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Abstract Background Cupriavidus strain STM 6070 was isolated from nickel-rich soil collected near Koniambo massif, New Caledonia, using the invasive legume trap host Mimosa pudica. STM 6070 is a heavy metal-tolerant strain that is highly effective at fixing nitrogen with M. pudica. Here we have provided an updated taxonomy for STM 6070 and described salient features of the annotated genome, focusing on heavy metal resistance (HMR) loci and heavy metal efflux (HME) systems. Results The 6,771,773 bp high-quality-draft genome consists of 107 scaffolds containing 6118 protein-coding genes. ANI values show that STM 6070 is a new species of Cupriavidus. The STM 6070 symbiotic region was syntenic with that of the M. pudica-nodulating Cupriavidus taiwanensis LMG 19424T. In contrast to the nickel and zinc sensitivity of C. taiwanensis strains, STM 6070 grew at high Ni2+ and Zn2+ concentrations. The STM 6070 genome contains 55 genes, located in 12 clusters, that encode HMR structural proteins belonging to the RND, MFS, CHR, ARC3, CDF and P-ATPase protein superfamilies. These HMR molecular determinants are putatively involved in arsenic (ars), chromium (chr), cobalt-zinc-cadmium (czc), copper (cop, cup), nickel (nie and nre), and silver and/or copper (sil) resistance. Seven of these HMR clusters were common to symbiotic and non-symbiotic Cupriavidus species, while four clusters were specific to STM 6070, with three of these being associated with insertion sequences. Within the specific STM 6070 HMR clusters, three novel HME-RND systems (nieIC cep nieBA, czcC2B2A2, and hmxB zneAC zneR hmxS) were identified, which constitute new candidate genes for nickel and zinc resistance. Conclusions STM 6070 belongs to a new Cupriavidus species, for which we have proposed the name Cupriavidus neocaledonicus sp. nov.. STM6070 harbours a pSym with a high degree of gene conservation to the pSyms of M. pudica-nodulating C. taiwanensis strains, probably as a result of recent horizontal transfer. The presence of specific HMR clusters, associated with transposase genes, suggests that the selection pressure of the New Caledonian ultramafic soils has driven the specific adaptation of STM 6070 to heavy-metal-rich soils via horizontal gene transfer.

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.