Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax, supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities.Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a  Metagenomic data and network analyses are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, Hessler et al. combine experiments with metagenome-informed, microbial consortia-based network analyses to identify interactions in microbial consortia grown under dozens of conditions. Microbial communities are critical to human health, agriculture, industrial bioprocesses and the functioning of natural environments such as soil, groundwater and oceans. However, our ability to predict the structures of microbial communities, and how these might be altered by perturbations such as sustained environmental changes, is lacking. Microbial communities are underpinned by numerous interactions, the understanding of which should enhance our ability to manipulate and improve microbiome functioning.1. In the context of microbial communities, such networks and interactions have, by and large, been predicted using abundance and taxonomic information inferred from 16 S rRNA gene amplicon sequencing data . However, 16 S rRNA sequencing does not provide any information about an organism’s functional potential and also suffers from the fact that the network nodes representing the quantifiable units of 16 S analysis  are not necessarily synonymous with independent microbial species. Thus, networks constructed from 16 S data likely do not represent co-occurrences of unique and independent species as well as lack any functional basis to explain why some organisms are network hubs or exhibit strong interdependencies with other organisms.Correlation-based network analysis is one of the longest-standing methods for identifying interacting organisms in ecosystems4 recently suggested moving away from correlation-based networks to modeling approaches. These include Generalized Lotka-Voltrerra models5 and Dynamic Flux balance analysis models6 that are based on genomic information. For example, genomic information has been used to generate metabolic models that predict the interactions between two species in co-culture7 and have demonstrated that cross-feeding is common. The inherent nature of cross-feeding between organisms that do not encode for the biosynthesis of their own metabolites necessary for growth gave rise to the Black Queen hypothesis8. This hypothesis supposes that the loss of genes and pathways enables the conservation of an organism’s resources and leads to microbial dependencies.To generate a mechanistic understanding of interactions in communities, Qian et al.Despite the progress and the promising outlook of these modelling approaches, they remain difficult to implement for complex microbial communities under varied conditions, and are therefore, largely limited to simple microbial systems. In contrast, we hypothesized that the functional basis for microbial interactions can be predicted if genome-resolved metagenomic data for complex microbial communities are incorporated into conventional network analyses.-) microbial culture originating from a mine tailings reservoir, and operated under varying conditions12. As vitamin B12  is produced by only a subset of organisms within these systems12, we hypothesize that vitamin production may underlie the functioning of specific keystone organisms in these communities. Vitamins are essential for cellular function, and vitamin auxotrophs are frequently observed within microbial communities14. Not all bacteria need certain vitamins. A vitamin auxotroph is therefore defined as an organism (i) unable to synthesize its own vitamin (ii) which it requires for growth. However, Xavier et al.15 predicted some vitamins and cofactors as essential in bacteria, including thiamine, coenzyme-A (for which pantothenic acid is required for biosynthesis) and NAD(H). Sokolovskaya et al.14 proposed cobamides as a model system for studying microbial interactions, in part because their biosynthetic pathways are well annotated and are near-essential. Experimental evidence supports this focus. For example, a prior study generated vitamin, amino acid, nucleotide and carbon metabolism auxotrophs in E. coli and found that vitamin auxotrophs were more likely to enter into cross-feeding interactions with organisms with complementary auxotrophies in mixed communities16.Our previous work has produced and analyzed metagenome datasets from numerous bioreactors which were inoculated with thiocyanate-degrading  concentrations, applied hydraulic retention times, and with or without the addition of molasses as an additional energy sourceBecause the bioreactors contained organisms able to degrade thiocyanate, the thiocyanate concentrations remained below detection levels, preventing any toxicity effects. The 92 metagenomic datasets included draft genomes for virtually all the relatively abundant organisms. We used this data to construct an abundance-based co-occurrence network onto which we overlaid functional capacity predictions, predicted vitamin auxotrophies, and identified and tested these predicted microbial interactions Fig. .Fig. 1Sc17 which implements the SparCC algorithm18, which has been developed to address the challenges associated with compositional data. We used positive linear correlations between the 309 species-representative genomes recovered across the 92 bioreactor metagenomes , three Betaproteobacteria , a member of the Gammaproteobacteria family Rhodanobaceraceae and a member of the Bacteroidiota family Chitinophagaceae.We delineated eight nodes as network hubs Fig.  based onThe network was partitioned into modules, subnetworks which make up the network, by computing the maximum modularity of the network based on Louvain heuristics Fig. . ModularChitinophagacaea (Node 221) was more frequent and abundant in planktonic communities as well as high thiocyanate samples. This was also true for the other nodes in this node’s module. In contrast, the module associated with the Alphaproteobacteria hub (Node 54) was more frequent and abundant in low thiocyanate samples and in planktonic communities. The other determined hub nodes showed little difference between these conditions, suggesting they have a broader ecological tolerance within these bioreactor systems.We investigated how specific conditions may affect the network structure. We categorized the samples into biofilm or planktonic as well as environments with high or low thiocyanate concentrations. Most network hubs showed similar frequency and abundance in biofilm and planktonic samples Figs. , S3. HowNitrospira (Node 176), Comamonas (Node 261) and Variovorax (Node 55) for the provisioning of thiamine, Chitinophagacaea (Node 221) for pantothenate, as well as a Rhodanobacter (Node 48) for the possible provisioning of biotin and riboflavin  with the genome from the metagenome for the hub organism. We, therefore, focused on the subnetwork for which Variovorax is the hub.We performed an isolation campaign in an attempt to recover as many organisms represented in the network as possible. This led to the isolation of 43 bacterial species and single yeast species. Only one hub organism was isolated, a Variovorax’s high thiamine hubness of 60.0  and 82 as auxotrophs with the ability to produce thiamine and recalculated Variovorax’s thiamine-hubness score. We repeated this process for a total of one thousand simulations  producers, but the majority of the organisms which were correlated with Variovorax were thiamine auxotrophs  are located separately in the Variovorax genome. Neither the standard thiamine transporter genes thiT  nor any of the ykoFEDC genes were identified in the Variovorax genome, possibly due to poor transporter annotation.A single thiamine-pyrophosphate (TPP) riboswitch-regulated operon contains the majority of the known thiamine biosynthetic genes within the ter Fig. . The bio23. This requires the mutation of three genes, one of which is the thiamine-monophosphate kinase (thiL). The isolated Variovorax thiL amino acid sequence appears functional, based on a comparison with a functional thiL sequence analysis performed by McCulloch et al.24. The active site residues of our Variovorax’s thiL are present and the additional conserved residues identified by McCulloch and co-authors were largely maintained , lipids, and complex and recalcitrant (often plant-derived) carbon compounds such as xylan and cellulose . Variovorax was found to be correlated with two pantothenate acid-producing bacteria, a Sphingobacteria and a Kapabacteria.The 7.9 Mbp ose Fig. . The genVariovorax belong to rare and understudied phyla including a Chloroflexota, a Kapabacteria, an Armaimondota and two Saccharibacteria  was previously predicted to be a Microbacterium ginsengsoli (Node 144) based on co-occurrence patterns identified through hierarchical clustering12. Neither Saccharibacteria nor Microbacterium have genomes that encode for the biosynthesis of thiamine, but nonetheless, all encode several genes coding for proteins which are known to require thiamine as a cofactor. The proliferation of Saccharibacteria to high abundance levels only occurred when Variovorax was reasonably abundant  for their capacity to produce thiamine. The capacity to synthesise thiamine was observed in 24.5% of Gammaproteobacteria genera, 20% of Proteobacterial genera and only 10% of all 9884 Proteobacteria genomes. Variovorax is among the Proteobacteria genera with the highest proportion of members that encode thiamin biosynthesis . Each of these 27 genomes encoded a thiazole synthase (thiG), 17 of which encode a complete thiamine biosynthesis pathway and the other 10 encode a near-complete pathway .To test the hypothesis that oph Fig. . We hypoure Fig. . VariovoVariovorax in minimal media with the addition of 25% spent media from a Cryptococcus five-day monoculture in minimal media. In minimal media without the addition of spent media, no visible growth of Variovorax was observed. The spent media enabled Variovorax to reach an optical density (OD600) of ~0.15 after 96 h  over the first 144 h.We performed growth experiments of ons Fig. . In all ons Fig. . Increasons Fig. , until tVariovorax sp. is a hub  and other organisms in its immediate network neighborhood, the number of thiamine autotrophs in this neighborhood set, but it also considers the number of connections between these thiamine auxotrophs and predicted thiamine producers other than Variovorax. This last term downplays the importance of a predicted interaction in cases where other organisms (within the immediate network neighborhood or outside of it) could be alternative sources of the resource. This metric can be readily applied to future analyses to assess auxotrophies and metabolic exchange in other microbial communities. In future work, it would be interesting to explore how higher concentrations of molasses, other complex substrates, or vitamin additives would reconfigure the network.Here by overlaying functional metagenome information onto co-occurrence networks we identified several microorganisms in a complex microbial community which we predict to be important for the provisioning of B vitamins. We developed a hubness metric that can be used to evaluate the extent to which a resource of interest is important for structuring microbial interactions within subnetworks of networks that describe microbial community co-occurrence patterns Fig. . We usedhub Fig.  because Variovorax, which we predicted to be important for the biosynthesis of thiamine. Thiamine is a cofactor required by enzymes throughout central metabolism including those of the tricarboxylic acid cycle25, pentose phosphate pathway26, and amino acid catabolism and anabolism27, yet not all bacteria in the bioreactor communities are predicted to encode the genes necessary for thiamine synthesis. Unlike most prior studies that have used genomic data to investigate potential microbial interdependencies, we tested the prediction experimentally and correctly predicted thiamine production and interdependence. We confirmed vitamin exchange through isolation and characterization of the Variovorax predicted to be responsible for thiamine production, together with an isolated thiamine auxotroph, Cryptococcus. We report evidence that Cryptococcus is a pantothenic acid producer, a B-vitamin for which Variovorax is auxotrophic. This complementarity led to a 90–130-fold increase in cell density for both members when grown in co-culture. Cryptococcus was not present within the correlation network, likely due to its occurrence in only a handful of communities. Although it is possible that these two organisms are not directly interacting with each other in the mixed bioreactor communities, the exchange of vitamins between them in co-culture and the resulting fitness effects demonstrate that vitamin exchange is likely to have a potent impact on Variovorax and thiamine auxotrophs in the bioreactor communities.We isolated a network hub organism Variovorax and two Saccharibacteria, a Kapabacteria, a Chloroflexi and an Arminatododetes sp. . The significantly larger genome size of genomes, such as Variovorax, that encoded for more vitamin biosynthesis pathways suggests a tradeoff between genome streamlining and vitamin auxotrophies, as noted recently by Rodríguez-Gijón et al.32. This may be an important observation for the identification of key vitamin providers in microbial communities.We noted a correlation between sp. Fig. . The preVariovorax has been shown to be an important member of rhizosphere microbial communities33. Previously reported Variovorax genomes encode a repertoire of complex carbon compound degrading genes, which is consistent with the genetic potential of our Variovorax  responsible for the phosphorylation of thiamine-phosphate, a thiamine permease (yuaJ) and active transporter responsible specifically for the influx of thiamine (ykoD). Analysis of the isolated Variovorax thiamine-monophosphate kinase (thiL) protein sequence appears functional based on a comparison with the crystal structure and sequence analysis performed by McCulloch et al.24. The active site residues of our Variovorax’s thiL appear conserved and the additional conserved residues identified by McCulloch and co-authors were largely maintained. This supports that the regulation of this operon is functional. We suggest that Variovorax has evolved to produce large quantities of thiamine to support dependent organisms some of which, in turn, produce pantothenate. It is likely that cheaters, organisms that consume thiamine but do not produce anything beneficial to Variovorax in return, exploit this thiamine-producing phenotype. Overcoming cheaters may explain why such high concentrations of thiamine are produced by Variovorax.We demonstrated that the Variovorax in minimal media could be stimulated through the addition of pantothenate. Supplementing greater concentrations of pantothenate led to a shorter duration of lag phase with higher supported cell densities. Thiamine overproduction was then observed during this lag phase. The observed change from thiamine production to consumption by Variovorax, at the start of exponential growth, confirms that the thiamine biosynthesis operon can be properly regulated and is not constitutively-on as occurs in dysregulated mutants44. We hypothesize that the production of high concentrations of thiamine during lag phase may have evolved in this Variovorax to stimulate the growth of primarily pantothenate-producing bacteria. Variovorax is correlated with two pantothenate producers. Although Crypotoccus did not occur frequently enough to be included in the network, it probably exemplifies this co-dependency. The extreme thiamine-producing phenotype and the prevalence of this operon across the Variovorax genus suggest the potential of Variovorax for biotechnological vitamin production.The growth of 45. The use of bioreactors to study microbial communities allows for many conditions to be maintained, such as temperature, dilution rate, and incoming solute concentrations. The steady-state conditions that are achieved rapidly in continuous stirred tank reactors leads to stable microbial communities and likely reduces noise and may have enabled more robust inference of microbial interaction from our network analysis. Our integration of network analysis with pathway reconstruction from genome-resolved metagenomics represents a readily implementable tool for identifying interacting microbial community members and their mechanism of interaction. The approach demonstrates the value of metagenomic datasets from sample series and is readily implementable in future studies of other microbial consortia.Recent studies simulating microbial communities with established microbial interactions have shown that inferring microbial interactions from correlations can be flawed, particularly, when correlations are drawn from noisy dataSaccharibacteria, Actinobacteria and Variovorax, and for vitamin exchange, such as between Variovorax and Cryptococcus. Our results predict that Variovorax in our consortia has evolved to overproduce thiamine to support organisms that depend on it for this vitamin and provide evidence to suggest that thiamine production is likely an important trait for these bacteria in many ecosystems.In summary, using laboratory consortia experiments and co-cultures of isolated microorganisms, we demonstrate the predictive power of combined network analyses, genome-resolved metagenomics, and pathway reconstruction for the elucidating interactions in complex microbial communities. We provide evidence for interdependencies such as between species of symbiotic 9, Kantor et al.10, Rahman et al.11 and Huddy et al.12. Briefly, 1 L glass stirred-tank reactors were inoculated with homogenized biofilm and planktonic samples taken from long-running thiocyanate-degrading bioreactors at the University of Cape Town. The reactors were stirred using a pitched-blade impeller at 270 rpm and sparged with filtered air at 0.9 L/min. The bioreactors were fed continuously with deionized water containing 0.28 mM KH2PO4 and were buffered to pH 7.0 using 5 N KOH. Variable concentrations of sodium-thiocyanate (50–2000 mg/L) were supplied in the medium as the predominant electron donor. Molasses was included in some of the bioreactor mediums at 0.15 g/L while being omitted in others. All of the bioreactors were operated continuously at hydraulic retention times varying from 12–42 h. Biofilm and planktonic samples were recovered from the bioreactors at chemical steady states as described by the aforementioned studies.The bioreactors used to study this microbial consortium were operated and sampled by Kantor et al.12 recovered and reconstructed from 92 thiocyanate bioreactor metagenomes were pooled and a final genome set was produced using dRep 46 at 95% ANI. Open reading frames (ORFs) were predicted using Prodigal v2.6.348 and annotated using Hmmscan (http://hmmer.org/) against KEGG (release 2022/04) and PFAM v35.0 databases. Vitamin pathways were recovered from KEGG website and applicable literature49. The capacity to produce a vitamin was determined based on a minimum set of genes representing different stages of each pathway. These minimum genes necessary for the deemed presence of a pathway are described in Supplementary data Previously published MAGshttps://github.com/wwood/CoverM). Coverm calculates the relative abundance of a genome by dividing the number of read bases that align with the genome by its total length. This value is then multiplied by the proportion of total reads mapped to the genome. Correlations, and associated p-values, between the genomes’ relative abundance values were calculated using FastSpar17 (https://github.com/scwatts/fastspar) which implements the SparCC algorithm18 and again separately using Flashweave19 .Reads were mapped to the dereplicated genome set, and relative abundance calculated, using CoverM  refers to summation of edges that these auxotrophic nodes share with nodes able to produce the vitamin.A third metric was developed in this study for the quantification of the importance of a vitamin producer within the network Eq. , termed http://www.cytoscape.org/). Network modules were determined using the Louvain method implemented by Networkx50. Module detection was repeated with the Girvan-Newman algorithm  were annotated as described above using KEGG HMMs and their capacity to synthesize thiamine evaluated. Genomes classified as Variovorax were then dereplicated at 98% average nucleotide identity (~subspecies level) using dRep46. GToTree v1.5.3152 was used to identify, align, trim and concatenate 16 universal ribosomal proteins from the Variovorax genomes. A maximum-likelihood Phylogenetic reconstruction of these alignments was performed using IQtree53 (-st AA -nt 48 -bb 1000 -m LG + G4 + FO + I). The phylogenetic tree was then annotated in iTol54 v6.5.8. The contamination of these genomes was estimated using CheckM v1.2.155. Complete thiamine biosynthesis pathways contained all KEGG annotations for (i) thiazole production, (ii) pyrimidine synthesis, (iii) the linking of these two moieties and (iv) the kinases involved in the overall biosynthesis process. Near-complete pathways were those that only lacked a phosphomethylpyrimidine synthase  from this pathway.Species representatives in GTDBwww.github.com/najoshi/sickle) and assembled using IDBA-UD56 using default settings. Annotation was performed as described above. Genome assemblies were manually inspected for contamination and completeness based on the GC, coverage and phylogeny of scaffolds and the presence of bacterial single copy marker genes using ggKbase (https://ggkbase.berkeley.edu).Microbial isolates were recovered from an in-house thiocyanate-degrading bioreactor by serial dilution in sterile 1x PBS buffer and spread plating onto R2A solid agar medium. Recovered isolates were grown in liquid R2A medium and 600 uL combined at 1:1 with 50% (v/v) glycerol before being stored at −80 °C. The remaining cell culture was pelleted at 10 000 g for 10 min and used for subsequent DNA extraction. Total DNA was extracted from the isolates using a DNAeasy® PowerSoil® Pro DNA extraction kit . Paired-end Illumina TruSeq libraries with fragment sizes of 500 bp were sequenced on an Illumina NovaSeq to yield 250 bp paired-end reads. Reads were trimmed using Sickle , with and without the addition of 0.5 mg/L thiamine. The Cryptococcus species identified as a possible thiamine auxotroph was grown in a 96-well plate in liquid M9 minimal media with (n = 6) and without (n = 6) the addition of 0.5 mg/L thiamine. Growth was quantified spectrophotometrically at 600 nm.The recovered isolates were screened for thiamine auxotrophies using solid M9 minimal media . Only biological and no technical repeats were performed in these experiments.To evaluate the effect of the growth of Variovorax was cultured in M9 minimal media in the presence of varying concentrations of pantothenate using the methodology described above but allowed to grow for a total of 9 days. The cultures were performed with four replicates and were sampled aseptically every 24 h and quantified for cell optical density. Subsequently, cells were pelleted at 10 000 g for 3 min in a benchtop centrifuge and filter sterilized using a 0.22 um filter. These solutions were then used for the quantification of extracellular thiamine.2PO4 (pH = 2.5), and (B) pure methanol. The flow rate was 1.0 mL/min. The mixture of these mobile phases were as follows: 0% mobile phase B from time of injection, 50% mobile phase B from 1.0 min to 75% mobile phase B from 10 to 25 min. We identified vitamins using a G1362A Refractive Index Detector at 220 nm. Vitamin standards were obtained from Sigma-Aldrich®.The quantity of thiamine produced by Variovorax was quantified during the growth in 75% fresh minimal media and 25% filter-sterilized spent medium from the final passage of the co-culture experiment as well as during the growth of Variovorax in M9 minimal media with varying concentrations of pantothenate. Thiamine was quantified on an Agilent 1200 liquid chromatograph equipped with a Agilent ZORBAX Eclipse Plus C-18 column with a 5 um particle size, maintained at 35 °C. Using a two-phase mobile phase of (A) 25 mM NaHFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1-5Supplementary Data 6Reporting SummarySource Data


The aim of this study was detailed analyses of the lingual surface, lingual glands and lyssa of the four wild species of Felidae. Macroscopic analysis and stereoscopy were used for the general description of the studied tongues. Light microscopy and scanning electron microscopy were used for detailed analysis of the lingual papillae and lingual glands structure. The intrinsic and extrinsic muscles of the tongue were not analyzed in the present study. In all four species of wild felids, typical mechanical lingual papillae were present. Fungiform and vallate papillae were also observed. The main difference was in the foliate papillae area. Histochemical analysis of the lingual glands showed the dominance of mucous secretion in all four wild species of Felidae. The obtained results broaden the anatomical knowledge regarding the similarities and differences of the papillae on the surface of the tongue as well as the lingual glands in biological aspects. Additionally, since the lyssa was characterized in the following study, this may be an introduction to the further comparative analysis of this interesting structure.Neofelis nebulosa and Panthera leo bleyenberghi and the last concern Lynx lynx and Otocolobus manul. Therefore, the present study aimed to characterize the features of the tongue surface, lingual glands and lyssa in the above-mentioned four selected wild species of the Pantherinae and Felinae subfamilies. Macroscopic, histological, histochemical and ultrastructural analyzes were used in the present work. Comparative analyzes of the dorsal tongue surface showed the presence of mechanical lingual papillae on five subtypes of filiform papillae on the apex and body and conical papillae on the root of the tongue. Gustatory papillae in the four analyzed species were fungiform papillae and various numbers of vallate papillae. Foliate papillae were absent in P. leo bleyenberghi and L. lynx, while delicate smooth folds, which were separated by parallel grooves but without taste buds, were present in N. nebulosa. The vallate and foliate papillae were accompanied by lingual glands, which produced a serous secretion, whereas the mixed lingual glands of the lingual root were with a predominance of mucus secretions comparable to four captive Felidae species. In the median plane on the ventral surface of the apex under its epithelium and within the muscle fibers, the lyssa was also observed to a varying degree, with the least developed, and thought about the size of the entire tongue, was in P. leo bleyenberghi. The lyssa structure in the four species was dominated by adipose tissue. The obtained results contribute knowledge concerning the functional anatomy of the tongue in four selected Felidae species, especially in terms of comparative anatomy.Although much attention has been paid in the literature to the morphology of the tongue in various animal species, including some Felidae, it has not yet been described in detail in the vulnerable  Pantherinae and Felinae, includes species with a notable variation in size but all with a hypercarnivorous diet [The family Felidae, composed of two subfamilies ous diet ,2. Theirous diet ,3. The fous diet ,2,4. ThiPanthera onca), the filiform papillae comprise large main papillae and secondary papillae in the apex, large cylinder-like papillae in the anterior part of the body and big conical papillae in the central part of the body [Panthera pardus saxicolor), the keratinized filiform papillae are distributed all over the entire dorsal surface of the tongue and contain small processes. They change into a cylindrical shape in the body and a conical shape in the root [Panthera tigris altaica) has hemispherical and horny-shaped papillae in the apex, as well as papillae with several pointed processes. The body contains giant club-shaped, conical or bifid and hoe-shaped papillae [Catopuma temminckii) has horny-shaped filiform papillae in the lingual apex, large and cylindrical in the anterior part of the body and large and conical papillae in the central part of the body [Leopardus pardalis), the filiform papillae, observed in large numbers in the apex and body, are structurally tapered and have a broader base compared with their apex, and their height increase from one region to another. The conical papillae are in the root [Prionailurus viverrinus), the filiform papillae in the lingual apex have several pointed processes, whereas large cylindrical papillae in the anterior part of the body are large and cylindrical, and large and conical papillae are in the central part of the body [Puma concolor), the margins of the apex are surrounded by numerous papillae with a bulky papillary body and a bifurcated tip, and the dorsal surface of the apex contain remarkably pointed papillae with many secondary projections, which emerge from the base of the main papilla. The mechanical papillae of the body contain filiform, longer, cylindrical papillae with blunt tips  and conical papillae exhibiting a pointed tip  [N. nebulosa in The tongue is an important organ of the digestive system and has a significant role in grasping, swallowing and scrolling foods . Meat anthe body . In the the root . The Sibpapillae . On the the body . In the the root . Additiothe body , while ihe body) . In our Gustatory papillae with taste buds include fungiform, vallate and foliate papillae, which are observed within the Felidae family species; however, foliate papillae are not developed in the majority of felids ,22,23,24Despite the well-known fact that the in some carnivores, the tongue contains a lyssa, whose functional importance is not fully understood ,27, littVery little attention has been paid to the lingual salivary gland ultrastructure in felids. A basic description was performed only in the ocelot , PersianNeofelis nebulosa), Katanga lion (Panthera leo bleyenberghi), Pallas’s cat (Otocolobus manul) and Eurasian lynx (Lynx lynx). Another goal of the work was to compare these structures of the tongue with the features of the tongues of other members of the Pantherinae and Felinae subfamilies and characterize the adaptation of the feline tongue to their hypercarnivorous diet. In addition, the obtained results will contribute to the knowledge of the functional anatomy of the taste organs in vulnerable species (according to the IUCN list) and may be helpful in future comparative studies and research on the adaptation of species to living habitats. The aim of our study was also the explanation of the relationship between the results obtained and the natural environment in which animals are found, their diet and their age.This study aimed to describe the macroscopic and microscopic structures of the lingual surface, the features of the lingual glands and the lyssa of the tongue in the clouded leopard (P. leo bleyenberghi)—male and female, clouded leopard (N. nebulosa), Eurasian lynx (L. lynx) and Pallas’s cat (O. manul)  . The matL. lynx was collected directly to the 4% formaldehyde stabilized with phosphate buffer (pH 7.2–7.4)). The storage temperature of samples was between 2 and 8 °C. After the tongues were rinsed and dried, the length, width and thickness of the tongues were measured using digital caliper (with an accuracy of 0.1 mm). The length of whole tongue, the width of apex, body and root as well as the thickness of the apex, body and root were measured using the same method in all studied animals  . Samples of the different types of lingual papillae from the apex, body and root of the tongue were collected (8 samples from each tongue ), includTissue sections were placed in 4% formaldehyde stabilized with phosphate buffer (pH 7.2–7.4) for at least 72 h. In the next stage, the collected tissues were dehydrated in a series of alcohol dilutions, and then they were placed in xylene and embedded in paraffin in the form of blocks, which were used for further analysis . The speFor histological evaluation of the tissues, each specimen was stained using three methods: hematoxylin and eosin (H&E), Azan trichrome and Masson–Goldner trichrome kit. To assess the secretion types of lingual glands, histochemical methods were used: periodic acid-Schiff (PAS), alcian blue pH 1.0 (AB pH 1.0), alcian blue pH 2.5 (AB pH 2.5), periodic acid–Schiff–alcian blue pH 2.5 (PAS-AB pH 2.5) and Hale’s dialyzed iron staining (HDI) . The sliSystematic sampling strategies were applied for the collection of the research material. Tissue samples for SEM  were takSamples of lingual papillae were placed in 2.0% glutaraldehyde dissolved in 0.1M phosphate buffer at pH 7.4. Further sample analyses were performed based on methodology of Čížek et al. . SEM samNomina Anatomica Veterinaria (2017) [Nomina Histologica Veterinaria (2017) [In this publication, all anatomical and histological terms are used based on the terminology of a (2017)  and Nomia (2017) .Anatomically, the tongues of the Felidae are divided into the apex, body and root . All tonI, FiII, FiIII, FiIV and FiV  was directed caudally and present on the apex of the tongue (II) was the largest subtype of the filiform papillae; it also had a caudal orientation and was present on the rostral part of the body of the tongue just behind the lingual apex (III) had a medio-caudal orientation and was present on the lateral parts of the body of the tongue (IV) had a caudal orientation located on the central part of the body of the tongue between FiIII papillae on each lateral side (V) had a caudal orientation and was located between the body and the root of the tongue  in mucous acini  was present on the lingual apex of the four examined species, and it was formed by the main papilla and several additional projections  additional small elongate projections  had a spatulate tip, and the anterior base of each main papilla was enlarged in all four species  had pointed tips, and they look more conical in shape  were conically elongated with pointed apexes , live in different areas in the natural environment; therefore, the basis of their diets also differs  [N. nebulosa, P. leo bleyenberghi, L. lynx and O. manul. Macroscopic analysis of lyssa revealed substantial differences in the length and thickness of this structure between the analyzed undomesticated Felidae species. However, a different structure was found in Panthera pardus saxicolor [P. leo bleyenberghi when compared in size to the length of the tongue. It is possible that with such a construction of the P. leo bleyenberghi tongue musculature, there is no need for a strong expansion of the lyssa, which in N. nebulosa, O. manul and L. lynx could play the role of a shock absorber. Further studies on the felid`s lyssa structure conducted on a much larger number of samples could be a continuation of the research mentioned above.Lyssa as a structure present on the ventral side of the tongue in the middle apex of the tongue and running along the caudal direction was observed in stic cat ,38, Leoppardalis  and Pantaxicolor . Moreoveaxicolor ,37,39, rfulgens)  and camefulgens) . Cat lysfulgens)  and was fulgens) , which waxicolor , where caxicolor  proposedaxicolor , who desaxicolor . In catsaxicolor . We add axicolor . We suggaxicolor , Shoeib axicolor  describeaxicolor  reportedaxicolor  describeaxicolor  so some Panthera pardus saxicolor were mainly composed of serous cells and a few mucous cells, which differed significantly from the results obtained in our histological observations of the posterior lingual glands in N. nebulosa, P. leo bleyenberghi, L. lynx and O. manul. In the undomesticated captive Felidae we studied, the glands of the tongue were dominated by mucous cells, hence the glands were also referred to as mixed mucoserous glands. Nevertheless, in the connective tissue located below the vallate papillae or foliate papillae (in those which were present), serous units of these lingual glands dominated.Mixed lingual glands present in the examined four species of undomesticated Felidae within the root of the tongue were characterized by the dominance of mucous acini. However, so far, little attention has been paid to the analysis of the composition of posterior lingual glands in various Felidae species. Such research was conducted, among others, on a cat . AccordiP. leo bleyenberghi male, while in the female of P. leo bleyenberghi, the tongue was shorter and with smaller mechanical papillae. The tongues of N. nebulosa, O. manul and L. lynx had comparable lengths; however, they were much shorter than in P. leo bleyenberghi. For the further comparative study of the tongues between the males and females of different felids, a larger collection of tongues is necessary. In addition, the age of animals can influence the keratinization process of the dorsal lingual surface. Typical for the Felidae family, the presence of mechanical papillae was confirmed on the dorsal surface of the tongue  between the apex and the rostral part of the body of the tongue in the four examined species. The keratinization level of these mechanical papillae was different between the examined species. This may be connected with the function of the tongue, especially in felids. In addition, because all the examined animals were collected from zoos, the diet of all these felids was different than in their natural environment, which can influence the level of keratinization of filiform papillae. The difference was also macroscopically and histologically confirmed in the gustatory papillae structure because, in the P. leo bleyenberghi and L. lynx, the foliate papillae were absent in contrast to O. manul where they were well developed. Furthermore, the type of secretion produced by the lingual glands of the root of the tongue differed slightly between the four undomesticated Felidae. The obtained results broaden the knowledge of descriptive (cognitive) anatomy and may constitute an introduction to the further analysis of the adaptation of wild felids, especially species endangered with extinction, to life in a specific environment and the consumption of food typical of these hypercarnivorous animals. In summary, a further comparative study based on a bigger size of samples should be performed for the explanation of age’s influence on the tongue structure and the possible lyssa function .Considering the obtained results, some concordances as well as divergences between the four examined species were found based on macroscopic, histological and SEM analyses. Macroscopically, the tongues had a similar elongated shape in all four felids; the largest tongue was observed in


With the internationalization of traditional Chinese medicine, the demand for medicinal and edible Codonopsis Radix (CR) has increased, and its medicinal resources have attracted attention. CR is a well-known traditional Chinese medicine with a long pharmaceutical and edible history. The Guizhou province in China has abundant CR resources, but in the absence of systematic studies on species identification and chemical compositions, the capacity of the capacity of the province to CR resource has not been fully utilized.We used plant morphology and DNA barcoding techniques to identify Luodang (LD) and Weidang (WD) species. To investigate the differences in metabolites between LD and WD, as well as three Chinese Pharmacopeia CRs, and to predict pharmacological mechanisms of action for the dominant differential metabolites, we utilized widely targeted metabolomics and network pharmacology. The results also revealed the material basis for the excellent food properties of both LD and WD.Codonopsis tangshen and Codonopsis pilosula, respectively. Widely targeted metabolomics analysis revealed that a total of 1,116 metabolites from 14 categories, including phenolic acids, lipids, flavonoids, were found in five CRs and shared 1,054 (94.4%) metabolites. LD and WD each contained 3 and 10 dominant differential metabolites, respectively, which were primarily flavonoids and amino acids. Amino acids, phenolic acids, and organic acids play important roles in their excellent food attributes. In CR, eight dominant differential metabolites were discovered for the first time, including isoorientin-7-O-(6″-feruloyl) glucoside, N-formyl-L-methionine, and cyclo (Phe-Glu), among others. Network pharmacology analyses showed that, in LD, dominant differential metabolites were closely related to anti-tumor, cardiovascular disease improvement, nervous system protection, and metabolic disease treatment, whereas in WD, they were closely related to nervous system protection and cardiovascular disease improvement.The plant traits and DNA barcoding molecular identification results indicated that Luodang and Weidang from Guizhou were The species of LD and WD were included in the Chinese Pharmacopeia, and their metabolite profiles were remarkably similar to CR from traditional producing areas. Therefore, LD and WD can be used and promoted medicinally as CR, and they have potential value for new drug development. This study enriched the database of CR compounds and provided a reference for quality control, resource development, and new drug development of CR. Codonopsis belonging to the family Campanulaceae  Nannf., Codonopsis tangshen Oliv., or Codonopsis pilosula Nannf.var.modesta (Nannf.) L.T.Shen of the family Campanulaceae  deficit, boost immunity, treat stomach ulcers, increase appetite, lower blood pressure, and other conditions. It is occasionally used as a ginseng alternative (Panax ginseng C. A. Mey.) (Codonopsis Radix (CR) is a perennial herbaceous dicotyledonous plant of the genus nulaceae . The genin China . The Chinulaceae . They arA. Mey.) . To dateA. Mey.) , 8.CR is a medicinal material for both medicine and food issued by the Health Commission of China within a limited range and dose . AccordiC. pilosula, C. pilosula var. modesta, and C. tangshen are Jincheng (Shanxi province) and Weiyuan (Gansu province), Jiuzhaigou (Sichuan province) and Weiyuan (Gansu province), and Wuxi (Chongqing) and Enshi (Hubei province), respectively  Ohwi  Ohwi , 29, CurLonga L. , Lycium barum L. , Scutells Georgi , and Sesdicum L. . In contPlant morphology and DNA barcoding molecular identity were merged in this study to distinguish LD and WD and explain their species. Furthermore, the metabolite differences between LD and WD, as well as the traditional CR-producing areas, were investigated using widely targeted metabolomics and network pharmacology analysis. The dominant differential metabolites of LD and WD were screened, the pharmacological mechanisms of action of the dominant differential metabolites were predicted, and their medicinal properties were analyzed. This study will aid in understanding the species information, metabolite characteristics, and pharmacological action mechanisms of LD and WD. It also aims to provide references for expanding the medicinal source of CR, improving quality standards, developing and utilizing LD and WD resources, and researching new drugs.C. pilosula (CP) and C. pilosula var. modesta (CPM) were collected from Weiyuan county and Wenxian county of Gansu province, respectively. C. tangshen (CT) of collected from Wuxi county of Chongqing city . Upon combining information from the origin survey, we initially identified the species of LD and WD.Observations on the stems, leaves, and flowers of plant specimens of CR were checked according to the Pharmacopeia of the People's Republic of China (2020 edition) and the The DNA barcoding molecular markers were applied to identified five species of CR according to the method described by Li et al. . After bhttp://its2.bioapps.biozentrum.uni-wuerzburg.de/). The resulting sequence was sequenced by the Blast database (https://blast.ncbi.nlm.nih.gov/Blast.cgi) for comparison, and the relevant reference sequences were downloaded based on the following comparison results: MF096135, MF096136, MF096142, MF096143, MF096146, MF096147, MF096150, KP318239, KP318243, KP318249, DQ889459, and AF136237. The Mega11.0 software was used to construct a phylogenetic tree using the neighbor-joining (NJ) method. The support of each branch of the clustering tree was examined using a bootstrap test (Bootstrap) with a self-expansion set to 1,000 iterations. The plant morphology and DNA barcode molecular identification methods were combined to identify the CR species.The standard ITS2 spacer sequence was obtained by excising the 5.8S and 28S regions at both ends of the sequence using the ITS2 database . After obtaining the signal intensities of each metabolite's distinctive ions in several samples, the chromatographic peak regions of those ions were integrated to indicate the metabolite's relative abundance. The peak areas were adjusted with retention time and peak type to make it easier to compare the same metabolites quantitatively between samples.The resultant mass spectra were compared in the Metware Biotechnology Co., Ltd. (MWDB) database. Interference signals, such as the repeated signals of Khttps://pubchem.ncbi.nlm.nih.gov/) and then entered into the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) for the prediction of corresponding target proteins  and Cytoscape v3.7.1. Gene Ontology  functional enrichment, Kyoto Encyclopedia of Genes and Genomes  pathway enrichment, and disease enrichment analyses were performed using the DAVID database (https://david.ncifcrf.gov/) (p < 0.01).A network was constructed and visualized with default parameters and similarity thresholds using STRING (http://www.r-project.org) was used to perform principal component analysis (PCA), hierarchical cluster analysis (HCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and graphing. Metabolites with variable importance in the projection  and fold change ≥2 or fold change ≤ 0.5 were considered differential metabolites (DMs) , respectively  content was 61.09%−63.87%, and the high GC content indicated that the DNA double-strand was stable and could be used as an auxiliary indicator for the identification of the above seven CR species . To eliminate individual differences among samples, we performed multiple sequence comparisons and calculated the average Kimura 2-parameter (K2P) distances among CR species separately. The results showed that the intraspecific and interspecific variation sites were 2 and 14, respectively; genetic distance: intraspecific (0)> interspecific (0.000–0.020). The K2P distances between C. pilosula, and C. pilosula var. modesta was 0.000, whereas those between C. tangshen and C. pilosula, C. pilosula var. modesta were 0.010, showing a tighter genetic affinity between C. pilosula and C. pilosula var. modesta. The neighbor-joining (NJ) clustering tree of ITS2 sequences clustered the seven CR sequences into three categories  are included in the Chinese Pharmacopeia as legal species for medicinal or food use throughout the country , C. pilosula var. modesta (CPM), and C. tangshen (CT) from other species of the genus Codonopsis but could not establish their separation. The reason for the unsuccessful identification was that these three species of CR were closely related, and the only difference between C. pilosula and C. pilosula var. modesta was in the two aspects of plant hair and dry root surface circular stripes (Flora of China (Vol. 19) changed C. pilosula var. modesta to C. pilosula subsp. pilosula (former subspecies) and C. tangshen was changed to C. pilosula subsp. tangshen, downgraded to a subspecies of C. pilosula, which provided an essential basis for the classification and affinities at the molecular level and also confirmed the correctness of the Chinese Pharmacopeia to include the three primitive species in the same herbal medicine as CR. Although the DNA barcoding molecular identification method has achieved some success in identifying Chinese herbs and their hybrids, there is still the problem of unsuccessful identification between subspecies, varieties, and original varieties. Follow-up studies might consider addressing this issue at the genomic or proteomic level.Our study found that LD and WD from Guizhou were  stripes . In 2011We used UPLC-ESI-MS/MS to analyze the metabolites to further understand the differences in metabolite accumulation of the five species of CR. Approximately 1,116 metabolites were found and identified in the five species of CR, divided into 14 different chemical classes . The numNumerous investigations on the chemical composition of CR have been published thus far. More than 200 different substances had been identified from CR, including polynyas, polyenes, flavonoids, sugars, volatile oils, alkaloids, organic acids, and amino acids , 39. AppWe also found 77.2 (6.9%) different species of saccharides in CR. Among different saccharides, polysaccharides are very significant macromolecules that are crucial for the development and growth of organisms . StudiesCodonopsis pilosula (Franch.) Nannf. in plant taxonomy, and their genetic relationship is very close. This supports the correctness in the Flora of China classification of C. pilosula, C. pilosula var. modesta, and C. tangshen as the species of Codonopsis pilosula (Franch.) Nannf. and the Chinese Pharmacopeia's classification of these three species as the source of CR. Meanwhile, LD and WD from Guizhou belong to the species included in the Chinese Pharmacopeia in terms of botanical taxonomy, and the chemical composition is highly similar to the traditional genuine producing areas. Therefore, LD and WD can be used and promoted as medicinal herbs. Compared to CP, CPM, and CT, 12, 14, and 18 metabolites were detected only in LD and 13, 10, and 18 metabolites were detected only in WD, respectively . In conclusion, species and environmental variables affect CR quality, and these considerations should be completely considered when introducing artificial cultivation to prevent substantial financial losses.The variation in the metabolic characteristics of medicinal plants is the result of the interaction of species, climate, altitude, rainfall, soil, and other environmental factors . Under rTo further evaluate the fundamental properties and variations of metabolites between LD and WD and CP, CPM, and CT, we carried out hierarchical cluster analysis and principal component analysis. The results of the cluster analysis revealed that the various CR samples were divided into two categories, where CP and CPM were clustered into one category and CT, LD, and WD were clustered into one category, indicating that CP and CPM metabolites had similar characteristics for accumulation, while CT, LD, and WD metabolites had similar characteristics for accumulation. In terms of metabolites, they were clustered into 6 categories, of which B, C, and E were dominated by phenolic components, accounting for 32%, 17%, and 20%, respectively. A, D, and F were dominated by lipids, amino acids and derivatives, and flavones, accounting for 33%, 28%, and 29%, respectively . Princip2(fold change) |>1 and VIP≥1 as criteria. LD and WD were compared with CP, CPM, and CT in a two-by-two comparison to obtain the following six comparison groups of differential metabolites: CP vs. LD, CPM vs. LD, CT vs. LD, CP vs. WD, CPM vs. WD, and CT vs. WD, whose specific expression of DMs is shown in Figures 6, 7. Compared with CP, CPM, and CT, 99, 68, and 105 metabolites were upregulated in LD, and 87, 67, and 135 metabolites were upregulated in WD. While LD upregulated metabolites were mainly concentrated in flavonoids, phenolic acids, alkaloids, and organic acids, WD upregulated metabolites were mainly concentrated in amino acids and derivatives, flavonoids, alkaloids, and organic acids glucoside, 4-Hydroxy-7-methoxycoumarin-β-rhamnoside, N-Phenylacetylglycine, and dioxindole-3-acetyl-3-O-glucoside; 25 prominent differential metabolites were detected in CP vs. LD, including 4,6-Dihydroxyquinoline, N-Phenylacetylglycine, 5,7-Dihydroxy-4-methylcoumarin, phlorizin, α-Hydroxycinnamic acid, and isoorientin-7-O-(6′′-feruloyl)glucoside; and 33 prominent differential metabolites were discovered in CT vs. LD, including isoorientin-7-O-(6′′-feruloyl)glucoside, 2-(Acetylamino)-3-phenyl-2-propenoic acid, N-Phenylacetylglycine, 3-Galloylshikimic acid, and phlorizin , and cyclo(Pro-Leu)*, were significantly upregulated in WD, with N-Formyl-L-Methionine, 4-Hydroxy-L-Isoleucine, cyclo(Phe-Glu), cyclo(Pro-Leu)*, cinnamic acid, hydrocinnamic acid, and 4-Hydroxymandelonitrile being among the seven prominent differential metabolites that were detected in CR for the first time.There were 57 dominant differential metabolites found in CP vs. WD, including dioxindole-3-acetyl-3-O-glucoside, N-Acetyl-L-Methionine, 7,8-Dihydroxy-4-phenylcoumarin, hesperetin-7-O-neohesperidoside(Neohesperidin), and alpha-hexylcinnamaldehyde. Approximately 25 prominent differential metabolites were detected in CPM vs. WD, including tryptamine, N-Acetyl-L-Methionine, 5,7-Dihydroxy-4-methylcoumarin, and abscisic acid. 2-(Acetylamino)-3-phenyl-2-propenoic acidT vs. WD . A comprBy estimating the appropriate target proteins of the two dominant differential metabolites in LD, a total of 196 targets were found. The protein-protein interaction (PPI) network was constructed using the 196 targets and visualized using Cytoscape 3.7.0, . The tarhttps://david.ncifcrf.gov/), GO functional enrichment analysis, KEGG pathway enrichment analysis, and disease enrichment analysis were carried out on the 196 targets. For the statistically significant GO functional analysis, KEGG pathway enrichment analysis, and disease enrichment analysis, a p < 0.01 was chosen. Approximately 169 items, including 98 BP, 32 CC, 39 MF, 25 KEGG pathway analysis entries (http://www.bioinformatics.com.cn/). Histone H3-K9 demethylation, notch receptor processing, protein phosphorylation, one-carbon metabolic process, amyloid precursor protein catabolic process, among others, were BP's primary inclusions in the GO functional analysis. Extracellular MF mostly comprises histone demethylase activity, dioxygenase activity, zinc ion binding, carbonate dehydratase activity, and hydro-lyase activity. CC primarily includes cytosol, plasma membrane, an important component of the plasma membrane, gamma-secretase complex, and other cellular components. Nitrogen metabolism, progesterone-mediated oocyte maturation, human T-cell leukemia virus 1 infection, prostate cancer, notch signaling pathway are among the major topics covered by KEGG pathway analysis. The illness enrichment analysis revealed that oncological diseases, cardiovascular system diseases, neurological disorders, metabolic system diseases, and metabolic diseases accounted for the majority of the 196 targets matching LD-dominating differential metabolites. A “drug-component-target-network” map of LD was created using Cytoscape software (3.7.0) based on the screening of 2 components, 196 targets, and 20 pathways  could not be accessed from the PubChem database. The PPI network map was visualized using Cytoscape (3.7.0), and it revealed that the targets with ≥50 degrees were SRC, MAPK1, HSP90AA1, CTNNB1, HDAC1, GRB2, RXRA, CREBBP, RELA, ESR1, MAPK14, and PTPN11. This suggests that the targets play a more crucial role in the PPI network map .https://david.ncifcrf.gov/). GO functional analysis, KEGG pathway analysis, and illness enrichment analysis were all chosen as statistically significant at a p < 0.01 each. Moreover, 645 GO functional analyses yielded a total of 645 entries (http://www.bioinformatics.com.cn/). Chemical synaptic transmission, proteolysis, a reaction to lipopolysaccharide, an excitatory postsynaptic potential, a response to the medication, etc., were the primary components of BP in the GO functional analysis. CC mostly consists of a membrane raft, a plasma membrane, a presynaptic membrane, an integral component of the plasma membrane, and other membranes. The majority of the KEGG pathway analysis topics include neuroactive ligand-receptor interaction, cancer-related pathways, prostate cancer, apoptosis, calcium signaling pathways, etc. The 487 targets that corresponded to the major differential metabolites of WD were primarily associated with neurological and cardiovascular disorders, according to the disease enrichment analysis. The “drug-component-target-network” network map of WD was created using Cytoscape software (3.7.0) based on the nine components, 487 targets, and 20 pathways discovered during the screening  metabolites with three species  of CR from traditional production areas, with remarkably similar metabolite profiles. Therefore, we believe that LD and WD produced in Guizhou can be utilized medicinally and promoted. Furthermore, LD and WD each had 3 and 10 dominant differential metabolites, respectively, of which many were flavonoids and amino acids. The dominant metabolites were mainly enriched in secondary metabolic biosynthesis, metabolic pathways, flavonoid biosynthesis, tryptophan metabolism, and linoleic acid metabolism. Compared with the traditional CR production areas, LD and WD were influenced by the climate of Guizhou with low latitude, low latitude, high altitude, high precipitation, high average annual temperature, and relative humidity. They were more prone to accumulating some amino acids, phenolic acids, and organic acids, which may be the reason for their excellent food attributes. The metabolites isoorientin-7-O-(6″-feruloyl) glucoside, N-formyl-L-methionine, 4-hydroxy-L-isoleucine, cyclo (Phe-Glu), cyclo (Pro-Leu)*, cinnamic acid, hydrocinnamic acid, and 4-hydroxymandelonitrile were detected in CR for the first time in our study. The network pharmacological analysis found that the two dominant differential metabolites of LD might be related to protecting the nervous system, improving the cardiovascular system, treating tumor diseases, and managing diabetes. The nine dominant differential metabolites of WD might be related to protecting the nervous system and curing cardiovascular diseases. This study provided a scientific foundation for the medical use and promotion of LD and WD, as well as a reference for CR quality control, resource exploitation, and novel drug development.In this study, with the results of plant traits and DNA barcoding molecular identification taken together, we believe that LD and WD are The original contributions presented in the study are included in the article/KZ: Validation, Writing—original draft, Investigation, Methodology. DZ: Validation, Writing—original draft, Conceptualization. QY: Resources, Writing—review and editing. LL: Writing—original draft. JX: Writing—review and editing. YW: Writing—review and editing. QY: Writing—review and editing. FW: Conceptualization, Funding acquisition, Writing—original draft. SL: Investigation, Methodology, Resources, Writing—original draft.


Based on network pharmacology and molecular docking, we investigated the mechanism of action of Sheng Xue Bao mixture (SXBM) in treating iron deficiency anemia (IDA). We screened the HERB and traditional Chinese medicine systems pharmacology database and analysis platform databases to identify the active ingredients and targets of SXBM. The targets associated with “iron deficiency anemia” were collected from GeneCards, TTD, and OMIM databases. A component-target interaction network was constructed using Cytoscape 3.8.2. The protein-protein interaction network of candidate targets was generated using the STRING database and visualized with Cytoscape 3.8.2 software. Core modules obtained from clustering analysis were subjected to Gene Ontology and Kyoto encyclopedia of genes and genomes enrichment analysis. Finally, molecular docking validation of key targets and active components was performed using Autodock Vina software. A total of 174 active components and 111 genes were identified as potential active components and targets for IDA treatment, including quercetin, kaempferol, luteolin, beta-sitosterol, and other flavonoids as main active components. Gene Ontology enrichment analysis show that interleaved genes are enriched in 2328 biological processes, 71 cellular component expression processes, and 157 molecular function processes. Kyoto encyclopedia of genes and genomes analysis mainly envolved Prostate cancer, Hepatitis B, Kaposi sarcoma-associated herpesvirus infection, Endocrine resistance, Lipid and atherosclerosis, Central carbon metabolism in cancer, Human cytomegalovirus infection and HIF-1 signaling pathway. STAT3, SRC, PIK3R1, and GRB2 were selected as core targets. The molecular docking results demonstrated strong interactions between key components and their respective target proteins. Network pharmacological analysis suggested that SXBM could treat IDA by regulating various biological processes and related signaling pathways. It laid the foundation for further elucidating the molecular mechanism of SXBM treatment of IDA. It is one of the most common anemias in the world and has a negative impact on the daily lives of more than 2 billion people worldwide. Due to iron deficiency, the activity of many enzymes is reduced, which affects cell metabolism, which has certain blood system manifestations on the immune function, behavior, and development of the human body, gastrointestinal tract, skin and mucous membranes, and nervous system. For example, patients with iron-deficiency anemia usually have features such as fatigue, palpitations, white eyelids and lips, and a yellow complexion. These phenomena are mainly caused by long-term iron deficiency in the body. However, from the perspective of microscopic pathology, it is manifested in low levels of red blood cells and hemoglobin backlog in blood, low transferrin in serum, and a relatively low iron level. Currently, the international treatment of iron deficiency the anemia is mainly based on the supplementation of inorganic iron sulphate or organic iron complex to improve the absorption of iron in the body. Nevertheless, these treatment options are prone to a range of side effects such as constipation, diarrhea and weight loss. As well as the use of various iron-fortified foods, which may not only have the above-mentioned adverse effects, but also have low absorption and utilization of inorganic salts by the body.Iron deficiency anemia (IDA) is a form of microcytic hypochromic anemia which is mainly caused by a deficiency of iron in the body, resulting in impaired hemoglobin synthesis in the cells. Chinese medicine considered the liver to be the main function of producing blood and the kidney to store essence, the inherent inner foundation of the body. As stated in “Plain Questions • Six Sections Zangxiang Lun Chapter 9”: “The liver... it is born in the tendons to generate blood and qi.” Therefore, in the treatment of iron-deficiency anemia, it is mainly treated from the perspective of nourishing the kidney and nourishing the essence, nourishing the blood, and regulating the liver. The modern Chinese patent medicine Sheng Xue Bao mixture (SXBM) meets the above requirements and has the effect of nourishing the liver and kidney, nourishing qi, and producing blood. Based on this, the modern proprietary Chinese medicine SXBM has the effect of nourishing the liver and kidneys, nourishing qi and promoting blood production, thus meeting the above requirements. Our previous meta-analysis study has confirmed that SXBM is indeed effective in the treatment of IDA. But the molecular mechanism of traditional Chinese medicine in the treatment of iron deficiency anemia still lacks modern scientific research. Recently, network pharmacology has gained worldwide prominence. It has multi-directional cross-integration features that enable comprehensive network analysis of herbal medicines and their compound prescriptions, and it provides a systems-level comprehension of the pathogenesis of diseases. Due to the integrity and systematic nature of its research strategy, it has obvious advantages and potential in elucidating its mechanism of action and explaining the composition of the formulation, in line with the overall concept of TCM evidence-based treatment. In this study, the pharmacological and molecular basis of the SXBM for the treatment of iron deficiency anemia was analyzed from the perspective of network pharmacology, and a “drug effect-element-target continuum” correlation network was established for a multi-group study of the SXBM. The results were further validated using molecular docking study techniques to provide a basis for the ensuing basic experimental studies and clinical trials.The research on “iron-deficiency anemia in traditional Chinese medicine has a history of more than 2000 years. Modern scholars believe that iron deficiency anemia belongs to the category of “blood deficiency.”http://tcmspw.com/tcmsp.php), the ingredients retrieved from the herb database (http://herb.ac.cn/) were used as potential active ingredients. Swiss target prediction is a similarity-based principle that utilizes reverse screening of a database designed to predict the most likely protein targets of small molecules, targets were obtained through the Swiss target prediction database.SXBM includes Heshouwu (Polygoni Multiflori Radix), Nvzhenzi (Fructus Ligustri Lucidi), Sangshen (mulberry fruit), Mohanlian (Eclipta Prostata), Baishao (Radix Paeoniae Alba), Gouji (Cibotium barometz), and Huangqi . The drugs in the SXBM were sequentially input into the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) database for retrieval, and the active ingredients and targets were screened according to the setting of OB value ≥ 30% and drug-like properties value ≥ 0.18. The OB value refers to the speed at which the drug is absorbed into the human body, drug-like properties refers to the structural similarity of herbal ingredients to a known drug. If the drug was not found in the TCMSP database (https://omim.org/), Genecards (https://www.genecards.org/), TTD database (http://db.idrblab.net/ttd/) to find the target of iron deficiency anemia-related diseases.In the previously mentioned meta-analysis, SXBM was found to be effective in treating iron deficiency anemia with significant therapeutic effects. In order to further understand the mechanism of action of SXBM for the treatment of iron deficiency anemia, we have to first identify the target of iron deficiency anemia. We identified the keyword as “iron deficiency anemia” in OMIM  to build a proteinprotein interaction （PPI) protein network map. In a PPI protein network diagram, each node represents a protein encoded by an active ingredient or gene, and the edges in the network diagram represent protein-protein relationships or protein-target relationships. It is to be noted that the protein type “Homo sapiens” should be selected for searching, and the Interaction between minimum threshold should be set to 0.9 to obtain the network relationship data of the target interaction. In order to further screen core genes, the obtained network relationship data of target interaction can be imported into Cytoscop 3.8.2, using the NetworkAnalyzer tool for in-depth topology analysis, and the MCODE module for gene cluster analysis and core target screening.The drug-disease common targets were entered into the String database  enrichment and KEGG pathway analysis. And visualize the results with Rstudio. Our flow chart of the study is shown as Figure https://rcsb.org) and changed it into a pdb format structure file, and used pymol software to convert the above-mentioned targets. The 4 targets were subjected to hydrogenation, water removal, solvent molecule removal, unwanted ligand removal, and homodimer retention of only single chains, and then exported to pdbqt format files using autodocktools software. Download the top 4 active ingredients in terms of degree value in the Pub Chem database (https://pubchem.ncbi.nlm.nih.gov/). The sdf format structure files of the components is exported to pdb format files after hydrogenation by pymol software, and they are then exported to pdbqt format files after defining Torsion using autolock tools software. Open the pdbqt format file of the receptor protein and ligand small molecule in the autolocktools software, generate the docking box and adjust the parameters, run autodock vina to dock the 4 targets with the 4 active components of SXBM, and analyze the docking results obtained. The binding strength and activity are evaluated based on the binding energy and the number of generated hydrogen bonds between the receptor protein and the ligand small molecule. The results were visualized using pymol and the Discovery Studio software.The above methods are all predictions of the target genes for the SXBM treatment of IDA. In the following, we will use the molecular docking method to verify whether the above predictions are accurate. The interaction between the core component of the SXBM and the key target is analyzed using the molecular docking technique. We downloaded SXBM-IDA Target PPI network in the RCSB PDB database , GRB2 (PDB: 1gry), STAT3 (PDB: 6NJS), SRC (PDB: 2h8h). The binding strength and activity were evaluated according to the binding energy and the number of generated hydrogen bonds. Since the higher the absolute value of the binding energy during the molecular docking process, the better the affinity between the receptor and the ligand is. In this study, the binding energy ≤ −5.0 kcal/mol was selected as the screening basis for the effective binding of key active ingredients to the core target. The molecular docking results are shown in Table IDA is mainly due to insufficient storage or intake of iron in the body. Lack of iron or insufficient utilization of iron can lead to problems in the transport and storage of oxygen, carriage of carbon dioxide, and redox metabolic processes in the body, which can affect human growth and development and even lead to various diseases such as anemia. Iron is one of the vital trace elements in the human body. It is the major ingredient of hemoglobin, myoglobin, cytochromes and some respiratory enzymes. It participates in the transport, exchange, and tissue respiration of oxygen and carbon dioxide in the body. The SXBM is composed of 7 traditional Chinese medicines, including Nvzhenzi, Heshouwu, Sangshen, Mohanlian, Baishao, Huangqi, and Gouji. Among them, Nvzhenzi, Mohanlian, and Sangshen have the function of tonifying the liver and kidney, as well as nourishing the vital energy and the blood. Heshouwu has the effect of nourishing blood, Baishao has the function of tonifying the liver and kidney, as well as nourishing the vital energy and the blood. Gouji is useful for cultivating the kidney. Therefore, the effect of SXBM is mainly to nourish the liver and kidney, nourish qi and consolidate the root, and promote blood and nourish the blood. On this basis, this study takes a look at the pathological mechanism of SXBM in the treatment of IDA to reference its clinical application.At present, oral iron preparations still cannot achieve the desired curative effect, so some scholars pointed out that the application of traditional Chinese medicine preparations such as SXBM in IDA treatment can promote the absorption of iron preparations and reduce its related adverse reactions. Quercetin has been found to promote the body absorption of ferritin. Studies have shown that kaempferol, which often exists as a variety of different glycosides, can reduce the expression of inflammatory factors such as TNF-ɑ and has anti-inflammatory, antioxidant, immunomodulatory and tumor suppressive effects, among which the antioxidant effect is more pronounced. Another study shows that the ethyl acetate extract of kaempferol has good antioxidant activity, and its mechanism is mainly to enhance the body against anemia by promoting the proliferation, differentiation, and immunity of red blood cells. In addition, the pathways collected by KEGG enrichment mainly include pathways related to cancer, immune system and hematopoietic function. Among them, the HIF-1 pathway is directly related to hematopoietic function. Studies have shown that the HIF pathway can direct the expression of EPO transcripts, hence promoting mRNA production. The PI3K-Akt signaling pathway as a critical signal transmission axon regulating hematopoietic cell survival, growth and the expansion of hematopoietic cells. Finally, molecular docking results showed that STAT3, SRC, PIK3R1, and GRB2 were the core groups in SXBM. Among them, STST3 is mainly involved in mediating the cellular response process of interleukin, LEP and other growth factors, and SRC mainly promotes the formation and transportation of platelets by regulating the formation of megakaryocytes. Studies have shown that GRB2 associates various cytokine signals with the proliferation pathway of HSPC, especially GRB2 associates IL3 signaling with the ERK/MAPK pathway to induce the proliferation and survival of hematopoietic stem cells.,19 Activation of cell surface receptors tyrosine kinase growth factor and hormone receptors by PI3Ks translates into downstream AKT activation to regulate cell metabolism, size, differentiation, proliferation, migration and apoptosis. The above core genes were highly matched with the target genes in SXBM, indicating that the target of SXBM was highly correlated with the IDA gene.In this paper, a total of 174 components of the SXBM were collected through TCMSP and other databases, mainly including quercetin, kaempferol, luteolin, beta-sitosterol, and other key active components, which constitute multiple common genetic targets with IDA. Quercetin is a flavonoid with anti-inflammatory, anti-viral, anti-allergic and other biological activities.This study investigates the mechanism of SXBM for IDA by utilizing network pharmacology. It is known to improve anemia in the body by promoting angiogenesis, anti-apoptosis, and anti-inflammation, providing a theory to define the mechanism of action of SXBM for IDA treatment. Considering the limitations of existing data analysis based on the network and the interaction of drugs in the decoction process, the current results can provide a reference direction for the follow-up research, but the specific results still need further experimental verification.Data curation: Xinhua Zhang.Project administration: Weiguo Liu.Resources: Hongxu Zhang.Supervision: Haixia Wang.Visualization: Huang Qinqin.Writing – original draft: Yun Wang.Writing – review & editing: Zhenhua Xiang, Yuming Gu.


Objective: To investigate and predict the targets and signaling pathways of sinomenium acutum (SA) in the treatment of rheumatoid arthritis (RA) through systems biology and network pharmacology, and to elucidate its possible mechanisms of action.Methods: We screened the active ingredients and corresponding target proteins of SA in Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN); and obtained the targets of rheumatoid arthritis diseases in a database of gene-disease associations (DisGeNET), Online Mendelian Inheritance in Man (OMIM) database. The two targets were mapped by Venn diagram and the intersection was taken. The intersecting targets were used to construct protein-protein interaction (PPI) network maps in the String database, and Metascape was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Finally, the molecular docking technique was applied to validate and further clarify the core target of SA for the treatment of rheumatoid arthritis.Results: A total of six active ingredients and 217 potential targets were obtained after screening; 2,752 rheumatoid arthritis-related targets and 66 targets common to RA and SA. GO function and KEGG pathway enrichment analysis yielded 751 GO function entries  and 77 KEGG signaling pathways. It mainly involves pathways related to neural activity ligand-receptor interaction pathways, cancer pathways, calcium signaling channels, Th17 cell differentiation and others, which are mainly classified into four categories, including regulation of immunity, anti-inflammation, regulation of cell growth and apoptosis, and signaling. The molecular docking results showed that the binding energy of PTGS2, CASP3, JUN and PPARG to the key components beta-sitosterol, 16-epi-Isositsirikine, Sinomenine and Stepholidine were ≤ −6.5 kcal/mol, suggesting the existence of molecular binding sites.Conclusion: SA acts on key targets such as PTGS2, CASP3, JUN, and PPARG to modulate signaling pathways such as neural activity ligand-receptor interaction, cancer, calcium ion, NF-κB, and Th17 cell differentiation to regulate immunity, anti-inflammation, modulation of cell cycle, bone metabolism, and signaling for the treatment of RA. It was also confirmed that the treatment of RA with SA has multi-component, multi-target, multi-pathway and multi-mechanism characteristics. Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune syndrome. It is characterized by non-specific, symmetric inflammation of the peripheral joints, chronic inflammation and hyperplasia of the synovial membrane, formation of vascular opacities, invasion of articular cartilage, subchondral bone, ligaments and tendons, etc., resulting in destruction of articular cartilage, bone and joint capsule, ultimately leading to joint deformity and loss of function. Some patients are associated with varying degrees of systemic manifestations, and in severe cases, a variety of cardiovascular, pulmonary, and skeletal complications . In the p < 0.00001 and p = 0.008).2) In terms of clinical symptoms: compared with NSAIDs, sinomenine was more effective in improving morning stiffness (p < 0.00001), joint pain (p = 0.03) and erythrocyte sedimentation rate (p < 0.00001), but there was no significant difference between the two therapies in the treatment of joint swelling, grip strength and C-reactive protein (p > 0.05).3) Safety: the frequency of digestive adverse events was lower during sinomenine treatment than during NSAID treatment (p = 0.0003), while neurological adverse events were similar for both treatments (p = 0.31)  is the vine stem of Qing Feng Vine or Mao Qing Vine, etc., of the family Fangjiidae, mainly distributed in China and Japan. The use of SA was first recorded in Bencao Tujing, which has been used from ancient times to the present . In Chin = 0.31) . In vivo in rats . In vitr pathway . SinomenThe concept of network pharmacology was first proposed by Li et al., in 2014 , and is Using the Chinese pinyin or Latin word of SA as the search term, the chemical composition of SA was searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and screened according to pharmacokinetic (ADME): oral bioavailability (OB) ≥ 30% and drug-like properties (DL) ≥ 0. 18. We obtained the active ingredients and corresponding target proteins of SA, and finally standardized the target gene names by the Uniprot database. The target protein supplementation of the active ingredients of Qingfengteng was done in the Traditional Chinese Medicines Integrated Database (TCMID) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN). And the Uniprot database was also used to standardize the target gene names. The network diagram of the relationship between cyanobacteria-active ingredient-target was also constructed with the help of cytoscape 3.9.1.https://www.disgenet.org/) and Online Mendelian Inheritance in Man (OMIM) (http://omim.org/) using “Rheumatoid Arthritis” as the search term. The targets were then converted into standard protein gene names in the UniProt database (https://www.uniprot.org/).The RA-related targets were retrieved from the database of gene-disease associations (DisGeNET) (http://bioinfogp.cnb.csic.es/tools/venny/index.html) to obtain the intersection targets of cytosine and rheumatoid arthritis. And the drug-component-potential action target-disease network map was constructed by Cytoscape 3.9.1.The obtained gene names of SA and RA targets were uploaded to Venny online mapping tool (https://string-db.org). Select mutiple proteins, upload the intersection target genes, and set the corresponding parameters: the protein species is limited to “Homo sapiens”, the minimum interaction threshold is selected as “medium confidence (0.400)", and other parameters were kept as default settings to obtain the PPI network graph. The key targets were filtered out by degree greater than the mean value.The obtained intersecting targets were used to construct protein-protein interaction (PPI) network maps in the String database (https://metascape.org/gp/index.html). The species was selected as “H. sapiens”, and the default settings were Min Overlap of 3, p value < 0.01, and Min Enrichment of 1.5.To illustrate the role of potential targets of SA in gene functions and pathways, the obtained crossover targets of SA and RA were subjected to GO functional annotation and KEGG signaling pathway enrichment analysis by Metascape gene analysis software (https://www.pdbus.org). Download the compound structures of ligands (active ingredients of drugs) in the TCMSP database . The receptors were processed by Pymol to remove water molecules, small molecule ligands, and hydrogenation, and then the ligand format was converted using AutoDock Tools 1.5.6 and the corresponding active pockets (Grid Box) were identified. Finally, molecular docking was performed using Autodock Vina software. Screening was performed based on binding energy < -6.5 kcal/mol, and the docking structures that met the conditions with the lowest binding energy were visualized with the help of Pymol.To validate the accuracy of the screened key targets of SA for RA, the active ingredients associated with potential targets of action screened by the regulatory network were molecularly docked to the top four target degree values of the core. Download the receptor (core target protein) 3D structure in the Protein Data Bank (PDB) database  network maps in the String database, and 10 target genes without interaction were excluded, for a total of 56 genes to construct network maps, as shown in The potential action targets of SA for RA treatment were entered into metascape gene analysis software for GO gene annotation and KEGG pathway enrichment analysis. The results showed that there were 751 GO gene annotation entries. Among them, there are 652 entries of biological process (BP), mainly involving cellular calcium ion homeostasis, adenylate cyclase-modulating G protein-coupled receptor signaling pathway, blood circulation, etc. A total of 59 entries were enriched for molecular function (MF), mainly related to G protein-coupled peptide receptor activity, peptide binding, G protein-coupled amine receptor activity, etc. A total of 40 entries were enriched for cellular composition (CC), mainly involving the integral component of presynaptic membrane, membrane raft, and external side of plasma membrane, etc. See p values were sorted from smallest to largest, and the top 14 pathways with the most significant enrichment were selected and plotted in a bar graph, see via key targets. It shows 44 pathways associated with the 21 key targets. Excluding the less relevant pathways, the top three pathways were Neuroactive ligand-receptor interaction, Pathways in cancer, and Calcium signaling pathway, in order of ranking. Classification of the screened pathways yielded that SA may play a therapeutic role in RA by reference to four aspects: immune modulation, anti-inflammation, cell cycle regulation and signaling ignaling . The claThe molecular docking results showed that the active ingredients beta-sitosterol, 16-epi-Isositsirikine, sinomenine and stepholidine have binding sites with PTGS2, CASP3, JUN and PPARG. Their corresponding minimum binding energies were all below −6.5 kcal/mol . It is sRA is designated as a refractory disease by the World Health Organization , and itsin vivo and in vitro  such as G protein-coupled receptor signaling pathway and blood circulation through cellular calcium homeostasis, adenylate cyclase; molecular functions (MF)such as G protein-coupled peptide receptor activity, peptide binding, and G protein-coupled amine receptor activity; and cellular composition (CC) such as components of the presynaptic membrane, membrane rafts, and the outer side of the plasma membrane for RA. The results of KEGG pathway enrichment analysis showed that SA may treat RA by acting on signaling pathways such as Neuroactive ligand-receptor interaction, Pathways in cancer, Calcium signaling pathway, NF-kappa B signaling pathway, Th17 cell differentiation. Li et al.  found thThe molecular docking results showed that the active ingredients beta-sitosterol, 16-epi-Isositsirikine, sinomenine and stepholidine of SA bind well to the key targets PTGS2, JUN, CASP3, and PPARG had good binding performance with the lowest binding energy of −8.1 to −6.5 kcal/mol, and reached steady state quickly. It indicates that SA can be useful in the treatment of RA.In summary, beta-sitosterol, 16-epi-Isositsirikine, sinomenine, and stepholidine are the main substance bases for the treatment of RA in SA, and PTGS2, JUN, CASP3, and PPARG are the potential targets of action. SA mainly treats RA by modulating inflammatory cytokines, immune cells, regulating cell cycle, such as apoptosis and scorching, and regulating osteoblasts and osteoclasts. This study also revealed the multi-functional synergistic mechanism of SA, involving the conduction pathways of Neuroactive ligand-receptor interaction, Pathways in cancer, Calcium signaling pathway, NF-kappa B signaling pathway, Th17 cell differentiation, further confirming the multi-component, multi-target, multi-pathway, and multi-mechanism characteristics of SA for the treatment of RA. In this study, we investigated the mechanism of action of SA, the source of sinomenine, in the treatment of rheumatoid arthritis by tracing the source, which is more beneficial to promote the development of new drugs. To provide a reference for in-depth research on the treatment of RA with SA. The shortcoming of this study is the prediction of the possible mechanism of action of SA in the treatment of RA by biological database and computer simulation, which needs to be verified by further basic research in the future.