Ralstonia solanacearum species complex (RSSC) is a genetically diverse group of plant pathogens, yet genomic data from South America remain limited. Here, we characterize 13 RSSC strains isolated from tomato, pepper, and eggplant in northeastern Argentina. Phylogenetic analysis of the egl marker gene assigned these strains to phylotype IIA and suggested two closely related lineages. Complete genomes (5.63–5.76 Mb) were generated for four representative strains, yielding high-quality (99.94% completeness with f_Burkholderiaceae CheckM markers), closed assemblies with canonical bipartite architecture. Phylogenetic analysis of the egl marker, 49 conserved bacterial genes, and average nucleotide identity (ANI) analyses, consistently assigned one lineage to sequevar IIA-50, forming a coherent and monophyletic group. In contrast, although egl analysis suggested the second lineage was related to one sequevar IIA-38 reference strain, genomic analysis did not support this assignment. Further, the genomic analysis revealed significant genomic distance between the genomes for two sequevar 38 representative strains, supporting a conclusion that sequevar 38 itself was not monophyletic and instead appears paraphyletic. These findings highlight limitations of single-locus classification and support genome-informed refinement of RSSC sub-phylotype taxonomy. Outcome statement: Reports of bacterial wilt disease in Argentina had not yet been published in the international literature although the disease has been long-standing. This study provides complete genome sequences for four Ralstonia solanacearum strains from Northern Argentina and places them within a global phylogenomic framework. The Argentine strains cluster into two closely related phylotype IIA lineages, indicating that bacterial wilt in this regional dataset is associated with genetically similar populations. For clear communication of which strains are present in Northern Argentina, we attempted to classify the lineages to the long-standing sequence variant (sequevar) system for naming R. solanacearum species complex (RSSC) strains. One lineage was confidently assigned to IIA-50 with genomic support that confirmed phylogenetic analysis of the classical genetic marker egl . However, newly available genomes for sequevar reference strains revealed an issue where two distantly related strains are currently recognized as references for sequevars. Overall, these results provide evidence supporting the need for genome-informed refinement of sub-phylotype classification and expand genomic representation of South American RSSC populations. Data summary: Complete genome assemblies and raw reads for INTABV18, INTABV29, INTABV624 and INTABV2657 are deposited to NCBI under the project number PRJNA1407867. The curated dataset of public RSSC genomes is available to users who register a free account on KBase via a KBase narrative ( https://narrative.kbase.us/narrative/189849 ). The narrative described in a living BioRxiv pre-print [1]. Supplemental files such as Figure S1, rectangular versions of all trees (Figure 2 and 3 and S1) and supplementary table S1, S2, S3 and S4 are available on Zenodo at doi.org/10.5281/zenodo.19502890

Ralstonia solanacearum species complex (RSSC) is a genetically diverse group of plant pathogens, yet genomic data from South America remain limited. Here, we characterize 13 RSSC strains isolated from tomato, pepper, and eggplant in northeastern Argentina. Phylogenetic analysis of the egl marker gene assigned these strains to phylotype IIA and suggested two closely related lineages. Complete genomes (5.63–5.76 Mb) were generated for four representative strains, yielding high-quality (99.94% completeness with f_Burkholderiaceae CheckM markers), closed assemblies with canonical bipartite architecture. Phylogenetic analysis of the egl marker, 49 conserved bacterial genes, and average nucleotide identity (ANI) analyses, consistently assigned one lineage to sequevar IIA-50, forming a coherent and monophyletic group. In contrast, although egl analysis suggested the second lineage was related to one sequevar IIA-38 reference strain, genomic analysis did not support this assignment. Further, the genomic analysis revealed significant genomic distance between the genomes for two sequevar 38 representative strains, supporting a conclusion that sequevar 38 itself was not monophyletic and instead appears paraphyletic. These findings highlight limitations of single-locus classification and support genome-informed refinement of RSSC sub-phylotype taxonomy.

The Geometric Pattern Transformation (GPT) has several advantages of use concerning contemporary algorithms that have been duly studied in previous research. Regarding some of its properties, four different but complementary aspects of the GPT are presented in this work. After a brief review of the GPT concept, how tied data are manifested in data sets is shown, to obtain a symmetric representation of the GPT, a linear transformation is performed that regularizes the geometric representation of the GPT and the theoretical relationship between the GPT and the phase-state representation of 1D signals is analyzed and formalized, then the study of the forbidden pattern is easily revealed, obtaining a strong relationship with the stable and unstable fixed points of the logistic equation. Finally, the characterization of colored noises and the application in real world signals taken through experimental procedures is analyzed. With these results, in this work is proposed an advance in the potential applications of the GPT in an integral way in the processing and analysis of data series.

The Virial theorem has been applied with considerable success in various fields of natural sciences. This work proposes an extension of the theorem applied to discrete data series. This application will be called the Virial theorem extension and can be applied to the numerical solution of nonlinear dynamic systems represented by difference equations, such as logistic, discubic and random number generators, the numerical solution of differential equations like the nonlinear double pendulum and a series of pseudorandom numbers and its reciprocals. For this purpose, a coefficient was derived from the discrete Virial formalism. This coefficient can be used to detect when a time series is obtained as the solution of a differential equation, in which case the coefficient is close to 1, and when the data come from other sources, in which case it takes different values. With reference to chaotic dynamic systems, the discrete Virial coefficient shows the feasibility in the detection of a change in behavior, as an alternative to the traditional calculation of Lyapunov exponents, and it is a thousand times faster. The convergence speed of the final value of the discrete Virial coefficient of a dynamic system in a non-chaotic regime is between one and five orders of magnitude greater than in the chaotic regime, thus extending results in non-Hamiltonian systems, previously found by another author in Hamiltonian systems. The results obtained show that the proposal characterizes and distinguishes different types of behavior from the series under study. It also shows great sensitivity to the evolution of the series, even anticipating critical points. The proposed method to construct the discrete Virial extension does not require the existence of a Hamiltonian, which allows its application to a series obtained experimentally or from any differential equation. From a general point of view, this research shows a series of properties that can be reinterpreted in light of the discrete Virial coefficient, providing a novel and versatile tool, given its minimal applicability requirements. For pseudorandom number series, the extension reveals a consistent, quasi-mirror behavior between its kinetic and potential factors, suggesting an underlying structural property.