MSACL 2017 EU Abstract

Defining Systemic Bacterial Infection Through Construction of a Murine Organ Atlas

John Lapek (Presenter)
University of California, San Diego

Bio: John obtained his Ph.D. at the University of Rochester School of Medicine and Dentistry in Toxicology, working the laboratory of Alan Friedman. Upon completion of his Ph.D., John completed a post-doctoral position in the laboratory of Willi Haas at the MGH Cancer Center, Harvard Medical School. His work there used quantitative proteomics and bioinformatics approaches to predict protein co-regulation networks in cancer cell lines. In 2015, John was the recipient of an Institutional Research and Academic Career Development Award (IRACDA) and transitioned to UCSD as a post-doctoral fellow. The IRACDA program places an emphasis on diversity, teaching and outreach. Concurrent with his IRACDA responsibilities, John performs research on host-pathogen interactions using quantitative proteomics as a primary investigative tool.

Authorship: John Lapek (1,2), Robert Mills (1,2), Ronnie Fang (3), Mario Malfavon (1), Richard Daneman (1), Nina van Sorge (4), Rob Knight (5), Liangfang Zhang (3), David Gonzalez (1,2)
(1) Department of Pharmacology, UCSD, (2) Skaggs school of pharmacy and pharmaceutical sciences, UCSD, (3), Department of NanoEngineering, UCSD, (4) Department of Medical Microbiology University Medical Center Utrecht, (5) Department of Pediatrics, UCSD

Short Abstract

Group A Streptococcus has a primary consequence of strep throat, but can also cause grossly invasive infections such as necrotizing fasciitis and bacteremia. Our understanding of the complex network of mechanisms that govern the interplay between host and pathogen during infection remains rudimentary. To better understand global host responses to systemic infection we utilize a mouse model to define niches within major organ systems in combination with multiplexed quantitative proteomics. We define organ specific markers of infection and demonstrate traceability of these markers in blood, establishing a clinically relevant link through analysis of human blood samples.

Long Abstract


Despite its sensitivity to penicillin, Group A Streptococcus (GAS) remains a top 10 human infectious agent worldwide. Though the primary consequence of infection is strep throat, systemic infections do occur and carry substantially high mortality rates. As reservoirs, during the establishment of infection, a host must cope with dynamic conditions that lead to activation and inactivation of numerous immune pathways. The complex network of mechanisms that govern the interplay between host and pathogen remain poorly understood. To address this gap in knowledge, we utilized a mouse model of systemic bacterial infection in conjunction with multiplexed quantitative proteomics to examine organ-level dynamics.


M1T1 GAS 5448 was used to infect eight-week old female CD-1 mice (5x10^6 CFU/100uL, n=10) by tail vein injection. Alternatively mice were mock infected with PBS. Mice were euthanized 48 hours post-infection and major organs were collected. Organs were homogenized in PBS for CFU enumeration. Organ homogenates were then lysed in an SDS and urea containing buffer, and proteins were reduced, alkylated and digested with trypsin. Peptides were desalted and randomly labeled with TMT 10-plex reagents. TMT 10-plexes were fractionated by basic pH reverse-phase liquid chromatography and analyzed on an Orbitrap Fusion in synchronous precursor selection mode. Markers were defined through comparison specific t-tests and outlier analysis.


Through our proteomics approach, we quantified and identified over 12,000 proteins across organ and blood samples. On average, over 10,500 proteins were quantified per organ, with 9,467 in common across all organs (excluding blood). Spearman’s correlation clustering allowed us to separate samples based on organ type and infection status except for the brain. By including additional Group B streptococcus (GBS) infected samples, we could show this was likely due to the blood brain barrier. GBS infection carried a 113-protein marker profile that distinguished it from GAS and mock infected animals. Proteomic analysis shows that organ specific markers are enriched as much as 64-fold relative to other organs; a similar pattern is noted for infection specific markers relative to mock infected samples. We find more proteins in common in response to infection across organ systems, highlighting coordination of immune response. Heme homeostasis and coagulation cascades are among the most significant pathways enriched through Gene Ontology analysis. Outlier analysis allowed for removal of systemic infection response across organs, uncovering organ specific pathway differences in the context of infection. From organ-level proteomic profiles, we define blood markers for organ specific GAS niches. Correlation of these markers with clinical human blood samples is ongoing and progress will be discussed.

Conclusions & Discussion

Beyond identification of innate and acute phase response proteins, a primary goal of this study was to gain valuable insight into disease processes that are specifically occurring in organs, given the numerous sequelae and post-infection complications associated with GAS infection. Our results indicated dynamic responses in each major organ, including regulation of mTOR, collagen remodeling and varied regulation of cytochrome P450s. While this study begins to lay the frame work for understanding host-pathogen interactions in an unbiased and systems scale fashion, there is still a need to identify GAS proteins in vivo, so that their host interaction partners can be defined. Granularity of this level will garner insight to the molecular mechanisms of pathogenesis. Emerging mass spectrometry techniques are allowing researchers to overcome difficulties associated with identification of low-level analytes. Combining these advances with clinical analysis of the plethora of sero-types of GAS will allow the most complete picture of GAS pathogenesis.

References & Acknowledgements:

This work is supported by the Ray Thomas Edwards Foundation (D.J.G.), the National Institutes of Health (R01EY025947) (L.Z.), the Defense Threat Reduction Agency Joint Science and Technology Office for Chemical and Biological Defense (HDTRA1-14-1-0064) (L.Z.). J.D.L. is an IRACDA fellow supported by NIGMS/NIH (K12GM068524).

Financial Disclosure

GrantsyesNIGMS/NIH K12GM068524
Board Memberno

IP Royalty: no

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