The genus Thiomargarita includes the world's largest bacteria. But as uncultured organisms, their physiology, metabolism, and basis for their gigantism are not well understood. Thus, a genomics approach, applied to a single Candidatus Thiomargarita nelsonii cell was employed to explore the genetic potential of one of these enigmatic giant bacteria. The Thiomargarita cell was obtained from an assemblage of budding Ca. T. nelsonii attached to a provannid gastropod shell from Hydrate Ridge, a methane seep offshore of Oregon, USA. Here we present a manually curated genome of Bud S10 resulting from a hybrid assembly of long Pacific Biosciences and short Illumina sequencing reads. With respect to inorganic carbon fixation and sulfur oxidation pathways, the Ca. T. nelsonii Hydrate Ridge Bud S10 genome was similar to marine sister taxa within the family Beggiatoaceae. However, the Bud S10 genome contains genes suggestive of the genetic potential for lithotrophic growth on arsenite and perhaps hydrogen. The genome also revealed that Bud S10 likely respires nitrate via two pathways: a complete denitrification pathway and a dissimilatory nitrate reduction to ammonia pathway. Both pathways have been predicted, but not previously fully elucidated, in the genomes of other large, vacuolated, sulfur-oxidizing bacteria. Surprisingly, the genome also had a high number of unusual features for a bacterium to include the largest number of metacaspases and introns ever reported in a bacterium. Also present, are a large number of other mobile genetic elements, such as insertion sequence (IS) transposable elements and miniature inverted-repeat transposable elements (MITEs). In some cases, mobile genetic elements disrupted key genes in metabolic pathways. For example, a MITE interrupts hupL, which encodes the large subunit of the hydrogenase in hydrogen oxidation. Moreover, we detected a group I intron in one of the most critical genes in the sulfur oxidation pathway, dsrA. The dsrA group I intron also carried a MITE sequence that, like the hupL MITE family, occurs broadly across the genome. The presence of a high degree of mobile elements in genes central to Thiomargarita's core metabolism has not been previously reported in free-living bacteria and suggests a highly mutable genome.

In vitro evolution experiments have long been used to evaluate the roles of RNA in both modern and ancient biology, and as a tool for biotechnology applications. The conditions under which these experiments have been conducted, however, do not reflect the range of cellular environments in modern biology or our understanding of chemical environments on the early earth, when the atmosphere and oceans were largely anoxic and soluble Fe2+ was abundant. To test the impact of environmental factors relevant to RNA's potential role in the earliest forms of life, we evolved populations of self-cleaving ribozymes in an anoxic atmosphere with varying pH in the presence of either Fe2+ or Mg2+. Populations evolved under these different conditions are dominated by different sequences and secondary structures, demonstrating global differences in the underlying fitness landscapes. Comparisons between evolutionary outcomes and catalytic activities also indicate that Mg2+ can readily take the place of Fe2+ in supporting the catalysis of RNA cleavage at neutral pH, but not at lower pH. These results highlight the importance of considering the specific environments in which functional biopolymers evolve when evaluating their potential roles in the origin of life, extant biology, or biotechnology.

Background: Patient-derived Xenograft (PDX) models are being widely used in preclinical studies to identify biomarkers of drug response and to enhance our understanding of cancer biology. Since patients with metastatic cancer have both intra-tumor and inter-site heterogeneity, PDX models generated from different tumor sites may provide a way to study tumor heterogeneity. Characterization of the genomic landscape in these models may also provide better insights into treatment response or resistance. It is rare to have multiple PDX models generated from a single patient over multiple time points during a treatment trajectory. Here, we report the genomic profiles of PDX models generated from 4 distinct tissue specimens over a 7-month period from a patient with metastatic colon adenocarcinoma. The first 2 PDX models were generated from circulating tumor cells (CTCs) and a liver biopsy prior to treatment with a combination pan-AKT + MEK inhibitor regimen. A third PDX model was generated from a liver biopsy while on-treatment and a fourth from an adrenal gland resection at progression. Clinically, all reported metastatic sites, except the adrenal gland, responded to the combination therapy. Results: Genomic characterization of the specimens obtained from these 4 PDX models led to the following observations: 1) PIK3CA E545K and KRAS G12D are present in all the specimens tested for all 4 models and are likely truncal driver mutations; 2) exclusive inter-model SNVs (single nucleotide variants) were identified, and may be model-specific variants representing inter-site heterogeneity in the patient; 3) variants involved in known resistance mechanisms to MEK inhibition were not present in any specimens; 4) overexpression of AKT3 has been reported as a resistance mechanism to a pan-AKT inhibitor and was observed in the adrenal tissue from the patient but not in any other PDX model derived from this patient; 5) intra-model and inter-model heterogeneity in whole genome CNV (copy number variant) profiles was observed between individual PDXs obtained from the pre-treatment CTC-derived model and the on-treatment liver biopsy model. Interestingly, one of the PDXs from the CTC-derived model presented a sub-clonal tumor fraction closely related to the on-treatment liver biopsy model. The multiple inter-model CNV profiles in the liver biopsy derived PDX models represent temporal heterogeneity within a tissue. Conclusions: We observed genomic heterogeneity in PDXs generated from specimens from a patient with metastatic colon adenocarcinoma. Both truncal and sub-clonal variants were identified representing various tumor fractions in these models. This case study illustrates how genomic profiling of multiple tumor sites at different times during course of treatment can provide insight into the complexity of tumor heterogeneity and tumor evolution in patients with metastatic disease. Citation Format: Biswajit Das, Chris Karlovich, Corrine E. Camalier, Rajesh Patidar, Li Chen, Vivekananda Datta, William D. Walsh, Sean P. McDermott, Tomas Vilimas, Palmer Fliss, Justine N. McCutcheon, Amanda Peach, Michelle Ahalt-Gottholm, Carrie Bonomi, Kelly Dougherty, John Carter, Shivaani Kummar, Yvonne A. Evrard, Melinda G. Hollingshead, Paul M. Williams, James H. Doroshow. PDX models generated from a patient with metastatic colon adenocarcinoma display both spatial and temporal tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1039.