Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 739 records · Page 41Linked to original sources

bioRxiv2023

Plant immunity activated and suppressed by a conserved effector protein family in mirid bug Riptortus pedestris

Riptortus pedestris (Fabricius) a major soybean pest migrates into soybean fields during pod filling stage resulting in a leaf and stem staygreen while pods without beans syndrome. Given the agricultural importance of this species and the lack of characterized HAMP from piercing-sucking insects we performed a large scale of screening by expression of 87 R. pedestris salivary proteins with signal peptides in Nicotiana benthamiana obtaining a candidate HAMP RPH1. RPH1 activated a series of PTI responses including ROS burst upregulation of defense marker genes such as PR1 WRKY7 WRKY8 Acre31 and CYP71D20 MAPK activation and biosynthesis of phytohormones in plants. RPH1 significantly enhances soybean resistance against R. pedestris feeding. PRR coreceptors BAK1 and SOBIR1 were required for RPH1-induced PTI responses. Remarkably RPH1 homologs were widely distributed in herbivorous insects and majority of homologs from selected species induced cell death or ROS. Thus our results demonstrated that RPH1 is a conserved HAMP within chewing and piercing-sucking insects. We also discovered that R. pedestris evolved four paralogs to overcome the plant immunity triggered by RPH1. This study filled a major gap of HAMP identification from piercing-sucking insect and also deciphered a novel evasion strategy of plant immunity exploited by herbivorous insects. One sentence summaryRiptortus pedestris RPH1, a conserved HAMP in herbivores, activates a variety of PTI responses in plants. To couterdefense, R. pedestris evolved four paralogs to suppress RPH1-induced PTI responses. The author(s) responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plcell/pages/General-Instructions) is: Ai Xia (xia@njau.edu.edu).

plant biology↗

bioRxiv2023

Structural insights into DNA Topoisomerase II of African Swine Fever Virus

Type II topoisomerases are ubiquitous enzymes that play a pivotal role in modulating the topological configuration of dsDNA. These Topo enzymes are indispensable for DNA metabolism and have been extensively investigated in both prokaryotic and eukaryotic organisms. However, understanding of virus-encoded Topo II remains limited. One intriguing example is the African swine fever virus (ASFV), which stands as the sole mammalian-infecting virus encoding a Topo II. In this work, we utilized multiple approaches involving cryo-EM, X-ray crystallography, atomic force microscopy and biochemical assays to investigate the structure and function of ASFV Topo , pP1192R. We determined the structures of pP1192R in different conformational states and confirming its enzymatic activity in vitro. Collectively, our results unveil the basic mechanisms of viral Topo II, thereby not only augmenting our understanding of this kind of intriguing enzymes but also presenting a potential avenue for the intervention strategies to mitigate the impact of African swine fever virus.

molecular biology↗

bioRxiv2023

Multitask Learning of Longitudinal Circulating Biomarkers and Clinical Outcomes: Identification of Optimal Machine-Learning and Deep-Learning Models

Many circulating biomarkers are assessed at different time intervals during clinical studies. Despite of the success of standard joint models in predicting clinical outcomes using low-dimensional longitudinal data (1-2 biomarkers), significant computational challenges are encountered when applying these techniques to high-dimensional biomarker datasets. Modern machine- or deep-learning models show potential for multiple biomarker processes, but systematic evaluations and applications to high-dimensional data in the clinical settings have yet to be reported. We aimed to enhance the scalability of joint modeling and provide guidance on optimal approaches for high-dimensional biomarker data and outcomes. We evaluated multiple deep-learning and machine-learning models using 24 clinical biomarkers and survival data from the SQUIRE trial, a phase 3 randomized clinical trial investigating necitumumab and standard gemcitabine/cisplatin treatment in patients with squamous non-small-cell lung cancer (NSCLC). Overall, we confirmed that longitudinal models enabled more accurate prediction of patients survival compared to those solely based on baseline information. Coupling multivariate functional principal component analysis (MFPCA) with Cox regression (MFPCA-Cox) provided the highest predictive discrimination and accuracy for the NSCLC patients with AUC values of 0.7 - >0.8 at various landmark time points and prediction timeframes, outperforming recent advanced Transformer and convolutional neural network deep-learning algorithms (TransformerJM and Match-Net, respectively). In conclusion, we identified that MFPCA-Cox represents a robust and versatile joint modeling algorithm for high-dimensional biomarker longitudinal data with irregular and missing data, capturing complex relationships within the data, yielding accurate predictions for both longitudinal biomarkers and survival outcomes, and gaining insights into the underlying dynamics.

pharmacology and toxicology↗

bioRxiv2023

Robust Adaptive Deep Brain Stimulation Control of Non-Stationary Cortex-Basal Ganglia-Thalamus Network Models in Parkinson's Disease

Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinsons disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering the accurate and robust control of PD neural dynamics using current closed-loop DBS methods. Here, we develop a new robust adaptive closed-loop DBS method for regulating cortex-BG-thalamus network dynamics in PD. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated PD neural state while reducing the systems sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as a testbed to simulate various nonlinear and non-stationary neural dynamics for evaluating DBS methods. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms state-of-the-art on-off and LTI DBS methods. These results have implications for future designs of clinically-viable closed-loop DBS systems to treat PD and other neurological and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

The diversity and ecological significance of microbial traits potentially involved in B12 biosynthesis in the global ocean

Cobalamin (B12), an essential nutrient and growth cofactor for many living organisms on the Earth, can be fully synthesized only by selected prokaryotes in nature. Therefore, microbial communities related with B12 biosynthesis could serve as an example subsystem to disentangle the underlying ecological mechanisms balancing the function and taxonomy of complex functional assemblages. By anchoring microbial traits potentially involved in B12 biosynthesis, we depict the biogeographic patterns of B12 biosynthesis genes and their carrying taxa in the global ocean, in light of the limitation to detect de novo B12 synthesizers via metagenomes alone. Both the taxonomic and functional composition of B12 biosynthesis genes were strongly shaped by depth, differentiating epipelagic from mesopelagic zones. The functional genes were relatively stably distributed across different oceans, but their carrying taxa varied considerably, showing clear functional redundancy of microbial systems. Microbial taxa carrying B12 biosynthesis genes in the surface water were influenced by environmental factors such as temperature, oxygen and nitrate. However, the composition of functional genes was weakly associated with these environmental factors. Null model analyses demonstrated that determinism governed the compositional variation of B12 biosynthesis genes, whereas a higher degree of stochasticity was associated with taxonomic variations. Significant associations were observed between chlorophyll a concentration and B12 biosynthesis traits, indicating their importance in global ocean primary production. Conclusively, this study revealed an essential ecological mechanism governing the assembly of microbes in nature: the environment selects function rather than taxonomy; functional redundancy underlies stochastic community assembly. Impact StatementA central question in ecology is how a galaxy of microbial taxa is assembled and distributed across space and through time, executing essential ecosystem functions. By anchoring microbial functional traits potentially involved in B12 biosynthesis and their carrying microbial taxa in the global ocean, this study addresses essential ecological questions from functional and taxonomic angles. Integrating multiple lines of evidence, we show that the ecosystem selects functional traits rather than taxonomic groups, and functional redundancy underlies stochastic taxonomic community assembly. Also, microbial communities potentially involved in B12 biosynthesis are significantly associated with chlorophyll a concentration, demonstrating their importance in global ocean primary production. This study provides valuable mechanistic insights into the complex microbial community assembly in natural ecosystems.

microbiology↗

bioRxiv2023

Herpes zoster mRNA vaccine induces superior vaccine immunity over licensed vaccine in mice and rhesus macaques

Herpes zoster remains an important global health issue and mainly occurs in aged and immunocompromised individuals with an early exposure history to Varicella Zoster Virus (VZV). Although the licensed vaccine Shingrix has a remarkably high efficacy, undesired reactogenicity and increasing global demand causing vaccine shortage urged the development of improved or novel VZV vaccines. In this study, we developed a novel VZV mRNA vaccine candidate (named as ZOSAL) containing sequence-optimized mRNAs encoding full-length glycoprotein E encapsulated in an ionizable lipid nanoparticle. In mice and rhesus macaques, ZOSAL demonstrated superior immunogenicity and safety in multiple aspects over Shingrix, especially in the induction of strong T cell immunity. Transcriptomic analysis revealed that both ZOSAL and Shingrix could robustly activate innate immune compartments, especially Type-I IFN signaling and antigen processing/presentation. Multivariate correlation analysis further identified several early factors of innate compartments that can predict the magnitude of T cell responses, which further increased our understanding of the mode of action of two different VZV vaccine modalities. Collectively, our data demonstrated the superiority of VZV mRNA vaccine over licensed subunit vaccine. The mRNA platform therefore holds prospects for further investigations in next-generation VZV vaccine development.

immunology↗

bioRxiv2023

A convolutional neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimers disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62x10-32; T1: r=0.61, p=1.45x10-26, FW+T1: r=0.77, p=6.48x10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: {beta}=-1.094, p=6.32x10-7; T1: {beta}=-1.331, p=6.52x10-7; FW+T1: {beta}=-1.476, p=2.53x10-10; executive function, FW: {beta}=-1.276, p=1.46x10-9; T1: {beta}=-1.337, p=2.52x10-7; FW+T1: {beta}=-1.850, p=3.85x10-17) and longitudinal cognition (memory, FW: {beta}=-0.091, p=4.62x10-11; T1: {beta}=-0.097, p=1.40x10-8; FW+T1: {beta}=-0.101, p=1.35x10-11; executive function, FW: {beta}=-0.125, p=1.20x10-10; T1: {beta}=-0.163, p=4.25x10-12; FW+T1: {beta}=-0.158, p=1.65x10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

neuroscience↗

bioRxiv2023

Thyroid hormone rewires cortical circuits to coordinate body-wide metabolism and exploratory drive

Animals adapt to varying environmental conditions by modifying the function of their internal organs, including the brain. To be adaptive, alterations in behavior must be coordinated with the functional state of organs throughout the body. Here we find that thyroid hormone-- a prominent regulator of metabolism in many peripheral organs-- activates cell-type specific transcriptional programs in anterior regions of cortex of adult mice via direct activation of thyroid hormone receptors. These programs are enriched for axon-guidance genes in glutamatergic projection neurons, synaptic regulators across both astrocytes and neurons, and pro-myelination factors in oligodendrocytes, suggesting widespread remodeling of cortical circuits. Indeed, whole-cell electrophysiology recordings revealed that thyroid hormone induces local transcriptional programs that rewire cortical neural circuits via pre-synaptic mechanisms, resulting in increased excitatory drive with a concomitant sensitization of recruited inhibition. We find that thyroid hormone bidirectionally regulates innate exploratory behaviors and that the transcriptionally mediated circuit changes in anterior cortex causally promote exploratory decision-making. Thus, thyroid hormone acts directly on adult cerebral cortex to coordinate exploratory behaviors with whole-body metabolic state.

neuroscience↗

bioRxiv2023

Screening the human druggable genome identifies ABHD17B as an anti-fibrotic target in hepatic stellate cells

Hepatic stellate cells (HSCs) are activated with chronic liver injury and transdifferentiate into myofibroblasts, which produce excessive extracellular matrices that form the fibrotic scar. While the progression of fibrosis is understood to be the cause of end-stage liver disease, there are no approved therapies directed at interfering with the activity of HSC myofibroblasts. We performed a high-throughput small interfering RNA (siRNA) screen in primary human HSC myofibroblasts to identify gene products necessary for the fibrotic phenotype of HSCs. We found that depletion of ABHD17B promotes the inactivation of HSCs, characterized by reduced COL1A1 and ACTA2 expression and accumulation of lipid droplets. Mice deficient for Abhd17b are also protected from fibrosis in the setting of in vivo liver injury. While ABHD17B is a depalmitoylase, our data suggest that ABHD17B promotes fibrosis through pathways independent of depalmitoylation that include interaction with MYO1B to modulate gene expression and HSC migration. Together, our results provide an analysis of the phenotypic consequences for siRNAs targeting RNAs from >9,500 genes in primary human HSCs and identify ABHD17B as a potential therapeutic target to inhibit liver fibrosis.

cell biology↗

bioRxiv2023

Functional dissection of KATP channel structures reveals the importance of a conserved interface

ATP-sensitive potassium channels (KATP) are inhibited by ATP but activated by Mg-ADP, coupling the intracellular ATP/ADP ratio to the potassium conductance of the plasma membrane. Although there has been progress in determining the structure of KATP channels, the functional significance of the domain-domain interface in the gating properties of KATP channels is not fully understood. In this study, we propose a new two-module assembly model for the KATP channel. Our mutagenesis experiments, based on this model, indicate that deleting ECL3 on the SUR1 subunit impairs KNtp-independent Mg-ADP activation. This finding demonstrates the essential role of intramolecular interactions between KATPcore and SURABC in Mg-ADP activation. Notably, this interface is functionally conserved between SUR1 and SUR2. Additionally, the hydrophobic residue F351 on ECL3 of SUR1 is crucial for maintaining the stability of this interface.

biophysics↗

bioRxiv2023

Next-generation anti-PD-L1/IL-15 immunocytokine elicits superior antitumor immunity in cold tumors with minimal toxicity

Immunocytokines, such as anti-PD-L1/IL-15, have shown promising efficacy in preclinical studies, but their clinical development still faces severe safety concerns, with the problem not easily overcome by simply reducing the cytokine activity. We proposed a next-generation immunocytokine concept of designing a tumor-conditional anti-PD-L1/IL-15 prodrug (LH05), which innovatively masks IL-15 with steric hindrance of its flanking moieties of anti-PD-L1 and IL-15R-sushi domain. The design successfully attenuated the cytokine sink effect of IL-15 and resulted in a significantly reduced systemic toxicity when compared to wild-type anti-PD-L1/IL-15. LH05 would be specifically cleaved in the tumor microenvironment (TME) to release the active IL-15/IL-15R-sushi domain (ILR) in a proteolytic cleavage-dependent manner and exhibited potent antitumor effects in mouse syngeneic models. Mechanistically, the antitumor efficacy of LH05 was dependent on both innate and adaptive immunity, which altered the TME to Th1-type by recruiting and stimulating both NK and CD8+ T cells and fired up cold tumors. LH05 also showed superior efficacy in restoring immunotherapy response in a refractory U251 xenograft model. Collectively, we introduced a novel next-generation immunocytokine strategy for tumor immunotherapy, contributing to the establishment of optimal treatment for patients with resistance to immune checkpoint inhibitors or cold tumors.

bioengineering↗

bioRxiv2023

Correlative single-cell X-ray tomography and X-ray fluorescence imaging

X-ray tomography (XRT) and X-ray fluorescence (XRF) imaging are two non-invasive imaging techniques to study cellular structures and chemical element distributions, respectively. However, correlative X-ray tomography and fluorescence imaging for the same cell have yet to be routinely realized due to challenges in sample preparation and X-ray radiation damage. Here we report an integrated experimental and computational workflow for achieving correlative multi-modality X-ray imaging of a single cell. The method consists of the preparation of radiation-resistant single-cell samples using live-cell imaging-assisted chemical fixation and freeze-drying procedures, targeting and labeling cells for correlative XRT and XRF measurement, and computational reconstruction of the correlative and multi-modality images. With XRT, cellular structures including the overall structure and intracellular organelles are visualized, while XRF imaging reveals the distribution of multiple chemical elements within the same cell. Our correlative method demonstrates the feasibility and broad applicability of using X-rays to understand cellular structures and the roles of chemical elements and related proteins in signaling and other biological processes.

cell biology↗

bioRxiv2023

Anti-PD-1-iRGD Peptide Conjugate Boosts Antitumor Efficacy via Engagement Augmentation and Penetration Enhancement of T cells

Despite the important breakthroughs of immune-checkpoint inhibitors (ICIs) in recent years, the overall objective response rate (ORR) remains limited in various cancers. Here, we synthesized programmed cell death protein-1 (PD-1) antibody iRGD conjugate (PD-1-(iRGD)2) through glycoengineering and bio-orthogonal reaction. PD-1-(iRGD)2 exhibited extra iRGD receptor dependent affinity to several cancer cell lines rather than normal cell lines. Via dual targeting, PD-1-(iRGD)2 engageed tumor cells and T cells thus mediating T cell activation and facilitating tumor elimination. Besides, the attachment of iRGD impressively improved the penetrability of both PD-1 antibody and PD-1+ T cells. In multiple syngeneic mouse models, PD-1-(iRGD)2 effectively reduced tumor growth with satisfactory biosafety. Moreover, results of flow cytometry and single-cell RNA-seq revealed that PD-1-(iRGD)2 remodeled the tumor microenvironment (TME) and expanded a unique population of "better effector" CD8+ tumor infiltrating T cells (TILs) expressing stem and memory associated genes including Tcf7, Il7r, Lef1 and Bach2. Conclusively, PD-1-(iRGD)2 could be a novel and promising therapeutic approach for cancer immunotherapy. Statement of significanceDesigned against the clinical dilemma of unsatisfied response rate after contemporary cancer immunotherapy, PD-1-(iRGD)2 engages T cells and tumor cells, promotes T cell infiltration and expands a unique population of "better effectors" with enhanced therapeutic potential for the treatment of cancer.

immunology↗

bioRxiv2023

Genetic regulatory effects in response to a high cholesterol, high fat diet in baboons

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWAS), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using nonhuman primate models.

genomics↗

bioRxiv2023

A systematic comparison of computational methods for expression forecasting

Expression forecasting methods use machine learning models to predict how a cell will alter its transcriptome upon perturbation. Such methods are enticing because they promise to answer pressing questions in fields ranging from developmental genetics to cell fate engineering and because they are a fast, cheap, and accessible complement to the corresponding experiments. However, the absolute and relative accuracy of these methods is poorly characterized, limiting their informed use, their improvement, and the interpretation of their predictions. To address these issues, we created a benchmarking platform that combines a panel of 11 large-scale perturbation datasets with an expression forecasting software engine that encompasses or interfaces to a wide variety of methods. We used our platform to systematically assess methods, parameters, and sources of auxiliary data, finding that performance strongly depends on the choice of metric, and especially for simple metrics like mean squared error, it is uncommon for expression forecasting methods to out-perform simple baselines. Our platform will serve as a resource to improve methods and to identify contexts in which expression forecasting can succeed.

bioinformatics↗

bioRxiv2023

Actin-Driven Nanotopography Enhances Integrin Molecular Clutch in Developing Tissue

Morphogenesis requires building stable macromolecular structures from highly dynamic proteins. Muscles are anchored by long-lasting integrin adhesions to resist contractile force. However, the mechanisms governing integrin diffusion, immobilization, and activation within developing tissues remain elusive. Here, we show that actin polymerisation-driven membrane protrusions form nanotopographies that enable strong adhesion at Drosophila muscle attachment sites (MAS). Super-resolution microscopy revealed that integrins assemble adhesive belts around Arp2/3-dependent actin protrusions, forming invadosome-like structures with membrane nanotopographies. Single protein tracking showed that, during MAS development, integrins became immobile and confined within diffusion traps formed by the membrane nanotopographies. Actin filaments also displayed restricted motion and confinement, indicating strong mechanical connection with integrins. Using isolated muscles cells, we show that substrate nanotopography, rather than rigidity, drives adhesion maturation by regulating actin protrusion, integrin diffusion and immobilization. These results thus demonstrate that actin-polymerisation driven membrane protrusions are essential for the formation of strong integrin adhesions sites in the developing embryo, and highlight the important contribution of geometry to morphogenesis.

cell biology↗

bioRxiv2023

An interbacterial lipase toxin with an unprecedented reverse domain arrangement defines a new class of type VII secretion system effector

The type VII protein secretion system (T7SS) is found in many Gram-positive bacteria and in pathogenic mycobacteria. All T7SS substrate proteins described to date share a common helical domain architecture at the N-terminus that typically interacts with other helical partner proteins, forming a composite signal sequence for targeting to the T7SS. The C-terminal domains are functionally diverse and in Gram-positive bacteria such as Staphylococcus aureus often specify toxic anti-bacterial activity. Here we describe the first example of a new class of T7 substrate, TslA, that has an unexpected reverse domain organisation. TslA is widely found across Bacillota including Staphylococcus, Enterococcus and Listeria. We show that the S. aureus TslA N-terminal domain is a phospholipase A with anti-staphylococcal activity that is neutralised by the immunity lipoprotein TilA. Two small helical partner proteins, TlaA1 and TlaA2 are essential for T7-dependent secretion of TslA and at least one of these interacts with the TslA C-terminal domain to form a helical stack. Cryo-EM analysis of purified TslA complexes indicate that they share structural similarity with canonical T7 substrates. Our findings suggest that the T7SS has the extraordinary feature of recognising a secretion signal present at either end of a substrate.

microbiology↗

bioRxiv2023

Traditional medicinal use is linked with apparency, not specialized metabolite profiles in the order Caryophyllales

A better understanding of the relationship between plant specialized metabolism and traditional medicinal use has the potential to aid in bioprospecting and the untangling of cross-cultural plant use patterns. However, given the limited information available for metabolites in most plant species, associating medicinal properties with a metabolite can be difficult. The order Caryophyllales has a unique pattern of lineages of tyrosine- or phenylalanine-dominant specialized metabolism, represented by mutually exclusive anthocyanin and betalain pigments, making the group ideal to work around a lack of detailed knowledge of specific metabolites. We compiled a list of medicinal species in selected tyrosine- or phenylalanine-dominant families of Caryophyllales across the globe (Nepenthaceae, Polygonaceae, Simmondsiaceae, Microteaceae, Caryophyllaceae, Amaranthaceae, Limeaceae, Molluginaceae, Portulacaceae, Cactaceae, and Nyctaginaceae) by searching scientific literature until no new uses were recovered, and tested for phylogenetic clustering of medicinal uses using a "hot nodes" approach. To test potential non-metabolite drivers of medicinal use, like how often humans encounter a species (apparency), we repeated the same analysis in North American species across the entire order and performed phylogenetic generalized least squares regression (PGLS) with occurrence data from the Global Biodiversity Information Facility (GBIF). We hypothesized families with Tyr-enriched metabolism would show clustering of different types of medicinal use compared to the ancestral Phe-enriched metabolism. Instead, weedy, wide-ranging clades in Polygonaceae and Amaranthaceae are overrepresented across nearly all types of medicinal use. Therefore, we found that apparency is a better predictor of medicinal use than metabolite profiles, although metabolism type may still be a contributing factor.

plant biology↗