel antifungal drug discovery.

Fungal infections are a major threat to human health. The limited availability of antifungal drugs, the emergence of drug resistance, and a growing susceptible population highlight the critical need for novel antifungal agents. The enzymes involved in fungal cell wall synthesis offer potential targets for antifungal drug development. Recent studies have enhanced our focus on the enzyme Fks1, which synthesizes ß-1,3-glucan, a critical component of the cell wall. These studies provide a deeper understanding of Fks1's function in cell wall biosynthesis, pathogenicity, structural biology, evolutionary conservation across fungi, and interaction with current antifungal drugs. Here, we discuss the role of Fks1 in the survival and adaptation of fungi, guided by insights from evolutionary and structural analyses. Furthermore, we delve into the dynamics of Fks1 modulation with novel antifungal strategies and assess its potential as an antifungal drug target.

Evaluation of the immunoprotective effect of the recombinant Eimeria intestinalis rhoptry protein 25 and rhoptry protein 30 on New Zealand rabbits.

BACKGROUND: Rabbit coccidiosis is a parasitism caused by either one or multiple co-infections of Eimeria species. Among them, Eimeria intestinalis is the primary pathogen responsible for diarrhea, growth retardation, and potential mortality in rabbits. Concerns regarding drug resistance and drug residues have led to the development of recombinant subunit vaccines targeting Eimeria species as a promising preventive measure. The aim of this study was to assess the immunoprotective efficacy of recombinant subunit vaccines comprising EiROP25 and EiROP30 (rhoptry proteins (ROPs)) against E. intestinalis infection in rabbits. METHODS: Cloning, prokaryotic expression, and protein purification were performed to obtain EiROP25 and EiROP30. Five groups of fifty 35-day-old Eimeria-free rabbits were created (unchallenged control group, challenged control group, vector protein control group, rEiROP25 group, and rEiROP30 group), with 10 rabbits in each group. Rabbits in the rEiROP25 and rEiROP30 groups were immunized with the recombinant proteins (100 µg per rabbit) for primary and booster immunization (100 µg per rabbit) at a two-week intervals, and challenged with 7 × 104 oocysts per rabbit after an additional two-week interval. Two weeks after the challenge, the rabbits were euthanized for analysis. Weekly collections of rabbit sera were made to measure changes in specific IgG and cytokine level. Clinical symptoms and pathological changes after challenge were observed and recorded. At the conclusion of the animal experiment, lesion scores, the relative weight increase ratio, the oocyst reduction rate, and the anticoccidial index were computed. RESULTS: Rabbits immunized with rEiROP25 and rEiROP30 exhibited relative weight gain ratios of 56.57% and 72.36%, respectively. Oocysts decreased by 78.14% and 84.06% for the rEiROP25 and rEiROP30 groups, respectively. The anticoccidial indexes were 140 and 155. Furthermore, there was a noticeable drop in intestinal lesions. After the primary immunization with rEiROP25 and rEiROP30, a week later, there was a notable rise in specific IgG levels, which remained elevated for two weeks following challenge (P < 0.05). Interleukin (IL)-2 levels increased markedly in the rEiROP25 group, whereas IL-2, interferon gamma (IFN-γ), and IL-4 levels increased substantially in the rEiROP30 group (P < 0.05). CONCLUSION: Immunization of rabbits indicated that both rEiROP25 and rEiROP30 are capable of inducing an increase in specific antibody levels. rEiROP25 triggered a Th1-type immune protection response, while rEiROP30 elicited a Th1/Th2 mixed response. EiROP25 and EiROP30 can generate a moderate level of immune protection, with better efficacy observed for EiROP30. This study provides valuable insights for the promotion of recombinant subunit vaccines targeting rabbit E. intestinalis infection.

Human-virus protein-protein interactions maps assist in revealing the pathogenesis of viral infection.

Many significant viral infections have been recorded in human history, which have caused enormous negative impacts worldwide. Human-virus protein-protein interactions (PPIs) mediate viral infection and immune processes in the host. The identification, quantification, localization, and construction of human-virus PPIs maps are critical prerequisites for understanding the biophysical basis of the viral invasion process and characterising the framework for all protein functions. With the technological revolution and the introduction of artificial intelligence, the human-virus PPIs maps have been expanded rapidly in the past decade and shed light on solving complicated biomedical problems. However, there is still a lack of prospective insight into the field. In this work, we comprehensively review and compare the effectiveness, potential, and limitations of diverse approaches for constructing large-scale PPIs maps in human-virus, including experimental methods based on biophysics and biochemistry, databases of human-virus PPIs, computational methods based on artificial intelligence, and tools for visualising PPIs maps. The work aims to provide a toolbox for researchers, hoping to better assist in deciphering the relationship between humans and viruses.

Design, Synthesis, and Herbicidal Activity of Substituted 3-(Pyridin-2-yl)Phenylamino Derivatives.

To discover protoporphyrinogen oxidase (PPO) inhibitors with robust herbicidal activity and crop safety, three types of substituted 3-(pyridin-2-yl)phenylamino derivatives bearing amide, urea, or thiourea as side chain were designed via structure splicing strategy. Postemergence herbicidal activity assessment of 33 newly prepared compounds revealed that many of our compounds such as 6a, 7b, and 8d exhibited superior herbicidal activities against broadleaf and monocotyledon weeds to commercial acifluorfen. In particular, compound 8d exhibited excellent herbicidal activities and high crop safety at a dosage range of 37.5-150 g ai/ha. PPO inhibitory studies supported our compounds as typical PPO inhibitors. Molecular docking studies revealed that compound 8d provided effective interactions with Nicotiana tabacum PPO (NtPPO) via diverse interaction models, such as π-π stacking and hydrogen bonds. Molecular dynamics (MD) simulation studies and degradation studies were also conducted to gain insight into the inhibitory mechanism. Our study indicates that compound 8d may be a candidate molecule for the development of novel herbicides.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era.

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Copper-Catalyzed Oxygenative Skeletal Rearrangement of Tetrahydro-ß-carbolines Using H2 O and O2 as Oxygen Sources.

Herein, we report an unprecedented skeletal rearrangement reaction of tetrahydro-ß-carbolines enabled by copper-catalyzed single-electron oxidative oxygenation, in which H2 O and O2 act as oxygen sources to generate a unique 2-hydroxyl-3-peroxide indoline intermediate. The synthetic reactivity of 2-hydroxyl-3-peroxide indoline species was demonstrated by a unique multi-step bond cleavage and formation cascade. Using a readily available copper catalyst under open-air conditions, highly important yet synthetically difficult spiro[pyrrolidone-(3,1-benzoxazine)] products were obtained in a single operation. The synthetic utility of this methodology is demonstrated by the efficient synthesis of the natural products donaxanine and chimonamidine, as well as the 3-hydroxyl-pyrroloindoline scaffold, in just one or two steps.

Protection against Eimeria intestinalis infection in rabbits immunized with the recombinant elongation factors EF1α and EFG.

Eimeria intestinalis is the most pathogenic species of rabbit coccidiosis, causing weight loss, diarrhea, and even acute death. The currently used anticoccidial drugs against E. intestinalis in rabbits are associated with drug resistance and residues. Immunological control might be a potential alternative. We cloned and expressed the E. intestinalis recombinant EF1α and EFG (rEi-EF1α and rEi-EFG, respectively). Rabbits were immunized subcutaneously every 14 days with 100 µg of rEi-EF1α and rEi-EFG and followed by 5 × 104 E. intestinalis sporulated oocysts orally challenge. Serum samples were collected every 7 days to measure the levels of specific antibodies and cytokines. On post-challenge day 14, rabbits were sacrificed and the anticoccidial index was evaluated. The rabbits of PBS challenged groups exhibited anorexia, diarrhea, marked intestinal wall thickening, and white nodules that formed patches, while rabbits from the rEi-EF1α or rEi-EFG challenged group exhibited milder symptoms. The rEi-EF1α group showed a 75.18% oocyst reduction and 89.01%wt gain; the rEi-EFG group had a 60.58% oocyst reduction and 56.04%wt gain. After vaccination, specific IgG levels increased and stayed high (P < 0.05). The IL-4 and IL-2 levels of rEi-EF1α immunized groups showed a significant increase after immunization (P < 0.05). Both rEi-EF1α and rEi-EFG could induce humoral and cellular immune responses. In contrast, rabbits immunized with rEi-EF1α were better protected from challenge by E. intestinalis than rEi-EFG.

Assessment of the Immunoprotective Efficacy of Recombinant 14-3-3 Protein and Dense Granule Protein 10 (GRA10) as Candidate Antigens for Rabbit Vaccines against Eimeria intestinalis.

Eimeria intestinalis infects rabbits, causing severe intestinal coccidiosis. Prolonged anticoccidial drug use might lead to coccidia resistance and drug residues in food. Thus, vaccines are required to control rabbit coccidiosis. In this study, recombinant E. intestinalis 14-3-3 and GRA10 proteins (rEi-14-3-3 and rEi-GRA10) were obtained via prokaryotic expression and used as recombinant subunit vaccines. Fifty 30-day-old rabbits were randomly grouped as follows: PBS-uninfected group, PBS-infected group, Trx-His-S control group, and rEi-14-3-3 and rEi-GRA10 immunized groups. The rabbits were subcutaneously immunized twice at 2-week intervals, challenged with 7 × 104 sporulated oocysts, and sacrificed 14 days later. The protective effects were assessed via clinical signs, relative weight gain, oocyst reduction, mean intestinal lesion score, ACI (anticoccidial index), cytokine, and specific antibody levels in sera. The rEi-14-3-3 and rEi-GRA10 groups had higher relative weight gain rates of 81.94% and 73.61% (p < 0.05), and higher oocyst reduction rates of 86.13% and 84.87% (p < 0.05), respectively. The two immunized groups had fewer intestinal lesions (p < 0.05) and higher IgG levels (p < 0.05). Higher levels of IL-2, IL-4, and IFN-γ cytokines in the rEi-14-3-3 group (p < 0.05) and a higher level of IFN-γ in the rEi-GRA10 group (p < 0.05) were observed. The ACI values of the rEi-14-3-3 and rEi-GRA10 groups were 168.24 and 159.91, with good and moderate protective effects, respectively. Both rEi-14-3-3 and rEi-GRA10 induced humoral immunity in the rabbits. In addition, rEi-14-3-3 induced Th1- and Th2-type immune responses. Both recombinant proteins were protective against E. intestinalis infection in rabbits, with rEi-14-3-3 showing a better protective effect.

Thermal imaging: The digital eye facilitates high-throughput phenotyping traits of plant growth and stress responses.

Plant phenotyping is important for plants to cope with environmental changes and ensure plant health. Imaging techniques are perceived as the most critical and reliable tools for studying plant phenotypes. Thermal imaging has opened up new opportunities for nondestructive imaging of plant phenotyping. However, a comprehensive summary of thermal imaging in plant phenotyping is still lacking. Here we discuss the progress and future prospects of thermal imaging for assessing plant growth and stress responses. First, we classify thermal imaging into ground-based and aerial platforms based on their adaptability to different experimental environments (including laboratory, greenhouse, and field). It is convenient to collect phenotypic information of different dimensions. Second, in order to enhance the efficiency of thermal image processing, automatic algorithms based on deep learning are employed instead of traditional manual methods, greatly reducing the time cost of experiments. Considering its ease of implementation, handling and instant response, thermal imaging has been widely used in research on environmental stress, crop yield, and seed vigor. We have found that thermal imaging can detect thermal energy dissipation caused by living organisms (e.g., pests, viruses, bacteria, fungi, and oomycetes), enabling early disease diagnosis. It also recognizes changes leaf surface temperatures resulting from reduced transpiration rates caused by nutrient deficiency, drought, salinity, or freezing. Furthermore, thermal imaging predicts crop yield under different water states and forecasts the viability of dormant seeds after water absorption by monitoring temperature changes in the seeds. This work will assist biologists and agronomists in studying plant phenotypes and serve a guide for breeders to develop high-yielding, stress-tolerant, and superior crops.

Grasping cryptic binding sites to neutralize drug resistance in the field of anticancer.

Drug resistance is a significant obstacle to successful cancer treatment. The utilization and development of cryptic binding sites (CBSs) in proteins involved in cancer-related drug-resistance (CRDR) could help to overcome that drug resistance. However, there is no comprehensive review of the successful use of CBSs in addressing CRDR. Here, we have systematically summarized and analyzed the opportunities and challenges of using CBSs in addressing CRDR and revealed the key role that CBSs have in targeting CRDR. First, we have identified the CRDR targets and the corresponding CBSs. Second, we discuss the mechanisms by which CBSs can overcome CRDR. Finally, we have provided examples of successful CBS applications in addressing CRDR. We hope that this approach will provide guidance to biologists and chemists in effectively utilizing CBSs for the development of new drugs to alleviate CRDR.

Protective efficacy of recombinant proteins AMA1 and IMP1 in rabbits infected with Eimeria intestinalis.

Eimeria intestinalis is one of the most pathogenic rabbit coccidia species causing severe intestinal damage and increased risk of secondary infection from opportunistic pathogens, which results in huge economic losses to the rabbit industry. Anticoccidial drugs are currently the main method to control coccidiosis; however, increasing resistance and drug residues have fueled research on anticoccidial vaccines. Apical membrane antigen 1 (AMA1) and immune mapped protein 1 (IMP1), as surface proteins, are associated with host invasion and might have the potential as candidate vaccine antigens. In the present study, recombinant IMP1 (rEiIMP1) and AMA1 (rEiAMA1) from E. intestinalis were expressed using Escherichia coli BL21. The immunoreactivity and immunoprotective effects of rEiIMP1 and rEiAMA1 were then analyzed. Fifty rabbits were grouped randomly (n = 10 per group): The unimmunized-unchallenged control group (sterilized phosphate-buffered saline (PBS)), the unimmunized-challenged control group (sterilized PBS), the vector protein-challenged control group (100 µg of pET-32a vector protein per rabbit), the rEiIMP1 immunized group (100 µg of rEiIMP1 per rabbit), and the rEiAMA1 immunized group (100 µg of rEiAMA1 per rabbit). After two immunizations, the rabbits were challenged with homologous oocysts (except for the unimmunized-unchallenged group). Serum specific antibody levels were assessed weekly throughout the experimental period; and the levels of different cytokines in the serum before the challenge were detected. The clinical symptoms, oocysts output, weight gain, feed conversion ratio (FCR), and lesion scores were recorded after experimental infection, and the anticoccidial indexes (ACIs) were calculated. The results showed that both rEiIMP1 and rEiAMA1 had good immunoreactivity. Rabbits immunized with rEiIMP1 and rEiAMA1 displayed 66.74 % and 63.14 % oocyst reduction, respective land 81.79 % and 78.87 % body weight gain, respectively. The rEiIMP1 and rEiAMA1 groups had lower FCRs (3.77:1 and 4.06:1, respectively) and lesion scores (P = 0.00). The rEiIMP1 and rEiAMA1 showed moderate effects, with an ACI of 152.09 and 147.17, respectively. Immunization induced high levels of anti-rEiIMP1 and -rEiAMA1 antibodies. Rabbits immunized with rEiIMP1 and rEiAMA1 displayed significantly increased interleukin (IL)- 2 (P = 0.00), interferon gamma (IFN)- γ (P = 0.00), and IL- 4 (P = 0.00) levels. Therefore, this study provided potential candidate vaccine antigens for E. intestinalis.

In silico resources help combat cancer drug resistance mediated by target mutations.

Drug resistance causes catastrophic cancer treatment failures. Mutations in target proteins with altered drug binding indicate a main mechanism of cancer drug resistance (CDR). Global research has generated considerable CDR-related data and well-established knowledge bases and predictive tools. Unfortunately, these resources are fragmented and underutilized. Here, we examine computational resources for exploring CDR caused by target mutations, analyzing these tools based on their functional characteristics, data capacity, data sources, methodologies and performance. We also discuss their disadvantages and provide examples of how potential inhibitors of CDR have been discovered using these resources. This toolkit is designed to help specialists explore resistance occurrence effectively and to explain resistance prediction to non-specialists easily.

Oxidative post-translational modification of catalase confers salt stress acclimatization by regulating H2O2 homeostasis in Malus hupehensis.

Reactive oxygen species (ROS) play an essential role as both signaling molecule and damage agent during salt stress. As a signaling molecule, proper accumulation of H2O2 is crucial to trigger stress response and enhance stress tolerance. However, the dynamic regulation mechanism of H2O2 remains unclear. Here, we show that MhCAT2 (catalase 2 in Malus hupehensis) undergoes oxidative modification in an O2•--dependent manner and that oxidation at His225 residue reduces the MhCAT2 activity. Furthermore, the substitution of His225 with Tyr weakens the activity of MhCAT2. The oxidation modification provides a post-translational brake mechanism for the excessive scavenging of H2O2 caused by salt stress-induced catalase (CAT) over-expression. Overall, this finding provides mechanistic insights on stress tolerance augmentation by an O2•--mediated switch that regulates H2O2 homeostasis in Malus hupehensis.

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment libraries and (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.