|Henry K. Lau, M.S.|
Microbiologist Team Leader
San Francisco Laboratory
1431 Harbor Bay Parkway, Alameda, CA 94502
13 years as a Microbiologist at FDA
Shigellae are gram negative, facultative anaerobic, non-motile, non-sporeforming rod bacteria responsible for approximately 10% of all foodborne outbreaks in this country (FDA, 2007). The infective dose of Shigella can be as low as 10 cells for S. dysenteriae to 500 cells for S. sonnei (Kothary and Babu, 2001). It is very similar genetically to Escherichia coli (E. coli) and also contains the shiga toxin I (stx I) gene similar to that of Enterohaemorrhagic E. coli (EHEC) (Lampel, 2001). Its effect in human, known as shigellosis, has symptoms such as diarrhea, fever, and stomach cramps, bloody diarrhea, seizures, and/or death. In some instances, shigellosis can develop into hemolytic uremic syndrome (HUS) that can cause fatal renal failure but it mostly affects children. The low infective dose of this pathogen is one of the reasons that Shigellae can spread from person to person easily. Shigella associated outbreaks occur every year and as recent as 2015 in San Jose, California. Shigellae have slowly but surely became a pathogen of concern.
Shigellae represent 10% of all foodborne outbreaks in the United States. The main source of outbreaks from this pathogen is from foods processed with contaminated water. Shigellae can cause shigellosis (bacillary dysentery) in individuals that have eaten Shigella contaminated food. The elderly, young children and immuno-compromised persons will have the most severe symptoms. The infective dose of Shigella can be as low as 10 organisms. Shigellae is easily be transmitted through fecal-oral route, and can be a deadly pathogen to certain individuals. There are four different species in the Shigella genus, additionally each species comprises a specific serogroup: S. dysenteriae (Serogroup A), S. flexneri (Serogroup B), S. boydii (Serogroup C), and S. sonnei (Serogroup D). Currently there are a few methods to identify Shigella. Those methods are selective plating, PCR, and serological antigens method. But each method only gives part of the needed information in an outbreak.
Currently FDA has a PCR assay that targets the ipaH gene for the detection of Shigella. Since two species (S. flexneri and S. sonnei) of Shigellae are more associated with outbreaks in the US (Warren, 2006); while S. dysenteriae and S. boydii cause majority of outbreaks in developing countries (Niyogi, 2005), it would be extremely useful not only to identify but to speciate, strain type, and serologyical identify Shigella present in a given sample with whole genome sequencing. This would allow FDA to have a rapid method to detect, contain, and prevent Shigella outbreaks.
Proposed Research Project for FDA Commissioner's Fellow
With the advancement of sequencing, laboratories now have the power to sequence whole genome. Yet, few laboratories know what to do with the vast amount of sequence data generated from the whole genome sequencing. It would be of interest to develop a strategy to analyze the whole genome sequencing data without a super-computer. Therefore, any laboratory with the computing power to sequence genomes can also be able to analyze them. There are certain well known markers that can be used for identification of genus, such as the 16S and 23S ribosome, but most cases lack the resolution for species identification. There are also many sequence analysis programs available online, but lack the computing power of analyzing whole genome. Having additional data from whole genome sequencing, we can further identify species, serological characteristics, and strain differentiation with the right strategy. These additional information would be valuable for the epidemiology purpose. Also, having sequence analyses perform using a conventional computer instead of a centralized super-computer can decrease the time, cost, and man-power it takes to identify outbreak microorganisms.
A panel of 13 Shigella isolates that includes 4 different serotypes from S. dysenteriae, S. flexneri, S. boydii, and one serotype of S. sonnei plus one exclusion control of Enteroinvasive Escherichia coli (EIEC) will be grown and whole genome sequence. The sequenced data will be cross-reference with the National Center for Biotechnology Information (NCBI) database for accuracy. Then the sequenced data will be used in the creation of a strategy for the identification of genus, species, serology group, and strain type of Shigella. The strategy will include using the current bioinformatics tools and computer programming to aid in finding region(s) of interest for identification. One strategy will be using simple coding to extract targeted genes for each isolate such as, but not limited to invAKJH, ipaABCDH, iucABCD, iutA, sodB, rfa/b, stx, virFGR, kcpA, oacB, adrA, etc. in addition to the common 16S rRNA and 23S rRNA and align for identification. Another strategy is to use simple coding to only look at the exons from the sequence and then align for identification. Once a framework has been developed, additional Shigella isolates will be added to the framework database to include 47 different serotypes of Shigella including 15 serotypes for S. flexneri, 13 serotypes for S. dysenteriae, 18 serotypes for S. boydii, and 1 serotype for S. sonnei.
- Must have a Master degree or above in Biological Science or Computer Science
- Must have experience in BioInformatics (2 semesters of course work or equivalent or 2 year of work experience)
- Must have experience in Whole genome sequencing (1 semesters of course work or equivalent or 1 year of work experience)
- Must have experience in computer programming, Python prefer, (2 semesters of course work or equivalent or 2 year of work experience)
- Must be able to work independently
- Must have experience designing and performing scientific project
- Must be locate in Alameda, CA as the duty station
Selected Recent Publications
1. Lau, H. K., Hall, G. M., Liu, E., Lee, T., Lau, D. K., Axelrad, J. A., Buhse, C., Microbial Growth Assessment and Challenge Study for Repackaged Avastin, Draft, 2015-2016.
2. Lau, H. K., Clotilde, L. M., Lin, A. P., Hartman, G. L., and Lauzon, C. R., Comparison of IMS Platforms for Detecting and Recovering Escherichia coli O157 and Shigella flexneri in Foods, Journal of Laboratory Automation, 2013, 178-183.
3. Lau, H. K., The Detection and Isolation of Shigella spp. in Foods by Immunomagnetic Separation, California State University East Bay Thesis, 2013
4. Lin, A., Sultan, O., Lau, H. K. , Wong, E., Hartman, G., and Lauzon, C. R., O Serogroup Specific Real Time PCR Assays for the Detection and Identification of Nine Clinically-relevant non-O157 STECs., Food Microbiology, 2010, 1-6.
5. Lin, A., Lau, H. K. , Wong, E., Hartman, G., Sultan, O., and Lauzon, C. R., Single Lab Validation of O Serogroup Specific Real Time PCR Assays for the Detection and Identification of non-O157 STECs, Laboratory Information Bulletin, No. 4447, Jan. 2010.