Download 박사님 별 연구주제 및 인턴으로서 하게 될 일 Dr. Ben Tall: I work with

박사님 별 연구주제 및 인턴으로서 하게 될 일
1) Dr. Ben Tall:
I work with Dr. Gopal Gopinathrao on a project that is about Cronobacter. Cronobacter are
global foodborne bacterial pathogens, causing infantile meningitis, septicemia, and necrotizing
enterocolitis and pneumonia, septicemia, and urinary tract infections in adults. Seven species
presently comprise the genus and species confirmation is accomplished through several sequence
based methods including species-specific single nucleotide polymorphisms (SNPs) that target either
a seven gene multilocus sequence typing assay, a seven single-plex PCR assay based on SNPs of the
rpoB gene, or a multiplex-PCR assay of the cgcA gene. Infantile disease is linked to the consumption
of contaminated powdered infant formula, and those infections in elderly and immunocompromised
adults suggest that other sources of contamination exists i.e., home environments; retail foods;
assorted dried foods or drinking water. Recent outbreaks suggest a rapid capacity for the pathogen
to adapt to new environmental niches, including new food sources and environments. From a
genomic perspective, horizontal gene transfer i.e., acquirement of plasmids and phage may account
for such adaptation and diversification of genomic content. Also unique gene regulation-based
adaptation, at the SNP-level may be responsible for the evolution of pathogenic strains. To
investigate the genomic diversity and evolutionary history of Cronobacter, a novel designed
Affymetrix custom microarray platform will be used to characterize a diverse collection of isolates
using microarray analysis (MA) and these studies will also focus on the development, refinement,
and international harmonization of isolation procedures and subsequent new microarray platforms
to define new genetic attributes for future analysis.
DNA sequencing (WGS) information of outbreak and food associated strains will be compared
bioinformatically, and cladistically to results of the Array. New gene sequences of species and strainspecific traits will be captured for development of the new Atlas Platform array so that the pan
genome can be better represented. This information will be used to design and develop a next
generation Gene Atlas system microarray for high-throughput and automated microarray processing.
This platform is currently being used for the identification of other foodborne pathogens by FDA
field labs.
So both Dr. Gopinaththrao’s and my student intern will be cross-trained in both the Cronobacter
project and Dr. Gopinathrao’s project. They will learn how to handle bacteria in a laboratory, how to
isolate bacteria from foods, how to isolate DNA from bacteria and how to prepare the DNA for both
MA and WGS studies. They will learn how to perform the microarray analysis and to generate data
from the FDA-Cronobacter custom high-density Atlas microarray platform.
By applying highly discriminatory molecular methods such as DNA microarray and WGS for
identification and tracking of bacterial pathogens, the nature of foodborne outbreaks caused by
these pathogens can be better understood thereby helping to ensure the safety and integrity of the
food supply. This research is crucial: for detection and characterization of Cronobacter from dried
foods, for addressing CFSAN’s mission on trace-back of this pathogen, and for global harmonization
of isolation protocols to a single method, all FSMA-mandated activities. By applying highly
discriminatory molecular methods such as DNA microarray for identification and tracking of bacterial
pathogens, the nature of foodborne outbreaks caused by these pathogens can be better understood
thereby helping to ensure the safety and integrity of the food supply.
2) Dr. Gopal Gopinathrao:
During many of the kill steps used in food processing to reduce pathogens contaminating
foods, a small fraction of cells typically survive through entering the so-called persister state.
Persister cells are increasingly being viewed as a major cause of recurrent chronic infectious disease
and in the emergence of foodborne disease. The phenomenon of persistence remains poorly
understood, but it is thought that persister cells form stochastically by switching into and out of a
state of dormancy. Only recently, a series of breakthrough discoveries has started to shed light on
persister cell physiology and the molecular and genetic underpinnings of persister formation. Toxinantitoxin (TA) systems have been implicated in the formation of the persistence phenotype in some
bacterial species including E.coli and Salmonella. There are five classes of TA systems identified in
bacteria. Currently the project is looking at the genomic landscape of the type II system in
Cronobacter and Salmonella using Whole genome sequencing (WGS) and microarray analysis (MA).
The students will learn how to handle bacteria in a laboratory, how to isolate bacteria from foods,
how to isolate DNA from bacteria and how to prepare the DNA for both MA and WGS studies. To
describe a few examples of projects that they be involved with include:
1) They will learn how to perform the microarray analysis and to generate data from WGS
analyses.
2) They will test out methods to prepare total DNA for Whole Genome Sequencing (WGS) of
spiked and naturally contaminated selected and high priority low water activity foods and
dietary supplements.
3) Workflows for mining metagenomics datasets to identify known markers of persistence
like various type II toxin-antitoxin loci, and other putative regulatory systems, their gene
(operon) prevalence and distribution associated with well recognized desiccant resistant
organism such as Salmonella spp., and Cronobacter spp. will be developed and tested.
4) Genomic and transcriptomic characterization of persister bacterial sub-populations in PIF
and dietary supplements, artificially contaminated, with Cronobacter and Salmonella. Only
persister cells that adapt in the food products are expected to survive and be amenable to
processing. The spiked organisms will be exposed to stress factors like desiccation and
specific gene expression to unravel persistence pathways. A time-course study of spiked
samples will be conducted.
In summary, the goal of this project will be to elucidate the molecular mechanisms that enable cells
to transition back and forth from a persister-dormant state to a state of normal physiological activity.
Knowledge of the underlying mechanisms driving this transition can then guide the development of
food processing protocols that will prevent bacteria from exploiting this strategy to survive in
susceptible food products.
3) Dr. Hediye Nese Cinar:
In spite of advances in sequencing and data analysis techniques, sequencing of nuclear
genome of the foodborne parasite, C. cayetanensis, has been a long-standing problem due to limited
sample availability. C. cayetanensis cannot be cultured in vitro so clinical fecal samples containing C.
cayetanensis oocysts are the sole source of DNA for Cyclospora, albeit a poor source. Using current
Cyclospora oocyst purification methods, we can decrease the fecal bacteria and other contaminant
DNA to low levels, but cannot eliminate these altogether. For this reason, to develop molecular
epidemiological methods for Cyclospora, alternative approaches to WGS of Cyclospora are needed.
The sequencing of Cyclospora genomes will be done using a metagenomics approach on Illumina’s
MiSeq and NextSeq platforms. Multicopy organellar DNA such as mitochondrion and apicoplast
genomes have been particularly informative tracing back the geographic origins of cases caused by
Plasmodium vivax and Plasmodium falciparum. We recently assembled the mitochondrial genome of
C. cayetanensis in our laboratory from metagenomics datasets using a targeted post-sequencing
metagenomics data analysis approach. This data was obtained from C. cayetanensis oocyst DNA
originating from fecal samples from Nepal. It is imperative to continue to gather organelle genome
data from different geographical locations in order to understand the level of genetic diversity in C.
cayetanensis. Resulting SNP data will be used to evaluate molecular approaches to develop barcode
assays to differentiate C. cayetanensis originating from different geographical regions. We will
develop and optimize a bioinformatics pipeline to analyze sequencing data from complex samples
containing C. cayetanensis DNA to achieve de novo assembly of genomic regions from
metagenomics reads. Also note that Dr. Cinar works with Dr. Gopinathrao as well.
The student intern will learn:
1) How to obtain oocysts from a variety of samples and learn how to isolate the DNA from the
oocysts.
2) How to sequence, assemble and annotate C. cayetanensis mitochondrial, and apicoplast
genomes of C. cayetanensis using Illumina MiSeq and NextSeq platforms.
3) How to develop comparative genomic analysis methods using multiple C. cayetanensis
mitochondrial, and apicoplast genomes, and evaluate molecular approaches to develop
barcoding assays for epidemiologic investigations.
4) Dr. Venugopal Sathyamoorthy:
The three most common food borne bacterial pathogens that have been implicated in food borne
outbreaks are Salmonella spp, Escherichia coli O157:H7 and Listeria monocytogenes. These
organisms cause diseases such as gastroenteritis, hemolytic uremic syndrome, invasive listeriosis etc.
Hence, it is important to identify these pathogens in ready-to-eat foods so that the contaminated
foods can be removed from the circulation. The current FDA methods to identify these pathogens
are laborious, time consuming and can take up to 7 days to get a confirmatory result. Also, there is
no existing method for simultaneous detection of all three organisms in contaminated foods
regulated by FDA; each one of the organisms has to be tested separately. On the other hand, nucleic
acid based methods are rapid, cost effective and highly sensitive for simultaneously detecting these
pathogens. However, selectively as well as simultaneously enriching and isolating the pathogens
from various food sources pose challenges. A real-time PCR method to simultaneously identify these
three pathogens was developed for meats by USDA. We have evaluated, optimized and adapted this
USDA method for FDA regulated foods such as soft cheese (5 kinds), spinach, cantaloupe, peanut
butter, salads, tomatoes, red onions, sprouts, mangoes, strawberries, lettuce, black pepper, cilantro
etc. The current proposed project is a continuation of a previous project which was completed using
overnight grown cultures. Contrarily, this project aims to develop a similar method in FDA regulated
foods with aged Salmonella spp, Escherichia coli O157:H7 and Listeria monocytogenes, simulating
the storage conditions of the supermarkets and other holding facilities using a ABI-7500 platform. In
order to go for the validation study of this method as a next step, this proposed project needs to be
completed. A rapid, validated method will be of importance for the reduction of foodborne diseases.
The student intern will learn how to handle bacteria in a laboratory, how to isolate bacteria from
foods, how to isolate DNA from bacteria in contaminated foods and then establish the limit of
detection and modify if necessary to achieve desired sensitivity of aged Salmonella spp, E. coli O157:
H7, and Listeria monocytogenes in artificially contaminated cheeses using a ABI-7500 real time PCR
platform and also determine that there are no false negative results.
A method for the simultaneous detection of all three organisms in contaminated foods regulated by
FDA will greatly reduce the time required for detection and further responses. We will evaluate,
optimize and adapt a real-time PCR method, developed at USDA, to detect these three pathogens all
together in ready-to-eat fruits and vegetables. Once standardized, this method could be used in FDA
Field laboratories to ensure industry compliance and also during outbreak investigations.
5) Ms. Isha Patel
She is our Microarray expert and the project that she had in mind is similar to the abstract
describing the Salmonella work.
Species of Salmonella cause more than 100 million symptomatic infections annually, including 16
million to 20 million cases of typhoid fever. The microorganism infects and hides out in immune cells
called macrophages, manipulating the metabolism of these cells to its own benefit. Recently, a strain
collection representing a 10 year Salmonella disease surveillance study, which took place in Peru
during 1995-2014 and involved over 1200 strains, was shared with the FDA for phylogenetic analysis
using Next Generation Sequencing (NGS), PCR, and Microarray (MA) analyses.
Pathogenic Escherichia coli are classified based on the virulence factors they carry or the clinical
manifestations they cause, so serotyping is not very useful for identifying these pathogens in general.
One exception may be Shiga toxin-producing E. coli (STEC) of serotype O157:H7, which is recognized
worldwide by its somatic (O) 157 and flagellar (H) 7 antigens. A custom Affymetrix DNA microarray
was developed by the FDA for the identification and characterization of pathogenic E. coli strains for
non-pathogenic strains. The array, designated FDA E. coli identification (FDAECID), incorporates
genetic signatures from over 250 whole-genome sequences, more than 40,000 E. coli genes, and
approximately 9,800 single nucleotide polymorphisms to provide a nearly true representation of the
E. coli pangenome.
The student intern will learn how to handle these bacteria in a laboratory, how to isolate DNA from
pure cultures and from foods, how to perform PCR, Next Generation Sequencing and how to analyze
the strains using these novel DNA pan genomic microarray. The student will also learn how to
bioinformatically mine biological significant data from the sequences and Microarray such as
serotype, MLST type, antibiotic resistance genes, and plasmid genes and other genes associated with
the mobilome to better understand the phylogenetic relatedness of the strains and in comparison
with other strains obtained from FDA’s global food safety partners. The student will evaluate,
optimize and adapt these protocols. In summary, these studies will demonstrate how NGS, MA and
bioinformatics data mining can be used in parallel to better understand the phylogenetic relatedness
among Salmonella strains in outbreak investigations.