Realistic Single Cell Modeling – from Experiment to Simulation

This tutorial gives a step by step explanation of how one uses experimental data to construct a biologically realistic multicompartmental model. Special emphasis is given on the many ways that this process can be imprecise. The tutorial is intended for both experimentalists who want to get into computer modeling and for computer scientists who use abstract neural network models but are curious about biological realistic modeling. The tutorial is not dependent on the use of a specific simulation engine, but rather covers the kind of data needed for constructing a model, how they are used, and potential pitfalls in the process.

Genotyping of Francisella tularensis strains by pulsed-field gel electrophoresis, amplified fragment length polymorphism fingerprinting, and 16S rRNA gene sequencing

We evaluated three molecular methods for identification of Francisella strains: pulsed-field gel electrophoresis (PFGE), amplified fragment length polymorphism (AFLP) analysis, and 16S rRNA gene sequencing. The analysis was performed with 54 Francisella tularensis subsp. holarctica, 5 F. tularensis subsp. tularensis, 2 F. tularensis subsp. novicida, and 1 F. philomiragia strains. On the basis of the combination of results obtained by PFGE with the restriction enzymes XhoI and BamHI, PFGE revealed seven pulsotypes, which allowed us to discriminate the strains to the subspecies level and which even allowed us to discriminate among some isolates of F. tularensis subsp. holarctica. The AFLP analysis technique produced some degree of discrimination among F. tularensis subsp. holarctica strains (one primary cluster with three major subclusters and minor variations within subclusters) when EcoRI-C and MseI-A, EcoRI-T and MseI-T, EcoRI-A and MseI-C, and EcoRI-0 and MseI-CA were used as primers. The degree of similarity among the strains was about 94%. The percent similarities of the AFLP profiles of this subspecies compared to those of F. tularensis subsp. tularensis, F. tularensis subsp. novicida, and F. philomiragia were less than 90%, about 72%, and less than 24%, respectively, thus permitting easy differentiation of this subspecies. 16S rRNA gene sequencing revealed 100% similarity for all F. tularensis subsp. holarctica isolates compared in this study. These results suggest that although limited genetic heterogeneity among F. tularensis subsp. holarctica isolates was observed, PFGE and AFLP analysis appear to be promising tools for the diagnosis of infections caused by different subspecies of F. tularensis and suitable techniques for the differentiation of individual strains.

Identification of the Causative Bacteria in Musculoskeletal Infections Using 16s rDNA - Denaturing Gradient Gel Electrophoresis Analysis

Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

Quantification of nanoparticles at the single-cell level: an overview about state-of-the-art techniques and their limitations.

With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

Revealing Assembly of a Pore-Forming Complex Using Single-Cell Kinetic Analysis and Modeling

Many biological processes depend on the sequential assembly of protein complexes. However, studying the kinetics of such processes by direct methods is often not feasible. As an important class of such protein complexes, pore-forming toxins start their journey as soluble monomeric proteins, and oligomerize into transmembrane complexes to eventually form pores in the target cell membrane. Here, we monitored pore formation kinetics for the well-characterized bacterial pore-forming toxin aerolysin in single cells in real time to determine the lag times leading to the formation of the first functional pores per cell. Probabilistic modeling of these lag times revealed that one slow and seven equally fast rate-limiting reactions best explain the overall pore formation kinetics. The model predicted that monomer activation is the rate-limiting step for the entire pore formation process. We hypothesized that this could be through release of a propeptide and indeed found that peptide removal abolished these steps. This study illustrates how stochasticity in the kinetics of a complex process can be exploited to identify rate-limiting mechanisms underlying multistep biomolecular assembly pathways.

Use of pulsed-field gel electrophoresis in surveillance of Salmonella in Houston, Texas

Background. Pulsed-field gel electrophoresis (PFGE) is a laboratory technique in which Salmonella DNA banding patterns are used as molecular fingerprints for epidemiologic study for "PFGE clusters". State and national health departments (CDC) use PFGE to detect clusters of related cases and to discover common sources of bacteria in outbreaks. ^ Objectives. Using Houston Department of Health and Human Services (HDHHS) data, the study sought: (1) to describe the epidemiology of Salmonella in Houston, with PFGE subtype as a variable; and (2) to determine whether PFGE patterns and clusters detected in Houston were local appearances of PFGE patterns or clusters that occurred statewide. ^ Methods. During the years 2002 to 2005, the HDHHS collected and analyzed data from routine surveillance of Salmonella. We implemented a protocol, between May 1, 2007 and December 31, 2007, in which PFGE patterns from local cases were sent via e-mail to the Texas Department of State Health Services, to verify whether the local PFGE patterns were also part of statewide clusters. PFGE was performed from 106 patients providing a sample from which Salmonella was isolated in that time period. Local PFGE clusters were investigated, with the enhanced picture obtained by linking local PFGE patterns to PFGE patterns at the state and national level. ^ Results. We found that, during the years 2002 to 2005, there were 66 PFGE clusters, ranging in size from 2 to 22 patients within each cluster. Between different serotypes, there were marked differences in the sizes of PFGE clusters. A common source or risk factor was found in fewer than 5 of the 66 PFGE clusters. With the revised protocol, we found that 19 of 66 local PFGE patterns were indistinguishable from PFGE patterns at Texas DSHS. During the eight months, we identified ten local PFGE clusters with a total of 42 patients. The PFGE pattern for eight of the ten clusters matched the PFGE patterns for cases reported to Texas DSHS from other geographic areas. Five of the ten PFGE patterns matched PFGE patterns for clusters under investigation at PulseNet at the national level. HDHHS epidemiologists identified a mode of transmission in two of the ten local clusters and a common risk factor in a third local cluster. ^ Conclusion. In the extended-study protocol, Houston PFGE patterns were linked to patterns seen at the state and national level. The investigation of PFGE clusters was more efficacious in detecting a common transmission when local data were linked to state and national data. ^

Porewater concentrations, pH, single cell number, anaerobic oxidation of methane (AOM) rate, sulfate reduction (SR) rate of samples during METEOR cruise M76/3b at the REGAB cold seep site from the West African margin in 2008

The giant pockmark REGAB (West African margin, 3160 m water depth) is an active methane-emitting cold seep ecosystem, where the energy derived from microbially mediated oxidation of methane supports high biomass and diversity of chemosynthetic communities. Bare sediments interspersed with heterogeneous chemosynthetic assemblages of mytilid mussels, vesicomyid clams and siboglinid tubeworms form a complex seep ecosystem. To better understand if benthic bacterial communities reflect the patchy distribution of chemosynthetic fauna, all major chemosynthetic habitats at REGAB were investigated using an interdisciplinary approach combining porewater geochemistry, in situ quantification of fluxes and consumption of methane, as well bacterial community fingerprinting. This study revealed that sediments populated by different fauna assemblages show distinct biogeochemical activities and are associated with distinct sediment bacterial communities. The methane consumption and methane effluxes ranged over one to two orders of magnitude across habitats, and reached highest values at the mussel habitat, which hosted a different bacterial community compared to the other habitats. Clam assemblages had a profound impact on the sediment geochemistry, but less so on the bacterial community structure. Moreover, all clam assemblages at REGAB were restricted to sediments characterized by complete methane consumption in the seafloor, and intermediate biogeochemical activity. Overall, variations in the sediment geochemistry were reflected in the distribution of both fauna and microbial communities; and were mostly determined by methane flux.