Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

The 5300-year-old Helicobacter pylori genome of the Iceman

Abstract: The stomach bacterium Helicobacter pylori is one of the most prevalent human pathogens. It has dispersed globally with its human host, resulting in a distinct phylogeographic pattern that can be used to reconstruct both recent and ancient human migrations. The extant European population of H. pylori is known to be a hybrid between Asian and African bacteria, but there exist different hypotheses about when and where the hybridization took place, reflecting the complex demographic history of Europeans. Here, we present a 5300-year-old H. pylori genome from a European Copper Age glacier mummy. The “Iceman” H. pylori is a nearly pure representative of the bacterial population of Asian origin that existed in Europe before hybridization, suggesting that the African population arrived in Europe within the past few thousand years.

Molecular architecture of the kinetochore-microtubule attachment site is conserved between point and regional centromeres

Abstract: Point and regional centromeres specify a unique site on each chromosome for kinetochore assembly. The point centromere in budding yeast is a unique 150-bp DNA sequence, which supports a kinetochore with only one microtubule attachment. In contrast, regional centromeres are complex in architecture, can be up to 5 Mb in length, and typically support many kinetochore-microtubule attachments. We used quantitative fluorescence microscopy to count the number of core structural kinetochore protein complexes at the regional centromeres in fission yeast and Candida albicans. We find that the number of CENP-A nucleosomes at these centromeres reflects the number of kinetochore-microtubule attachments instead of their length. The numbers of kinetochore protein complexes per microtubule attachment are nearly identical to the numbers in a budding yeast kinetochore. These findings reveal that kinetochores with multiple microtubule attachments are mainly built by repeating a conserved structural subunit that is equivalent to a single microtubule attachment site.

Clinical Significance of CTNNB1 Mutation and Wnt Pathway Activation in Endometrioid Endometrial Carcinoma

Abstract: Endometrial carcinoma (EC) is the most common gynecological cancer in the western world, with approximately 49560 EC cases estimated in the United States in 2013 (1). In contrast to many other cancers, the incidence of endometrial cancer is increasing, likely because of the fact that obesity is a major risk factor for EC (2). This increased incidence is also associated with increased mortality, as the deaths from EC in the US have increased dramatically, from 2900 deaths in 1987 to 8190 deaths in 2013, a 2.8x increase over 25 years. Endometrial cancer is clinically categorized into two subtypes that help to determine risk of recurrence and guide treatment (3). Type I carcinomas, which account for the majority of cases (70–80%), are typically associated with a good prognosis, early stage at diagnosis, estrogen signaling, obesity, and low-grade endometrioid histology (EEC). Type II cancers are characterized by high stage at time of diagnosis, nonendometrioid histology, and poor prognosis. Differences in molecular aberrations between these two types of EC have been previously reported (3–5). Clustering analysis of all EC samples together commonly segregates cases based largely on differences between serous vs endometrioid histologies (3,6). A more defined tumor classification for EEC, the largest histological group of EC, is needed. Whereas type II EC invariably exhibits poor prognosis, the clinical course for type I EC can be unpredictable (7). Overall outcomes for EEC vary with International Federation of Gynecology and Obstetrics (FIGO) stage and tumor grade, but individual patients with endometrioid carcinomas have statistically significantly different clinical courses and show different responses to therapy, despite having tumors with similar histopathology (8). Histology is therefore insufficient to predict clinical course for EEC, and presently no clinical laboratory assay addresses this unmet need. We propose that molecular subtyping of EEC may inform diagnosis and prognosis of women with low grade, early-stage disease by identifying molecular attributes defining EEC case patients at risk for a more aggressive clinical course; patients with such tumors may benefit from more aggressive management. We performed new analyses of whole-exome and RNA sequencing, RPPA profiling, and clinical data archived by TCGA for more than 200 EEC case patients. Reanalysis of the TCGA data of EEC samples and excluding those with serous histology identified four transcriptome subtypes in EEC that exhibited distinct clinicopathologic characteristics and mutation spectra. One of the subtypes identifies an aggressive variant of type I EEC previously not recognized.

Blood metabolome predicts gut microbiome α-diversity in humans.

Abstract: Depleted gut microbiome α-diversity is associated with several human diseases, but the extent to which this is reflected in the host molecular phenotype is poorly understood. We attempted to predict gut microbiome α-diversity from ~1,000 blood analytes (laboratory tests, proteomics and metabolomics) in a cohort enrolled in a consumer wellness program (N = 399). Although 77 standard clinical laboratory tests and 263 plasma proteins could not accurately predict gut α-diversity, we found that 45% of the variance in α-diversity was explained by a subset of 40 plasma metabolites (13 of the 40 of microbial origin). The prediction capacity of these 40 metabolites was confirmed in a separate validation cohort (N = 540) and across disease states, showing that our findings are robust. Several of the metabolite biomarkers that are reported here are linked with cardiovascular disease, diabetes and kidney function. Associations between host metabolites and gut microbiome α-diversity were modified in those with extreme obesity (body mass index ≥ 35), suggesting metabolic perturbation. The ability of the blood metabolome to predict gut microbiome α-diversity could pave the way to the development of clinical tests for monitoring gut microbial health. Multiomics reveals that almost half of gut microbiome diversity in humans can be explained by 40 blood metabolites.