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Dive into the research topics where Taylor Sittler is active.

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Featured researches published by Taylor Sittler.


Proceedings of the National Academy of Sciences of the United States of America | 2003

Conserved pathways within bacteria and yeast as revealed by global protein network alignment

Brian P. Kelley; Roded Sharan; Richard M. Karp; Taylor Sittler; David E. Root; Brent R. Stockwell; Trey Ideker

We implement a strategy for aligning two protein–protein interaction networks that combines interaction topology and protein sequence similarity to identify conserved interaction pathways and complexes. Using this approach we show that the protein–protein interaction networks of two distantly related species, Saccharomyces cerevisiae and Helicobacter pylori, harbor a large complement of evolutionarily conserved pathways, and that a large number of pathways appears to have duplicated and specialized within yeast. Analysis of these findings reveals many well characterized interaction pathways as well as many unanticipated pathways, the significance of which is reinforced by their presence in the networks of both species.


PLOS ONE | 2010

A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America.

Alexander L. Greninger; Eunice C. Chen; Taylor Sittler; Alex Scheinerman; Nareg Roubinian; Guixia Yu; Edward Y. Kim; Dylan R. Pillai; Cyril Guyard; Tony Mazzulli; Pavel Isa; Carlos F. Arias; John R. Hackett Jr.; Gerald Schochetman; Steve Miller; Patrick Tang; Charles Y. Chiu

Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.


Nature | 2005

The Plasmodium protein network diverges from those of other eukaryotes

Silpa Suthram; Taylor Sittler; Trey Ideker

Plasmodium falciparum is the pathogen responsible for over 90% of human deaths from malaria. Therefore, it has been the focus of a considerable research initiative, involving the complete DNA sequencing of the genome, large-scale expression analyses, and protein characterization of its life-cycle stages. The Plasmodium genome sequence is relatively distant from those of most other eukaryotes, with more than 60% of the 5,334 encoded proteins lacking any notable sequence similarity to other organisms. To systematically elucidate functional relationships among these proteins, a large two-hybrid study has recently mapped a network of 2,846 interactions involving 1,312 proteins within Plasmodium. This network adds to a growing collection of available interaction maps for a number of different organisms, and raises questions about whether the divergence of Plasmodium at the sequence level is reflected in the configuration of its protein network. Here we examine the degree of conservation between the Plasmodium protein network and those of model organisms. Although we find 29 highly connected protein complexes specific to the network of the pathogen, we find very little conservation with complexes observed in other organisms (three in yeast, none in the others). Overall, the patterns of protein interaction in Plasmodium, like its genome sequence, set it apart from other species.


Mbio | 2012

Toward an Understanding of Changes in Diversity Associated with Fecal Microbiome Transplantation Based on 16S rRNA Gene Deep Sequencing

Dea Shahinas; Michael S. Silverman; Taylor Sittler; Charles Y. Chiu; Peter T. Kim; Emma Allen-Vercoe; Scott Weese; Andrew Wong; Donald E. Low; Dylan R. Pillai

ABSTRACT Fecal microbiome transplantation by low-volume enema is an effective, safe, and inexpensive alternative to antibiotic therapy for patients with chronic relapsing Clostridium difficile infection (CDI). We explored the microbial diversity of pre- and posttransplant stool specimens from CDI patients (n = 6) using deep sequencing of the 16S rRNA gene. While interindividual variability in microbiota change occurs with fecal transplantation and vancomycin exposure, in this pilot study we note that clinical cure of CDI is associated with an increase in diversity and richness. Genus- and species-level analysis may reveal a cocktail of microorganisms or products thereof that will ultimately be used as a probiotic to treat CDI. IMPORTANCE Antibiotic-associated diarrhea (AAD) due to Clostridium difficile is a widespread phenomenon in hospitals today. Despite the use of antibiotics, up to 30% of patients are unable to clear the infection and suffer recurrent bouts of diarrheal disease. As a result, clinicians have resorted to fecal microbiome transplantation (FT). Donor stool for this type of therapy is typically obtained from a spouse or close relative and thoroughly tested for various pathogenic microorganisms prior to infusion. Anecdotal reports suggest a very high success rate of FT in patients who fail antibiotic treatment (>90%). We used deep-sequencing technology to explore the human microbial diversity in patients with Clostridium difficile infection (CDI) disease after FT. Genus- and species-level analysis revealed a cocktail of microorganisms in the Bacteroidetes and Firmicutes phyla that may ultimately be used as a probiotic to treat CDI. Antibiotic-associated diarrhea (AAD) due to Clostridium difficile is a widespread phenomenon in hospitals today. Despite the use of antibiotics, up to 30% of patients are unable to clear the infection and suffer recurrent bouts of diarrheal disease. As a result, clinicians have resorted to fecal microbiome transplantation (FT). Donor stool for this type of therapy is typically obtained from a spouse or close relative and thoroughly tested for various pathogenic microorganisms prior to infusion. Anecdotal reports suggest a very high success rate of FT in patients who fail antibiotic treatment (>90%). We used deep-sequencing technology to explore the human microbial diversity in patients with Clostridium difficile infection (CDI) disease after FT. Genus- and species-level analysis revealed a cocktail of microorganisms in the Bacteroidetes and Firmicutes phyla that may ultimately be used as a probiotic to treat CDI.


PLOS Pathogens | 2016

Correction: A Novel Rhabdovirus Associated with Acute Hemorrhagic Fever in Central Africa

Gilda Grard; Joseph N. Fair; Deanna Lee; Elizabeth Slikas; Imke Steffen; Jean-Jacques Muyembe; Taylor Sittler; Narayanan Veeraraghavan; J. Graham Ruby; Chunlin Wang; Maria Makuwa; Prime Mulembakani; Robert B. Tesh; Jonna A. K. Mazet; Anne W. Rimoin; Travis Taylor; Bradley S. Schneider; Graham Simmons; Eric Delwart; Nathan D. Wolfe; Charles Y. Chiu; Eric Leroy

The authors would like to correct Fig 1 and Supporting Information S2 Fig. Fig 1 Map of Africa showing countries that are affected by viral hemorrhagic fever (VHF) outbreaks. For Fig 1, some of the countries (Sierra Leone, Liberia, Ivory Coast, and Ghana) were mislabeled and dengue and yellow fever were not mentioned as other causes of viral hemorrhagic fever circulating in Africa. The authors now provide a corrected version of the Fig 1, with the countries correctly labelled, along with the addition of a phrase stating that dengue and yellow fever is widespread throughout Africa. For Supporting Information S2 Fig, the original blot used to generate this figure contained additional lanes that had been removed while preparing the figure for publication. In addition, the incorrect lane 4 was inserted into the published figure. Furthermore, a black-and-white inversion and global gamma correction was applied to the entire image for ease of visualization prior to cropping. The authors now provide a corrected version of S2 Fig, with appropriate marks showing the cropped lanes that were included in the published figure, and without the inversion or gamma correction. The uncropped original blot for S2 Fig is shown as supporting information in S1 File. The authors confirm that these changes do not alter their findings. The authors have provided raw, uncropped blots as for S2 Fig as Supporting Information S1 File.


PLOS Pathogens | 2017

Correction: Correction: A Novel Rhabdovirus Associated with Acute Hemorrhagic Fever in Central Africa

Gilda Grard; Joseph N. Fair; Deanna Lee; Elizabeth Slikas; Imke Steffen; Jean-Jacques Muyembe; Taylor Sittler; Narayanan Veeraraghavan; J. Graham Ruby; Chunlin Wang; Maria Makuwa; Prime Mulembakani; Robert B. Tesh; Jonna A. K. Mazet; Anne W. Rimoin; Travis Taylor; Bradley S. Schneider; Graham Simmons; Eric Delwart; Nathan D. Wolfe; Charles Y. Chiu; Eric Leroy

[This corrects the article DOI: 10.1371/journal.ppat.1002924.].


Proceedings of the National Academy of Sciences of the United States of America | 2005

Conserved patterns of protein interaction in multiple species

Roded Sharan; Silpa Suthram; R. Kelley; Scott McCuine; Peter Uetz; Taylor Sittler; Richard M. Karp; Trey Ideker


Genome Research | 2014

A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples

Samia N. Naccache; Scot Federman; Narayanan Veeraraghavan; Matei Zaharia; Deanna Lee; Erik Samayoa; Jerome Bouquet; Alexander L. Greninger; Ka-Cheung Luk; Barryett Enge; Debra A. Wadford; Sharon Messenger; Gillian Genrich; Kristen Pellegrino; Gilda Grard; Eric Leroy; Bradley S. Schneider; Joseph N. Fair; Miguel Ángel Martínez; Pavel Isa; John A. Crump; Joseph L. DeRisi; Taylor Sittler; John Hackett; Steve Miller; Charles Y. Chiu


PLOS Pathogens | 2012

A Novel Rhabdovirus Associated with Acute Hemorrhagic Fever in Central Africa

Gilda Grard; Joseph N. Fair; Deanna Lee; Elizabeth Slikas; Imke Steffen; Jean Jacques Muyembe; Taylor Sittler; Narayanan Veeraraghavan; J. Graham Ruby; Chunlin Wang; Maria Makuwa; Prime Mulembakani; Robert B. Tesh; Jonna A. K. Mazet; Anne W. Rimoin; Travis Taylor; Bradley S. Schneider; Graham Simmons; Eric Delwart; Nathan D. Wolfe; Charles Y. Chiu; Eric Leroy


arXiv: Data Structures and Algorithms | 2011

Faster and More Accurate Sequence Alignment with SNAP

Matei Zaharia; William J. Bolosky; Kristal Curtis; Armando Fox; David A. Patterson; Scott Shenker; Ion Stoica; Richard M. Karp; Taylor Sittler

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Gilda Grard

Aix-Marseille University

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Bradley S. Schneider

University of Texas Medical Branch

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Deanna Lee

University of California

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Eric Leroy

Centre national de la recherche scientifique

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Anne W. Rimoin

University of California

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Graham Simmons

University of California

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J. Graham Ruby

University of California

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