Scott Steelman
Broad Institute
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Publication
Featured researches published by Scott Steelman.
Proceedings of the National Academy of Sciences of the United States of America | 2012
Yonatan H. Grad; Marc Lipsitch; Michael Feldgarden; Harindra Arachchi; Gustavo C. Cerqueira; Michael C. Fitzgerald; Paul A. Godfrey; Brian J. Haas; Cheryl Murphy; Carsten Russ; Sean Sykes; Bruce J. Walker; Jennifer R. Wortman; Qiandong Zeng; Amr Abouelleil; James Bochicchio; Sara Chauvin; Timothy DeSmet; Sharvari Gujja; Caryn McCowan; Anna Montmayeur; Scott Steelman; Jakob Frimodt-Møller; Andreas Petersen; Carsten Struve; Karen A. Krogfelt; Edouard Bingen; François-Xavier Weill; Eric S. Lander; Chad Nusbaum
The degree to which molecular epidemiology reveals information about the sources and transmission patterns of an outbreak depends on the resolution of the technology used and the samples studied. Isolates of Escherichia coli O104:H4 from the outbreak centered in Germany in May–July 2011, and the much smaller outbreak in southwest France in June 2011, were indistinguishable by standard tests. We report a molecular epidemiological analysis using multiplatform whole-genome sequencing and analysis of multiple isolates from the German and French outbreaks. Isolates from the German outbreak showed remarkably little diversity, with only two single nucleotide polymorphisms (SNPs) found in isolates from four individuals. Surprisingly, we found much greater diversity (19 SNPs) in isolates from seven individuals infected in the French outbreak. The German isolates form a clade within the more diverse French outbreak strains. Moreover, five isolates derived from a single infected individual from the French outbreak had extremely limited diversity. The striking difference in diversity between the German and French outbreak samples is consistent with several hypotheses, including a bottleneck that purged diversity in the German isolates, variation in mutation rates in the two E. coli outbreak populations, or uneven distribution of diversity in the seed populations that led to each outbreak.
Genome Biology | 2010
Niall J. Lennon; Robert E. Lintner; Scott Anderson; Pablo Alvarez; Andrew Barry; William Bennett Brockman; Riza Daza; Rachel L. Erlich; Georgia Giannoukos; Lisa Green; Andrew Hollinger; Cindi A. Hoover; David B. Jaffe; Frank Juhn; Danielle McCarthy; Danielle Perrin; Karen Ponchner; Taryn L Powers; Kamran Rizzolo; Dana Robbins; Elizabeth Ryan; Carsten Russ; Todd Sparrow; John Stalker; Scott Steelman; Michael Weiand; Andrew Zimmer; Matthew R. Henn; Chad Nusbaum; Robert Nicol
We present an automated, high throughput library construction process for 454 technology. Sample handling errors and cross-contamination are minimized via end-to-end barcoding of plasticware, along with molecular DNA barcoding of constructs. Automation-friendly magnetic bead-based size selection and cleanup steps have been devised, eliminating major bottlenecks and significant sources of error. Using this methodology, one technician can create 96 sequence-ready 454 libraries in 2 days, a dramatic improvement over the standard method.
Nature Genetics | 2013
Andrew Kirby; Andreas Gnirke; David B. Jaffe; Veronika Barešová; Nathalie Pochet; Brendan Blumenstiel; Chun Ye; Daniel Aird; Christine Stevens; James Robinson; Moran N. Cabili; Irit Gat-Viks; Edward Kelliher; Riza Daza; Matthew DeFelice; Helena Hůlková; Jana Sovová; Petr Vylet’al; Corinne Antignac; Mitchell Guttman; Robert E. Handsaker; Danielle Perrin; Scott Steelman; Snaevar Sigurdsson; Steven J. Scheinman; Carrie Sougnez; Kristian Cibulskis; Melissa Parkin; Todd Green; Elizabeth Rossin
Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (∼1.5–5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.
bioRxiv | 2018
Arnon Arazi; Deepak A. Rao; Celine C. Berthier; Anne Davidson; Yanyan Liu; Paul J. Hoover; Adam Chicoine; Thomas Eisenhaure; A. Helena Jonsson; Shuqiang Li; David J. Lieb; Edward P. Browne; Akiko Noma; Danielle Sutherby; Scott Steelman; Dawn E. Smilek; Patti Tosta; William Apruzzese; Elena Massarotti; Maria Dall'Era; Meyeon Park; Diane L. Kamen; Richard A. Furie; Fernanda Payan-Schober; Jill P. Buyon; Michelle Petri; Chaim Putterman; Kenneth C. Kalunian; E. Steve Woodle; James A. Lederer
Lupus nephritis is a potentially fatal autoimmune disease, whose current treatment is ineffective and often toxic. To gain insights into disease mechanisms, we analyzed kidney samples from lupus nephritis patients and healthy controls using single-cell RNA-seq. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid, T, NK and B cells, demonstrating both pro-inflammatory and resolving responses. We found evidence of local activation of B cells correlated with an age-associated B cell signature, and of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, pointing to potential therapeutic targets. Gene expression of immune cells in urine and kidney was highly correlated, suggesting urine may be a surrogate for kidney biopsies. Our results provide a first comprehensive view of the complex network of leukocytes active in lupus nephritis kidneys.
Nature Genetics | 2018
Andrew O. Giacomelli; Xiaoping Yang; Robert E. Lintner; James M McFarland; Marc Duby; Jaegil Kim; Thomas P. Howard; David Y. Takeda; Seav Huong Ly; Eejung Kim; Hugh S. Gannon; Brian Hurhula; Ted Sharpe; Amy Goodale; Briana Fritchman; Scott Steelman; Francisca Vazquez; Aviad Tsherniak; Andrew J. Aguirre; John G. Doench; Federica Piccioni; Charles W. M. Roberts; Matthew Meyerson; Gad Getz; Cory M. Johannessen; David E. Root; William C. Hahn
Unlike most tumor suppressor genes, the most common genetic alterations in tumor protein p53 (TP53) are missense mutations1,2. Mutant p53 protein is often abundantly expressed in cancers and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models3–8. To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53 wild-type and null cell lines. We found that loss or dominant-negative inhibition of wild-type p53 function reliably enhanced cellular fitness. By integrating these data with the Catalog of Somatic Mutations in Cancer (COSMIC) mutational signatures database9,10, we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.Large-scale loss-of-function screens and TP53 saturation mutagenesis screens in human cancer cell lines suggest that mutational processes combine with phenotypic selection to shape the landscape of somatic mutations at the TP53 locus.
Blood | 2018
Zhuting Hu; Annabelle Anandappa; Jing Sun; Jintaek Kim; Donna E. Leet; David J. Bozym; Christina Chen; Louise Williams; Sachet A. Shukla; Wandi Zhang; Diana Tabbaa; Scott Steelman; Oriol Olive; Kenneth J. Livak; Hiroyuki Kishi; Atsushi Muraguchi; Indira Guleria; Jonathan Stevens; William J. Lane; Ute E. Burkhardt; Edward F. Fritsch; Donna Neuberg; Patrick A. Ott; Derin B. Keskin; Nir Hacohen; Catherine J. Wu
Recent studies have highlighted the promise of targeting tumor neoantigens to generate potent antitumor immune responses and provide strong motivation for improving our understanding of antigen-T-cell receptor (TCR) interactions. Advances in single-cell sequencing technologies have opened the door for detailed investigation of the TCR repertoire, providing paired information from TCRα and TCRβ, which together determine specificity. However, a need remains for efficient methods to assess the specificity of discovered TCRs. We developed a streamlined approach for matching TCR sequences with cognate antigen through on-demand cloning and expression of TCRs and screening against candidate antigens. Here, we first demonstrate the systems capacity to identify viral-antigen-specific TCRs and compare the functional avidity of TCRs specific for a given antigen target. We then apply this system to identify neoantigen-specific TCR sequences from patients with melanoma treated with personalized neoantigen vaccines and characterize functional avidity of neoantigen-specific TCRs. Furthermore, we use a neoantigen-prediction pipeline to show that an insertion-deletion mutation in a putative chronic lymphocytic leukemia (CLL) driver gives rise to an immunogenic neoantigen mut-MGA, and use this approach to identify the mut-MGA-specific TCR sequence. This approach provides a means to identify and express TCRs, and then rapidly assess antigen specificity and functional avidity of a reconstructed TCR, which can be applied for monitoring antigen-specific T-cell responses, and potentially for guiding the design of effective T-cell-based immunotherapies.
Nature Biotechnology | 2015
Sachet A. Shukla; Michael S. Rooney; Mohini Rajasagi; Grace Tiao; Philip M. Dixon; Michael S. Lawrence; Jonathan Stevens; William J. Lane; Jamie L. DellaGatta; Scott Steelman; Carrie Sougnez; Kristian Cibulskis; Adam Kiezun; Nir Hacohen; Vladimir Brusic; Catherine J. Wu; Gad Getz
Archive | 2011
Andreas Gnirke; Robert Nicol; Louise Williams; Maura Costello; Scott Steelman
Archive | 2015
Scott Steelman; Robert Nicol
Archive | 2013
Scott Steelman; Robert Nicol