The granulocyte orphan receptor CEACAM4 is able to trigger phagocytosis of bacteria.

Human granulocytes express several glycoproteins of the CEACAM family. One family member, CEACAM3, operates as a single-chain phagocytic receptor, initiating the detection, internalization, and destruction of a limited set of gram-negative bacteria. In contrast, the function of CEACAM4, a closely related protein, is completely unknown. This is mainly a result of a lack of a specific ligand for CEACAM4. By generating chimeric proteins containing the extracellular bacteria-binding domain of CEACAM3 and the transmembrane and cytoplasmic part of CEACAM4 (CEACAM3/4) we demonstrate that this chimeric receptor can trigger efficient phagocytosis of attached particles. Uptake of CEACAM3/4-bound bacteria requires the intact ITAM of CEACAM4, and this motif is phosphorylated by Src family PTKs upon receptor clustering. Furthermore, SH2 domains derived from Src PTKs, PI3K, and the adapter molecule Nck are recruited and associate directly with the phosphorylated CEACAM4 ITAM. Deletion of this sequence motif or inhibition of Src PTKs blocks CEACAM4-mediated uptake. Together, our results suggest that this orphan receptor of the CEACAM family has phagocytic function and prompt efforts to identify CEACAM4 ligands.

Granular layer in the periplasmic space of gram-positive bacteria and fine structures of Enterococcus gallinarum and Streptococcus gordonii septa revealed by cryo-electron microscopy of vitreous sections.

High-resolution structural information on optimally preserved bacterial cells can be obtained with cryo-electron microscopy of vitreous sections. With the help of this technique, the existence of a periplasmic space between the plasma membrane and the thick peptidoglycan layer of the gram-positive bacteria Bacillus subtilis and Staphylococcus aureus was recently shown. This raises questions about the mode of polymerization of peptidoglycan. In the present study, we report the structure of the cell envelope of three gram-positive bacteria (B. subtilis, Streptococcus gordonii, and Enterococcus gallinarum). In the three cases, a previously undescribed granular layer adjacent to the plasma membrane is found in the periplasmic space. In order to better understand how nascent peptidoglycan is incorporated into the mature peptidoglycan, we investigated cellular regions known to represent the sites of cell wall production. Each of these sites possesses a specific structure. We propose a hypothetic model of peptidoglycan polymerization that accommodates these differences: peptidoglycan precursors could be exported from the cytoplasm to the periplasmic space, where they could diffuse until they would interact with the interface between the granular layer and the thick peptidoglycan layer. They could then polymerize with mature peptidoglycan. We report cytoplasmic structures at the E. gallinarum septum that could be interpreted as cytoskeletal elements driving cell division (FtsZ ring). Although immunoelectron microscopy and fluorescence microscopy studies have demonstrated the septal and cytoplasmic localization of FtsZ, direct visualization of in situ FtsZ filaments has not been obtained in any electron microscopy study of fixed and dehydrated bacteria.

Identification and characterisation of ncRNAs in dormant bacteria

Recent years have led to increasing interest and appreciation of the possible importance of single cell heterogeneity in various biological processes. One of the examples of phenotypic heterogeneity in bacterial populations is antibiotic tolerant persister cells. Such an antibiotic tolerance phenotype is of considerable clinical relevance since dormant bacteria can re-establish infections rapidly after the antibiotic treatment has been terminated. Up to now mechanisms for establishing the persistence phenomenon in bacteria have remained largely enigmatic. Persisters are cells considered to be in a dormant state with down regulated gene expression. Only recently small regulatory RNAs (sRNAs) have been appreciated as important regulators of gene expression in response to environmental stimuli and several theoretical studies have suggested a possible involvement of sRNAs in the mechanisms of regulated heterogeneity in bacteria. We have experimentally addressed this potential link between sRNAs and persistence/dormancy in E. coli as an example of heterogeneity. Beside classical sRNAs we are focusing also on sRNAs directly associating with and possibly regulating the ribosome, the central enzyme of gene expression. The persister and dormant cell specific sRNA profile is studied by the comparative analysis of sRNA profile changes of the whole bacterial population after antibiotic killing. From RNA-Seq data ~ 25 000 potentially stable RNA fragments were identified and initial analysis predicted ~300 of them to be dormant/persister cell specific. After further evaluation the most prominent dormant/persister cell specific sRNAs are functionally characterized and their potential role in the persistence/dormancy will be evaluated by applying genetic, molecular and biochemical tools. The potential results of this project will provide a better understanding on the molecular mechanism of bacterial persistence/dormancy and on the role of ribosome-bound sRNA molecules in fine-tuning gene expression.

Identification and characterisation of ncRNAs in dormant bacteria

Recent years have led to increasing interest and appreciation of the possible importance of single cell heterogeneity in various biological processes. One of the examples of phenotypic heterogeneity in bacterial populations is antibiotic tolerant persister cells. Such an antibiotic tolerance phenotype is of considerable clinical relevance since dormant bacteria can re-establish infections rapidly after the antibiotic treatment has been terminated. Up to now mechanisms for establishing the persistence phenomenon in bacteria have remained largely enigmatic. Persisters are cells considered to be in a dormant state with down regulated gene expression. Only recently small regulatory RNAs (sRNAs) have been appreciated as important regulators of gene expression in response to environmental stimuli and several theoretical studies have suggested a possible involvement of sRNAs in the mechanisms of regulated heterogeneity in bacteria. We have experimentally addressed this potential link between sRNAs and persistence/dormancy in E. coli as an example of heterogeneity. Beside classical sRNAs we are focusing also on sRNAs directly associating with and possibly regulating the ribosome, the central enzyme of gene expression. The persister and dormant cell specific sRNA profile is studied by the comparative analysis of sRNA profile changes of the whole bacterial population after antibiotic killing. From RNA-Seq data ~ 25 000 potentially stable RNA fragments were identified and initial analysis predicted ~300 of them to be dormant/persister cell specific. After further evaluation the most prominent dormant/persister cell specific sRNAs are functionally characterized and their potential role in the persistence/dormancy will be evaluated by applying genetic, molecular and biochemical tools. The potential results of this project will provide a better understanding on the molecular mechanism of bacterial persistence/dormancy and on the role of ribosome-bound sRNA molecules in fine-tuning gene expression.

Identification and characterisation of ncRNAs in dormant bacteria

Recent years have led to increasing interest and appreciation of the possible importance of single cell heterogeneity in various biological processes. One of the examples of phenotypic heterogeneity in bacterial populations is antibiotic tolerant persister cells. Such an antibiotic tolerance phenotype is of considerable clinical relevance since dormant bacteria can re-establish infections rapidly after the antibiotic treatment has been terminated. Up to now mechanisms for establishing the persistence phenomenon in bacteria have remained largely enigmatic. Persisters are cells considered to be in a dormant state with down regulated gene expression. Only recently small regulatory RNAs (sRNAs) have been appreciated as important regulators of gene expression in response to environmental stimuli and several theoretical studies have suggested a possible involvement of sRNAs in the mechanisms of regulated heterogeneity in bacteria. We have experimentally addressed this potential link between sRNAs and persistence/dormancy in E. coli as an example of heterogeneity. Beside classical sRNAs we are focusing also on sRNAs directly associating with and possibly regulating the ribosome, the central enzyme of gene expression. The persister and dormant cell specific sRNA profile is studied by the comparative analysis of sRNA profile changes of the whole bacterial population after antibiotic killing. From RNA-Seq data ~ 25 000 potentially stable RNA fragments were identified and initial analysis predicted ~300 of them to be dormant/persister cell specific. After further evaluation the most prominent dormant/persister cell specific sRNAs are functionally characterized and their potential role in the persistence/dormancy will be evaluated by applying genetic, molecular and biochemical tools. The potential results of this project will provide a better understanding on the molecular mechanism of bacterial persistence/dormancy and on the role of ribosome-bound sRNA molecules in fine-tuning gene expression.

SAMPLING METHODOLOGY FOR AIRBORNE SEMIVOLATILE ORGANIC POLLUTANTS USING POLYURETHANE FOAMS (COLLECTION, PESTICIDES, VOLATILE)

Indoor and ambient air organic pollutants have been gaining attention because they have been measured at levels with possible health effects. Studies have shown that most airborne polychlorinated biphenyls (PCBs), pesticides and many polycyclic aromatic hydrocarbons (PAHs) are present in the free vapor state. The purpose of this research was to extend recent investigative work with polyurethane foam (PUF) as a collection medium for semivolatile compounds. Open-porous flexible PUFs with different chemical makeup and physical properties were evaluated as to their collection affinities/efficiencies for various classes of compounds and the degree of sample recovery. Filtered air samples were pulled through plugs of PUF spiked with various semivolatiles under different simulated environmental conditions (temperature and humidity), and sampling parameters (flow rate and sample volume) in order to measure their effects on sample breakthrough volume (V(,B)). PUF was also evaluated in the passive mode using organo-phosphorus pesticides. Another major goal was to improve the overall analytical methodology; PUF is inexpensive, easy to handle in the field and has excellent airflow characteristics (low pressure drop). It was confirmed that the PUF collection apparatus behaves as if it were a gas-solid chromatographic system, in that, (V(,B)) was related to temperature and sample volume. Breakthrough volumes were essentially the same using both polyether and polyester type PUF. Also, little change was observed in the V(,B)s after coating PUF with common chromatographic liquid phases. Open cell (reticulated) foams gave better recoveries than closed cell foams. There was a slight increase in (V(,B)) with an increase in the number of cells/pores per inch. The high-density polyester PUF was found to be an excellent passive and active collection adsorbent. Good recoveries could be obtained using just solvent elution. A gas chromatograph equipped with a photoionization detector gave excellent sensitivities and selectivities for the various classes of compounds investigated. ^

Optimization of a DNSH passive sampling method to measure airborne carbonyls

Various airborne aldehydes and ketones (i.e., airborne carbonyls) present in outdoor, indoor, and personal air pose a risk to human health at present environmental concentrations. To date, there is no adequate, simple-to-use sampler for monitoring carbonyls at parts per billion concentrations in personal air. The Passive Aldehydes and Ketones Sampler (PAKS) originally developed for this purpose has been found to be unreliable in a number of relatively recent field studies. The PAKS method uses dansylhydrazine, DNSH, as the derivatization agent to produce aldehyde derivatives that are analyzed by HPLC with fluorescence detection. The reasons for the poor performance of the PAKS are not known but it is hypothesized that the chemical derivatization conditions and reaction kinetics combined with a relatively low sampling rate may play a role. This study evaluated the effect of absorption and emission wavelengths, pH of the DNSH coating solution, extraction solvent, and time post-extraction for the yield and stability of formaldehyde, acetaldehyde, and acrolein DNSH derivatives. The results suggest that the optimum conditions for the analysis of DNSHydrazones are the following. The excitation and emission wavelengths for HPLC analysis should be at 250nm and 500nm, respectively. The optimal pH of the coating solution appears to be pH 2 because it improves the formation of di-derivatized acrolein DNSHydrazones without affecting the response of the derivatives of the formaldehyde and acetaldehyde derivatives. Acetonitrile is the preferable extraction solvent while the optimal time to analyze the aldehyde derivatives is 72 hours post-extraction. ^

Characterization of the East Houston particulate matter <2.5 atmosphere; a novel method for desorbing organic constituents from airborne particulates

I have developed a novel approach to test for toxic organic substances adsorbed onto ultra fine particulate particles present in the ambient air in Northeast Houston, Texas. These particles are predominantly carbon soot with an aerodynamic diameter (AD) of <2.5 μm. If present in the ambient air, many of the organic substances will be absorbed to the surface of the particles (which act just like a charcoal air filter), and may be adducted into the respiratory system. Once imbedded into the lungs these particles may release the adsorbed toxic organic substances with serious health consequences. I used a Airmetrics portable Minivol air sampler time drawing the ambient air through collection filters samples from 6 separate sites in Northeast Houston, an area known for high ambient PM 2.5 released from chemical plants and other sources (e.g. vehicle emissions).(1) In practice, the mass of the collected particles were much less than the mass of the filters. My technique was designed to release the adsorbed organic substances on the fine carbon particles by heating the filter samples that included the PM 2.5 particles prior to identification by gas chromatography/mass spectrometry (GCMS). The results showed negligible amounts of target chemicals from the collection filters. However, the filters alone released organic substances and GCMS could not distinguish between the organic substances released from the soot particles from those released from the heated filter fabric. However, an efficacy tests of my method using two wax burning candles that released soot revealed high levels of benzene. This suggests that my method has the potential to reveal the organic substances adsorbed onto the PM 2.5 for analysis. In order to achieve this goal, I must refine the particle collection process which would be independent of the filters; the filters upon heating also release organic substances obscuring the contribution from the soot particles. To obtain pure soot particles I will have to filter more air so that the soot particles can be shaken off the filters and then analyzed by my new technique. ^

Systematic interpretation of molecular beacon polymerase chain reaction for identifying rpoB mutations in Mycobacterium tuberculosis isolates with mixed resistant and susceptible bacteria

Detection of multidrug-resistant tuberculosis (MDR-TB), a frequent cause of treatment failure, takes 2 or more weeks to identify by culture. RIF-resistance is a hallmark of MDR-TB, and detection of mutations in the rpoB gene of Mycobacterium tuberculosis using molecular beacon probes with real-time quantitative polymerase chain reaction (qPCR) is a novel approach that takes ≤2 days. However, qPCR identification of resistant isolates, particularly for isolates with mixed RIF-susceptible and RIF-resistant bacteria, is reader dependent and limits its clinical use. The aim of this study was to develop an objective, reader-independent method to define rpoB mutants using beacon qPCR. This would facilitate the transition from a research protocol to the clinical setting, where high-throughput methods with objective interpretation are required. For this, DNAs from 107 M. tuberculosis clinical isolates with known susceptibility to RIF by culture-based methods were obtained from 2 regions where isolates have not previously been subjected to evaluation using molecular beacon qPCR: the Texas–Mexico border and Colombia. Using coded DNA specimens, mutations within an 81-bp hot spot region of rpoB were established by qPCR with 5 beacons spanning this region. Visual and mathematical approaches were used to establish whether the qPCR cycle threshold of the experimental isolate was significantly higher (mutant) compared to a reference wild-type isolate. Visual classification of the beacon qPCR required reader training for strains with a mixture of RIF-susceptible and RIF-resistant bacteria. Only then had the visual interpretation by an experienced reader had 100% sensitivity and 94.6% specificity versus RIF-resistance by culture phenotype and 98.1% sensitivity and 100% specificity versus mutations based on DNA sequence. The mathematical approach was 98% sensitive and 94.5% specific versus culture and 96.2% sensitive and 100% specific versus DNA sequence. Our findings indicate the mathematical approach has advantages over the visual reading, in that it uses a Microsoft Excel template to eliminate reader bias or inexperience, and allows objective interpretation from high-throughput analyses even in the presence of a mixture of RIF-resistant and RIF-susceptible isolates without the need for reader training.^

RESPONSES OF INDICATOR AND PATHOGENIC BACTERIA TO THE PRESENCE OF CARBARYL IN WATER

Biodegradability is a desirable, if not a necessary characteristic of pesticides. Carbaryl, as Sevin, is one of the more widely used insecticides for the control of agricultural pests and has been reported to be readily degraded by microorganisms. Because of its broad application, the concentration of Sevin in surface waters has been reported to reach nearly four parts per million (PPM) in surface waters, where it has been reported to affect the growth and metabolic rates of aquatic bacterial populations. Following these reports, it is of public health importance to determine the effects of this insecticide on the growth and metabolic rates of bacteria used to indicate water pollution, and on pathogenic organisms which are found in polluted water.^ This study was conducted to determine the effect of carbaryl on the growth and metabolic rates of indicator and pathogenic organisms. Escherichia coli and Streptococcus faecalis were used as indicators, while Staphylococcus aureus and Salmonella typhimurium were the pathogens studied. Pure and mixed cultures of these organisms were exposed to two concentrations of carbaryl (Sevin).^ The study demonstrated that the fecal pollution indicator organisms, E. coli and S. faecalis respond differently to the presence of small concentrations of carbaryl in water as do the two pathogens tested, (S. typhimurium and S. aureus). The growth of all test organisms as measured by spread plate counts, was reduced by the presence of either one mg/l or five mg/l carbaryl within a period of eight days. Survival of the organisms in the presence of five mg/l carbaryl varied dependent upon whether the organism was in pure or mixed culture. In the presence of five mg/l carbaryl, both pure and mixed culture of E. coli showed longer survival. S. faecalis survived for more than eight days in pure culture, neither S. typhimurium nor S. aureus survived for eight days in pure culture.^ The metabolic rate of S. faecalis and S. aureus was reduced by both five mg/l and one mg/l Sevin concentrations, contrary to E. coli and S. typhimurium which had reduced metabolic rate with the introduction of five mg/l Sevin but showed an increase in the metabolic rate with one mg/l Sevin. There was no difference between the test and control when mixed populations were exposed to five mg/l Sevin and the metabolic rate tested. A mixture of E. coli and S. typhimurium populations showed a respiration increase over the control when exposed to one mg/l Sevin concentration. If similar effects occur in polluted surface waters, misleading results from bacteriological water quality testing may occur. ^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^