Kumar Hari

STRait Razor: a length-based forensic STR allele-calling tool for use with second generation sequencing data.

Recent studies have demonstrated the capability of second generation sequencing (SGS) to provide coverage of short tandem repeats (STRs) found within the human genome. However, there are relatively few bioinformatic software packages capable of detecting these markers in the raw sequence data. The extant STR-calling tools are sophisticated, but are not always applicable to the analysis of the STR loci commonly used in forensic analyses. STRait Razor is a newly developed Perl-based software tool that runs on the Linux/Unix operating system and is designed to detect forensically-relevant STR alleles in FASTQ sequence data, based on allelic length. It is capable of analyzing STR loci with repeat motifs ranging from simple to complex without the need for extensive allelic sequence data. STRait Razor is designed to interpret both single-end and paired-end data and relies on intelligent parallel processing to reduce analysis time. Users are presented with a number of customization options, including variable mismatch detection parameters, as well as the ability to easily allow for the detection of alleles at new loci. In its current state, the software detects alleles for 44 autosomal and Y-chromosome STR loci. The study described herein demonstrates that STRait Razor is capable of detecting STR alleles in data generated by multiple library preparation methods and two Illumina(®) sequencing instruments, with 100% concordance. The data also reveal noteworthy concepts related to the effect of different preparation chemistries and sequencing parameters on the bioinformatic detection of STR alleles.

The Microbial Rosetta Stone Database: A compilation of global and emerging infectious microorganisms and bioterrorist threat agents

BackgroundThousands of different microorganisms affect the health, safety, and economic stability of populations. Many different medical and governmental organizations have created lists of the pathogenic microorganisms relevant to their missions; however, the nomenclature for biological agents on these lists and pathogens described in the literature is inexact. This ambiguity can be a significant block to effective communication among the diverse communities that must deal with epidemics or bioterrorist attacks.ResultsWe have developed a database known as the Microbial Rosetta Stone. The database relates microorganism names, taxonomic classifications, diseases, specific detection and treatment protocols, and relevant literature. The database structure facilitates linkage to public genomic databases. This paper focuses on the information in the database for pathogens that impact global public health, emerging infectious organisms, and bioterrorist threat agents.ConclusionThe Microbial Rosetta Stone is available at http://www.microbialrosettastone.com/. The database provides public access to up-to-date taxonomic classifications of organisms that cause human diseases, improves the consistency of nomenclature in disease reporting, and provides useful links between different public genomic and public health databases.

Comprehensive Genome Scale Phylogenetic Study Provides New Insights on the Global Expansion of Chikungunya Virus

ABSTRACT Since the India and Indian Ocean outbreaks of 2005 and 2006, the global distribution of chikungunya virus (CHIKV) and the locations of epidemics have dramatically shifted. First, the Indian Ocean lineage (IOL) caused sustained epidemics in India and has radiated to many other countries. Second, the Asian lineage has caused frequent outbreaks in the Pacific islands and in 2013 was introduced into the Caribbean, followed by rapid spread to nearly all of the neotropics. Further, CHIKV epidemics, as well as exported cases, have been reported in central Africa after a long period of perceived silence. To understand these changes and to anticipate the future of the virus, the exact distribution, genetic diversity, transmission routes, and future epidemic potential of CHIKV require further assessment. To do so, we conducted the most comprehensive phylogenetic analysis to date, examined CHIKV evolution and transmission, and explored distinct genetic factors associated with the emergence of the East/Central/South African (ECSA) lineage, the IOL, and the Asian lineage. Our results reveal contrasting evolutionary patterns among the lineages, with growing genetic diversities observed in each, and suggest that CHIKV will continue to be a major public health threat with the potential for further emergence and spread. IMPORTANCE Chikungunya fever is a reemerging infectious disease that is transmitted by Aedes mosquitoes and causes severe health and economic burdens in affected populations. Since the unprecedented Indian Ocean and Indian subcontinent outbreaks of 2005 and 2006, CHIKV has further expanded its geographic range, including to the Americas in 2013. Its evolution and transmission during and following these epidemics, as well as the recent evolution and spread of other lineages, require optimal assessment. Using newly obtained genome sequences, we provide a comprehensive update of the global distribution of CHIKV genetic diversity and analyze factors associated with recent outbreaks. These results provide a solid foundation for future evolutionary studies of CHIKV that can elucidate emergence mechanisms and also may help to predict future epidemics.

The Microbial Rosetta Stone database: A common structure for microbial biosecurity threat agents.

Infectious microorganisms are important to multiple communities engaged in biodefense and biosecurity, including the agencies responsible for health, defense, law enforcement, agriculture, and drug and food safety. Many agencies have created lists of high priority infectious microorganisms to prioritize research efforts or to formally control the possession and distribution of specific organisms or toxins. However, the biological classification of infectious microorganisms is often complex and ambiguous, leading to uncertainty and confusion for scientists involved in biosecurity work. To address this problem, we created a database, known as the Microbial Rosetta Stone, which resolves many of these ambiguities and includes links to additional information on the microbes, such as gene sequence data and scientific literature. Here we discuss the efforts to coordinate organism names from pathogen lists from various governmental agencies according to biological relatedness and show the overlap of high-priority organisms from multiple agencies. To our knowledge, this is the first comprehensive coordination of pathogens, synonyms, and correct taxonomic names. The organized tables and visual aids are freely available at http://www.microbialrosettastone.com. This website provides a single location where access to information on a broad range of disease-causing organisms and toxins is available to members of the biosecurity community.

Integrated whole-genome sequencing and temporospatial analysis of a continuing Group A Streptococcus epidemic

Analysis of microbial epidemics has been revolutionized by whole-genome sequencing. We recently sequenced the genomes of 601 type emm59 Group A Streptococcus (GAS) organisms responsible for an ongoing epidemic of invasive infections in Canada and some of the United States. The epidemic has been caused by the emergence of a genetically distinct, hypervirulent clone that has genetically diversified. The ease of obtaining genomic data contrasts with the relatively difficult task of translating them into insightful epidemiological information. Here, we sequenced the genomes of 90 additional invasive Canadian emm59 GAS organisms, including 80 isolated recently in 2010–2011. We used an improved bioinformatics pipeline designed to rapidly process and analyze whole-genome data and integrate strain metadata. We discovered that emm59 GAS organisms are undergoing continued multiclonal evolutionary expansion. Previously identified geographic patterns of strain dissemination are being diluted as mixing of subclones over time and space occurs. Our integrated data analysis strategy permits prompt and accurate mapping of the dissemination of bacterial organisms in an epidemic wave, permitting rapid generation of hypotheses that inform public health and virulence studies.

The Microbial Rosetta Stone: a database system for tracking infectious microorganisms

The Microbial Rosetta Stone (MRS) database system was developed to support the law enforcement community by providing a comprehensive and connected microbial pathogen data–information repository. To handle the myriad types of pathogen information required to support law enforcement and intelligence community investigations, a data model previously developed for medical and epidemiological information was enhanced. The data contained in MRS are a broad collection of expert-curated microbial pathogen information, but given the multitude of potential microbes and toxins that may be used in a biocrime or bioterrorism act continual information collection and updating are required. The MRS currently relates governmental community-specific pathogen priority lists, sequence metadata, taxonomic classifications, and diseases to strain collections, specific detection and treatment protocols, and experimental results for biothreat agents. The system contains software tools that help to load, curate, and connect the data. A shared MRS database can be populated in real time by multiple users in multiple locations. Querying tools also provide simple and powerful means to access the data in any part of the database.

The Microbial Rosetta Stone Central Agricultural Database: An Information Resource on High-Consequence Plant Pathogens

Microbial pathogens of humans, animals, and plants can serve as potential agents of biowarfare, bioterrorism, and biocrime. Previously, the Microbial Rosetta Stone (MRS) Central database, an easily accessible informational resource tool, was developed to assist law enforcement personnel in the event of a disease investigation by providing key information on pathogens of concern. Although the database already contained information on a few high-profile plant pathogens, the coverage was insufficient considering the large number of plant pathogens that pose a threat, not only to agricultural production but also to natural plant resources such as forests and rangelands. In this project, 100 plant pathogens of high consequence were selected for study, existing literature on these agents was reviewed, and both the sources and key pathogen information provided therein were curated in the new Agricultural Database (AgDB), an accessory to the existing MRS Central Database. Chosen for inclusion in the MRS Central AgDB were plant pathogens having significant potential for damage to U.S. agricultural and natural ecosystems. The selection process included review of several previously developed plant-pathogen threat lists and recommendations from experts within the U.S. plant biosecurity community. Pathogen information was collected by searching a number of relevant literature databases, sites on the World Wide Web, and other resources. For inclusion in the MRS, the information was curated into categories: pathogen taxonomy, nomenclature synonyms, disease symptoms and geographic distribution, plant hosts, insect vectors, detection and diagnostic methods, laboratory and field protocols, sample collection, and epidemiology. The resulting AgDB enhances the MRS Central Database by summarizing and linking key information on high-threat plant diseases and their causal agents to relevant scientific literature and internet resources. The AgDB contains critical, key information on high-consequence plant pathogens, curated in a format that is readily accessible and easily searched. The resource enhances the existing MRS Central Database and provides law enforcement, forensic, and investigative personnel with an additional tool with which to respond to microbial emergencies, particularly those affecting the agricultural and environmental sectors.

Gemina: a web-based epidemiology and genomic metadata system designed to identify infectious agents

The Gemina system (http://gemina.tigr.org) developed at TIGR is a tool for identification of microbial and viral pathogens and their associated genomic sequences based on the associated epidemiological data. Gemina has been designed as a tool to identify epidemiological factors of disease incidence and to support the design of DNA-based diagnostics such as the development of DNA signature-based assays. The Gemina database contains the full complement of microbial and viral pathogens enumerated in the Microbial Rosetta Stone database (MRS) [1]. Initially, curation efforts in Gemina have focused on the NIAID category A, B, and C priority pathogens [2] identified to the level of strains. For the bacterial NIAID category A-C pathogens, for example, we have included 38 species and 769 strains in Gemina. Representative genomic sequences are selected for each pathogen from NCBI’s GenBank by a three tiered filtering system and incorporated into TIGR’s Panda DNA sequence database. A single representative sequence is selected for each pathogen firstly from complete genome sequences (Tier 1), secondly from whole genome shotgun (WGS) data from genome projects (Tier 2), or thirdly from genomic nucleotide sequences from genome projects (Tier3). The list of selected accessions is transferred to Insignia when new pathogens are added to Gemina, allowing Insignia’s Signature Pipeline [3] to be run for each pathogen identified in a Gemina query.

Molecular Virologic and Clinical Characteristics of a Chikungunya Fever Outbreak in La Romana, Dominican Republic, 2014

Since emerging in Saint Martin in 2013, chikungunya virus (CHIKV), an alphavirus transmitted by the Aedes aegypti mosquito, has infected approximately two million individuals in the Americas, with over 500,000 reported cases in the Dominican Republic (DR). CHIKV-infected patients typically present with a febrile syndrome including polyarthritis/polyarthralgia, and a macropapular rash, similar to those infected with dengue and Zika viruses, and malaria. Nevertheless, many Dominican cases are unconfirmed due to the unavailability and high cost of laboratory testing and the absence of specific treatment for CHIKV infection. To obtain a more accurate representation of chikungunya fever (CHIKF) clinical signs and symptoms, and confirm the viral lineage responsible for the DR CHIKV outbreak, we tested 194 serum samples for CHIKV RNA and IgM antibodies from patients seen in a hospital in La Romana, DR using quantitative RT-PCR and IgM capture ELISA, and performed retrospective chart reviews. RNA and antibodies were detected in 49% and 24.7% of participants, respectively. Sequencing revealed that the CHIKV strain responsible for the La Romana outbreak belonged to the Asian/American lineage and grouped phylogenetically with recent Mexican and Trinidadian isolates. Our study shows that, while CHIKV-infected individuals were infrequently diagnosed with CHIKF, uninfected patients were never falsely diagnosed with CHIKF. Participants testing positive for CHIKV RNA were more likely to present with arthralgia, although it was reported in just 20.0% of CHIKF+ individuals. High percentages of respiratory (19.6%) signs and symptoms, especially among children, were noted, though it was not possible to determine whether individuals infected with CHIKV were co-infected with other pathogens. These results suggest that CHIKV may have been underdiagnosed during this outbreak, and that CHIKF should be included in differential diagnoses of diverse undifferentiated febrile syndromes in the Americas.

Case study: use of a library of antisense inhibitors for gene functionalization and drug target validation

Abstract The genomics revolution of the past decade has allowed the sequences of all human genes to be determined. The challenge for the future is to establish the functions of all of these genes. Antisense technology is a powerful tool for gene functionalization. This review describes a system used to test antisense oligonucleotides to over 2000 genes in multiple cell-based assays. These assays were designed to help assign gene function. The data generated from these assays is subsequently added to a searchable database that allows potential drug targets to be identified.