Center for Systems Biology of EnteroPathogens (SysBEP)

Systems Biology for EnteroPathogens uses a systems biology approach involving the use of iterative and complementary computational and experimental “omics” methodologies to analyze, identify, quantify, model, and ultimately predict the overall molecular processes involved in the pathogenesis of Salmonella and Yersinia species in macrophages.

The following are data sets generated by SysBEP with pointers to relevant publications about the data, pointers to the data, and sets of important genes/proteins identified by the set of experiments and the criteria for their selection.


Sub-cellular proteomic survey of Salmonella

The project performed a subcellular proteomic analysis of Salmonella enterica subsp. enterica serovar Typhimurium str. 14028 grown under standard laboratory and phagosome-mimicking conditions in vitro. Analysis of proteins from cytoplasmic, inner membrane, periplasmic, and outer membrane fractions yielded coverage of 25% of the theoretical proteome. Confident subcellular location could be assigned to over 1000 proteins, with good agreement between experimentally observed location and predicted/known protein properties. Comparison of protein location under the different environmental conditions provided insight into dynamic protein localization and possible moonlighting (multiple function) activities.

Sample-matched multi-omic analysis of Salmonella regulatory mutants

Sample-matched multi-omic analysis of regulators required for virulence was extended to include metabolomics analysis. Here the transcriptome, proteome and metabolome of an additional six regulators required for virulence were analyzed in a sample-matched fashion to facilitate analysis of the Salmonella metabolic model.

Systems analysis of Salmonella regulatory mutants

Sample-matched multi-omic measurements of fourteen virulence-essential regulator mutants were coupled with computational network analysis to efficiently identify Salmonella virulence factors.  A subset of computationally predicted virulence factors was determined to be secreted into the host cytoplasm, and two of these, SrfN and PagK2, were required for full mouse virulence and defined a new class of translocated effectors involved in pathogenesis.

Salmonella secretome  analysis

Researchers identified effector proteins secreted into defined minimal medium designed to induce expression of the SPI-2 TTSS and its effectors. The secretome of the parent strain was compared to those of strains missing essential (ssaK::cat) or regulatory (ΔssaL) components of the SPI-2 TTSS.  20 known SPI-2 effectors were identified. To identify novel effector proteins, the secretome data was coupled with machine learning and 12 candidate proteins were selected for further characterization. Using CyaA’ reporter fusions, six novel type III effectors were identified and two additional proteins that were secreted into J774 macrophages independently of a TTSS were also identified.

Salmonella growth condition adaptation

To determine the impact of a low Mg(2+)/pH defined growth medium (MgM) on the proteome of Salmonella enterica serotype Typhimurium, researchers cultured S. Typhimurium cells in the medium under two different conditions termed MgM Shock and MgM Dilution and then comparatively analyzed the bacterial cells harvested from these conditions by a global proteomic approach.

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using “shotgun” proteomics to accurately uncover the translational landscape and post-translational features.


Multi-omic analysis of Yersinia response to temperature shift

A temporal multi-omic analysis of Y. pestis and Y. pseudotuberculosis at physiologically relevant temperatures was performed to gain insights into how an acute and highly lethal bacterial pathogen, Y. pestis, differs from its less virulent progenitor, Y. pseudotuberculosis.

E. coli

Evolved E. coli Data Consistent with Computed Optimal Growth

Differential gene and protein expression from wild-type and adaptively evolved strains supports observed growth phenotype changes, and is consistent with GEM-computed optimal growth states


In silico method for modelling metabolism and gene product expression at genome scale

A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism’s molecular constitution as a function of genetic and environmental parameters. A model of metabolism and macromolecular expression is prototyped using the simple microorganism Thermotoga maritima. The model accurately simulates variations in cellular composition and gene expression.

Host Response Data

Mouse Macrophage

Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation

Macrophages are central players in immune response, manifesting divergent phenotypes to control inflammation and innate immunity through release of cytokines and other signaling factors. Recently, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pathophysiology, ranging from cancer to aging, often converge on metabolic responses. Genome-scale modeling and multi-omics (transcriptomics, proteomics, and metabolomics) analysis are used to assess metabolic features that are critical for macrophage activation.

Proteomic investigation of the time course responses of RAW 264.7 macrophages to infection with Salmonella enterica

To investigate the extent to which macrophages respond to Salmonella infection, we infected RAW 264.7 macrophages with Salmonella enterica serotype Typhimurium and analyzed macrophage proteins at various time points following infection by using a global proteomic approach. A total of 1,006 macrophage and 115 Salmonella proteins were identified with high confidence.


Characterization of macaque pulmonary fluid proteome during monkeypox infection: dynamics of host response

Understanding viral pathogenesis is challenging because of confounding factors, including nonabrasive access to infected tissues and high abundance of inflammatory mediators that may mask mechanistic details. In diseases such as influenza and smallpox where the primary cause of mortality results from complications in the lung, the characterization of lung fluid offers a unique opportunity to study host-pathogen interactions with minimal effect on infected animals. This investigation characterizes the global proteome response in the pulmonary fluid, bronchoalveolar lavage fluid, of macaques during upper respiratory infection by monkeypox virus (MPXV), a close relative of the causative agent of smallpox, variola virus.