The complete genome sequence of the \u3ci\u3eArabidopsis\u3c/i\u3e and tomato pathogen \u3ci\u3ePseudomonas syringae\u3c/i\u3e pv. \u3ci\u3etomato\u3c/i\u3e DC3000

We report the complete genome sequence of the model bacterial pathogen Pseudomonas syringae pathovar tomato DC3000 (DC3000), which is pathogenic on tomato and Arabidopsis thaliana. The DC3000 genome (6.5 megabases) contains a circular chromosome and two plasmids, which collectively encode 5,763 ORFs. We identified 298 established and putative virulence genes, including several clusters of genes encoding 31 confirmed and 19 predicted type III secretion system effector proteins. Many of the virulence genes were members of paralogous families and also were proximal to mobile elements, which collectively comprise7%of the DC3000 genome. The bacterium possesses a large repertoire of transporters for the acquisition of nutrients, particularly sugars, as well as genes implicated in attachment to plant surfaces. Over 12% of the genes are dedicated to regulation, which may reflect the need for rapid adaptation to the diverse environments encountered during epiphytic growth and pathogenesis. Comparative analyses confirmed a high degree of similarity with two sequenced pseudomonads, Pseudomonas putida and Pseudomonas aeruginosa, yet revealed 1,159 genes unique to DC3000, of which 811 lack a known function. Includes published article and additional supporting materials

Assessment of disease progression in dysferlinopathy. A 1-year cohort study

Jain COS Consortium.[Objective] To assess the ability of functional measures to detect disease progression in dysferlinopathy over 6 months and 1 year.[Methods] One hundred ninety-three patients with dysferlinopathy were recruited to the Jain Foundation's International Clinical Outcome Study for Dysferlinopathy. Baseline, 6-month, and 1-year assessments included adapted North Star Ambulatory Assessment (a-NSAA), Motor Function Measure (MFM-20), timed function tests, 6-minute walk test (6MWT), Brooke scale, Jebsen test, manual muscle testing, and hand-held dynamometry. Patients also completed the ACTIVLIM questionnaire. Change in each measure over 6 months and 1 year was calculated and compared between disease severity (ambulant [mild, moderate, or severe based on a-NSAA score] or nonambulant [unable to complete a 10-meter walk]) and clinical diagnosis.[Results] The functional a-NSAA test was the most sensitive to deterioration for ambulant patients overall. The a-NSAA score was the most sensitive test in the mild and moderate groups, while the 6MWT was most sensitive in the severe group. The 10-meter walk test was the only test showing significant change across all ambulant severity groups. In nonambulant patients, the MFM domain 3, wrist flexion strength, and pinch grip were most sensitive. Progression rates did not differ by clinical diagnosis. Power calculations determined that 46 moderately affected patients are required to determine clinical effectiveness for a hypothetical 1-year clinical trial based on the a-NSAA as a clinical endpoint.[Conclusion] Certain functional outcome measures can detect changes over 6 months and 1 year in dysferlinopathy and potentially be useful in monitoring progression in clinical trials.[ClinicalTrials.gov identifier] NCT01676077.The estimated US $4 million needed to fund this study is being provided by the Jain Foundation. The John Walton Centre Muscular Dystrophy Research Centre is part of the MRC Centre for Neuromuscular Diseases (grant MR/K000608/1)

Complete genome sequence of Caulobacter crescentus

The complete genome sequence of Caulobacter crescentus was determined to be 4,016,942 base pairs in a single circular chromosome encoding 3,767 genes. This organism, which grows in a dilute aquatic environment, coordinates the cell division cycle and multiple cell differentiation events. With the annotated genome sequence, a full description of the genetic network that controls bacterial differentiation, cell growth, and cell cycle progression is within reach. Two-component signal transduction proteins are known to play a significant role in cell cycle progression. Genome analysis revealed that the C. crescentus genome encodes a significantly higher number of these signaling proteins (105) than any bacterial genome sequenced thus far. Another regulatory mechanism involved in cell cycle progression is DNA methylation. The occurrence of the recognition sequence for an essential DNA methylating enzyme that is required for cell cycle regulation is severely limited and shows a bias to intergenic regions. The genome contains multiple clusters of genes encoding proteins essential for survival in a nutrient poor habitat. Included are those involved in chemotaxis, outer membrane channel function, degradation of aromatic ring compounds, and the breakdown of plant-derived carbon sources, in addition to many extracytoplasmic function sigma factors, providing the organism with the ability to respond to a wide range of environmental fluctuations. C. crescentus is, to our knowledge, the first free-living α-class proteobacterium to be sequenced and will serve as a foundation for exploring the biology of this group of bacteria, which includes the obligate endosymbiont and human pathogen Rickettsia prowazekii, the plant pathogen Agrobacterium tumefaciens, and the bovine and human pathogen Brucella abortus

Evaluation of cell-free DNA approaches for multi-cancer early detection

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test. [Display omitted] •Clinical LOD is a useful benchmark to assess cfDNA-based test performance•cTAF accounts for cfDNA cancer signal variation across cancer types and stages•cfDNA methylation was the most promising genomic feature for cancer signal detection•The results informed the development of a cfDNA-based multi-cancer early detection test Jamshidi et al. compare several approaches for circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) tests. A whole-genome methylation-based approach has the best performance among those evaluated. In addition, they define a metric—clinical limit of detection (LOD)—based on tumor fraction to enable future comparison of cfDNA-based tests