Background: Fusobacterium sp. plays a crucial role in the tumorigenesis and development of gastrointestinal tumors. Our research group previously disclosed that Fusobacterium sp. was more abundant in gastric cancer (GC) tissues than adjacent non-cancerous (NC) tissues. However, Fusobacterium sp. did not exist in all GC tissues and the differentiated features of GC with or without Fusobacterium sp. infection is not clear.Methods: The expression data of 61 GC tissues came from 16S rRNA gene sequencing. Comparison groups were defined based on sOTU at the genus level of Fusobacterium sp., which was performed by the Qiime2 microbiome bioinformatics platform. We used Chi-square and Fisher's exact test to compare clinicopathological parameters, and used Kaplan-Meier analysis, Cox univariate and multivariate analysis to compare prognosis. Micro-ecological environment comparison was characterized by 16S rRNA gene sequencing, and the metabolic function prediction was applied by PICRUSt2. Results of microbial diversity, differential enrichment genus and metabolic function in GC with or without Fusobacterium sp. infection was validated with 229 GC tissues downloaded from an independent cohort in ENA database (PRJNA428883).Results: The infection rate of Fusobacterium sp. in 61 GC tissues was 52.46% and elderly GC patients were more prone to Fusobacterium sp. infection. GC patients infected with Fusobacterium sp. were more likely to have tumor-infiltrating lymphocytes and p53 expression. The microbial diversity and microbial structure showed significant differences between two GC tissue groups with 42 differential enrichment genera. The metabolic function of Fusobacterium sp.-positive GC tissues was related to the biosynthesis of lysine, peptidoglycan, and tRNA. The differences in microbial structure, the existence of some differential enrichment genera and the metabolic function of Fusobacterium sp.-positive GC tissues, were then validated by 229 GC tissues of an independent cohort.Conclusions: Fusobacterium sp. infection can affect the phenotypic characteristics, micro-ecological environment, and metabolic functions of GC, which may provide a basis for further exploring the relationship between Fusobacterium sp. infection and carcinogenesis of GC. Fusobacteria are Gram-negative, obligated anaerobic, rod-shaped bacterium with neither motility nor spore formation, acting as a normal part of the oropharyngeal, gastrointestinal tract, and genital microbiota This study consisted of 61 GC patients who received subtotal gastrectomy at the First Affiliated Hospital of China Medical University from June 2012 to June 2014. The recruited 61 GC tissues were immediately frozen and stored at -80 °C after the operation. Genomic DNA was then extracted for amplification and gene sequencing based on V4-V5 regions of 16S rRNA gene after quality examinations. The inclusion and exclusion criteria of patients, the methods of DNA extraction, and 16S rRNA gene sequencing were the same as our previous paper After 16S rRNA gene sequencing raw sequence data was split, intercepted, spliced, and filtered, we obtained clean tags (fastq reads data). Fastq reads data was then processed by using Qiime2 microbiome bioinformatics platform For the recruited 61 GC patients, general clinicopathological variables information including age, gender, tumor size, differentiation, Lauren's classification, depth of invasion, tumor lymphocyte infiltration, vascular cancer embolus, lymphatic metastasis, and TNM stage were collected from their medical records. The immunohistochemical information of tumor biomarkers including Ki67, p53, CEA, Her-2 were collected from the patients' pathological reports. The prognostic information including survival state, distant metastasis, overall survival (OS), and date of death were collected through telephone follow-up every six months with a follow-up period until November 13, 2019.P values < 0.5 were considered genus enrichment differentiation statistically significant. Spearman's correlation analysis was performed to analyze the correlation coefficients  between enrichment genera. Genera with strong correlations  were screened to construct a correlation network visualized by Cytoscape V.3.7.0.R software vegan package was used to calculate α diversity indexes  whole diversity indexes) PICRUSt2 was used to predict metabolic functions by analyzing sOTUs in Fusobacterium sp. positive and negative GC tissues based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database and MetaCyc database P < 0.05 was considered statistically significant.Mann-Whitney U test was used to compare α diversity between Fusobacterium sp. - positive and negative GC tissues. PERMANOVA was used to test β diversity differences. LEfSe was performed to analyze differential genus enrichment and differential functions. LDA absolute values > 2.0 were considered significant. Spearman's correlation analysis was performed to calculate correlation coefficients  between enrichment genera with r absolute values > 0.7 as a strong correlation. Chi-square test, Fisher's exact test, and Mann - Whitney U test were applied to analyze the correlation of Fusobacterium sp. infection and clinicopathological variables. Kaplan-Meier analysis, Cox univariate and multivariate analysis were applied to evaluate the differences in OS between two GC groups. Mann-Whitney U test, Chi-square test, Fisher's exact test, Kaplan Meier analysis, Cox univariate and multivariate analysis were all statistically analyzed by SPSS 25.0 software . The pictures were drawn by Prism GraphPad 8.4.1, Cytoscape V.3.7.0 and R software. In this study, the age of 61 GC patients ranged from 26 to 83 years with a median age of 61 years. Among these patients, 46 were male (75.41%) and 15 were female (24.59%). Through the Qiime2 microbiome bioinformatics platform, we obtained sOTU absolute abundance data . Taking P = 0.041) and tumor lymphocyte infiltration was related to Fusobacterium sp. infection (P = 0.040). However, for gender, tumor size, differentiation, Lauren's classification, depth of invasion, vascular cancer embolus, lymphatic metastasis, and TNM stage, there were no significant differences between two GC groups (P > 0.05) (Table P = 0.016) and the expression level was higher . Considering the above clinicopathological parameters, Kaplan Meier survival analysis also showed no significant difference between two GC groups (P > 0.05). After Cox univariate analysis, parameters with P < 0.1  were included in multivariate analysis. After adjusting parameters that affect prognosis, Fusobacterium sp. infection could not be regarded as an independent risk factor of prognosis (P > 0.05)  .P > 0.05) (P = 0.001), unweighted UniFrac (P = 0.001), and weighted UniFrac distance metrics (P = 0.042) showed a statistical difference between two GC groups  and phylogenetic diversity (PD) whole tree indexes in Fusobacterium sp.-positive GC tissues were higher than negative ones Figure , while S > 0.05) . In termC groups , suggestr= 0.72, P < 0.05). While in the Fusobacterium sp. - negative group, the correlation was more simple  had higher abundances in Fusobacterium sp. - positive ones . Among them, 25 enzymes and 4 KOs were highly enriched in Fusobacterium sp. -positive GC tissues, 14 enzymes and 1 KO were highly enriched in Fusobacterium sp. -negative GC tissues (We used PICRUSt2 to predict metabolic function and found some enzymes and metabolic pathways between Fusobacterium sp. positive and negative GC groups were significantly different ( tissues . As for  tissues . Among tP =0.039) and Weighted Unifrac distance metrics (P =0.023) were statistically significant. The consistent result of β diversity index indicated that Fusobacterium sp. infection could affect the microbial structure of GC tissues. As for differential enrichment genus, 21 were enriched in Fusobacterium sp.- negative GC tissues and 26 were enriched in the positive ones. Of the 26 genus in Fusobacterium sp.- positive GC tissues, 16 showed the same enrichment as the above results (r < 0.7). In Fusobacterium sp.- positive GC tissues, Fusobacterium sp. showed a middle correlation with Catonella sp. (r=0.47) and Selenomonas sp. (r=0.46). Regarding of the metabolic function, we used PICRUSt2 to predict metabolic pathways through KEGG and metacyc database , which could be affected by MSI status in vivo and in vitro experiments.In the present study, we compared clinicopathological parameters  between GC tissues with or without Fusobacterium sp. infection. A relationship only occurred in tumor-infiltrating lymphocytes: the lymphocyte infiltration was lower in Fusobacterium sp.-negative GC tissues, but higher in Fusobacterium sp.-positive ones. Previous studies on colorectal cancer have demonstrated the relationship between Fusobacterium sp. infection and tumor-infiltrating lymphocytes , p53 expression was related to Fusobacterium sp. infection: the positive and high expression of p53 was more likely to appear in GC tissues with Fusobacterium sp. infection. Wild-type p53 has the effect of blocking cell cycle and inhibiting tumor progression, and mutant p53 plays a role in promoting cancer In the aspect of prognosis evaluation, our work showed no correlation between Fusobacterium sp. infection and prognosis of GC patients. Previous studies in colorectal cancer and esophageal cancer have shown that Fusobacterium may be used as a prognostic biomarker: the higher of Fusobacterium nucleatum DNA (a species of Fusobacterium sp.), the shorter of OS of cancer patients H.pylori-associated superficial gastritis, atrophic gastritis, and intestinal metaplasia In this study, there were differences in microbial diversity, enriched genera, and metabolic function between GC with or without Fusobacterium sp. infection. Compared with Fusobacterium sp.-negative GC tissues, microbial abundance and community genetic diversity were higher in Fusobacterium sp.-positive group. Differences also occurred in microbial structure, which were further validated by 229 GC tissues. These results indicated that the abundance of Fusobacterium sp.- correlated bacteria may increase due to its infection, causing the overall community to change during the evolution of bacteria and affecting the structure of microbial community, but the specific role still needs to be explored. In further analysis of differential enrichment genus, Phenylobacterium and other two genera had higher abundance in Fusobacterium sp.- negative GC tissues, and 39 genera of Prevotella and Bacteroides had higher abundance in Fusobacterium sp.- positive ones. Among them, Fusobacterium sp. had a strong positive correlation with Porphyromonas. This relationship has ever been confirmed in After further metabolic function prediction by PICRUSt2, we identified the role of Fusobacterium sp. in metabolic functions of GC tissues. Based on the MetaCyc database, the metabolic pathway of L-glutamate degradation V (via hydroxyglutarate) was confirmed to be related to Fusobacteria in Fusobacterium sp.-positive GC, which may due to the suitable anaerobic environment for the growth of bacteria. Based on the KEGG database, the differences in metabolic functions between two GC groups were mainly related to amino acids, carbohydrate, vitamins, some compounds and energy metabolism, as well as some genetic information processing pathways such as DNA replication, nucleotide excision repair processes and translation processes (ribosome metabolism and tRNA biosynthesis). To improve the accuracy of metabolic function prediction, we integrated the results of these two databases and concluded that the metabolic functions of Fusobacterium sp.-positive GC were related to the biosynthesis of lysine, peptidoglycan and tRNA. This result was fully validated in the independent cohort of 229 Chinese GC tissues. This suggested that Fusobacterium sp. and its related flora may be involved in the biosynthesis of lysine secreted by gastric juice and also in the peptidoglycans synthesis of Gram-positive and Gram-negative bacterial cell walls. Interestingly, previous studies indicated that the trmFO gene in Firmicutes, Proteobacteria, Fusobacteria, Acidobacteria and an actinomycete could encode the enzyme that catalyzes tRNA formation According to the results of the present study, the infection rate of Fusobacterium sp. was 52.46% in 61 GC tissues. Elderly GC patients were more prone to Fusobacterium sp. infection and the degree of tumor-infiltrating lymphocyte in Fusobacterium-positive GC tissues was higher. GC patients infected with Fusobacterium sp. were more likely to have p53 expression and the expression level was higher. The microbial diversity and microbial structure showed significant differences in GC tissues with or without Fusobacterium sp. infection with 42 differential enrichment genera. Among them, the strong correlation between Fusobacterium sp. and Porphyromonas sp. in Fusobacterium sp. - positive GC tissues suggested that Fusobacterium sp. may affect microbial distribution by affecting Porphyromonas sp. or both. Moreover, the metabolic function of Fusobacterium sp.-positive GC tissues was related to the biosynthesis of lysine, peptidoglycan, and tRNA. Microbial structure diversity, differential enrichment genus and metabolic function were further validated by an independent cohort of 229 Chinese GC tissues. In conclusion, Fusobacterium sp. infection can affect the phenotypic characteristics, micro-ecological environment, and metabolic functions of GC. This may provide a basis and clue for further exploring the relationship between Fusobacterium sp. infection and carcinogenesis, development and prognosis of GC. This may also lay a foundation for further in-depth exploration of the mechanism of Fusobacterium sp. affecting metabolic functions of GC.Supplementary figures and tables.Click here for additional data file.


Hydrodynastes gigas , given its wide distribution throughout South America, including the validity of the recently described Hydrodynastes melanogigasStudies with integrative approaches (based on different lines of evidence) are fundamental for understanding the diversity of organisms. Different data sources can improve the understanding of the taxonomy and evolution of snakes. We used this integrative approach to verify the taxonomic status of H. gigas and H. melanogigas.We performed a phylogenetic analysis of Bayesian Inference with mtDNA 16S and Cytb, and nuDNA Cmos and NT3 concatenated . In addition, we performed traditional morphometric analyses, meristic, hemipenis morphology and coloration pattern of H. gigas is widely distributed throughout South America. We found no evidence to support that H. gigas and H. melanogigas species are distinct lineages, therefore, H. melanogigas is a junior synonym of H. gigas. Thus, the melanic pattern of H. melanogigas is the result of a polymorphism of H. gigas. Melanic populations of H. gigas can be found in the Tocantins-Araguaia basin.According to molecular and morphological characters,  Species are considered lineages with distinct evolutionary histories . TaxonomCurrently, species delimitation must be based on the integration of more than one type of data set , which helps improve taxonomic understanding . An inteAtractus spp.: Apostolepis spp.: Corallus spp.: Drymoluber spp.: Among the morphological characteristics adopted in taxonomic studies that usually result in inaccurate nomenclatural decisions are coloration pattern variations  distributed in Colombia, Venezuela, French Guiana, Guyana, Suriname and Brazil . We used the species Pseudoboa nigra and Xenopholis scalaris as outgroup of Hydrodynastes , Porto Nacional, and Lajeado, which are all located in the state of Tocantins, Brazil. Unfortunately, most of the type series was lost in the 2010 fire that occurred at the Instituto Butantan. Currently, only three individuals remain from the type series: two at the proper Institute in São Paulo (paratypes IBSP 65978 and IBSP 66387) and one at the Museu Nacional do Rio de Janeiro (paratype MNRJ 15101). From the remaining type-series, we analyzed all the remaining individuals.H. gigas and H. melanogigas, we conducted a principal component analysis (PCA) and took the first two principal components of the ordination to create a MANOVA. We ran this analysis with adult males and females separately, and performed the analysis in R software . Our concatenated dataset tree grouped Hydrodynastes melanogigas within H. gigas .We recovered the genus H. gigas . The uncfor Cytb . IntraspHydrodynastes gigas and H. melanogigas  and females  we found no significant morphometric differences between both species . In their description of H. melanogigas, H. gigas based on meristic characters and hemipenis morphology. The only superficial distinction that remains between these two taxa is the presence of melanism in the latter. Geographic or regional melanism has already been reported for several populations of Squamata  description of Xenodon gigas did not refer to any voucher specimen. The authors only cited that M. A. d’Orbigny collected three individuals in Rio de La Plata, Corrientes Province, Argentina (without further information). The authors also mentioned a plate , which only presents a cranial picture. Overall, Hydrodynastes gigas.Description of the lectotype MNHN 3623 (NHN 3623 : Adult oColor of the preserved lectotype (ethanol 70%) (nol 70%) : Head brDiagnosis:Hydrodynastes gigas is distinguished from its congener H. bicinctus by the following combination of characters: dorsal scales normally 19/19/15; ventral scales in males 150–168 and in females 152–172; subcaudal scales in males 58–88 and in females 49–84; maxillary teeth 15–17; two apical pits in the dorsal scales; post-ocular stripe that extends longitudinally (on each side); ventral body with three lines of continuous spots up to the middle of the body.Variation: All variation in morphometric and meristic data are presented in H. gigas (H. gigas –7J dorsuDistribution: Hydrodynastes gigas is widely distributed throughout South America, east of the Andes, occurring in Amazon, East Brazil, La Plata, North Brazil, Northeast South America, Parnaiba and Tocantins-Araguaia hydrobasins (robasins .H. gigas and H. melanogigas based on molecular, meristic, morphometric and hemipenial characters. Therefore, the melanistic pattern of Hydrodynastes melanogigas is characterized here as the result of polymorphism within H. gigas. Although our integrative approach helped elucidate the taxonomic status of H. melanogigas, we believe future, multi-loci phylogeographic studies are needed in order to better understand the evolutionary history of the populations belonging to the two remaining species H. gigas and H. bicinctus.Our results did not separate 10.7717/peerj.10073/supp-1Appendix S1* prepared hemipenes.Click here for additional data file.10.7717/peerj.10073/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.10073/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.10073/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.10073/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj.10073/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj.10073/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj.10073/supp-8Supplemental Information 8Click here for additional data file.


Hymenophyllum caudiculatum (restricted to lower canopy) and Hymenophyllum dentatum (reach upper canopy) during a desiccation/rehydration cycle.Filmy-ferns (Hymenophyllaceae) are poikilohydric, homoiochlorophyllous desiccation-tolerant (DT) epiphytes. They can colonize lower and upper canopy environments of humid forest. Filmy-ferns desiccate rapidly (hours), contrasting with DT angiosperms (days/weeks). It has been proposed that desiccation tolerance in filmy-ferns would be associated mainly with constitutive features rather than induced responses during dehydration. However, we hypothesize that the inter-specific differences in vertical distribution would be associated with different dynamics of gene expression within the dehydration or rehydration phases. A comparative transcriptomic analysis with an artificial neural network was done on H. dentatum and 34,726 transcripts for H. caudiculatum. Few transcripts showed significant changes in differential expression (DE). H. caudiculatum had ca. twice DE genes than H. dentatum and higher proportion of increased-and-decreased abundance of genes occurs during dehydration. In contrast, the abundance of genes in H. dentatum decreased significantly when transitioning from dehydration to rehydration. According to the artificial neural network results, H. caudiculatum enhanced osmotic responses and phenylpropanoid related pathways, whilst H. dentatum enhanced its defense system responses and protection against high light stress.Raw reads were assembled into 69,599 transcripts for Our findings provide a deeper understanding of the mechanisms underlying the desiccation tolerance responses of two filmy ferns and the relationship between the species-specific response and the microhabitats these ferns occupy in nature. Plant evolution has shaped several acclimation mechanisms and adaptations to withstand short and long-term periods of water deficit. However, most plants cannot survive desiccation, except for a small group of so-called resurrection plants , 2. DesiLindernia brevidens, an angiosperm species from tropical rain forests [Surprisingly, resurrection plants are also found in humid environments such as tropical and temperate rain forests . One exa forests . The epi forests . The mem forests , 11. Bec forests , 12, 13.Hymenophyllum caudiculatum and Hymenophyllum pectinatum are restricted to the lower portion of the host trunk , where light availability is very low (10–100 μmol photons m− 2 s− 1), and humidity is high. Other species  extend their vertical distribution to heights above 10 m  [in situ or under experimental conditions. Here we used RNA-seq on the Illumina Hi-seq platform to study and compare the transcriptional responses of H. caudiculatum and H. dentatum, two Hymenophyllaceae species with contrasting vertical microhabitat preferences along host trees and different rates of water loss  , 13, 15. 2 s− 1) . AdvanceH. dentatum losses water faster than H. caudiculatum, reaching 18 and 30% RWC respectively. During this period of dehydration, the maximum quantum efficiency (Fv/Fm) drastically decayed from about 0.7 to 0.2 in H. dentatum but remained nearly 0.78 in H. caudiculatum  by the end of the experiment. Recovery of photochemical efficiency at the whole frond level was confirmed by imaging fluorescence , both reaching ca. 60% of relative water content (RWC) Fig. a. From 3H. caudiculatum and H. dentatum, on the Illumina HiSeq2000 platform  were obtained after sequencing libraries of H. dentatum, and ~ 65% H. caudiculatum; Additional file H. caudiculatum and H. dentatum had among their top hits a high amount of sequences belonging to the model moss Physcomitrella patens and the lycophyte Sellaginella moellendorffii . Finally, in the molecular function category (MF), the highest accumulation of sequences was found to be in the antioxidant activity, followed by binding process  . Both species showed similar enrichment pattern of sequences for each GO category Fig. . For exaess Fig. .Fig. 5GH. caudiculatum, and 128 for H. dentatum show that there are broadly three main processes involved in the desiccation tolerance of these two filmy ferns, namely translation, photosynthesis and antioxidant activity . For the dehydrated and re-hydrated conditions, respectively, the enrichment of transcripts was observed in Nodes 3 and 2 in H. caudiculatum  were enriched in functional categories related to stress signaling and response, photosynthesis and photosystem II stabilization and repair, unsaturation of fatty acid, and lignin biosynthetic process. Next, transcripts in the rehydration state (Node 2) were enriched in responses to oxidative stress, lignin biosynthetic process, photosynthesis, protein-chromophore linkage, cellular redox homeostasis, and translation. On the other hand, in H. dentatum, the dehydrated state (Node 2) was enriched in functional categories related mainly with antioxidant responses such as glutathione metabolic process and ROS detoxification systems, drought response, transcription, translation regulators, photosystems II stabilization, ATP synthesis and proton transport, photoprotection, and ABA non-regulated stress responses. For the rehydrated state (Node 6), transcripts were enriched in functional categories corresponding mainly to ethylene and abscisic acid related signaling, photosynthesis, proton transport, plasmodesmata-mediated intercellular transport, response to stress and to toxic substances.From the annotated DE genes, we studied the dynamics of gene expression in these two resurrection filmy ferns to identify, firstly, transcripts with similar accumulation patterns in response to a given hydration status, and secondly, the complexity of the interaction and co-expression of genes related with their desiccation and rehydration responses. The self-organizing maps (SOM) partitioned the DE genes into six clusters (hereafter nodes) arranged as a map Fig.  a-c. Thetum Fig. b, and Notum Fig. d. In ordH.caudiculatum, and 1, 2 and 6 in H. dentatum), we carefully reviewed the annotated genes with high scale expression to construct weighted gene coexpression networks for each node ; light harvesting complexes and reaction centers of photosystems I and II ; lipid metabolism and transport . Under desiccation, the resultant network showed six hub genes (> 100 connections), and they were part of one of the modules. Hub genes were involved in: cell wall reinforcement (WUN1); glutathione metabolism ; mitochondrial uncoupling protein (PUMP4); glycosylation (U85A3); nitrogen mobilization (NRTs). At the rehydration state, the resultant network contained only eighteen genes, all with the same number of connections among them. Two main process were represented by these genes, namely cell wall structure and architecture , and stress response and signaling .From these SOM nodes , chloroplast development , and cell wall structure and architecture . Under desiccation, the resultant network contained a total of forty-two coexpressed genes. Among them, we found genes involved in flavonoid biosynthesis (CHSY), structure of photosystems I and II , stress response (GL82), ubiquitination (UBIQP), aldo-keto reductases (ALKR4), immune system and Salicylic acid homeostasis (DLO2), non-symbiotic hemoglobins (HBL) which function in signal transduction pathways of several hormones, Jasmonic acid precursor (OPR7). Lastly, at the rehydration state the resultant network contained only 6 coexpressed genes. They were mainly involved in membrane metabolism , stress response and signaling , and plant immunity , and sugar metabolism (GRG1).Regarding rks Fig. b. At thek-means clustering [H. caudiculatum and H. dentatum occupy along the vertical distribution over host trees.Previous studies have indicated at different scales, from cellular to ecophysiological approaches, how Hymenophyllaceae species from temperate rain forest responds to desiccation –17, 23. ustering , these mustering . The chaustering , 20, proustering , 30, 31.ustering , 32, disustering , 34, andustering –37, assoAt a fully hydrated state, the patterns of transcripts accumulation in both species reflect normal functioning of primary metabolic process such as photosynthesis and respiration. After dehydration, the clustering patterns and abundance of differentially expressed identified transcripts, shared mechanisms associated with the maintenance of redox homeostasis, stabilization and maintenance of the photosynthetic apparatus, and chloroplast operational signaling. In contrast, the species-specific responses were particularly associated to phenolic compounds biosynthetic pathways  and photoinhibition related processes. Both general and species-specific responses agree with physiological, ultrastructural, and chemical changes, as with the homoiochlorophyllous strategy of these filmy ferns , 15, 23.LATE EMBRYOGENESIS ABUNDANT PROTEIN 14 gene (LEA14) which has been reported as an atypical LEA protein localized in the cytoplasm and nucleus, with important roles against abiotic stress, particularly osmotic and drought stress [It must be noted that because the relatively few transcripts showing differential expression, the desiccation tolerance response of these two filmy ferns would rely mainly on constitutive mechanisms, as it has been suggested by proteomic analyses . Based ot stress , 39.Glutathione-S-Transferases (GST), while there is a decrease of GST genes following rehydration. GST enzymes scavenge a wide variety of toxic compounds . When ttes; see . Efficietes; see , 6, 36.,tes; see ), these  enzymes . Evidenc enzymes ), theref enzymes .Craterostigma pumilum, in which the inverse pattern occurs [Both species also shared patterns of gene expression involved in the control of structure and function of photosystems. During desiccation both species accumulate transcripts encoding for components of reaction centers of Photosystem I and II while there is a decrease in transcripts abundance encoding for light-harvesting antenna and oxygen-evolving complexes. This response differs with what has been reported for the model resurrection plant n occurs . A plausn occurs , and theAAA-ATPase genes which are known to be involved in ROS signaling and the presence of components of signal transduction such as Auxin and calcium signaling, oxylipin metabolism, and ethylene and ABA responsive transcription factors points to the chloroplast as the signaling orchestrator [DREB, ERF, RAP), which are known to be involved in responses to environmental stimuli, especially for redox, osmotic and drought stress [The coordination of the complex mechanisms such as those mentioned above require intertwined signaling pathways for systemic responses against the internal and external constraints associated with the resurrection strategy. The increases of transcript abundance of estrator . Becauseestrator , 46, 47,estrator . Accordit stress , 34. Mort stress , activatH. caudiculatum underpins enhanced osmotic responses and phenylpropanoid related pathways, whereas in H. dentatum the specific responses point to enhanced protection against oxidative damage and high light stress. By the other hand, the gene co-expression networks analysis provides a detailed interaction of central genes conferring each species-specific response. Examining the responses of H. caudiculatum during the dehydration-rehydration cycle, we observed an increase in the abundance of the DOG1 gene when full hydrated and rehydrated. This gene is involved in controlling the timing of seed dormancy in response to environmental signals such as temperature by altering gibberellin metabolism [DOG1 gene in H. caudiculatum suggest an induced mechanism linked to ABA and GA balance by a common intermediary such as DELLAs proteins [One of the most ambitious goals of our study was to associate the different niche preference of these two filmy fern species with species-specific transcriptional responses to have insights into particular physiological conditions that may prevail under different frond hydration states. In general, based on the DE analysis and the pairwise comparison among hydration states Table , the spetabolism . Given tproteins . Based oproteins , 52, whiproteins , membranELI6 gene which encodes an early light inducible protein  and posttranscriptional regulations that may have central roles in the desiccation tolerance strategy of these species when subjected to rapid loss-and-gain of water as occurs in the natural environment. Also, studies under an evolutionary developmental biology approach would help to decipher and understand the genetic basis of physiological, developmental and morphological variation associated with the microclimatic conditions in which these resurrection filmy ferns have evolved.Hymenophyllum caudiculatum (Mart.) var. productum (K. Presl.) and Hymenophyllum dentatum (Cav.)  Fig.  were colhttp://www2.udec.cl/~herbconc/index.htm, Herbario CONC, Departamento de Botánica, Universidad de Concepción, Barrio Universitaro s/n, Casilla 160-C, Concepción, Chile.)It is worth to note that the deposit of specimens to an herbarium was not necessary, since they already exist in the collection of the Herbarium of the Universidad de Concepción , dehydrated (DH), and rehydrated (RH)  in which fronds of a fluorescence signals obtained from attached fronds using a modulated fluorometer  as previously described in [− 2 s− 1) was applied to obtain the maximum fluorescence (Fm). Variable fluorescence (Fv) and Fv/Fm ratio were calculated according to [P value ≤0.05. When data did not meet the normality assumptions, we used the non-parametric test of Kruskal-Wallis. Additionally, fluorescence images of Fv/Fm were obtained using detached fronds under each hydration condition FH, DH and RH using a Maxi-Imaging PAM  to observe the rate of recovery of the quantum yield of fluorescence (YII) at the whole frond level of both species  was calculated from chlorophyll ribed in . Brieflyrding to  at ambieCarlsbad, CA, USA) and purified with Total RNA I kit  according to manufacturer’s instructions. The yield and quality of the RNA isolation samples was determined by an Agilent 2100 Bioanalyzer. The RNA was precipitated with two volumes of acetate:ethanol solution (1:10 v/v) and sent for sequencing to Macrogen Inc., Korea. A total of six samples were sequenced in a single lane of an Illumina HiSeq 2000 platform  obtaining 100 bp paired end reads. After quality filtering with the NGSQC Toolkit v2.3 ([http://www.nipgr.res.in/ngsqctoolkit.html) and Q-score composition .Reads from each sample were mapped to their corresponding final transcriptome using default RSEM parameters (RSEM = RNA-Seq by Expectation Maximization) written in the align_and_estimate_abundance.pl script. The resulting RSEM-estimated gene abundances for each fern were merged in a matrix and analyzed with run_DE_analysis.pl script from Trinity, which involves the Bioconductor package edgeR in R statistical environment , 59. Trahreshold . Functiohreshold , www.panH. caudiculatum and H dentatum that met the expression values determined from the model described above were used for the SOM clustering method [H. caudiculatum and H. dentatum. Scaled expression values were used to cluster genes in both species across fronds hydration states into a multidimensional 2 × 3 hexagonal SOM using the Kohonen package on R [Normalized RSEM-estimated counts of both g method . Specifig method ;) separaage on R . One hunage on R , AdditioH. dentatum and H. caudiculatum were selected, respectively. For the selection of genes, those transcripts from SOM nodes with the highest scaled accumulation patterns for a given hydration state were chosen. Then, only those genes with GO annotation were selected. .In order to go further the gene co-expression patterns obtained from the SOM analysis, a further Gene Regulatory Network-based (GRN) approach was used to study the interactions between gene expression and fronds hydration state of each fern species. From the SOM clustering method, a subset of 67 and 183 annotated genes from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE140234 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE140238.The quality-filtered, barcode-sorted, and trimmed short read data set used for transcriptome assembly and gene expression analysis, was deposited in the NCBI Sequence Read Archive (SRA) under accession SRR5195043, SRR5272488, SRR5272490, SRR6452149, SRR6452987, and SRR6453153. Additionally, the gene expression profiles of the assembled transcriptomes were deposited in the NCBI Gene Expression Omnibus database (GEO). For confidential access to the public GEO records use the following links: Additional file 1: Table S1. Statistics for RNA-seq libraries sequencing of H. caudiculatum (Hca) and H. dentatum (Hdent) for each of their hydrated states. Statistics shows total number of reads (No. of reads), high quality reads that passed quality control (No. of HQ reads), reads that were mapped to transcriptomes (No. of mapped reads) and their percentage of mapping (Mapping rate) Table S2. Assembly statistics for H. caudiculatum and H. dentatum transcriptomes before (raw) and after refinement (filtered). The total number of transcripts (No. transcripts), number of trinity components (Trinity components), putative transcriptome in mega base pairs (Transcriptome Size), basic statistics on transcript lengths  and assembly quality as N50 (N50) Table S3. Blast results for H. caudiculatum and H. dentatum against SwissProt database. Table shows the counts distribution per sequence size (Size range) of blast hit (Blast Hit) and missing hits (Unknow) and the cumulative percentages (Cums %)Additional file 2: Dataset S1. Matrix of the DE genes among pairwise comparissons between frond's hydration states of H. caudiculatum. Columns indicates de sequnce ID (id), fold change (log FC), counts per million (log CPM), the significance , the false discovery rate value (FDR), and the normalized counts for each hydration state , Dataset S2. Matrix of the DE genes among pairwise comparissons between frond's hydration states of H. dentatum. Columns indicates de sequnce ID (id), fold change (log FC), counts per million (log CPM), the significance , the false discovery rate value (FDR), and the normalized counts for each hydration state , Dataset S3. Matrix showing those highly abundant genes without significant changes between frond's hydration states of H. caudiculatum and H. dentatum. Columns shows the gene id, transcript id, the counts abundance for each hydration state, the UniProt ID, the percentage of similitud of the Blast query, and the Protein Name, Dataset S4. Matrix of the Self-Organizing Maps output for the Nodes 2, 3 and 6 for H. caudiculatum, Dataset S5. Matrix of the Self-Organizing Maps output for the Nodes 1, 2 and 4 to 6 for H. dentatum.Additional file 3 : Figure S1. Quality scores and accuracy of Illumina Hiseq 100-bp paired end reads for H. caudiculatum and H. dentatum after quality filters. Bad quality reads that showed values 20 on the histogram were discarded. All reads above the value of 30 indicates 99.9% of accuracy, regarding to bases correctly read by the sequencer, Figure S2. Training progress of the average distances of genes of H. caudiculatum and H. dentatum using Self-Organizing Maps showing the effect of neighborhood shrinking to include the winning unit, i.e., when the vectors in the dataset reach the closest similarity. Figure S3. Codebbook vectors for H. caudiculatum and H. dentatum showing the clusters of differentially expresed genes with maximum neighbouring after training process. The codebook vectors represent the expression profile of genes associated to a given state after the constructionof the mapAdditional file 4: Dataset S6. Compiled GO enrichment data for H. caudiculatum, Dataset S7. Compiled GO enrichment data for H. dentatum.


Ophiocordyceps sinensis (Berk.) is a well-known entomopathogenic and medicinal fungus. It parasitizes and mummifies the underground ghost moth larvae to produce a fruiting body named Chinese cordyceps. Specific for the fungus, O. sinensis experiences a biotrophic vegetative growth period spanning over 5 months. During this vegetative growth, it appears successively in the host hemocoel in three/four morphotypes, namely, the yeast-like blastospores (subdivided into proliferative (BP) and stationary phase (BS)), prehyphae (PreHy) and the hyphae (Hy). This peculiar morphogenesis has been elucidated through morphological and ultrastructural observations, but its molecular basis remains cryptic. In this study, transcriptome and metabolome profiling of BP, BS, PreHy and Hy stages were performed to characterize the key genes, metabolites, and signaling pathways that regulated the vegetative development of O. sinensis in Thitarodes xiaojinensis larva.O. sinensis in the host hemocoel. Genes homologous to Saccharomyces cerevisiae MAPK cascade were significantly up-regulated during the transition from blastospore to hypha. The up-regulation of Sho1, a regulator protein, suggested nutrient starvation act a role in activation of MAPK pathway and filamentous growth. In addition, up-regulation of several fatty acid synthesis genes and their corresponding products accumulation in the samples of BS might explain more lipid droplets were observed in BS than in BP. Coupled with the up-regulation of fatty acid degradation during PreHy and Hy stages, it is presumed that lipid accumulation and mobilization play important roles in filamentous development.The molecular events and metabolic pathways that regulated different intracellular processes at various stages were examined. Cluster analyses of differentially expressed genes across the four stages revealed the stage specifically enriched pathways. Analysis of metabolome profiles showed that carbon metabolism and several amino acids biosynthesis were significantly perturbed during the tested development stages of O. sinensis in vivo. Our findings provide new perspectives into the key pathways and hub genes involved in morphological changes of fungus developed in the hemocoel of its host, and are expected to guide future studies on morphogenesis and morphotype changes of entomopathogenic fungi in vivo.This is the first report comprehensively describing developmental transcriptomics and metabolomics of The online version contains supplementary material available at 10.1186/s12864-020-07209-2. Dimorphism is a common phenomenon in fungi, especially in pathogenic fungi, which widely occurs in insects, plants, and mammals . DimorphMetarhizium spp. and Beauveria spp., have been chosen as models to describe the molecular events sustaining pathogenesis [Ophiocordyceps sinensis , distributed in the alpines of the Tibetan Plateau, exhibits a different life cycle. Specifically, it parasitizes larva of the genera Hepialus and Thitarodes , but does not kill its host until it develops into the last instar stage, which lasts more than 5 months under optimum laboratory conditions [O. sinensis successively appear in the host hemocoel. Yeast-like unicellular blastospores, that occupy almost 90% of biotrophic parasitizing duration, are the first to occur and are sequentially subdivided into blastospores in proliferative stage (BP) and blastospores in stationary stage (BS) depending on whether they are actively budding or not. Upon establishment of the parasitization, BP undergoes extensive proliferation and growth to reach a threshold density, at which period the blastospores enter the stationary phase. As the host larva enters the last instar, the BS develops and transforms to pod-like multinuclear unbranched segmented filaments, which is nominated prehyphae (PreHy). Hyphae (Hy) germinates from the PreHy approximately 2 weeks later, fuses and intertwines with each other to form a hyphal network that finally kills the larva [In previous studies of entomopathogenic fungi, some biocontrol agents, including ogenesis , 17. Oncogenesis . Howevernditions . Its fruhe larva . The thrO. sinensis development in vivo is quite limited [O. sinensis with its host in laboratory settings [O. sinensis morphogenesis and morphotype transition within the host hemocoel have not been studied. Transcriptome analysis has been widely applied to investigate gene expression patterns at RNA levels. However, only a handful studies have characterized the temporal and spatial expression of O. sinensis genes at different developmental stages [Up to date, investigation of  limited , since isettings . In addil stages , 22–24, l stages . IntegraO. sinensis development in the hemocoel of the host larva of Thitarodes xiaojinensis. Specifically, we analyzed four fungal morphotypes (sub-morphotypes), including BP, BS, PreHy, and Hy, and unraveled the molecular features of each morphotype as well as the transformation mechanisms within the host insect. Taken together, our results provide a better understanding of the developmental biology of O. sinensis and the underlying molecular mechanisms for morphotype changes in entomopathogenic fungi.In this study, we conducted a combined metabolome and transcriptome analyses of O. sinensis genome [Sequencing of total RNA samples from the four morphotypes, BP, BS, PreHy, and Hy Fig. , with ths genome  as referA summary of differentially expressed genes (DEGs) between the two adjacent groups was provide in Additional file The 3569 DEGs from the four stages were subjected to hierarchical cluster analyses  Fig. c. The upGene expression patterns in the PreHy Fig. . In clusMost up-regulated genes (831) annotated in Hy  samples ensured detection stability  were not increased during the stationary stage, with the most obvious changes occurring when a large number of lipid droplets accumulate in the BS cells . ParticuBased on the transcriptome and metabolome results, some major pathways associated with fatty acid synthesis were constructed, which mapped the glucose utilization, tricarboxylic acid (TCA) cycle inhibition, acetyl-CoA and NADPH generation, and fatty acid biosynthesis Fig. a. The glO. sinensis and its host insect have not been sufficiently explored in nature. However, previous reports have indicated that O. sinensis is highly dependent on ghost moths for survival and sexual reproduction [The life cycles of oduction . To effioduction , 3.O. sinensis coexists with its host as the yeast-like blastospores occupying about 90% of its biotrophic duration. During this long coexistence period (more than 5 month), blastospores continuously duplicate along with the growth of the asymptomatic host until reaching to a density of more than 6 × 108 spores/mL in the host hemocoel. This enables a longer and peaceful coexistence between a pathogen and its host, and ensures that the highest biomass could be accumulated in a single host, which is important for the low infection rate of O. sinensis [Candida albicans [Highly polarized unicellular yeast-like form of pathogenic fungi is the in vivo form that is used to evade its host immune system . Adoptedsinensis . It is osinensis . Specifialbicans .O. sinensis-ghost moth larva parasitic system is that before a true Hy develops, an intermediate morphotype, PreHy occurs between the Y-to-H transformations at the last instar of ghost moth larva [A peculiar characteristic of this th larva . This phth larva .The filamentous hyphae grow by tip extension and generate significant tip pressure, which facilitates tissue penetration during infection –37. WithS. cerevisiae, MAPK pathways is used to regulate various cellular functions, such as osmolarity adaptation, mating, cell wall integrity, and filamentation [O. sinensis. In contrast, up-regulation of the Sho1 homolog in O. sinensis was consistent with its role in activation of hypha formation. Hog1 protein has been shown to regulates invasive growth and morphological changes in C. albicans [O. sinensis.In entation . Studiesentation –42. The entation , 43. Thealbicans . In this8 spores/mL host hemolymph. At the same time, the spore size increased from the initial BP stage 1.5–2.5 × 7.7–17.8 μm, to 4–4.9 × 27.3–49 μm at PreHy stage, which almost occupied the entire space of the host hemocoel [The nutrient-rich insect hemolymph is the most important site for the proliferation and growth of entomopathogenic fungi. Previous studies have reported that fungal infection is often accompanied by a significant decline in insect hemolymph nutrients, consistent with its parasitic fungus nutrient and energy acquisition , 45. In hemocoel . This reO. sinensis development in the ghost moth. These results provide a simple systemic biological overview of the underlying molecular and biochemical events. Specifically, our results from the four transcriptome and three of metabolome data revealed that the four O. sinensis morphotypes within the host hemocoel had distinct signatures. Moreover, genes in the O. sinensis MAPK cascade may function during the yeast to hypha switch, which might be due to nutrient starvation. Additionally, fatty acid synthesis and degradation potentially playing important roles in the aforementioned morphotype changes. This is the first study that investigated molecular events of O. sinensis developing and changing within its host hemocoel with methodologies of transcriptomic and metabolomic, which would be helpful to understand the morphogenesis and morphotype changes of entomopathogenic fungi in vivo.Overall, transcriptome and metabolome profiling unraveled the pathways associated with morphotype characteristics and morphological changes during T. xiaojinensis, were collected from Xiaojin county, Sichuan province, China , and subsequently reared in the laboratory for three generations. O. sinensis was isolated from fresh Chinese cordyceps collected from the same place. Fifth instar larvae were inoculated by injection using a glass capillary loaded with 5 μL diluted BP suspension (3 × 106 blastospores/μL). Four developmental stages of O. sinensis were harvested from T. xiaojinensis hemolymph  and Sickle (https://github.com/najoshi/sickle) with default parameters. Levels of gene expression for each gene were expressed as fragments per kilobase of exon model per million mapped reads (FPKM) [O. sinensis genome [P-values using the Benjamini and Hochberg method [2 (Fold Change) │ ≥1 and a FDR ≤ 0.005 in a comparison were identified as DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was carried out using KOBAS [https://cran.r-project.org/web/packages/pheatmap/index.html). Raw Illumina sequencing data of O. sinensis were submitted to NCBI as BioProject PRJNA625214. Sequences of MAPK, PKA and Hog1 proteins from S. cerevisiae were downloaded from NCBI and yeast genome database (www. yeastgenome.org).Reads quality was verified using FastQC software, then the raw reads trimmed and quality controlled using SeqPrep (s (FPKM) , then his genome  with Hiss genome . The reas genome . R statis genome . The falg method . Genes wng KOBAS . To visuO. sinensis extract using a Thermo Vanquish UHPLC (Thermo Fisher) with a Hyperil Gold C18 column coupled to a Mass Spectrometer detector QE HF-X (Thermo Fisher). Samples were injected into a Hyperil Gold column  using a 16-min linear gradient at a flow rate of 0.3 mL/min. Eluents for the positive polarity mode were eluent A (0.1% formic acid in water) and eluent B (Methanol). The eluents for the negative polarity mode were eluent A  and eluent B (Methanol). The solvent gradient was as previously described [Six biological replicates were analyzed at each stage, namely BP, BS and PreHy. Samples for each replicate were isolated from a mixture of 3 independent single samples. Liquid chromatography-tandem mass spectrometry (LC-MS / MS) was used to analyze the composition of escribed .http://www.chemspider.com/) and mzCloud (https://www.mzcloud.org/).The raw data files, generated by UHPLC-MS / MS, were processed using the Compound Discoverer 3.0  for peak alignment, peak picking, and quantitation for each metabolite. Furthermore, peaks were matched using online libraries at ChemSpider (http://www.genome.jp/kegg/) [http://www.hmdb.ca/) [http://www.lipidmaps.org/) [P-value) and fold changes (FC) of the metabolites, between two group means, were calculated using univariate analysis (t-test). To evaluate the overfitting of the model, 200 permutation tests were performed in the PLS-DA model [The metabolites were annotated using the KEGG database (p/kegg/) , HMDB damdb.ca/)  and Lipips.org/) , 57. Prips.org/) . StatistDA model .P-value < 0.05 and FC ≥ 2 or ≤ 0.5 were regarded as differential, and their roles determined by pathway analysis using MetaboAnalyst [P-values from pathway enrichment analysis (y-axis) and pathway impact values from pathway topology analysis (x-axis). In summary, pathway impact was calculated as the sum of the importance measures of the matched metabolites normalized by the sum of the importance measures of all metabolites in each pathway [Metabolites with Variable Importance in the Projection (VIP) > 1 and oAnalyst , 61. Pat pathway . QC samp–ΔΔCT method [P < 0.05). All the statistical analyses and visualizations were performed using the Graphpad prism 7 or R platform.Total RNA was isolated from the integument using TRIzol reagent . 2 μg of the RNA was reverse-transcribed to cDNA using the SuperRT cDNA Kit . qRT-PCR was performed on a Stratagene MX3000P qPCR system , according to the manufacturer’s instructions. All the primers used in this study were shown in the Additional file T method . The obtAdditional file 1: Table S1. Summary of sequencing quality. Table S2. All differentially expressed genes FPKM value during the deformation process of O. sinensis and gene annotation details. Table S3. KEGG functional classification of differentially expressed genes. Table S4. The detailed information of differentially expressed metabolites in this study. Table S5. Summary of 43 pathways annotated by MetaboAnalyst. Table S6. Results of BLASTp analysis of S. cerevisiae dimorphism related proteins with O. sinensis genome. Table S7. A list of homologous of Hog1 and PKA cascade protein of S. cerevisiae. Table S8. Oligonucleotide primer sequences used in this study.Additional file 2: Figure S1. Principal component analysis of the RNA-Seq data. Figure S2. Analysis of DEGs between two adjacent stages. Figure S3. KEGG enrichment analysis for differentially expressed genes (DEGs). Figure S4. PLS-DA score plot and validation plots of the metabolic profiling results.


Gossypium hirsutum L.) fields in Texas in 2016 and 2017 to identify common weed species present as escapes and estimate seed rain potential of Palmer amaranth  and waterhemp [A. tuberculatus (Moq.) J.D. Sauer], two troublesome species with high fecundity. A total of 400 cotton fields across four major cotton-producing regions in Texas  were surveyed. Amaranthus palmeri, Texas millet [Urochloa texana (Buckley) R. Webster], A. tuberculatus, ragweed parthenium (Parthenium hysterophorus L.), and barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] were reported as the top five weed escapes in cotton fields. Amaranthus palmeri was the most prevalent weed in the HP and Lower GC regions, whereas A. tuberculatus escapes were predominantly observed in the Upper GC and Blacklands regions. On average, 9.4% of an individual field was infested with A. palmeri escapes in the Lower GC region; however, 5.1 to 8.1% of a field was infested in the HP region. Average A. palmeri density ranged from 405  to 3,543 plants ha–1 (Lower GC). The greatest seed rain potential by A. palmeri escapes was observed in the upper HP region (13.9 million seeds ha–1), whereas the seed rain potential of A. tuberculatus escapes was the greatest in the Blacklands (12.9 million seeds ha–1) and the upper GC regions (9.8 million seeds ha–1). Seed rain from late-season A. palmeri and A. tuberculatus escapes is significant in Texas cotton, and effective management of these escapes is imperative for minimizing seedbank inputs and impacting weed species persistence.Weed escapes are often present in large production fields prior to harvest, contributing to seed rain and species persistence. Late-season surveys were conducted in cotton ( Widespread adoption of herbicide-resistant crops, primarily glyphosate-resistant (GR) crops, has allowed growers to apply broad-spectrum postemergence (POST) herbicides for effective management of weeds. However, weeds may survive management interventions that are typically carried out during the early season (i.e. early-season survivors) or avoid these management practices by emerging later in the season (i.e. late-emerging cohorts), and then be present at crop harvest as “escapes” .Amaranthus spp., to emerge for an extended period during the growing season allows the late-emerging cohorts to avoid management practices. A study conducted in Pendleton, South Carolina reported that Palmer amaranth  emergence occurred from early May to late October, with peak emergence from mid-May to mid-July [A. tuberculatus (Moq.) J.D. Sauer], a species closely related to A. palmeri, also exhibits a prolonged emergence window in the Midwestern and Southern United States  shipments from the United States to China , A. tuberculatus, ragweed parthenium (Parthenium hysterophorus L.), and barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] as the top-five frequently found weed species among the late-season escapes (relative frequency points ranged between 0.5 and 1.7 out of the maximum possible points of 3.0)  among all the weed species, illustrating the prevalence of A. palmeri escapes across the major cotton production regions in Texas. Moreover, A. palmeri was the most commonly occurring weed species in the HP  and Lower GC regions, and was also among the top-five weeds in the Blacklands and Central Texas regions (Data for objective 1 (i.e. commonly found species to document weed escapes in cotton) were pooled across the years and the primary and secondary survey sites. This survey ranked  of 3.0) ; Fig 1. A. palmeri was the most common and problematic weed in cotton production systems across the United States , silverleaf nightshade (Solanum elaeagnifolium Cav.), Texas blueweed (Helianthus ciliaris DC.), and johnsongrass [Sorghum halepense (L.) Pers.] were also among the top-ten commonly found weed escapes in Texas cotton , and the lowest in the Central Texas region (2.4 million ha–1) , followed by the HP region (5.1 to 8.1%)  ; Fig 3. surveyed . In someto 8.1%) .–1), and seed production (2.4 million seeds ha–1) by A. palmeri escapes , density  rotation is predominant in the Upper HP region. The majority of cotton grown in recent years in the HP region, until the introduction of dicamba-resistant cotton technology in 2017, were GR cultivars [A. palmeri escapes were observed in fewer fields in the HP region in 2017, compared to that in 2016, with 29, 28, and 26% reductions in the Upper HP, Central HP, and Lower HP regions, respectively (®) in 2017 in the HP region; more than 70% of cotton in the Texas HP region in 2017 comprised of XtendFlex® cultivars [Cotton is typically grown in monoculture in the Central and Lower HP regions, whereas cotton-corn  in the Upper GC region and the lowest (200 plants ha–1) in the Lower GC region. The greatest seed rain potential (12.9 million seeds ha–1) of A. tuberculatus escapes were documented in the Blacklands region; lowest (0.2 million seeds ha–1) seed rain potential was observed in the Central Texas region  by A. tuberculatus was significant in terms of sustainable seedbank management. Assuming a 50% incorporation of the seed to the soil seedbank, a 10% seedling emergence [–1 will escape the control measures. Considering a nominal fecundity of 75,000 seeds plant–1, the total seed rain from these four plants to the soil seedbank will be about 300,000 ha–1, suggesting a continued increase in the soil seedbank size.This late-season weed survey conducted in major cotton-producing regions of Texas has revealed that mergence  the follA. palmeri [A. palmeri and A. tuberculatus [An effective strategy to reduce weed escapes begins with the development and implementation of a robust, diversified weed management program. For example, application of overlapping residual herbicides showed season-long control of  palmeri , therebyrculatus , 35.Amaranthus spp. that exist in the late-season after implementation of robust in-field weed management can be targeted with harvest weed seed control (HWSC) strategies to reduce seedbank replenishment [Problematic weeds such as nishment . The HWSnishment . Howevernishment , 39.A. palmeri and A. tuberculatus plants occurred commonly as late-season escapes in cotton production fields in Texas, and the seed rain potential from these escapes is significant, though the density of occurrence and fecundity highly varied across environments. Our estimations could have been affected by actual variations in field distribution of the weeds as we extrapolated information to large production fields, possibly leading to errors (underestimation or overestimation). Nevertheless, the information generated in this research is highly valuable for creating awareness among weed managers on the importance of managing late-season escapes of Amaranthus spp. for minimizing seed rain potential and long-term population persistence.Overall, results of this survey showed that S1 Table(DOCX)Click here for additional data file.


Leishmania donovani species complex consists of all L. donovani and L. infantum strains mainly responsible for visceral leishmaniasis (VL). It was suggested that genome rearrangements in Leishmania spp. occur very often, thus enabling parasites to adapt to the different environmental conditions. Some of these rearrangements may be directly linked to the virulence or explain the reduced efficacy of antimonial drugs in some isolates. In the current study, we focused on a large-scale analysis of putative gene conversion events using publicly available datasets. Previous population study of L. donovani suggested that population variability of L. donovani is relatively low, however the authors used masking procedures and strict read selection criteria. We decided to re-analyze DNA-seq data without masking sequences, because we were interested in the most dynamic fraction of the genome. The majority of samples have an excess of putative gene conversion/recombination events in the noncoding regions, however we found an overall excess of putative intrachromosomal gene conversion/recombination in the protein coding genes, compared to putative interchromosomal gene conversion/recombination events.The  Leishmania donovani species complex consists of all L. donovani and L. infantum strains responsible for visceral leishmaniasis (VL) [L. donovani is considered to be an anthroponotic agent, L. infantum is zoonotic, with dogs and numerous wild mammals being involved in the disease transmission [L. donovani and L. infantum being the India/East Africa and the Middle East, respectively [L. chagasi in the New World was historically referred to as a separate species, recent studies have demonstrated that it is a mere subpopulation of L. infantum [L. donovani spp. complex differ depending on the immune status of the infected individuals, parasite strains and transmitting sand fly vector’s species [The sis (VL) ,2. Besidsis (VL) ,4. Whilesmission . Both spectively . Althouginfantum , which hinfantum . The cli species .Leishmania spp. occur very often, thus enabling parasites to adapt to the different environmental conditions [Leishmania spp. It was suggested that genome rearrangements in nditions ,11. Somenditions ,13 or exnditions . Below, Leishmania spp. [Leishmania of the subfamily Leishmaniinae [Lipophosphoglycan (LPG) is one of the most abundant surface glycoconjugates, which is mainly involved in parasite colonization of the vector’s midgut . The LPGnia spp. ,19. Of nnia spp. ,21) relamaniinae . Variant surface glycoproteins (VSGs) facilitate immune evasion, while VSG-encoding genes define antigenic variation in trypanosomes . These gLeishmania [Leishmania spp., sequenced thus far, harbor at least two long, as well as variable numbers of short GP63-encoding sequences. This suggests that mosaic gene conversion has a high impact on the evolutionary history of these species [Leishmania are genes encoding cysteine proteases [hsp70 gene cluster [One of the essential virulence factors, the glycoprotein 63 (GP63), is encoded in a variable number of copies in different species of ishmania . All Lei species ,27. Otheroteases , hsp70 g cluster , amastin cluster ,31. L. donovani suggested that population variability of L. donovani is fairly low, however the authors used masking procedures and strict read selection criteria [L. donovani genome was documented. The majority of samples have an excess of putative gene conversion events in the noncoding regions, however we found an overall excess of putative intrachromosomal gene conversion/recombination in the protein coding genes, compared to putative interchromosomal gene conversion/recombination events.In the current study we focused on a large-scale analysis of putative gene conversion events using publicly available datasets. Previous population study of criteria ,32. We dLeishmania donovani genomes. The number of B-type reads  is approximately equal to that of the S-type reads (sole mapped reads) and substantially greater than that for the C- and D-type reads  (We studied five types of read configurations  in 28 Lectively) . The fraTo test the possibility that the reason for the observed B-type reads prevalence are because of errors of read mapping with numerous mismatches , we have analyzed reads with the similarity level 90–95%. We found only a few reads that were largely located in noncoding DNA . Thus, iχ2 = 0.029, a modified χ2 test, see Materials and Methods). No other significant pairwise differences were detected. We also compared the distribution of reads in protein coding regions  to the uniform distribution using the Pearson’s χ2 test, the B-type read distribution was significantly different from the uniform distribution (Pχ2 = 0.006) whereas C-, D- and S-type read distributions were not significantly different from the uniform distribution.Polarity is one of the properties of gene conversion: in almost all cases the frequency of conversion exhibits a gradient “across” the gene ,34,35. HLeishmania donovani genome and it varies across different L. donovani strains  remains obscure . For exaTrypanosoma brucei, where they have been implicated in quorum sensing regulation of differentiation in this species [Leishmania biology is under researched. Their expression was documented to be restricted to the sandfly-dwelling promastigotes in the case of L. donovani [Leishmania spp. testifies to their importance and warrants future investigations into their functional role(s). This is further exemplified by the case of trypanosomatid receptor adenylate cyclases , which a species . Some me species . Neverthdonovani . Our finLeishmania donovani and Saccharomyces cerevisiae. For L. donovani, we used complete genomic data for the isolate BPK282A1 [www.ebi.ac.uk/ena/data/view/PRJEB2086, 30 genomes). In the original study [L. donovani BPK282, resulting in SNPs (single-nucleotide polymorphisms) being called at 26,086,795 or 80.4% of the total nuclear genome [S. cerevisiae, we used DNA-seq data for isolate S288C . Read data are available under study ERP000140 at the ENA . In both cases, sequence reads were generated using the same Illumina HiSeq 2000 platform and standard protocols.We studied DNA-seq data for BPK282A1 . Reads wal study  the refer genome . We did www.sanger.ac.uk/science/tools/smalt-0) for the mapping of paired reads. Firstly, we indexed the reference genomic sequences (ref_genome): smalt_x86_64 index -k 20 -s 13 ref_genome ref_genome.fas and then used paired reads (sampl1 and sample2) with the following set of parameters: smalt_x86_64 map -n 8 -f cigar -o output_file ref_genome sample1.fastq sample2.fastq We used the SMALT program : (A-type) mates are in proper orientation within the limits specified by the -i and -j options ; (B-type) mates in proper orientation outside the limits specified by the -i and -j options, but on the same chromosome ; (C-type) mates are not in proper orientations, but on the same chromosome (mostly sequencing errors and inversion events that are known to be rare); (D-type) mates are mapped to different chromosomes ; (S-type) a read was mapped as a single read . Manual inspection of the B-type reads suggested that two samples were obvious outliers . They we2 test was used for analyses of 2 × 3 contingency tables [We applied only one filter. We removed all reads with 95% identity, min 60 bases ungapped region; the percent identity for a B-type  read should be equal or more 95% and more than the best overlapping A type read . This filter effectively removed errors of whole-genome sequencing procedures. All types of reads were analyzed as single reads . After filtering, all overlapping reads were merged. If a merged set of reads (a merged read) overlapped with a known protein-coding sequence, we assigned this merged read to the set of reads that overlap with protein coding genes. We used the 2-tail Fisher exact test to evaluate homogeneity of 2 × 2 contingency tables . A modify tables .Evolutionary analyses were conducted in the package MEGA X  as descr


Dinobdella ferox is the most frequently reported leech species parasitizing the mammalian nasal cavity. However, the molecular mechanism of this special parasitic behavior has remained largely unknown.D. ferox, which was annotated with strong certainty using bioinformatics methods. The phylogenetic and genomic alterations of D. ferox were then studied extensively alongside the genomes of other closely related species. The obligatory parasitism mechanism of D. ferox was investigated using RNA-seq and proteomics data.PacBio long-read sequencing, next-generation sequencing (NGS), and Hi-C sequencing were employed in this study to generate a novel genome of D. ferox. Examining secretory proteins in D. ferox saliva helped to identify intimate connections between these proteins and membrane proteins in nasal epithelial cells. These interacting proteins played important roles in extracellular matrix (ECM)–receptor interaction, tight junction, focal adhesion, and adherens junction. The interaction between D. ferox and mammalian nasal epithelial cells included three major steps of pattern recognition, mucin connection and breakdown, and repair of ECM. The remodeling of ECM between epithelial cells of the nasal mucosa and epithelial cells of D. ferox may produce a stable adhesion environment for parasitism.PacBio long-read sequencing and NGS yielded an assembly of 228 Mb and contig N50 of 2.16 Mb. Along Hi-C sequencing, 96% of the sequences were anchored to nine linkage groups and a high-quality chromosome-level genome was generated. The completed genome included 19,242 protein-coding genes. For elucidating the molecular mechanism of nasal parasitism, transcriptome data were acquired from the digestive tract and front/rear ends of Our study represents the first-ever attempt to propose a molecular model for specific parasitism. This molecular model may serve as a practical reference for parasitism models of other species and a theoretical foundation for a molecular process of parasitism.The online version contains supplementary material available at 10.1186/s13071-023-05837-7. Dinobdella ferox, Limnatis nilotica, and Myxobdella africana were the most common species parasitizing humans [D. ferox is the most frequently examined praobdellid leech. Numerous case studies of D. ferox infestations in the upper airway have been reported [Family Praobdellidae have a life cycle of parasitizing on mammalian mucous membranes , 57. Prag humans , 42. Prereported , 56.D. ferox, its development curve during the parasitic phase, and the behavioral inclination of free-living individuals before and after the parasitic period [D. ferox could only parasitize mammals and not avian or amphibian hosts, and its growth curve was correlated with host size. Within a month, its mean parasitizing biomass expanded more rapidly in rabbits than in rats, and host mortality was indeed caused by its infestation. Furthermore, there was a notable inclination to dwell at the water surface before parasitizing, and it remained sensitive to airflow and vibration from hosts [In the early 2000s, researchers examined the host specificity of c period , 34. It om hosts . In contD. ferox helped us to gain insights into the above puzzle. The high-quality chromosome-level genome of D. ferox was composed of 228 Mb, 335 contigs, and nine chromosomes. This genome facilitated a deeper understanding of the genetic basis of D. ferox parasitism, life history, and reproductive transition.Despite exciting discoveries on its behavior, life history, and host specialization, the molecular processes of its specificity to the parasitic mammalian nasal cavity remain elusive. Thus genome-wide analysis of D. ferox were collected from Nankang Village, Lujiang Town, Longyang District, and Baoshan City in Yunnan Province, China . The detailed sampling procedure was as follows: The hosts for nasal leeches in this research were cattle. Cattle were exposed to sunlight for 1–2 h, making them thirsty. Subsequently, a bucket with some water was placed in front of the cattle, but they were not allowed to drink from it. At this point, the nasal leeches also required water, prompting them to extend the anterior part of their body out of the nostril. A hemostatic forceps was then used to firmly grasp and extract the leech. Leeches were brought back to the laboratory alive. Tissues of different parts were separated by ophthalmic scissors and immediately placed in liquid nitrogen for DNA/RNA/protein extraction.Samples of Genomic DNA was extracted by the classic phenol–chloroform method and total RNA extracted with TRIzol Reagent (Invitrogen). The quality and quantity of extracted DNA/RNA were assessed with an Agilent 2100 Bioanalyzer , and integrity was further evaluated on agarose gel after a stain of ethidium bromide. The resulting DNA/RNA samples were stored at −80 °C until subsequent library construction and genomic/transcriptomic sequencing. All samples were collected by our own staff.https://www.pacb.com/products-and-services/consumables/). For Hi-C sequencing, genomic DNA samples were pretreated according to Rao et al. [https://www.illumina.com/techniques/sequencing/ngs-library-prep.html).PacBio libraries were constructed and sequenced on the PacBio sequencing platform  data, low-quality reads, linker sequences, and repetitive sequences were removed using Trimmomatic  and the num/Kdepth, where Knum and Kdepth denote the total number and peak depth of 17-mers, respectively.Genomic size was estimated by the k-mer method with short-insert library reads. Here, 17-mer was selected for k-mer analysis, and genomic size (Mb) was estimated with the following formula: G = KPacBio's third-generation data were corrected to obtain higher accuracy. Clean data were processed with Canu  softwareD. ferox was performed using BUSCO  [http://korflab.ucdavis.edu/datasets/cegma/) [Quality assessment of genomic assemblies for ab.org/)  and CEGM/cegma/) . BUSCO uhttp://www.girinst.org/repbase/), using RepeatMasker [http://www.uniprot.org/), Nr (http://www.ncbi.nlm.nih.gov/protein), Pfam (http://pfam.xfam.org), Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/), InterPro (https://www.ebi.ac.uk/interpro/), and other databases to obtain gene functional information. Also, tRNAscan-SE [Genomic annotation included the three major aspects of repetitive sequence annotation, gene annotation, and non-coding RNA (ncRNA) annotation. Two annotation methods were used for repetitive sequence annotation, homologous sequence alignment and de novo prediction. The homologous sequence alignment method was based upon the repeat sequence database  . The phyRNA sequencing (RNA-seq) data were acquired for the digestive tract and front/back body ends. Raw reads were filtered and the remaining high-quality reads aligned to the assembled genome using HISAT2 . The traFirst, the digestive tract tissues of nasal leeches were collected and the microbes in the digestive tract secretions were removed via differential centrifugation. Subsequently, protein extraction was performed using a well-established method from previous research. Exogenous protein contamination could not be completely avoided during sampling. In the following steps, a highly reliable nasal leech protein database was obtained through genomic and transcriptomic data, which was used to filter out non-leech proteins during proteomics analysis by searching against the database.5 counts.The data-dependent mode of the Q Exactive Orbitrap Mass Spectrometer  was selected for automatic transition between full-scan mass spectroscopy (MS) and tandem MS (MS/MS collection. Full-scan MS spectra (m/z 350–1300) were acquired with a resolution of 70,000 (m/z 200) after accumulating ions to a 3106 target value based upon predicted automated gain control from the previous full scan. Dynamic exclusion time was set at 18 s. The MS2 scanning technique selected and fragmented the 10 most intense multiply charged ions (z = 2) successively using higher-energy collisional dissociation (HCD) with a fixed injection duration of 60 ms and a resolution of 17,500 (m/z 200). The spray voltage was set to 2 kV. There was no sheath or auxiliary gas flow. The capillary was heated to 250 °C, the normalized HCD collision energy was 27 eV, and the underfill ratio was 0.1%. The ion selection threshold for MS/MS was set at 1 × 10A protein library was generated with RNA-seq and proteomics employed for assessing the protein composition of saliva and digestive fluid. Then the secretome was compiled with SignalP , TargetPProteomics data of human nasal epithelium were downloaded from publicly available databases. Then subcellular localization data of these proteins were generated using the Human Protein Atlas (HPA) and UniProt databases.The STRING  database was searched for all secreted proteins and human nasal epithelial membrane proteins. And the interaction between secreted proteins and human nasal epithelial membrane proteins was generated with default settings. Then the KEGG Orthology-Based Annotation System (KOBAS)  with deft-test. Chi-square or Fisher’s exact test was utilized for significance analysis of Gene Ontology (GO) enrichment according to data features and hypergeometric test of KEGG.Significant intergroup differences were assessed with the two-tailed Student c oxidase subunit 1 (COI) gene sequence of the target species in this study was obtained through Sanger sequencing. By phylogenetically comparing it with the COI sequences of D. ferox and other species in NCBI, the target species was confirmed to be D. ferox  of clean data, with an average read length of 10.63 Kb , as well as W. pigra (unpublished data from our laboratory). The collinearity in the genome was examined  served as crucial attachment proteins in the early stages of attachment [D. ferox adheres to nasal mucosa through interactions.Regarding ECM destruction and regeneration, CTSB, ADAMTS3, SERPINB3, and SERPINB8 may play critical roles in smosomes . Likely smosomes , 9, 41. smosomes , 64, 72.smosomes , 35. Thitachment , 65, 75.D. ferox and the nasal cavity, creating an extremely stable adhesion environment for the nasal parasite life of D. ferox from juvenile to adult. Individual cells in diverse surroundings attach to ECM and their neighbors through the integrin and cadherin complexes. These dynamic interactions secure the creation and maintenance of complex tissues. A growing body of evidence has highlighted the roles of Rap1 GTPase and its accompanying signaling network [Furthermore, a P4HB-mediated sub-network operated inside the interaction network. Secreted protein might interact with 16 nasal epithelial membrane proteins. P4HB catalyzed the formation, breakage, and rearrangement of disulfide bonds , 43, 77. network , 49. AlsDinobdella ferox is parasitic on the nasal mucosa of mammals from its juvenile stage and completes its maturation through a lengthy parasitic cycle of several months. During parasitism, D. ferox withstands intense sneezing and breathing by the host due to foreign body sensation. However, its adherence stability and spatial structure are vastly superior to that of other leeches by interspecific molecular interactions  enrichment analysis of rapidly evolving genes in D. ferox genome. Table S12. KeyWords enrichment analysis of rapidly evolving genes in D. ferox genome. Table S13. Pfam domain enrichment analysis of rapidly evolving genes in D. ferox genome. Table S14. Prediction of the secretion ability of salivary protein in D. ferox genome by SignalP. Table S15. Prediction of the secretion ability of salivary protein in D. ferox genome by TargetP. Table S16. Prediction of the secretion ability of salivary protein in D. ferox genome by TMHMM.


Burkholderia cepacia complex (BCC) encompasses a group of at least 22 genetically distinct gram-negatives bacterial species ubiquitous in nature. Recognised as a group of genetically and phenotypically flexible species, the BCC inhabits diverse ecological niches causing both plant and human diseases. Comparative genomic analysis provides an in depth understanding into the population biology, phylogenetic relationship, and genomic architecture of species.The Burkholderia anthina isolated from patients with chronic lung infections, an understudied pathogen within the Burkholderia cepacia complex.Here, we genomically characterise B. anthina is polyphyletic and constitutes two distinct evolutionary lineages. Core- and pan-genome analyses demonstrated substantial metabolic diversity, with B. anthina Clade I enriched in genes associated with microbial metabolism in diverse environments, including degradation of aromatic compounds and metabolism of xenobiotics, while B. anthina Clade II demonstrated an enhanced capability for siderophore biosynthesis.We demonstrate that B. anthina to recognise a distinct species harbouring increased potential for iron metabolism via siderophore synthesis, for which we propose the name Burkholderia anthinoferum (sp. nov.).Based on our phylogenetic and comparative genomic analyses, we suggest stratifying  Burkholderia cepacia complex (BCC) represents a group of metabolically versatile and highly adaptable bacteria found inhabiting diverse ecological niches. In the early 1980’s, the BCC emerged as an opportunistic pathogen in patients with cystic fibrosis (CF), gaining notoriety due to its intrinsic resistance to antibiotics and propensity to spread rapidly within the community causing devasting outbreaks  database to date, only 31 (1.27%) correspond to B. anthina strains, with most isolates originating from an environmental source. In the current study, we examined phylogenetic relationships among Burkholderia species within the BCC and conducted comparative genomic analyses of B. anthina. Whole genome sequencing of Burkholderia isolates collected from patients with CF in Queensland, Australia identified a further five strains of B. anthina. Genomic characterisation of B. anthina genomes identified two evolutionarily distinct clades with considerable genomic divergence. Based on phylogenetic evidence, whole genome average nucleotide identity, and comparative genome analyses, we propose the division of B. anthina into two separate species: B. anthina and B. anthinoferrum (sp. nov.).Burkholderia infections detected in patients with CF attending The Prince Charles Hospital and the Mater Hospital, Queensland, Australia, between 2017 and 2022 were included in the study. Clinical specimens were collected from the Prince Charles Hospital as per the Research Collaboration Agreement HREC/17/QPCH/277, and the Mater Hospital as per HREC/14/QPAH/275. Bacterial isolation was performed from expectorated sputum samples. Briefly, a direct inoculum from sputum was plated out onto Burkholderia cepacia selective agar (BCSA) and incubated at 37°C under aerobic conditions for 48 h. The medium, supplemented with crystal violet, vancomycin and gentamicin, inhibits growth of gram-positive bacteria and gram-negative bacilli Pseudomonas, for increased selectivity of Burkholderia. Bacteria were grown under aerobic conditions in lysogeny broth (LB) (1% (w/v) tryptone, 1% (w/v) yeast extract, 0.5% (w/v) sodium chloride) at 37°C, with shaking at 220 rpm overnight.Cases of De novo assembly of the reads was conducted using SPAdes  as per the manufacturer’s instructions. DNA concentration and purity were assessed using a Nanodrop 1,000 spectrophotometer. Whole genome sequencing (WGS) was performed by MicrobesNGg SPAdes . Genome g SPAdes . Refereng SPAdes .Burkholderia cepacia complex typing databaseatpD, gltB, gyrB, recA, lepA, phaC, and trpB are assessed to identify differences in the allelic profile to define the sequence type (ST). Taxonomic classification was assigned using the Genome Taxonomy Database Toolkit  with reference database r207. A concatenated set of 975 core genes were produced using BPGA and the resultant output used to predict phylogeny  . Genomeshylogeny . Phylogehylogeny  and visuB. anthina genomes were included in the comparative genomic analyses. Statistical analyses for comparing distribution of genome size, number of CDSs, and coding density were determined using an unpaired t-test. The Bacterial Pan Genome Analysis (BPGA) pipeline using the USEARCH tool was used to cluster protein sequences into gene families  biosynthetic gene cluster was conducted through BLASTn searches. Streptomyces sp. MA5143a was used as the reference sequence and encodes for an EDHA operon containing four genes denoted AesA, AesB, AesC, and AesD. The genetic organisation of the EDHA gene cluster was visualised using the ‘gggenes’ (v0.5.1) and ‘ggplot2’ (v3.4.4) packages in Rstudio (v4.1.3) and R (v4.2.3). Identification of iron genes and iron gene operons was predicted using the bioinformatic tool FeGenie  displayed the same ST-622 and clustered tightly together. Phylogenetic placement of Burkholderia genomes identified several distinct phylogenetic clades within B. anthina. Notably, all five B. anthina isolates clustered within Clade II, displayed the same ST-2133, and represent the first clinical isolates reported within the group. Based on a well-supported phylogeny, it is evident that B. anthina Clade II represents a truly distinct group to B. anthina Clade I. As shown in B. anthina is polyphyletic with Clade I, as well as B. vietnamiensis, and B. ambifaria, diverging earlier than B. anthina Clade II. Phylogenetic placement of B. anthina Clade II suggest that this lineage shares a more recent common ancestor with B. cenocepacia, B. cepacia, B. stabilis, and B. pyrrocinia.Phylogenetic analysis was performed using a set of 975 core genes produced using BPGA and inferred using RAxML. MLST analysis was performed to inform strain relatedness among isolates. As part of this study, we obtained four isolates belonging to nique ST . While fB. anthina is further reflected in the genomic architecture between the two clades. B. anthina Clade I genomes have a significantly larger genome than B. anthina Clade II (p < 0.0001), with a mean size of 7.7 Mbp as compared to 7.4 Mbp (B. anthina Clade I have a significantly greater number of predicted coding sequences than B. anthina Clade II (p = 0.0029), with an average of 472 more coding sequences  shared by all strains, and a pan genome of 24,274 genes (87.8%) (B. anthina Clade I highlight the genetic variability within the group and reflects the differences among genomes.The phylogenetic separation in  7.4 Mbp . Accordiequences . The codequences . The pan (87.8%) . The gen (87.8%)  and Clad (87.8%)  genomes B. anthina and closely related species as indicated by phylogenetic placement. A threshold of 98% ANI is considered the cut-off for strain classification within species, whereas a threshold of 95% ANI is considered the cut-off for species delineation  was calculated to determine strain relatedness and assess the species boundaries of ineation . Consist anthina . Pairwisidentity . Taken tB. anthina clades, the pangenome was analysed according to their KEGG ortholog pathways. Both groups demonstrated a similar KEGG ortholog distribution profile regarding the relative proportion of core, accessory, and unique genes assigned to each KEGG pathway. However, B. anthina Clade II, displayed a higher relative proportion of unique genes associated with cellular processes and motility. KEGG categories associated with metabolism, including amino acid and carbohydrate metabolism were the most abundant categories across both B. anthina clades for core, accessory, and unique genes  identified in Clade I harboured the genes FhuB, FhuC, and FhuD required for uptake of ferric aerobactin. The synthesis and transport of the aerobactin siderophore is frequently produced by several Enterobacteriaceae, including Escherichia, Vibrio, Salmonella, and Shigella  in I and II . Genes cerophore . To gain genomes . General genomes , while gClade II . Genome Clade II . All B. Shigella . Given tBurkholderia cepacia complex represents a significant group of organisms heterogeneously distributed in the natural environment, and contains species of ecological, pathogenic, and biotechnological interest . Herein, Clade I will be referred to as B. anthina, and Clade II will be referred to as B. anthinoferrum.The interest . Harbourinterest . ThroughB. anthina has been isolated from several sources including the rhizosphere soil of gardens and house plants, commercial solutions, and from the sputum of patients with CF  according to the threshold for species delimitation by ANI, it was proposed that B. cenocepacia be amended to recognise a new species B. oribcola sp. nov. From our analyses, B. anthina and B. anthinoferrum were found to be polyphyletic, having ancestrally diverged from each other, which is further reflected by differences in their genetic and functional profiles. Pan-genomic analysis demonstrated substantial genetic variance within the population. The low number of shared genes observed in the population is consistent with the pan-genome of several other Burkholderia species, which are considered to be highly heterogenous , and xenobiotic degradation and metabolism . The ability to metabolise and utilise xenobiotic contaminants as a carbon or nitrogen source serves as a competitive advantage for microorganisms, particularly in nutrient-harsh environments . Cells are gram negative, non-motile, non-sporulating, coccobacilli bacteria. Growth is observed in LB, MacConkey and BCSA agar at 30, 37, and 42°C. Colonies in LB and BCSA are circular, convex, and cream coloured, while colonies in MacConkey are light pink coloured. Growth in BCSA produces an alkaline medium due the fermentation of lactose and sucrose and is strain dependent. The G + C content for the members of the species is 67.0%. Strains have been isolated predominately from environmental samples, but recently from clinical samples as described in this study. We propose that Burkholderia anthinoferrum sp. nov. XXVI be used as the type strain, a rhizosphere bacterium isolated from a mango orchid in Mexico. The strain holds a central position in the phylogeny of its clade and has been characterised in the literature (terature , 2018.The datasets generated during this study are available on the NCBI database under the BioProject PRJNA1033429. Whole-genome sequences for Burkholderia isolates are under the Biosample accession SAMN38033600-SAMN38033617.The studies involving humans were approved by The Prince Charles Hospital and QLD Princess Alexandra Hospital Research Ethics Committees. The studies were conducted in accordance with the local legislation and institutional requirements. The human samples used in this study were acquired from primarily isolated as part of your previous study for which ethical approval was obtained. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements.AP: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing. JV: Writing – review & editing, Investigation. DC: Resources, Writing – review & editing. DS: Resources, Writing – review & editing. DR: Resources, Writing – review & editing. LB: Resources, Writing – review & editing. TW: Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing.