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1.
Microb Genom ; 10(5)2024 May.
Article in English | MEDLINE | ID: mdl-38787376

ABSTRACT

Lyme disease (LD), caused by spirochete bacteria of the genus Borrelia burgdorferi sensu lato, remains the most common vector-borne disease in the northern hemisphere. Borrelia outer surface protein A (OspA) is an integral surface protein expressed during the tick cycle, and a validated vaccine target. There are at least 20 recognized Borrelia genospecies, that vary in OspA serotype. This study presents a new in silico sequence-based method for OspA typing using next-generation sequence data. Using a compiled database of over 400 Borrelia genomes encompassing the 4 most common disease-causing genospecies, we characterized OspA diversity in a manner that can accommodate existing and new OspA types and then defined boundaries for classification and assignment of OspA types based on the sequence similarity. To accommodate potential novel OspA types, we have developed a new nomenclature: OspA in silico type (IST). Beyond the ISTs that corresponded to existing OspA serotypes 1-8, we identified nine additional ISTs that cover new OspA variants in B. bavariensis (IST9-10), B. garinii (IST11-12), and other Borrelia genospecies (IST13-17). The IST typing scheme and associated OspA variants are available as part of the PubMLST Borrelia spp. database. Compared to traditional OspA serotyping methods, this new computational pipeline provides a more comprehensive and broadly applicable approach for characterization of OspA type and Borrelia genospecies to support vaccine development.


Subject(s)
Antigens, Surface , Bacterial Outer Membrane Proteins , Lipoproteins , Lyme Disease , Bacterial Outer Membrane Proteins/genetics , Lyme Disease/microbiology , Lipoproteins/genetics , Antigens, Surface/genetics , Borrelia burgdorferi/genetics , Borrelia burgdorferi/classification , Computer Simulation , Humans , Genome, Bacterial , Borrelia burgdorferi Group/genetics , Borrelia burgdorferi Group/classification , High-Throughput Nucleotide Sequencing/methods , Serogroup , Phylogeny , Bacterial Vaccines
2.
Nucleic Acids Res ; 50(D1): D1307-D1316, 2022 01 07.
Article in English | MEDLINE | ID: mdl-34648031

ABSTRACT

The United States has a complex regulatory scheme for marketing drugs. Understanding drug regulatory status is a daunting task that requires integrating data from many sources from the United States Food and Drug Administration (FDA), US government publications, and other processes related to drug development. At NCATS, we created Inxight Drugs (https://drugs.ncats.io), a web resource that attempts to address this challenge in a systematic manner. NCATS Inxight Drugs incorporates and unifies a wealth of data, including those supplied by the FDA and from independent public sources. The database offers a substantial amount of manually curated literature data unavailable from other sources. Currently, the database contains 125 036 product ingredients, including 2566 US approved drugs, 6242 marketed drugs, and 9684 investigational drugs. All substances are rigorously defined according to the ISO 11238 standard to comply with existing regulatory standards for unique drug substance identification. A special emphasis was placed on capturing manually curated and referenced data on treatment modalities and semantic relationships between substances. A supplementary resource 'Novel FDA Drug Approvals' features regulatory details of newly approved FDA drugs. The database is regularly updated using NCATS Stitcher data integration tool that automates data aggregation and supports full data access through a RESTful API.


Subject(s)
Databases, Factual , Databases, Pharmaceutical , Pharmaceutical Preparations/classification , United States Food and Drug Administration , Humans , National Center for Advancing Translational Sciences (U.S.) , Translational Research, Biomedical/classification , United States
3.
Nucleic Acids Res ; 49(D1): D1179-D1185, 2021 01 08.
Article in English | MEDLINE | ID: mdl-33137173

ABSTRACT

The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Registration System (GSRS) and produce a non-proprietary version of the database for public benefit. In 2019, more than half of all new drugs in clinical development were proteins, nucleic acid therapeutics, polymer products, structurally diverse natural products or cellular therapies. While multiple databases of small molecule chemical structures are available, this resource is unique in its application of regulatory standards for the identification of medicinal substances and its robust support for other substances in addition to small molecules. This public, manually curated dataset provides unique ingredient identifiers (UNIIs) and detailed descriptions for over 100 000 substances that are particularly relevant to medicine and translational research. The dataset can be accessed and queried at https://gsrs.ncats.nih.gov/app/substances.


Subject(s)
Databases, Chemical , Databases, Factual , Databases, Pharmaceutical , Public Health/legislation & jurisprudence , Biological Products/chemistry , Biological Products/classification , Datasets as Topic , Drugs, Investigational/chemistry , Drugs, Investigational/classification , Humans , Internet , Nucleic Acids/chemistry , Nucleic Acids/classification , Polymers/chemistry , Polymers/classification , Prescription Drugs/chemistry , Prescription Drugs/classification , Proteins/chemistry , Proteins/classification , Public Health/methods , Small Molecule Libraries/chemistry , Small Molecule Libraries/classification , Software , United States , United States Food and Drug Administration , Xenobiotics/chemistry , Xenobiotics/classification
4.
Genome Announc ; 3(5)2015 Oct 29.
Article in English | MEDLINE | ID: mdl-26514762

ABSTRACT

We report here the first complete sequences of two Keystone virus (KEYV) genomes isolated from Florida in 2005, which include the first two publicly available complete large (L) gene sequences. The sequences of the KEYV L segments show 75.99 to 83.86% nucleotide similarity with those of other viruses in the California (CAL) serogroup of bunyaviruses.

5.
J Virol ; 84(11): 5715-8, 2010 Jun.
Article in English | MEDLINE | ID: mdl-20237080

ABSTRACT

The initial wave of swine-origin influenza A virus (pandemic H1N1/09) in the United States during the spring and summer of 2009 also resulted in an increased vigilance and sampling of seasonal influenza viruses (H1N1 and H3N2), even though they are normally characterized by very low incidence outside of the winter months. To explore the nature of virus evolution during this influenza "off-season," we conducted a phylogenetic analysis of H1N1 and H3N2 sequences sampled during April to June 2009 in New York State. Our analysis revealed that multiple lineages of both viruses were introduced and cocirculated during this time, as is typical of influenza virus during the winter. Strikingly, however, we also found strong evidence for the presence of a large transmission chain of H3N2 viruses centered on the south-east of New York State and which continued until at least 1 June 2009. These results suggest that the unseasonal transmission of influenza A viruses may be more widespread than is usually supposed.


Subject(s)
Disease Outbreaks , Influenza A Virus, H1N1 Subtype , Influenza A Virus, H3N2 Subtype , Influenza, Human/transmission , Animals , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H1N1 Subtype/isolation & purification , Influenza A Virus, H3N2 Subtype/genetics , Influenza A Virus, H3N2 Subtype/isolation & purification , Influenza A virus/genetics , Influenza A virus/isolation & purification , Influenza, Human/epidemiology , Influenza, Human/virology , New York/epidemiology , Phylogeny , Seasons , Sequence Analysis , Swine
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