While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank. Proteins are essential building blocks of almost every biological process; therefore, understanding their functions is critical to many applications, from drug discovery , 2 to taUnfortunately, gaining such insights regarding the function of proteins through their structures is severely hampered by the lack of high-quality, experimentally determined structures. As of 2022, the Universal Protein Resource (UniProt) contains around 204 million nonredundant amino acid sequences, while the Protein Data Bank (PDB) , 7 contade novo predictions without homologous templates than ever before [A practical approach to addressing this challenge relies on high-accuracy computational models to complement the experimentally determined structures when the latter are unavailable for a certain protein of interest . The ther before , 17. ThiWhile these new techniques are increasingly accurate, it is important that they are supplemented with reliable estimates of model confidence both for the whole model and locally for each residue. Researchers should not expect all predictions to be equally accurate neither globally nor in every region, and confidence estimates should hence be used to determine if a predicted structure can be used for downstream analysis . Commonlab initio modeling approaches, can be used to generate an experimentally validated pool of IDP models. PED provides access to such conformational ensembles but also those based on other experimental approaches. Considering the limitations of certain tools highlights the importance of using models and methods from various synergistic software and data providers to mitigate the weaknesses of individual modeling techniques.Another important consideration when relying on any structure prediction tool is to consider its limitations. While structures in the PDB have the advantage of experimental data backing the coordinates, enabling experimental as well as geometric validation, it is a relatively small dataset, as discussed above. Template-based models have the distinct advantage of enabling the mapping of a model to homologues with known structures, thus mapping to experimentally derived structures that can be in distinct conformational states or in complex with other molecules. Some tools excel at general-purpose protein structure modeling; others specialize in placing relevant ligands in the context of a model or representing conformational flexibility with ensembles of potential conformations , 22–24 . On the While many prediction software and several publicly accessible data resources host and archive protein structures, these resources are fragmented and often rely on their own data standards to describe the necessary meta-information essential for providing context for a specific model. They also offer distinct data access mechanisms, requiring the users to learn multiple sets of technical details when interacting with various resources. The lack of standardization can severely impede the comparative analysis of these models, making it difficult to gain valuable insights.Here, we present the 3D-Beacons Network, an open, collaborative platform for providing programmatic access to 3-dimensional coordinates and their standardized meta-information from both experimentally determined and computationally modeled protein structures.The 3D-Beacons Network is an open collaboration between providers of experimentally determined and computationally predicted protein structures. To date, 10 data providers make their protein structures available through this platform   conformational ensembles. We defined the categories as follows:We divided the protein structures into 4 categories: (i) experimentally determined, (ii) template based, (iii) Experimentally determined structures are based on data from techniques such as X-ray crystallography, cryo-electron microscopy, nuclear magnetic resonance spectroscopy, or small-angle scattering. This category is exemplified by structures in the PDB and the SASBDB databases.Template-based models use alignments to similar sequences with known structure  as their main input. SWISS-MODEL is an example of data providers with such models.Ab initio models can use templates as an auxiliary input but do not depend on them. AlphaFold models are considered ab initio in this framework.conformational ensembles are created using a combination of experimental data and computational modeling, yielding a large number of possible conformations. Ensembles in the PED database are an example of this category.Finally, Researchers can view the number of models under each category and inspect which parts of the amino acid sequences are covered by which models in a 2D viewer, PDB ProtVista . Users cThe purpose of the 3D-Beacons Network is to standardize the representation of protein structure models and associated metadata and to provide efficient, high-throughput programmatic access to experimentally determined and theoretical models and their standardized metadata. The current version (as of 29 July 2022) of 3D-Beacons supports querying any number of UniProt accessions, while future updates are planned to collate models based on other identifiers such as taxonomy IDs or domain IDs. This platform enables both the scientific community and developers of data visualization and data-providing services to access and seamlessly integrate 3-dimensional models from various protein structure data providers.While designing the data access points and data formats, we had extensive discussions with scientists and developers who provided specific use cases that are relevant to their work. We used these data to drive the development of 3D-Beacons, starting with the most frequently requested data  that can answer the question, “What experimental or theoretical structures are available for my protein of interest?” Going forward, we will address more of the collated use cases, such as searching by sequence or by gene identifiers and selecting structures based on protein families. Already, the API endpoints of 3D-Beacons provide easy access to models from sparse and fragmented data resources, supporting researchers and software developers alike.For example, the 3D-Beacons infrastructure allows users of Jalview, a workbench for creating multiple sequence alignments (MSAs) and analyzing them, to discover 3-dimensional models for MSAs of proteins from the UniProt and place them in the context of genetic variation from Ensembl . It can The Protein Data Bank in Europe–Knowledge Base (PDBe-KB)  displaysThe SWISS-MODEL Repository (SMR)  fetches By providing easy access to experimentally determined and computationally predicted protein structures, we aim to make these data an essential part of the toolbox of researchers in the broader scientific fields of life sciences. Establishing an infrastructure of federated model providers if a scalable and expandable approach can efficiently adjust to include new models and provides a more sustainable model than if a single data repository would try and archive all the data in one place. By taking advantage of the 3D-Beacons Network, protein structures can better realize their full impact on fields from structure-based drug discovery , 34 to sThe infrastructure of the 3D-Beacons Network consists of a registry, a hub, and the data access implementations. The 3D-Beacons Network is open to data providers of protein structures. Such data resources are invited to contact the 3D-Beacons consortium to discuss ways their data can be linked. Briefly, the common steps are as follows: data providers review the consortium guidelines and the latest API specification. The data providers then convert their metadata to the specified format and make these data available either through their APIs or by setting up a 3D-Beacon client. Once these steps are completed, the registry can be updated to link the new data resource with the 3D-Beacons Hub API. The following sections give more detailed information on each of these elements of the infrastructure.The 3D-Beacons Registry is a transparent, publicly accessible registry that stores information on all the data providers linked to the 3D-Beacons Network. The registry is available on GitHub. It contains information on the public URLs of data providers, a brief description of the protein structures they provide, and a list of API endpoints they support. For example, PDBe , 41 suppThe API endpoints comply with the data exchange format, which the 3D-Beacons members collaboratively design and improve. We defined the data exchange format as a JavaScript Object Notation (JSON) specification, an industry-standard format for sharing textual meta-information. The specification is available on Apiary and GitHub.ab initio methods [Members of the 3D-Beacons Network can either implement their own API endpoints according to the API specification described above or install a local instance of the 3D-Beacons client. This client is a Docker-containerized, lightweight Python package that can import and parse PDB or mmCIF formatted protein structure files and their corresponding meta-information (in JSON format). It also includes capabilities to add model confidence scores using QMEANDisCo  if model methods . The cliAt the core of the 3D-Beacons infrastructure lies the Hub API, a programmatic aggregator of the meta-information from all the member data providers. We implemented the Hub API using the FastAPI framework. This API relies on the previously described registry to retrieve information on which data provider supports which specific API endpoints. It aggregates data and provides its own API endpoints that researchers, services, and software can directly access to retrieve the location of available model files and their corresponding meta-information, such as the overall model quality or residue-level confidence measures. It is important to note that in the current implementation, the model confidence measures are provided by the original data sources, and different providers might have different approaches to estimating confidence. This can hamper effective comparison of the models based on these scores, and it is an active focus area both within the 3D-Beacons Network and the broader modeling community to design a broadly applicable confidence measure.Finally, we provide a graphical user interface that contains documentation and showcases the information one can retrieve using the 3D-Beacons Hub API. We implemented this interface using the Angular framework, and it relies on the sequence feature viewer, PDB ProtVista , and theThe source codes of the 3D-Beacons Registry, Client, Hub API, and front-end application are all publicly available:Project name: 3D-Beaconshttps://3d-beacons.orgProject homepage: Operating system(s): Platform independentProgramming language: Python, TypeScriptOther requirements: Python 3.7 or higher, Angular 11.1.3 or higherLicense: Apache License 2.0biotools: 3d-beaconshttps://www.ebi.ac.uk/pdbe/pdbe-kb/3dbeacons/api/. The specification of the data exchange format is available at https://3dbeacons.docs.apiary.io/#. An archival copy of the code and other supporting data are also available via the GigaScience database GigaDB [All the data provided through the network are freely available for academic and commercial use under Creative Commons Attribution 4.0 license terms. Documentation of the 3D-Beacons Hub API is available at e GigaDB .API: Application Programming Interface; IDP: intrinsically disordered proteins; JSON: JavaScript Object Notation; lDDT: local distance difference test; MSA: multiple sequence alignment; PDB: Protein Data Bank; PDBe-KB: Protein Data Bank in Europe–Knowledge Base; PED: Protein Ensemble Database; SASBDB: Small-Angle Scattering Biological Data Bank; SMR: SWISS-MODEL Repository; UniProt: Universal Protein Resource.The authors declare no competing interests.M.V. created the initial draft, handled project and data management at PDBe and AlphaFold DB, and designed and developed the 3D-Beacons webpages. S.N. led the development of the 3D-Beacons registry, Hub API, and PDBe and AlphaFold API implementation, as well as contributed to the development of the 3D-Beacons client and the webpages. I.S. worked on the 3D-Beacons client and on the Genome3D beacon. G.T. contributed to the management of 3D-Beacons. M.V., G.T., A.M.W., and S.B. contributed to the API design. A.L. and N.A. provided management support for AlphaFold DB. A.H., S.T., L.T.-K., E.S., and D.P. contributed to the PED beacon. A.M.W., S.B., and G.T. contributed to the SWISS-MODEL and ModelArchive beacons. S.B. contributed QMEANDisCo for the client. S.B. and G.T. connected with the ModelCIF working group. T.H. and E.S. contributed to the HegeLab beacon. M.L.H. and R.P.J. contributed to the AlphaFill beacon. C.B., Dm.S, and D.M. contributed to the SASBDB beacon. M.S., M.J.S., and S.L.S. contributed to the isoform.io beacon. M.D. and S.A. worked on data visualization and infrastructure. S.V., C.O., and T.S. provided oversight as co-principal investigators. I.S., G.T., D.M., T.H., S.V., R.J., and E.S. contributed to the manuscript drafts. Every coauthor reviewed the final manuscript.giac118_GIGA-D-22-00215_Original_SubmissionClick here for additional data file.giac118_GIGA-D-22-00215_Revision_1Click here for additional data file.giac118_GIGA-D-22-00215_Revision_2Click here for additional data file.giac118_GIGA-D-22-00215_Revision_3Click here for additional data file.giac118_GIGA-D-22-00215_Revision_4Click here for additional data file.giac118_Response_to_Reviewer_Comments_Original_SubmissionClick here for additional data file.giac118_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giac118_Response_to_Reviewer_Comments_Revision_2Click here for additional data file.giac118_Response_to_Reviewer_Comments_Revision_3Click here for additional data file.giac118_Reviewer_1_Report_Original_SubmissionLim Heo, Ph.D. -- 9/13/2022 ReviewedClick here for additional data file.giac118_Reviewer_2_Report_Original_SubmissionCarlos Rodrigues, PhD -- 9/16/2022 ReviewedClick here for additional data file.


Hyphessobrycon is one of the most species rich and widely distributed genera in the family Characidae, with more than 160 species ranging from Veracruz, Mexico to Mar Chiquita Lagoon in Buenos Aires, Argentina. The majority of Hyphessobrycon diversity shows a cis-Andean distribution; only nine species are trans-Andean including H. compressus (Meek 1908). It is well established that Hyphessobrycon is not monophyletic but it has been suggested that natural groups can be identified within the larger Hyphessobrycon species group. In this study, we tested the monophyly of trans-Andean species of Hyphessobrycon and investigated the placement of H. compressus. We inferred the first phylogenomic hypothesis of trans-Andean Hyphessobrycon that includes nearly complete taxonomic sampling  using ultraconserved elements (UCEs). We analyzed 75% (1682 UCEs), 90% (1258 UCEs), and 95% (838 UCEs) complete data matrices, and inferred phylogenomic hypotheses under concatenation and coalescent approaches. In all cases, we recovered the monophyly of trans-Andean Hyphessobrycon inclusive of H. compressus, strong support for three species groups, and evidence of cryptic diversity within the widespread H. compressus and H. condotensis. We used our phylogenomic hypothesis to investigate the biogeographic history of Hyphessobrycon in Middle America. Our ancestral range estimation analysis suggests a single event of cis- to trans-Andean colonization followed by stepwise colonization from the Pacific slope of northwestern South America (Chocó block) to northern Middle America (Maya block). Our work supports the recognition of the trans-Andean species as Hyphessobrycon sensu stricto and provides an evolutionary template to examine morphological characters that will allow us to better understand the diversity of Hyphessobrycon in Middle America. The Neotropics are home to the world’s most diverse assemblage of freshwater fishes, with more than 6200 described species occupying a wide array of aquatic habitats spanning from the Central Mexican Plateau in North America to Tierra del Fuego in South America , 2. The Hyphessobrycon Durbin 1908 (Characidae: Stethaprioninae) is a representative example of this taxonomic uncertainty. This genus is widely distributed from southern Mexico to Mar Chiquita Lagoon in Buenos Aires, Argentina and includes more than 160 valid species  that is consistent with the multispecies coalescent model . ASTRAL-gcf and—df-tree. We annotated our species tree using the option -t 16 in ASTRAL-III to calculate the NQS of the main topology (preferred species tree) and its branches and the two alternative topologies. For both of these analyses we focused on the recovered relationships of trans-Andean species of Hyphessobrycon within Stethaprioninae (monophyly vs non-monophyly). Furthermore, we investigated the recovered relationships between species of trans-Andean Hyphessobrycon.Recently, it has been highlighted that standard measures of support in phylogenomic inference  have some limitations , 59. An trans-Andean Hyphessobrycon by leveraging species delimitation methods that do not rely on prior assignment of samples to species or lineages. Instead of delimiting species our main goal was to use these approaches to explore if there are genetic discontinuities across currently recognized species of trans-Andean Hyphessobrycon. We generated a reduced UCE dataset  , 71transis” Figs  and 5. IColombia . Despitea et al. . The tax in flux , 33, 95  in flux . Our wora et al. ). For exaracters . Our robColombia  proposedH. ecuadoriensis is not unambiguously resolved. Specifically, we observed a similar proportion of gene trees that support recognition of the Chocó species group excluding H. ecuadoriensis. This hypothesis resolved H. ecuadoriensis as the sister to all trans-Andean Hyphessobrycon  and Atlantic (H. bussingi and H. panamensis) slopes of the Chorotega block [in situ may have occurred within the Atlantic slope of the Chorotega block. The ‘compressus’ species group is comprised of three lineages: H. compressus, H. “compressus”, and H. tortuguerae. The recovered close relationships between these three lineages support the hypothesis of Böhlke [H. compressus, H. tortuguerae, and H. milleri  regardless of differences in coloration among other characters [H. compressus  it belongs to the previously recognized H. milleri, hence extending its distribution into southern and northern Belize, or b) it represents a newly uncovered lineage of the ‘compressus’ species group. Specimens of Hyphessobrycon in the Motagua River basin, where the type locality of H. milleri is located, have not been collected since 1974 despite recent collecting efforts by the authors (DJE and CDM). The inclusion of samples from the Motagua basin for molecular analyses would be key for testing our proposed hypotheses regarding the identity of the H. “compressus” lineage.The ‘panamensis’ species group is comprised of three species, bussingi . These tga block . The sisga block  that splf Böhlke , who allaracters . The uncmpressus  is remar species  across Mmpressus . Interesmpressus  mirrors con Figs  and 5. Wtrans-Andean Hyphessobrycon that proposed the ‘H. panamensis species-group’ sensu Ota et al. [H. bussingi, H. columbianus, H. condotensis, H. daguae, H. panamensis, and H. savagei. Coloration patterns alone or in combination with morphological characters have been used to propose relationships among species of trans-Andean Hyphessobrycon. For example, it has been suggested that pigmentation (or lack thereof) on the dorsal fin reflects relationships among species of trans-Andean Hyphessobrycon including the ‘H. panamensis species-group’ [H. panamensis species-group’ sensu Ota et al. [trans-Andean Hyphessobrycon. Finally, it is worth noting that for the Central American species of Hyphessobrycon , three morphological synapomorphies that unite these species have been proposed: a) premaxilla with seven teeth in the inner row, b) round foramen in the ventral region of the quadrate, and c) two foramina in the ventral margin of the epiotic bone, see García-Alzate et al. [Hyphessobrycon sensu stricto.Finally, the relationships recovered among the three species groups, ), do not support the recent hypothesis of relationships for some species of a et al.  is comprs-group’ , 31, 32.a et al.  and caste et al. . Future cis-Andean taxa and trans-Andean Hyphessobrycon  to North (Maya block), followed by in-situ diversification within each geological block , a marine corridor likely extirpated ancestral populations and limited gene flow between populations on either side of the barrier that gave origin to the ‘panamensis’ and ‘compressus’ groups. Finally, present-day disjunct distributions between species in the ‘compressus’ group  Inferred phylogeny based on the 75% complete data matrix B) inferred phylogeny based on the 90% complete data matrix, and C) inferred phylogeny based on the 75% complete data matrix. All nodes are supported with ultrafast bootstrap (UFBoot2) = 100 and SH-like approximate ratio test (SH-aLRT) = 100 unless noted. Nodes with gray circles UFBoot2 < 90 and SH-aLRT < 90. Species names with asterisk indicates samples from Melo et al. [(PDF)Click here for additional data file.S2 Figtrans-Andean Hyphessobrycon. A) trans-Andean Hyphessobrycon sister to a clade comprise of M. gracilima, H. levis, and M. xinguensis (see trans-Andean Hyphessobrycon sister to H. diancistrus. C) trans-Andean Hyphessobrycon sister other characins of the sub-family Stethaprioninae. Number of trees decisive for the branch (gN) = 1646, effective number of genes for a branch of interest (EN) = 1220.72. gCF = gene concordance factor, gDF1 = gene discordance factor for NNI-1 branch, gDF2 = gene discordance factor for NNI-2 branch, gene discordance factor due to polyphyly (gDFP) = 65.37. NQS = normalized quartet score.Gene concordance factors (gCF) and normalized quartet scores (NQS) for the main topology/quartet (A) and the two alternative quartets (B & C) for the inferred sister relationships of nsis see . B) tran(PDF)Click here for additional data file.S1 TableSamples in bold were used for the cryptic diversity analyses. Museum codes follow Sabaj (2020). Newly generated sequence data is archived in the Sequence Archive Repository (SRA) BioProject PRJNA887072.(XLSX)Click here for additional data file.S2 Tablek = number of parameters, d = dispersal rate, e = extinction rate or range loss rate, j = jum-dispersal rate, AICc = Akaike information criterion corrected. AICc wt = Akaike information criterion corrected weighted. The best biogeographic model was selected based on the highest AICc wt, in bold.LnL = log-likelihood score for the model. (PDF)Click here for additional data file.


Juglans species, Juglans regia and J. mandshurica, are both diploid (2n = 32), monoecious perennial economic tree species with high edible, pharmaceutical, and timber value. The identification, characterization, and expression patterns of LEA proteins in J. regia and its wild relative, J. mandshurica, would not only provide the genetic basis of this gene family, but it would also supply clues for further studies of the evolution and regulating mechanisms of LEA proteins in other tree species.Late Embryogenesis Abundant (LEA) proteins are a class of proteins associated with plant stress resistance. Two LEA gene family in Juglans regia and its wild relative, Juglans mandshurica, respectively. The results of phylogenetic analysis showed that the LEA members were divided into eight main subgroups. Predictions of their physicochemical properties showed the variable characteristics of LEA proteins, and the subcellular localization analysis indicated that most LEA proteins are localized in the nucleus. Chromosomal localization analysis and gene replication pattern prediction indicated that WGD is the predominant duplication mode of LEA genes. The results of the comparative analysis indicated a high level of collinearity between the two Juglans species. Analysis of cis-acting elements indicated that LEA genes had a relatively wide range of responses to abiotic stresses and phytohormonal processes, particularly in two phytohormones, methyl jasmonate and abscisic acid. Transcriptome profiling and qRT-PCR experiments showed that JrLEAs are commonly expressed in leaves, green husks, and male and female flowers, and most JmLEAs are more highly expressed in male flowers. We also hypothesized that JrLEAs are involved in the process of anthracnose resistance. Anthracnose-resistant varieties of JrLEAs presented relatively high expression levels at later stages.In this study, we identified 25 and 20 members of the LEA genes in J. regia and J. mandshurica. Analysis of cis-acting elements and gene expression indicated that JrLEAs and JmLEAs play important roles in resistance to biotic stresses in these species.In this study, we provide a theoretical basis for the functional study of The online version contains supplementary material available at 10.1186/s12870-023-04096-z. Plants have unique molecular response mechanisms and physiological reactions that mitigate the effects of external stresses upon themselves when negatively affected by the external environment, a process known as plant resilience . ExternaLEA gene expression is of great importance for modern plant molecular biology. LEA proteins are highly tolerant to dry environments in cotton [OsLEA can increase the sensitivity and osmotic tolerance of rice to abscisic acid under drought stress [CaLEA1 enhances stomatal sealing and the expression of the related downstream genes in response to drought and salt stress [AtLEA14 [SiLEA14 [TaLEA [ZmLEA3 [SmLEA [As osmoprotective and desiccation damage repair agents, Late Embryogenesis Abundant (LEA) proteins, existing widely in the plant kingdom, are a class of dehydration-resistance-associated glycine-rich proteins with low molecular weights 10–30 kDa) . LEA pro–30 kDa .n cotton . Subsequn cotton  had showt stress . Similart stress . Further[SiLEA14  genes ha4 [TaLEA , ZmLEA3  [ZmLEA3 , and SmL3 [SmLEA  have alsJuglans regia L., 2n = 32), also known as the common walnut, belonging to the genus Juglans in the family Juglandaceae and the monoecious perennial tree [Prunus dulcis) [J. regia is mainly grown and cultivated in the provinces of Xinjiang, Shaanxi, Yunnan, and Hebei [Juglans mandshurica (2n = 32), a closely related wild species of the Persian walnut, is an ecologically important, wind-pollinated, and endemic species that grows in northern and northeastern China, Korea, Japan, and the far eastern section of Russia [LEA gene family is important for plant growth and developmental processes, and so far, LEA genes have been identified in many plants, such as Arabidopsis [LEA gene family members in Juglans, as well as their expression patterns, are still unknown. Hence, Juglans, identifying and characterizing LEA gene family members across the genomes of the two Juglans species and conducting a comprehensive comparative study are necessary.The Persian (English) walnut  . In Chinnd Hebei . Walnutsf Russia –25. The bidopsis , poplar bidopsis , cucumbebidopsis , and oilbidopsis . HoweverLEA gene family for the first time in J. regia and its wild relative, J. mandshurica. We determined their phylogenetic relationships, predicted their physicochemical properties, identified their conserved structural domains, investigated their chromosomal localization and gene duplication patterns, and performed gene structure analysis and cis-acting element analysis for LEA gene members in the J. regia and J. mandshurica genomes. Additionally, we produced LEA gene expression profiles using transcriptome sequencing and qRT-PCR based on multi-tissue organs and biotic stress treatment conditions. The results not only provide a fundamental basis for studying LEA gene function in J. regia and J. mandshurica, but they also provide clues for further studies of the evolution and regulating mechanisms of LEA proteins in other tree species.In the present study, we identified and analyzed the LEA gene family in two Juglans species, 51 LEA protein sequences of Arabidopsis thaliana (https://www.arabidopsis.org/) were adopted as query sequences to perform the genome-wide BLASTP in the J. regia and J. mandshurica [https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi), Pfam (http://pfam.xfam.org/), and SMART (http:/ /smart.embl.de/ /smart.embl.de/) databases, respectively. The candidate genes which contained any of the LEA_1, LEA_2, LEA_3, LEA_4, LEA_5, LEA_6, SMP, or Dehydrin structural domains were considered to be members of LEA gene family. Afterward, the identified JrLEAs and JmLEAs were submitted to the online website of GSDs (http://gsds.gao-lab.org/) for gene structure analysis and visualized using TBTOOLS software [To identify the candidate members of the dshurica . Subsequsoftware .LEA proteins in J. regia and J. mandshurica were predicted using the ExPASy online tools (http://www.expasy.org/tools/protparam.html). Subcellular localization of all identified LEA genes in J. regia and J. mandshurica were predicted using the WoLF PSORT online tools (https://wolfpsort.hgc.jp/).Physicochemical properties of all identified LEA genes in J. regia and J. mandshurica were performed using TBTOOLS software according to the gene annotation [JrLEAs and JmLEAs using MCScanX software [cis-acting element prediction was executed by using 2000 bp sequences upstream of the identified LEA genes via PlantCARE (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/).Chromosomal localization of all identified notation . For subsoftware . Moreovesoftware  was utilLEA members in Arabidopsis thaliana, J. regia, and J. mandshurica was constructed by using the IQTREE software [https://itol.embl.de/login.cgi).The maximum likelihood phylogenetic tree of the software , in whicJuglans species to the STRING online website (https://cn.string-db.org) to predict protein-protein interactions. All genomic sequences of identified LEA members were submitted as candidates to predict of potential miRNAs, using the default parameters of psRNATarget online website (https://www.zhaolab.org/psRNATarget/) [Uploading LEA protein sequences of two Target/) . VisualiTarget/) .https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147083) [J. regia using HISAT2 software [For the transcriptome analysis, multi-tissue gene expression data were obtained from our previously determined transcriptome data , 37. MeaE147083) , in whicE147083) , after wsoftware . Finallysoftware .J. mandshurica and J. regia trees according to the following botanical characteristics: leaves, buds, male flowers, female flowers, stems, and fruits. We obtained the permissions to collect those plant samples from ZNFP. The voucher specimen of J. regia and J. mandshurica (deposition accession numbers: NWU2020016 and NWU2020036) were stored at the Evolutionary Botany Laboratory, College of Life Sciences, Northwest University .Subsequently, the qRT-PCR were implemented to furtherly explore the expression pattern of the identified LEA genes. The leaves, green husks, male and female flowers of the two species in the same developmental period (maturity) were selected for the qRT-PCR verification. A total of 3 biological replicates were present per species/tissue organ. This study was approved by the Chinese government and carried out according to the laws of the People’s Republic of China. All participants had a license approval letter from the College of Life Sciences, Northwest University. Both male and female flowers were harvested in mid-April from the Zhuque National Forest Park (ZNFP) in Xi’an, Shaanxi Province , while the leaves and green husks were harvested from ZNFP in late August. All samples were immediately frozen in liquid nitrogen after collection for further utilization. In this study, Prof. Peng Zhao identified individual J. regia β-Actin was selected as the internal reference gene and primers were designed using the Primer3Plus online website (https://www.primer3plus.com). The primer design sequences are shown in Table S-ΔΔCT method [Total RNA was extracted from each sample using an RNA extraction kit (plant RNA Kit (50) OMEGA, USA). Complementary DNA (cDNA) was synthesized using 5× PrimeScript RT Master Mix (Takara) reverse transcriptase. The above cDNA was diluted 5-fold as qRT-PCR template. Subsequently, qRT-PCR experiments were performed on a Bio-Rad CFX96 fluorescent quantitative PCR instrument using 2× Plus SYBR real-time PCR mixture (Biotec) as a fluorescent dye. Each sample had 3 biological replicates and 3 technical replicates. T method .LEA gene family members in J. regia and 20 LEA gene family members in J. mandshurica were present in the samples, and we renamed all members identified in two Juglans species according to their positions on the chromosomes. Details regarding the names, gene IDs, and protein sequences of all identified J. regia and J. mandshurica LEA members were shown in Table SA total of 25 LEA members in J. regia and J. mandshurica. All members of the LEA family of Arabidopsis, J. regia and J. mandshurica could be divided into eight groups with high bootstraps value (=1000), as follows: LEA_1, LEA_2, LEA_3, LEA_4, LEA_5, LEA_6, SMP, and Dehydrin, each of which corresponded to a unique domain  tree was reconstructed for the s value =000, as fJ. regia ranged from 88 amino acids (JrLEA5) to 534 amino acids (JrLEA4), with an average length of 186.28 amino acids  to 773 amino acids (JmLEA15), with an average length of 223.45 amino acids. The molecular weights of LEA proteins in J. regia ranged from 9659.57 Da (JrLEA5) to 59,259.16 Da (JrLEA4), with an average of 20,219.93 Da. Similarly, the molecular weights of JmLEAs were greater than those of J. regia, which ranged from 9815.01 Da (JmLEA3) to 59,504.39 Da (JmLEA19), with an average of 24,325.8545 Da. In addition, 17 and 13 LEA proteins in J. regia  and J. mandshurica  were acidic proteins (Isoelectric point < 7), respectively. A total of 11 and 7 LEA proteins were present in J. regia and J. mandshurica, respectively, with instability index values > 40. Almost all identified LEA proteins in J. regia and J. mandshurica had a positive Grand Average of Hydropathicity (GRAVY) with only five exceptions , which suggested that the majority of LEA proteins in J. reiga and J. mandshurica were hydrophobic. In addition, the identified LEA members were distributed in mitochondria, chloroplasts, the nucleus, the cytoskeleton, peroxisomes, and the extracellular matrix. Most of the identified LEA members were located in the nucleus , followed by chromosome 8 . For J. mandshurica . Chromosome 2  and chromosome 8  both possessed four LEA genes, and chromosome 7 had two LEA genes (JmLEA12 and JmLEA13). The remaining LEA genes were located in unique chromosomes.For LEA gene duplication, of which Whole Genome Duplication (WGD) was the major mode in Juglans  in J. regia and 10 out of 20 LEA genes (50%) in J. mandshurica experienced WGD. Furthermore, the Tandem Duplication (TD) mode was found in JrLEA9, JrLEA10, JrLEA14, and JmLEA1. Four JrLEAs  and five JmLEAs  underwent Dispersed Duplication (DSD). Notably, several LEA genes, identified as singleton genes, did not appear to show duplication, and the JrLEA13 and JmLEA19 were considered to have Proximal Duplication (PD).The results of gene duplication analysis showed four patterns of ans Fig. ; Table 2J. regia and J. mandshurica, we first constructed a phylogenetic tree of the two species using their LEA protein sequences  without collinearity and five JmLEAs  without collinearity were present. Therefore, these genes may be specific to J. regia and J. mandshurica. In addition, 23 orthologous gene pairs were present between Arabidopsis and J. regia, and 15 orthologous gene pairs were present between Arabidopsis and J. mandshurica  and ABRE (associated with the abscisic acid hormone response). JmLEAs’ response to light involves more components than that of JrLEAs; therefore, J. mandshurica is presumably more sensitive to light.To investigate the potential functions of ght Fig. . The proJ. mandshurica  were expressed in four selected tissues of J. mandshurica. The majority of JmLEA genes (7 out of 8) were highly expressed in male flowers. Only one gene, namely JmLEA1, was highly expressed in leaves, and JmLEA17 presented a high expression level in green husks. All of those without collinear JmLEAs (unique) were not expressed in female and male flowers, leaves, or green husks. For those without collinear JrLEAs , JrLEA13 and JrLEA16 were expressed at high levels in male and female flowers, JrLEA9 was expressed at high levels in leaves, and the other four genes  were all expressed at low levels in the four selected organs  than in anthracnose-susceptible varieties (F423) after infection  in anthracnose-susceptible varieties . reached peak expression at 48 h of stress. JrLEAs presented a relatively high expression level at the late stage in anthracnose-resistant varieties . Of the seven unique JrLEAs, JrLEA1, JrLEA5, JrLEA14, and JrLEA16 had higher expression levels at 48 hours of infection in variety F423. JrLEA1 and JrLEA5 had higher expression levels at 120 hours of infection in variety F26. The other three genes  showed low expression levels in both F26 and F423 varieties at different periods of infection  and its wild relative, J. mandshurica, are both economically valuable tree species [Juglans species have become a current research hotspot [LEA gene family has been extensively studied in plant species, with reports of a total of 51 LEA members identified in Arabidopsis [LEAs in J. regia and J. mandshurica , presenting similar proportions observed in other species with TD, accounting for 9.6% in the banana [LEAs, they presented variable genic structures in J. regia and J. mandshurica  and abscisic acid (ABA)  Fig. , suggests tomato  and wheas tomato . For exaiccation . Thus, tJuglans genome provided an excellent opportunity to deeply explore the functional network and regulation mechanism of the candidate genes. LEA genes were once considered to be responsive to abiotic stress; however, they also play a pivotal role in biotic resistance [cis-acting elements, we also explored LEA expression patterns in various tissues and in anthracnose-resistant varieties (F26), as well as in anthracnose-susceptible varieties (F423).Perennial crops were once regarded as intractable systems due to their large size and their long juvenile phase and generation length. Recently, the development of perennial crops has been garnering increasing attention, as they are essential components for sustainable agriculture that provide alternative food sources under changing environments. The published high quality sistance . Anthracsistance , as it iJrLEAs were expressed in leaves, green husks, male flowers, and female flowers, suggesting that these genes play an important role in the development of all four selected tissues. In contrast, most JmLEAs might play a role in other organs or in other developmental stages of the selected tissues. JrLEA8 and JrLEA19 were highly expressed in both leaves and green husks and had similar expression patterns, suggesting that they might possess the function of synergetic regulation in the development of leaves and green husks. Five JmLEAs were highly expressed in the male flowers of J. mandshurica, suggesting that these genes are more valuable candidates for studying male flower development in J. mandshurica  as well as JrLEA2 and JrLEA5  are thought to have a possible direct or indirect effect on dichogamy in J. regia. Six genes were more highly expressed in male flowers than in female flowers, and two genes presented the opposite pattern, suggesting that LEA genes also influence dichogamy in J. mandshurica. The tissue-specific expression of these LEAs may be associated with dichogamy in two Juglans species, although the regulatory mechanisms involved remain to be further investigated.ica Fig. . The majies Fig.S. Plants ichogamy . JrLEA4 LEA genes for anthracnose-resistant varieties (F26) than those for anthracnose-susceptible varieties (F423), indicating that LEA genes might play a role in anthracnose resistance in J. regia , JrLEA3 and JrLEA23 (LEA_5), and JrLEA18 and JrLEA24 (Dehydrin). The expression levels of most JrLEAs increase with time within 48 h after infection [JrLEA12 and JrLEA22 were only expressed in F26 varieties, indicating that these two genes are closely associated with anthracnose resistance in J. regia. In addition, the LEA gene family was also shown to be a gene family associated with disease resistance in J. mandshurica [ZmLEA3, which can respond to biotic stresses, and the overexpression of ZmLEA3 in tobacco results in its increased tolerance to the pathogen pst dc3000 (the pathogen Pseudomonas syringae pv. Tomato DC3000) [LEAs are not only able to respond to abiotic stresses but also to biotic stresses. J. regia is more susceptible to disease than its wild relative, J. mandshurica [J. mandshurica has been shown to have better resistance to disease to lesion nematode [J. mandshurica is recommended as a rootstock for J. regia to confer disease tolerance/resistance [JmLEAs may exhibit better expression for biotic stresses compared with JrLEAs, but further studies are still needed in this regard.In addition, we found higher expression levels of ieties F2 than thogia Fig. . Moreovenfection . JrLEA12dshurica . A simil DC3000) . These rdshurica . J. mandnematode . Therefosistance –56. FurtLEA gene family members in J. regia and its wild relative, J. mandshurica. The phylogenetic analysis showed that the LEA genes in J. regia and J. mandshurica are divided into eight subgroups, similar to results from other plants. The phylogenetic and collinearity analyses indicated that the LEA gene family is relatively evolutionarily conserved. The analysis of cis-acting elements and gene expression indicated that JrLEAs and JmLEAs play important roles in resistance to biotic stresses in J. regia and J. mandshurica. Further exploration is necessary to determine the specific roles of JrLEAs and JmLEAs in other stresses, such as metal ion stress, extreme temperatures, UV radiation, etc.In this study, we systematically identify Additional file 1: Figure S1. Protein interaction network and schematic representation of the regulatory network relationships between the putative miRNAs and their targeted LEA genes. Elliptics represent proteins, rectangles represent miRNAs. The black line indicates protein interactions and the pink line indicates miRNA targeting of LEA genes. Figure S2. Expression patterns of LEA genes without collinearity in four selected organs of two Juglans species. The colored scale reflects gene expression levels. Figure S3. Expression patterns of LEA genes without collinearity under biotic stress of J. regia. F26 indicated anthracnose-resistant varieties, F423 indicated anthracnose-susceptible varieties. The colored scale reflects gene expression levels.Additional file 2: Table S1. Primers for the qRT-PCR experiment. Table S2. Protein sequences of all LEA genes in J. regia and J. mandshurica. Table S3. Homologous LEA gene pairs and Ka/Ks values in J. regia and J. mandshurica. Table S4. Homologous LEA gene pairs in Arabidopsis and two Juglans species. Table S5. The FPKM values of all LEA genes in different tissues of J. regia. Table S6. The FPKM values of all LEA genes in different tissues of J. mandshurica. Table S7. The putative miRNAs and their targeted LEA genes. Table S8. The FPKM values of all LEA genes in anthracnose-resistant varieties (F26) and anthracnose-susceptible varieties (F423) with the time after infection of J. regia.


Mycobacterium tuberculosis and Mycobacterium africanum. Whereas M. tuberculosis is widely spread, M. africanum is restricted to West Africa, where it remains a significant cause of tuberculosis. Although several differences have been identified between these 2 pathogens, M. africanum remains a lot less studied than M. tuberculosis. Here, we discuss the genetic, phenotypic, and clinical similarities and differences between strains of M. tuberculosis and M. africanum. We also discuss our current knowledge on the immune response to M. africanum and how it possibly articulates with distinct disease progression and with the geographical restriction attributed to this pathogen. Understanding the functional impact of the diversity existing in TB-causing bacteria, as well as incorporating this diversity in TB research, will contribute to the development of better, more specific approaches to tackle TB.Tuberculosis (TB), one of the deadliest threats to human health, is mainly caused by 2 highly related and human-adapted bacteria broadly known as  Tuberculosis (TB) is one of the oldest, deadliest, and more devastating infectious diseases affecting humankind . DespiteMycobacterium tuberculosis as its causative agent, our understanding of the pathogen has greatly evolved. M. tuberculosis belongs to the Mycobacterium tuberculosis complex (MTBC), which comprises phylogenetically related TB-causing bacteria that differ in their host specificity [M. tuberculosis sensu stricto; strains belonging to L5, 6, and to the newly discovered L9 are classified as Mycobacterium africanum also known as M. tuberculosis var africanum [Mycobacterium bovis, Mycobacterium caprae, and Mycobacterium suricatae. The phylogenetic structure of the MTBC is shown in Since Robert Koch’s initial identification of TB as an infectious disease, and of cificity . Nine hufricanum –9. Severfricanum . Strainsfricanum . Among tM. tuberculosis lineages across the globe [M. tuberculosis lineages are mostly classified as generalists with the exception of L7 that is restricted to Ethiopia in the horn of Africa [M. tuberculosis lineage, being the most prevalent in Europe and America, but also commonly found in all other continents [M. africanum lineages  and sublineages are geographically restricted to specific regions of Africa M. tubercountries –23, althountries ,23. It wan areas . TB causountries –28. Impocestries . Howeveric areas . Similar to 2015 , 2 of th to 2015 . Addition Brazil . AlthougM. africanum strains were initially divided into 2 main subtypes based on their geographic origin: M. africanum subtype I, for strains originating from West Africa and M. africanum subtype II for strains from East Africa [M africanum subtype II, also known as the “Uganda genotype,” as belonging to a sublineage of L4, thus leaving M. africanum strains restricted to West Africa [M. tuberculosis and M. africanum, allowing M. africanum strains to be subdivided into 2 genetically distinct lineages: L5 and L6  [M. tuberculosis and M. africanum strains are readily distinguishable by the deletion of the region of difference (RD) 9 in the genome of M. africanum strains. The genome of strains within L5 has a further deletion in RD711, while genomes of strains within L6 are characterized by a deletion of RD702 [M. africanum from M. tuberculosis strains and allowing the genomic identification of L5 and L6 strains  ,35  and produce dysgonic colonies, contrary to M. tuberculosis strains that exhibit eugonic colonies [M. africanum L6 strains are adapted to growth under hypoxic conditions [M. tuberculosis and M. africanum strains. The nitrate reductase activity is strong in the case of M. tuberculosis strains and weak to negative for both L5 and L6 strains [M. tuberculosis L4 and M. africanum L6 strains present a stronger average urease activity, which is directly linked to the bacteria nitrogen metabolism, than L5 [M. tuberculosis. No phenotypic data pertaining L9 strains exist thus far, and so it is as yet not possible to include L9 strains in these comparisons. Hence, the classification of TB-causing isolates into the different lineages of M. tuberculosis or M. africanum based in genotypic differences  locus, a complex cell wall lipid unique to mycobacteria associated with its virulence [M. africanum L6 was shown to induce considerably less IFN-β by infected bone marrow–derived macrophages than M. tuberculosis strains from L2 or L4 [M. africanum isolate also triggered cGAS and STING, infections of macrophages by this pathogen induced less mitochondrial stress, thus decreased production of mitochondrial reactive oxygen species that contributed to less type I IFN being produced [M. africanum strains was subsequently studied in mouse models. In agreement with the detrimental role of type I IFN in TB [M. africanum infection [M. africanum infection are potentially pathogenic [M. africanum strains infect macrophages, inducing a cytokine response, while adapting to the host cell. The molecular mechanisms underlying these responses, such as the recognition of M. africanum strains by pattern recognition receptors, remain however elusive. M. africanum strains were shown to bind recombinant human mannose-binding lectin (MBL), a plasma opsonin, more efficiently than M. tuberculosis strains and a protective association between TB and the human MBL2 G57E variant, associated with lower MBL levels, was described, only in TB caused by M. africanum [M. africanum strains to MBL may favour the bacteria uptake by macrophages, promoting the establishment of infection in vivo, and thus the protective MBL deficiency may have been selected in the human population in regions endemic for M. africanum. Another study has identified increased levels of TLR9 expression in unstimulated blood of patients infected with M. africanum isolates as compared to other MTBC strains infections [M. africanum strains. Of note, the levels of IL-12p70 and IL12A were also significantly higher in M. africanum-infected patients, while those of IL-15, IL8, and MIP-1α were higher in M. tuberculosis-infected patients [M. africanum- and M. tuberculosis-infected patients showed no differences at diagnosis, although there were distinct signatures associated with each infection posttreatment, predominantly associated with immune responses and metabolic diseases [Infection of human monocyte-derived macrophages with distinct strains of the MTBC showed variation of the induced cytokine responses including between the 2 isolates of response . Interesterparts . Anotherirulence . More reL2 or L4 . Althougproduced . The in FN in TB , lack ofnfection . These rthogenic . Collectthogenic  demonstrfricanum . It is pfections , which mpatients . A broaddiseases .M. tuberculosis- or M. africanum-infected TB patients before chemotherapy and following overnight stimulation of whole blood with ESAT-6/CFP-10 or with purified protein derivative (PPD) showed higher single-TNF-α-producing CD4 and CD8 T cells and lower single-IL-2-producing T cells in the case of M. africanum infections [M. africanum-infected individuals posttreatment [M. tuberculosis-infected TB patients [M. africanum isolate, also associated with restricted lung pathology [M. africanum infection, which although precluding the clearance of the pathogen, may protect the host from tissue immune pathology. This hypothesis is compatible with a slower progressing infection and may be explained by pathogen-associated factors. Pathogens belonging to the MTBC are known to have remarkably hyperconserved T cell epitopes, suggesting that ensuring T cell responses is more important to these agents than evading them [M. africanum were significantly more genetically diverse than the L5 ones, including in predicted T cell epitopes [M. africanum strains.Comparison of T cell responses from fections . Additioreatment . Howeverreatment , both bereatment . Interespatients ,76. In tathology . Taken aing them . Interesepitopes . Additioepitopes . Thus, iM. africanum to the host population, particularly to the host immune response, is a conceivable hypothesis to explain the geographic restriction of this pathogen. Previous studies provide compelling evidence towards this hypothesis in the case of M. africanum L5 strains. In a study in Ghana, M. africanum was significantly more common in TB patients belonging to the Ewe ethnic group an association that was mainly driven by L5 strains [M. africanum infection and human genetic diversity were also described in other studies. A polymorphism in the exonic allele (g.760A) of the ALOX5 gene  was  strains . Furtherisolates . Thus, hh groups . It is tM. africanum isolates could contribute to the high susceptibility of West African individuals to infections with this pathogen has been proposed [M. africanum strains presented less microbiome diversity than individuals infected with M. tuberculosis isolates or healthy controls and were enriched in bacteria from the Enterobacteriaceae phylum Proteobacteria as compared to healthy controls [M. africanum.More recently, the hypothesis that differences in the intestinal microbiota of patients infected with proposed . Patientcontrols . Since aM. africanum infections, which are less related to the host immune response. It is possible that M. africanum is an attenuated member of the human-adapted TB-causing bacteria, being therefore outcompeted by M. tuberculosis. This hypothesis is supported by the reduction of TB cases caused by M. africanum strains over time for some countries [M. africanum L6 strains share a common ancestor with animal (nonhuman) adapted strains ..M. africM. africanum strains. A striking feature characterizing these TB-causing bacteria is its geographical restriction, which contrasts with the widespread distribution of M. tuberculosis strains and remains largely unexplained. Adaptation of M. africanum strains to the West African population, perhaps mediated through differential modulation of the immune response, is a likely hypothesis. Importantly, infections of humans and experimental models with strains of M. africanum are generally more attenuated than those with M. tuberculosis strains. This offers an opportunity to learn from M. africanum and its interactions with the host, with the aim of better controlling M. tuberculosis. There are several outstanding questions that would advance our knowledge in this field towards better strategies to tackle TB:Up to 50% of the TB cases in West Africa have been attributed to M. africanum? Are there nonhuman reservoirs relevant in supporting human transmission? This would provide important information on the evolution of specific members of the MTBC, as well as potentially guide measures to mitigate M. africanum infections.What is the actual origin of M. tuberculosis and M. africanum distinct entities? This remains a matter of debate, as although recent studies suggest that both pathogens belong to the same species, phenotypic differences between M. tuberculosis and M. africanum strains are well documented. Additional studies are required to fill this knowledge gap further informing similarities and particularities of different MTBC members of relevance for TB management.Are M. africanum and M. tuberculosis strains? The fact that both pathogens are endemic in the same geographic area would suggest a scenario where coinfections are possible. Clarifying this question would be interesting to understand which pathogen would impact more disease presentation or if different clinical/immune response characteristics would prevail.Are there coinfections caused by M. tuberculosis infections? Does M. africanum modulate innate or T cell responses in specific populations? Is this associated with increased susceptibility of the population or decreased virulence of the pathogen? Disclosing the immune signatures of M. africanum infections and correlating those with the disease manifestation will provide valuable knowledge to develop potential immune interventions in TB, including vaccines.What are the differences between TB and the immune response during infection with L5, L6, and L9 strains? How does this correlate with M. tuberculosis and M. africanum strains? Elucidating this question is hampered by our inability to categorize the pathogen species in latent cases. However, by revealing immune signatures of M. africanum infections, it may be possible to then look at latent and progressing cohorts in an attempt to establish latent signatures specific of the different MTBC members. This will further our knowledge on the natural history of TB, again potentially offering novel targets to control TB.Are there differences in latency establishment, duration, or reactivation between M. africanum and M. tuberculosis strains will provide valuable knowledge towards identifying the cellular and molecular determinants allowing the widespread of the M. tuberculosis strain lineages, which are a global threat. This knowledge will also advance our understanding on the biology of M. africanum and its interactions with the human host, which is highly relevant considering the TB burden in West Africa. Furthermore, consistently stratifying for the type of infecting bacteria in human-based studies will contribute to a better interpretation of novel TB intervention tools, including diagnosis and vaccines. All this will in turn inform the development of better, more specific approaches to tackle TB.Answering these questions to understand the differences between


Neisseria gonorrhoeae strains resistant to extended-spectrum cephalosporins (ESCs) is a worldwide concern because this class of antibiotics represents the last empirical treatment option for gonorrhea. The abusive use of antimicrobials may be an essential factor for the emergence of ESC resistance in N. gonorrhoeae. Cephalosporin resistance mechanisms have not been fully clarified. In this study, we mapped mutations in the genome of N. gonorrhoeae isolates after resistance induction with cefixime and explored related metabolic pathways. Six clinical isolates with different antimicrobial susceptibility profiles and genotypes and two gonococcal reference strains (WHO F and WHO Y) were induced with increasing concentrations of cefixime. Antimicrobial susceptibility testing was performed against six antimicrobial agents before and after induction. Clinical isolates were whole-genome sequenced before and after induction, whereas reference strains were sequenced after induction only. Cefixime resistance induction was completed after 138 subcultures. Several metabolic pathways were affected by resistance induction. Five isolates showed SNPs in PBP2. The isolates M111 and M128 (ST1407 with mosaic penA-34.001) acquired one and four novel missense mutations in PBP2, respectively. These isolates exhibited the highest minimum inhibitory concentration (MIC) for cefixime among all clinical isolates. Mutations in genes contributing to ESC resistance and in other genes were also observed. Interestingly, M107 and M110 (ST338) showed no mutations in key determinants of ESC resistance despite having a 127-fold increase in the MIC of cefixime. These findings point to the existence of different mechanisms of acquisition of ESC resistance induced by cefixime exposure. Furthermore, the results reinforce the importance of the gonococcal antimicrobial resistance surveillance program in Brazil, given the changes in treatment protocols made in 2017 and the nationwide prevalence of sequence types that can develop resistance to ESC.The emergence of  Neisseria gonorrhoeae (gonococcus) is the causative agent of gonorrhea, a sexually transmitted infection with an estimated 87 million new cases per year globally , encoded by penA. Some isolates have acquired several mutations in penA by DNA transformation and recombination with penA genes from commensal Neisseria spp.  of 015–2016  and, in Eight gonococcal isolates were selected: a single blood culture isolate from an inpatient at the University Hospital of the Federal University of Santa Catarina; five male urethral discharge isolates selected from a nationwide study, the Brazilian-GASP  ; and twoThese isolates were selected based on cefixime susceptibility profile and ST. We included cefixime-susceptible isolates with an 8- to 32-fold minimum inhibitory concentration (MIC) lower than 0.125 mg/L and an MIC of 0.125 mg/L (susceptibility threshold breakpoint). ST1407 was included because of previous reports related to ESC resistance spread . ST338 wN. gonorrhoeae isolates were identified using a Vitek2 Compact instrument . All isolates were stored at −80°C in casein-peptone soymeal-peptone broth  containing 20% glycerol until further analysis.2 for 18 to 24 h. In vitro induction was considered complete when all isolates achieved stable growth at a cefixime concentration above the resistance breakpoint, according to guidelines of the Brazilian Committee on Antimicrobial Susceptibility Testing (BrCAST) . After resistance induction, all isolates were confirmed as N. gonorrhoeae using a Vitek2 Compact instrument and stored at −80°C in casein-peptone soymeal-peptone broth containing 20% glycerol.Gonococcal isolates were recovered from cryopreservation on chocolate agar plates  and subcultured on the same medium. To induce resistance to cefixime, we subcultured a single colony on GC agar  supplemented with 1% Vitox  containing different concentrations of cefixime, starting from 0.002 mg/L. The colonies were subcultured on two GC plates: one containing the same concentration of cefixime and another with a higher concentration (1.5- to 2-fold each test). When the isolate grew on the higher-concentration plate, it was challenged to an even higher concentration of cefixime. All plates were incubated at 35 ± 1°C in 5% COhttp://brcast.org.br/) standards. N. gonorrhoeae WHO F, G, K, L, and M were used as controls  was performed by PCR and sequencing of two N. gonorrhoeae genes (porB and tbpB), following the protocol developed by http://www.ng-mast.net, accessed in 2018) (in 2018) .All isolates were sequenced, except WHO F and WHO Y before resistance induction. Genomic DNA was extracted using a PureLink™ Genomic DNA Mini Kit  and quantified using the Qubit dsDNA BR Assay Kit (Thermo Fisher Scientific Inc). After quantification, DNA was diluted to 0.5 ng/µl. Illumina sequencing libraries were generated using an Illumina Nextera XT DNA Library Kit . Whole-genome sequencing of paired-end libraries  was performed using the Illumina MiSeq platform (Illumina Inc.).https://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and quality-based trimming and filtering were performed using Trimmomatic version 0.39 .Raw read quality was checked using FastQC version 0.11.8   version 3.1.1 (ry 2021) . Mutatiory 2021) .N. gonorrhoeae isolates after selection for resistance to cefixime -calling pipeline was constructed by mapping reads from genomes sequenced after resistance induction onto the assembled genomes. This procedure was performed using BWA version 0.7.17-r1188 . SAMToolcefixime .The Institutional Ethics Review Board of the University Hospital of the Federal University of Santa Catarina (HU/UFSC) approved this study under reference number CAAE 13727619.4.0000.0121.Raw data and genome assemblies of all gonococcal isolates were deposited in the NCBI database under accession numbers SAMN26195797 to SAMN26195810.N. gonorrhoeae are described in Draft genome sequences of isolates before selection for resistance to cefixime were used for genotypic characterization and identification of possible AMR determinants. Relevant genetic traits for antimicrobial resistance in All isolates included in this study were found susceptible to the antimicrobials currently in use for the treatment of gonococcal infection in Brazil (ceftriaxone plus azithromycin) . Of all penA-34.001. The penA mosaic allele, generated by DNA transformation followed by recombination with commensal Neisseria spp., is associated with reduced susceptibility/resistance to ESCs, having a greater impact on the MIC of cefixime than that of ceftriaxone. The MIC of cefixime against these isolates (0.125 mg/L) revealed borderline resistance, according to BrCAST criteria (resistance = MIC > 0.125 mg/L); the MIC of ceftriaxone ranged from 0.03 to 0.06 mg/L. In addition to alterations in the primary ESC resistance mechanism, ST1407 isolates also exhibited alterations in PorB1b porin and MtrCDE efflux pump, influencing the MIC of ESCs; such alterations promote decreased influx and increased efflux of ESCs, respectively.Urethral discharge samples  showed similar resistance determinants according to ST profile. Samples belonging to ST1407/ST1901  had a mosaic penA-19.001 non-mosaic allele, and no alteration was found in the major determinants of ESC resistance. Of the six antimicrobials analyzed, M107 and M110 were only resistant to ciprofloxacin and penicillin. This pattern was associated with mutations in GyrA, ParC, and PBP1 as well as with the presence of β-lactamase-producing plasmid carrying blaTEM-1, which confers high resistance to penicillin but has no impact on the MIC of ESCs.The MIC of ESCs for samples belonging to ST338/ST1588 (M107 and M110) was lower than that for ST1407. M107 and M110 harbored the Isolates belonging to ST1407 and ST338 were resistant to ciprofloxacin because they contained mutations in GyrA and ParC. The 2-fold variation in MIC between STs may be explained by the extra GyrA mutation (D95G) observed in ST1407.In vitro resistance induction of N. gonorrhoeae isolates to cefixime was completed after 138 subcultures. There was an increase in cefixime MIC, such that all susceptible isolates became resistant according to BrCAST (resistant = MIC > 0.125 mg/L) and CLSI (resistant = MIC > 0.25 mg/L) criteria  were observed in five isolates: WHO F and M009, which do not have the penA mosaic form, and M043, M111, and M128, which belong to ST1407. M111 acquired one (A488V) and M128 acquired four  novel mutations in penA. These isolates exhibited the highest cefixime MIC. Subculturing of isolates with cefixime resulted in mutations in genes related or not to ESC resistance. SNPs in the main resistance determinant , associated with motility, adhesion, and secretion, were also affected at the DNA level. The other mutated genes were related to DNA recombination; energy production; metabolism/transport of amino acids, organic ions, carbohydrates, and coenzymes; post-transcriptional modifications; and translation. One gene was associated with an unknown function.In addition to mutations in penA. M107 and M110, which belong to ST338, formed a group. The other group was formed by WHO F isolates, M009 and M043, which exhibited the lowest cefixime MIC values.A significant variation in mutation patterns was identified after induction with cefixime. No gene was altered in all isolates. M111 and M128 were grouped for having the highest number of mutations in penA but exhibited an increase in the MIC of ESCs, suffered mutations in some resistance genes, including porin PorB1b (A26V), MtrC (S23P), and MtrD (M570K). Mutations in PilQ were observed in M128 (G590D) and WHO Y (guanine insertion between nucleotides 1566 and 1567), resulting in a frameshift. Interestingly, M107 and M110 did not acquire mutations in the main determinants of resistance to ESCs. Only M110 acquired an SNP in ponA (PBP1), which resulted in an A615V amino acid change in this protein. Nevertheless, we observed alterations in genes involved in cellular division. M107 acquired a guanine insertion between nucleotides 299 and 300, resulting in a frameshift in zapA, and M110 acquired the A318V mutation in FtsZ.WHO Y, which did not show any mutation in N. gonorrhoeae isolates after cefixime exposure. WHO F, WHO Y, one N. gonorrhoeae isolate from blood culture, and the two most prevalent STs in Brazil were used . WHO D possessed non-mosaic penA, adenine deletion in the mtrR promoter region, and L421P amino acid change in PBP1. Furthermore, N. gonorrhoeae, only penA was mutated in WHO D (A501V). Although in vitro in N. gonorrhoeae compared with cefixime.The MIC of cefixime increased above the breakpoint (as determined by CLSI and BrCAST criteria) for all isolates postselection, indicating that isolates acquired resistance to this antimicrobial. A study conducted by via an acylation reaction, contains three conserved motifs: SxxK, which comprises the amino acids Ser-310 and Lys-313 (α2 helix); SxN, which contains Ser-362 and Asn-364 (between helices α4 and α5); and KTG, comprising amino acids Lys-497, Tre-498, and Gly-499 (β3 sheet)  . The pre-lactams . The fir-lactams . Ceftria-lactams . The A31penA, these isolates previously exhibited mutations in PorB1b and the mtrR promoter region, which probably helped to increase the MIC. The contribution of PBP2 mutations in M111 and M128 after induction, as well as the ability of the microorganism to face these changes, still needs to be investigated.Interestingly, the isolates for which MIC values were highest showed amino acid changes not previously described. M128 showed four amino acid changes  and M111 exhibited the A488V mutation, also not previously described. These mutations appear close to conserved motifs that are part of the PBP2 active site. Furthermore, the presence of T534A mutations in M111 and A311V mutation in M128, associated with the P551S mutation, whose simultaneous occurrence in isolates with ESC resistance is not common, may be responsible for the high MIC values. It is noteworthy that, in addition to the acquired mutations in penA-34.001. The isolate led to treatment failure with the use of cefixime. Transformation experiments confirmed that only this new mutation was responsible for ESC resistance , suggesting that other mutations might have contributed to the increase in MIC in M111.The amino acid change T534A, found in this study only in M111, was described in Austria in an isolate belonging to ST1407 with mosaic sistance . The AuspenA. Kinetic analysis of β-lactam acylation at the active site of PBP2 indicated that two mutations (P551S and F504L) are responsible for reducing the acylation index, which minimizes the affinity for PBP2–antimicrobial complex formation  (mtrR promoter region (found here in ST1407 isolates) and the G45D amino acid change in MtrR  and outer membrane channel (MtrE) proteins, exports antimicrobials out of the bacterial cell . MutatiomtrR) . Such ch in MtrR . In 2018 in MtrR . Thus, sria spp. . The prox system . The mutr mosaic . Point mN. gonorrhoeae; it plays a role in the formation of channels or pores through which the pilus is externalized  was responsible for an increase in ceftriaxone MIC. In M107 and M110, mutations were observed in zapA and ftsZ, respectively, two genes involved in cell division. ftsZ is part of a group of genes involved in both cell division and synthesis of peptidoglycan, which initiates cell division by forming a polymer called the Z ring. This structure gives rise to new bacterial cells  arose in six out of eight isolates postselecion, including isolates mosaic penA-34.001 and nonmosaic.In 2020, a study identified different alleles of RNA polymerase associated with ceftriaxone resistance . They evN. gonorrhoeae isolates in vitro. Although not currently used in Brazil, cefixime can serve as a marker of resistance, given that its MIC is generally higher than that of ceftriaxone. It was interesting to note that different STs acquired mutation resistance to ESCs after exposure to cefixime by different mechanisms. Isolates with penA mosaic were more likely to develop mutations in the penA gene itself. These findings reinforce the importance of the gonococcal antimicrobial resistance surveillance program in Brazil, given the changes in treatment recommendations in 2017, and the nationwide prevalence of STs that can acquire resistance to these antimicrobials.In the current study, we observed the ability of the antimicrobial cefixime to induce resistance in The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below:https://www.ncbi.nlm.nih.gov/, SAMN26195797,https://www.ncbi.nlm.nih.gov/, SAMN26195798https://www.ncbi.nlm.nih.gov/, SAMN26195799https://www.ncbi.nlm.nih.gov/, SAMN26195800https://www.ncbi.nlm.nih.gov/, SAMN26195801https://www.ncbi.nlm.nih.gov/, SAMN26195802https://www.ncbi.nlm.nih.gov/, SAMN26195803https://www.ncbi.nlm.nih.gov/, SAMN26195804https://www.ncbi.nlm.nih.gov/, SAMN26195805https://www.ncbi.nlm.nih.gov/, SAMN26195806https://www.ncbi.nlm.nih.gov/, SAMN26195807https://www.ncbi.nlm.nih.gov/, SAMN26195808https://www.ncbi.nlm.nih.gov/, SAMN26195809https://www.ncbi.nlm.nih.gov/, SAMN26195810.MAS and MB conceived and designed the study. MCS assisted with sample isolation and identification. MAS, FB, JM, HM, HG, and JP conducted lab experiments. MAS, DM, and JP carried out genome analysis. MRS assisted in bioinformatics analysis. MAS, JP, and MB interpreted the data and wrote the manuscript. MB supervised the study. All authors edited, commented, and approved the final version of the manuscript. All authors contributed to the article and approved the submitted version.The present study was supported by the Ministry of Health of Brazil, through its Secretariat for Health Surveillance/Department of Diseases of Chronic Condition and Sexually Transmitted Infections.N. gonorrhoeae isolate identification and MIC determination.We thank the Ministry of Health of Brazil and its Diseases of Chronic Condition and Sexually Transmitted Infections for offering support in The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Frankia is at present the sole genus in the family Frankiaceae and encompasses filamentous, sporangia-forming actinomycetes principally isolated from root nodules of taxonomically disparate dicotyledonous hosts named actinorhizal plants. Multiple independent phylogenetic analyses agree with the division of the genus Frankia into four well-supported clusters. Within these clusters, Frankia strains are well defined based on host infectivity range, mode of infection, morphology, and their behaviour in culture. In this study, phylogenomics, overall genome related indices (OGRI), together with available data sets for phenotypic and host-plant ranges available for the type strains of Frankia species, were considered. The robustness and the deep radiation observed in Frankia at the subgeneric level, fulfilling the primary principle of phylogenetic systematics, were strengthened by establishing genome criteria for new genus demarcation boundaries. Therefore, the taxonomic elevation of the Frankia clusters to the rank of the genus is proposed. The genus Frankia should be revised to encompass cluster 1 species only and three novel genera, Protofrankia gen. nov., Parafrankia gen. nov., and Pseudofrankia gen. nov., are proposed to accommodate clusters 2, 3, and 4 species, respectively. New combinations for validly named species are also provided.The genus  FrankiaFrankiaceae , Allocasuarina and Casuarina (Casuarinaceae), and Comptonia and Myrica (Myricaceae), while cluster 2 contains strains that infect Coriariaceae, Datiscaceae, Dryadoideae (Rosaceae), and Ceanothus (Rhamnaceae). Cluster 3 contains Frankia associated with Elaeagnaceae, Colletieae (Rhamnaceae), Morella (Myricaceae), and Gynmnostoma (Casuarinaceae). Members of cluster 3 have been also occasionally isolated from Alnus, Allocasuarina, Casuarina, Ceanothus, and Dryadoideae root nodules * * .1 /(T1 + T2)] × 100, where C1 and C2 represent the conserved proteins numbers between the genome pair, while T1 and T2 are the total numbers of compared proteins in each genome  and Jatrophihabitans .An update of the 16S rRNA phylogeny was, here made available using the largest possible dataset of sequences (n = 72) from all type strains and candidate species, and those available in public databases or extractable from genome sequences providing a size of ≥ 900 nt . A more glnA  genes are totally absent in the asymbiotic cluster 4 . The nif genes are, however, organised in different ways with respect to each cluster (hup) genes are clustered into two operons for clusters 1 and 3, while only one operon is present for clusters 2 and 4  encoding a nitroreductase family deazaflavin-dependent oxidoreductase in cluster 3. Clusters 1 and 4 contain only one copy of murC2 with the ORF encoding a nitroreductase family deazaflavin-dependent oxidoreductase only present in cluster 1.Some genes and operon organisation show some distinctiveness for each of the four clusters . There a cluster . The Ni- 2 and 4 . Anotherre found . Two copOverall differentially encoded proteins between genomes of the four clusters were provided in Frankia clusters found additional support in the ecological lifestyle interaction with host plants and cultural behaviours among the Frankia strains of each cluster. Frankia strains from cluster 1 (except those nodulating Allocasuarina and Casuarina) and cluster 3 are globally distributed in soils irrespective of the presence or absence of compatible host plants .Frankia phylogenetic cluster 2. Host plants include Coriariaceae, Datiscaceae, Dryadoideae (Rosaceae), and Ceanothus (Rhamnaceae) species. Genome sizes in the range of 5.3–5.8 Mb with G + C mol% content of 68.0–70.2%. The type species is Protofrankia coriaria.The genus is defined by the taxonomic elevation of the taxon previously defined as Protofrankia coriaria .Frankia coriaria .The description of Parafrankia .Parafrankia is defined by the taxonomic elevation of the taxon previously defined as Frankia phylogenetic cluster 3. Host plants include members of Elaeagnaceae, Colletieae, Morella, and Gynmnostoma. Genome sizes range from 6.6 to 11.2 Mb with G + C mol% of 69.7–72.3. The type species is Parafrankia elaeagni. In addition, four species can be reclassified as members of the genus. Frankia discariae .Frankia elaeagni (Basonym: elaeagni .Parafrankia elaeagni is the same as that given by F. elaeagni. The type strain is BMG5.12T (= DSM 46783T = CECT 9031T).The description of Parafrankia discariae .Frankia discariae (Basonym: iscariae .Parafrankia discariae is the same as that given by F. discariae. The type strain is BCU110501T (= DSM 46785T = CECT 9042T).The description of Parafrankia irregularis .Frankia irregularis (Basonym: egularis .Parafrankia irregularis is the same as that given by F. irregularis. The type strain is G2T (= DSM 45899T = CECT 9038T).The description of Parafrankia soli .Frankia soli (Basonym: kia soli .Parafrankia soli comb. nov. is the same as that given by F. soli. The type strain is CjT (= DSM 100623T = CECT 9041T = NRRL B-16219T).The description of Parafrankia colletiae .Frankia colletiae (Basonym: olletiae .Parafrankia colletiae comb. nov. is the same as that given by F. colletiae. The type strain is Cc1.17T (= DSM 43829T = CECT 9313T).The description of Pseudofrankia .Pseudofrankia gen. nov. is defined by the taxonomic elevation of the taxon previously defined as Frankia phylogenetic cluster 4. Members of the genus have been isolated from actinorhizal root nodules and are non-infective and/or non-nitrogen-fixing taxa. The size range of the genomes is 6.6–9.9 Mb with 71.2–72.3 of G + C mol%. The type species is Pseudofrankia inefficax. In addition, two other species can be reclassified as members of the genus. Frankia asymbiotica  should be named Pseudofrankia asymbiotica and Pseudofrankia saprophytica, respectively.mbiotica  and F. sPseudofrankia inefficax .Frankia inefficax (Basonym: nefficax .Pseudofrankia inefficax comb. nov. is the same as that given by F. inefficax. The type strain is EuI1cT (=DSM 45817T = CECT 9037T).The description of Pseudofrankia asymbiotica .Frankia asymbiotica (Basonym: mbiotica .Pseudofrankia asymbiotica comb. nov. is the same as that given by F. asymbiotica. The type strain is M16386T (= DSM 100626T = CECT 9040T = NRRL B-16386T).The description of Pseudofrankia saprophytica .Frankia saprophytica (Basonym: ophytica .Pseudofrankia saprophytica comb. nov. is the same as that given by F. saprophytica. The type strain is CN3T (=DSM 105290T = CECT 9314T).The description of The original contributions presented in this study are included in the article/MG conceived the study, performed the analyses, and wrote the manuscript.


Trifolium pratense L.) is a diploid perennial temperate legume with 14 chromosomes (2n = 14) native to Europe and West Asia, with high nutritional and economic value. It is a very important forage grass and is widely grown in marine climates, such as the United States and Sweden. Genetic research and molecular breeding are limited by the lack of high-quality reference genomes. In this study, we used Illumina, PacBio HiFi, and Hi-C to obtain a high-quality chromosome-scale red clover genome and used genome annotation results to analyze evolutionary relationships among related species.Red clover (Trifolium medium and distantly related to Glycine max, Vigna radiata, Medicago truncatula, and Cicer arietinum among legumes. Analyses of gene family expansions and contractions and forward gene selection revealed gene families and genes related to environmental stress resistance and energy metabolism.The red clover genome obtained by PacBio HiFi assembly sequencing was 423 M. The assembly quality was the highest among legume genome assemblies published to date. The contig N50 was 13 Mb, scaffold N50 was 55 Mb, and BUSCO completeness was 97.9%, accounting for 92.8% of the predicted genome. Genome annotation revealed 44,588 gene models with high confidence and 52.81% repetitive elements in red clover genome. Based on a comparison of genome annotation results, red clover was closely related to We report a high-quality de novo genome assembly for the red clover at the chromosome level, with a substantial improvement in assembly quality over those of previously published red clover genomes. These annotated gene models can provide an important resource for molecular genetic breeding and legume evolution studies. Furthermore, we analyzed the evolutionary relationships among red clover and closely related species, providing a basis for evolutionary studies of clover leaf and legumes, genomics analyses of forage grass, the improvement of agronomic traits.The online version contains supplementary material available at 10.1186/s12870-022-03707-5. Trifolium pratense L.)  native to Europe and West Asia. It is not only inexpensive and rich in nutritional value but also contains a crude protein content of about 20%, with dry matter digestibility of about 70%, making it highly palatable and easily eaten by animals   (37.6%) . The Ill (37.6%)  of 97.9%Hi-C is a high-throughput chromosome conformation capture technology. Taking the entire nucleus as the research object, this approach fixes and captures the interacting parts of the chromosome, followed by high-throughput sequencing to evaluate the spatial distribution of chromatin DNA throughout the genome and to obtain high-resolution chromosomal regulatory elements from positional relationships , 37. In Gene functions in the genome are inferred by computational homology-based alignments and the prediction of repeat sequences. In this study, we identified miniature inverted-repeat transposable elements (MITEs) and long terminal repeat (LTR) transposable elements. Structural features were used for prediction, and these elements accounted for 52.81 and 30.01% of the total sequences, respectively. LTR-retrotransposons classified as Copia and Gypsy accounted for 11.26 and 7.70%, respectively, and 7605 simple repeats were found in the assembled genome. In addition, 16,227 ncRNAs were found and included 13 types.Similarly, 44,588 high-confidence gene models and 46,089 transcripts were obtained using RNA-seq and de novo prediction strategies after removing the gene models containing early stop codons and frameshifts . The genMedicago truncatula (MtrunA17r5.0-ANR from NCBI), Trifolium medium (ASM349008v1 from NCBI), Vigna radiate (ver6 from NCBI), Cicer arietinum (ASM33114v1 from NCBI), and Glycine max (v4.0 from NCBI). Among these, soybean had the largest genome (1012 Mb) [T. meduium assembly had the largest number of genes (119102), C. arietinum the fewest (28772), and the other three closely related species had similar gene counts and average CDS lengths  , which wT. medium had the most gene families (5230). As visualized by a Venn diagram, 6602 gene families were shared by all species  as the outgroup [G. max, V. radiata, M. truncatula, T. medium, and C. arietinum to form a monophyletic group. Red clover was most closely related to T. medium, with an estimated divergence time of about 12 million years ago. The collinearity of several closely related species was then evaluated, revealing that red clover and M. truncatula show a certain degree of synteny  events are important indicators of plant evolution and are considered to be the driving force behind plant adaptation to various environments . Using dely Fig. c. In add.75 Fig. d.Genetic and genomic data for leguminous plants with excellent agronomic traits are important resources for the study of genetics, breeding, and functional omics. In this study, we assembled a high-quality diploid genome for a widely important forage crop, the autodiploid red clover. A highly contiguous and complete reference genome is necessary for detailed population genetics analyses and experimental studies. The new genomic data contribute to the legume genome resource bank and provide a good reference for further research on other crops in the clover genus. By combining state-of-the-art technologies , we generated a representative red clover diploid genome. Compared with the previously reported red clover reference genome, the continuity and completeness of the newly assembled red clover genome showed a high quality: 13 Mbp contig N50, 55 Mb scaffold N50, and 97.9% BUSCO score. The assembly result was high-quality in comparison with legume genomes published to date. Notably, after combining high-throughput sequencing and Hi-C scaffolding, the total sequence length across all seven chromosomes was 412 Mbp, which was very similar to the size of the assembled genome (423 Mb). Genome annotation revealed 44,588 genes with high confidence models, providing an important resource for molecular breeding and evolutionary studies.Trifolium species arose after the differentiation of G. max, V. radiata, M. truncatula, and C. arietinum, followed by the divergence of red clover and T. medium. Red clover and Medicago truncatula showed good genomic collinearity and were closely related based on the phylogeny and sequence similarity. The genome of red clover will help to clarify the evolutionary processes shaping legume species.Red clover belongs to the legume family, and its evolutionary history is not well-understood. Our analyses of gene family expansion and contraction and positive selection revealed the molecular basis underlying survival under geographical environment and climate change as well as its excellent agronomic traits. The genetic information provides very important resources for future research on legume improvement and stress-resistant species. According to a phylogenetic analysis, We report a high-quality chromosomal-level red clover genome assembled using third-generation HiFi sequencing. The newly generated genome has the highest coverage and integrity among published legume genomes. This study provides an excellent genetic resource for molecular breeding and the improvement of legumes and provides an important basis for research on the evolution of legumes.For genomic DNA sequencing, the leaves samples of well-grown from single red clover were collected by a professional graduate student and were collected into vacutainer tubes. Red clover (2n = 14) was grown in a light incubator at the Grassland Agri-husbandry Research Center. The study followed ethics norms and was in compliance with Chinese and international regulations.G = Knum/Kdepth, where Knum is the number of k-mers, Kdepth is the expected depth of k-mers.The red clover Emerson was chosen as the test plant. Plants were grown in an incubator at the Qingdao Agricultural University in Shandong, China. After the leaves were treated with liquid nitrogen, DNA was extracted using the Tiangen DNA Secure Kit for Genome Sequencing . Genome sequencing was performed by Berry Hekang  using the third-generation PacBio Sequel II assembly sequencing platform. The extracted DNA was used for library preparation and paired-end (PE) sequencing of the library using Illumina NovaSeq , 43, 44.The quality of genomic DNA was checked using a NanoDrop 2000 spectrophotometer. The purified genome was used to construct the SMRTbell library and sequenced using PacBio SMRT technology , 47. TheHiFi reads were assembled using hifiasm, and purge-dups was used to remove hybridized fragments in the contig sequence , 49. A sThe leaf tissue (100 mg) of red clover which was the same individual used in HiFi sequencing. It was soaked in paraformaldehyde, a cell cross-linking agent, for 15 minutes. Glycine was then added to the mixture to stop the chromatin cross-linking reaction, and the treated tissue was collected and frozen in liquid nitrogen. These tissues were then ground into a powder to extract DNA. Biotin-labeled oligonucleotide ends were added during end-repair, and the extracted DNA was subsequently fragmented into 350 bp fragments using a Covaris breaker , 50. TheRepeat sequences were analyzed and predicted using RepeatMasker, MITE Hunter, LTRharvest, LTR Finder, LTR retriever, and RepeatModeler, and MITES and LTR transposable elements were identified using structure-based prediction methods –59. The G. max, V. radiata, M. truncatula, T. medium, and C. arietinum were downloaded. These coding sequences were subjected to Blast (v. 2.2.20) searches against the red clover genome [Except for tandem repeats, all repeat regions were soft-masked and subsequently used for the annotation of protein-coding genes . The codr genome . Homologr genome , 66. Oper genome , GeneMarr genome , Glimmerr genome , and SNAr genome . Predictr genome , 72, andr genome –75. A VeG. max, V. radiata, M. truncatula, T. medium, A. thaliana, and C. arietinum) [M. truncatula-T. pratense (17.23–32.3 Mya), M. truncatula- V. radiata (44.0–74.5 Mya) and G. max-V. radiata (20.7–29.5 Mya) based on available TimeTree (http://timetree.org) [Ks values for all paralogous gene pairs and Ks values of ortholog gene pairs between the genomes of red clover, M. truncatula, and V. radiata were then drawn using Matlab [A collinearity analysis of red clover and closely related species was performed using MCscan with parameters -g 1000 -c 90 -l 200 . Notablyietinum) . First, ietinum) . The Marietinum) , 79, 80.ietinum) . Multiplietinum) , 83. An ietinum) –86. The ietinum) , 88. Theietinum) . After aree.org) . The braree.org) . After aree.org) . CODEML ree.org) . The resree.org) . A densig Matlab .Additional file 1: Table S1. GO, eggNOG, NR, KEGG and SP annotation results.Additional file 2: Table S2. The gene families described (including their GO terms) and their numbers between red clover and the gene family expansion in red clover.Additional file 3: Table S3. The genes in red clover under positive selection were described (including their GO terms) and their numbers.Additional file 4: Table S4. URLs and code of the software.Additional file 5: Figure S1. Red clover and its closely related species synteny analysis. (a) The beginning of NC represents the chromosome of M.truncatula, while the beginning of CHR represents the chromosome of red clover. (b) The beginning of NC represents the chromosome of C.arietinum, while the beginning of CHR represents the chromosome of red clover. (c) The beginning of NC represents the chromosome of G.max, while the beginning of CHR represents the chromosome of red clover. (d) The beginning of NC represents the chromosome of V.radiata, while the beginning of CHR represents the chromosome of red clover.


Pseudomonas aeruginosa isolates from the past decade. All β-lactams and fluoroquinolones demonstrated decreased susceptibilities following breakpoint changes. Enterobacter cloacae experienced the largest average decrease in susceptibility amongst the Enterobacterales at 5.3% and P. aeruginosa experienced an average decrease in susceptibility of 9.3%.We assessed breakpoint changes of 13,101 Enterobacterales and  Pseudomonas aeruginosa. As noted by the CLSI subcommittee on antimicrobial susceptibility testing, a microorganism’s susceptibility to an antimicrobial agent may decrease over time, thus warranting the refinement of MIC breakpoints. Additionally, the new breakpoints were made to better fit MIC distribution patterns emerging in clinical practice.The Clinical and Laboratory Standards Institute (CLSI) is a governing body responsible for establishing minimum inhibitory concentration (MIC) breakpoints. Over the past decade, multiple changes to MIC breakpoints have occurred for both Enterobacterales and  and summarized by Humphries et al. These changes made by CLSI directly affect the susceptibility of antibiotics. Specifically, susceptibilities of β-lactams and fluoroquinolones are of particular concern due to their common use within the inpatient setting.Individual breakpoint changes can be found both on the CLSI website and another demonstrated increases in institutional resistance of 6% for Escherichia coli and Enterobacter cloacae. As bacteria continue to adapt, we must update breakpoints accordingly, otherwise we risk the provision of suboptimal treatment. In this study, we have described the impact of CLSI breakpoint changes on gram-negative organism susceptibilities in the last decade at our academic medical center.Questions remain regarding the quantitative effect of breakpoint changes on institutional susceptibilities. One study demonstrated a decrease in ciprofloxacin susceptibilities of 5% for EnterobacteralesEnterobacter cloacae, Escherichia coli, Klebsiella aerogenes, K. oxytoca, K. pneumoniae, and Pseudomonas aeruginosa between the years 2010 and 2019. We assessed aztreonam, cefepime, ceftazidime, ceftriaxone, ertapenem, and meropenem for the Enterobacterales. Fluoroquinolones were not evaluated because automated panels were unable to determine low enough MICs. We assessed ciprofloxacin, levofloxacin, meropenem and piperacillin-tazobactam for P. aeruginosa. The institutional isolates and their respective MICs were obtained from the institutional antibiogram data set. This data set also stratifies isolates that come from specific intensive care units (ICUs) including the cardiovascular ICU (CVICU), the medical ICU (MICU), and the neurosurgical ICU (NSICU).This single-center retrospective study was conducted at the University of Kentucky Chandler Medical Center. We collected consecutive nonduplicate clinical isolates of Susceptibilities were assessed based upon historic CLSI breakpoints in 2010 as well as the current CLSI breakpoints from the most recent CLSI MIC breakpoints, the 29th edition of document M100, published in 2019. MICs were determined using automated panels in BD Phoenix software . The genus and species of isolates were determined through use of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF). Additionally, if further susceptibility testing was warranted, then an E-test was performed.P < 0.05, was considered statistically significant.Susceptibility differences were calculated by subtracting the new susceptibilities from the old susceptibilities. Statistical analysis was performed utilizing the McNemar test to compare previous susceptibilities to current susceptibilities. P. aeruginosa isolates. The Enterobacterales group consisted of 5,273 E. coli, 1,237. E. cloacae, 471 K. aerogenes, 610 K. oxytoca, and 2,412 K. pneumoniae isolates. Table E. cloacae experienced the largest average change in susceptibility for all antibiotics at 5.3%, followed by K. aerogenes at 3.3%, E. coli at 2.1%, K. pneumoniae at 1.9%, and K. oxytoca at 1.8%. Table E. coli and E. cloacae experiencing statistically significant changes for all antibiotics. Table P. aeruginosa. At Chandler Hospital, there was an average change in susceptibility of 9.3% for P. aeruginosa, with piperacillin-tazobactam demonstrating a 15.4% decrease in susceptibility. All drugs assessed with P. aeruginosa had a statistically significant reduction in susceptibilities , who will accept CLSI breakpoint recommendations after an extensive review process.The decreased susceptibilities make it clear that microbiology laboratories should accept new MIC breakpoints. However, one study assessed the uptake of current CLSI breakpoints by microbiology laboratories in California and found that ∼1 in 3 labs were utilizing out-of-date breakpoints.Enterobacterales. The outdated levofloxacin MIC was a predictor of 30-day mortality, with an odds ratio of 6.05. Additionally, the outdated MIC was associated with the emergence of resistance, 25% versus 7.5%.Although our study has demonstrated decreased susceptibilities, there is no correlation with clinical outcomes. Another study assessed clinical outcomes by determining mortality associated with previous and current levofloxacin breakpoints with P. aeruginosa at our institution, both hospital-wide and in intensive care units. Although the impact was less for Enterobacterales isolates, ertapenem, ceftriaxone, and cefepime demonstrated significant susceptibility changes. Understanding and evaluating the impact of the breakpoint changes is of paramount importance. Institutions should ensure that their breakpoints are up to date to allow for the most optimized treatment.In conclusion, changes in breakpoints had a significant impact on the susceptibility of all antimicrobials for