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1.  Nonspecific Adherence by Actinobacillus actinomycetemcomitans Requires Genes Widespread in Bacteria and Archaea 
Journal of Bacteriology  2000;182(21):6169-6176.
The gram-negative coccobacillus, Actinobacillus actinomycetemcomitans, is the putative agent for localized juvenile periodontitis, a particularly destructive form of periodontal disease in adolescents. This bacterium has also been isolated from a variety of other infections, notably endocarditis. Fresh clinical isolates of A. actinomycetemcomitans form tenacious biofilms, a property likely to be critical for colonization of teeth and other surfaces. Here we report the identification of a locus of seven genes required for nonspecific adherence of A. actinomycetemcomitans to surfaces. The recently developed transposon IS903φkan was used to isolate mutants of the rough clinical isolate CU1000 that are defective in tight adherence to surfaces (Tad−). Unlike wild-type cells, Tad− mutant cells adhere poorly to surfaces, fail to form large autoaggregates, and lack long, bundled fibrils. Nucleotide sequencing and genetic complementation analysis revealed a 6.7-kb region of the genome with seven adjacent genes (tadABCDEFG) required for tight adherence. The predicted TadA polypeptide is similar to VirB11, an ATPase involved in macromolecular transport. The predicted amino acid sequences of the other Tad polypeptides indicate membrane localization but no obvious functions. We suggest that the tad genes are involved in secretion of factors required for tight adherence of A. actinomycetemcomitans. Remarkably, complete and highly conserved tad gene clusters are present in the genomes of the bubonic plague bacillus Yersinia pestis and the human and animal pathogen Pasteurella multocida. Partial tad loci also occur in strikingly diverse Bacteria and Archaea. Our results show that the tad genes are required for tight adherence of A. actinomycetemcomitans to surfaces and are therefore likely to be essential for colonization and pathogenesis. The occurrence of similar genes in a wide array of microorganisms indicates that they have important functions. We propose that tad-like genes have a significant role in microbial colonization.
PMCID: PMC94753  PMID: 11029439
2.  RNAi screen of Salmonella invasion shows role of COPI in membrane targeting of cholesterol and Cdc42 
A genome wide RNAi screen identifies 72 host cell genes affecting S. Typhimurium entry, including actin regulators and COPI. This study implicates COPI-dependent cholesterol and sphingolipid localization as a common mechanism of infection by bacterial and viral pathogens.
Genome-scale RNAi screen identifies 72 host genes affecting S. Typhimurium host cell invasion.Step-specific follow-up assays assign the phenotypes to specific steps of the invasion process.COPI effects on host cell binding, ruffling and invasion were traced to a key role of COPI in membrane targeting of cholesterol, sphingolipids, Rac1 and Cdc42.This new role of COPI explains why COPI is required for host cell infection by numerous bacterial and viral pathogens.
Pathogens are not only a menace to public health, but they also provide excellent tools for probing host cell function. Thus, studying infection mechanisms has fueled progress in cell biology (Ridley et al, 1992; Welch et al, 1997). In the presented study, we have performed an RNAi screen to identify host cell genes required for Salmonella host cell invasion. This screen identified proteins known to contribute to Salmonella-induced actin rearrangements (e.g., Cdc42 and the Arp2/3 complex; reviewed in Schlumberger and Hardt, 2006) and vesicular traffic (e.g., Rab7) as well as unexpected hits, such as the COPI complex. COPI is a known organizer of Golgi-to-ER vesicle transport (Bethune et al, 2006; Beck et al, 2009). Here, we show that COPI is also involved in plasma membrane targeting of cholesterol, sphingolipids and the Rho GTPases Cdc42 and Rac1, essential host cell factors required for Salmonella invasion. This explains why COPI depletion inhibits infection by S. Typhimurium and illustrates how combining bacterial pathogenesis and systems approaches can promote cell biology.
Salmonella Typhimurium is a common food-borne pathogen and worldwide a major public health problem causing severe diarrhea. The pathogen uses the host's gut mucosa as a portal of entry and gut tissue invasion is a key event leading to the disease. This explains the intense interest from medicine and basic biology in the mechanism of Salmonella host cell invasion.
Tissue culture infection models have delineated a sequence of events leading host cell invasion (Figure 1; Schlumberger and Hardt, 2006): (i) pathogen binding to the host cell surface; (ii) activation of a syringe-like apparatus (‘Type III secretion system 1', T1) of the bacterium and injection of a bacterial toxin cocktail into the host cell. These toxins include SopE, a key virulence factor triggering invasion (Hardt et al, 1998), which was analyzed in our study; (iii) toxin-triggered membrane ruffling. To a significant extent, this is facilitated by SopE-triggered activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection; (iv) engulfment of the pathogen within a vesicular compartment (SCV) and (v) maturation of the SCV, a process driven by a second Type III secretion system (T2), which is expressed by the pathogen upon bacterial entry (Figure 1). This sequence of events mediates Salmonella invasion into the gut epithelium and illustrates that this pathogen can be used for probing mechanisms of host cell actin control, membrane biogenesis, vesicle formation and vesicular trafficking.
SopE is a key virulence factor of invasion and triggers the activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection. We have employed a SopE-expressing S. Typhimurium strain and RNAi screening technology to identify host cell factors affecting invasion. First, we developed an automated fluorescence microscopy assay to quantify S. Typhimurium entry in a high-throughput format (Figure 1C). This assay was based on a GFP reporter expressed by the pathogen after invasion and maturation of the SCV. Using this assay, we screened a ‘druggable genome' siRNA library (6978 genes, 3 oligos each, 1 oligo per well) and identified 72 invasion hits. These included established regulators of the actin cytoskeleton (Cdc42, Arp2/3, Nap1; Schlumberger and Hardt, 2006), some of which have not been implicated so far in Salmonella entry (Pfn1, Cap1), as well as proteins not previously thought to influence infection (Atp1a1, Rbx1, COPI complex). Potentially, these hits could affect any step of the invasion process (Figure 1A).
In the second stage of the study, we have assigned each ‘invasion hit' to particular steps of the invasion process. For this purpose, we developed step-specific assays for Salmonella binding, injection, ruffling and membrane engulfment and re-screened the genes found as hits in the first screen (four siRNAs per gene). As expected, a significant number of ‘hits' affected binding to the host cell, others affected binding and ruffling (e.g., Pfn1, Itgβ5, Cap1), a few were specific for the ruffling step (e.g., Cdc42) and some affected SCV maturation, namely Rab7a, the trafficking protein Vps39 and the vacuolar proton pump Atp6ap2. Thus, our experimental strategy allowed mechanistic interpretation and linked novel hits to particular phenotypes, thus providing a basis for further studies (Figure 1).
COPI depletion impaired effector injection and ruffling. This was surprising, as the COPI complex was known to regulate retrogade Golgi-to-ER transport, but was not expected to affect pathogen interactions at the plasma membrane. Therefore, we have investigated the underlying mechanism. We have observed that COPI depletion entailed dramatic changes in the plasma membrane composition (Figure 6). Cholesterol and sphingolipids, which form domains (‘lipid rafts') in the plasma membrane, were depleted from the cell surface and redirected into a large vesicular compartment. The same was true for the Rho GTPases Rac1 and Cdc42. This strong decrease in the amount of cholesterol-enriched microdomains and Rho GTPases in the plasma membrane explained the observed defects in S. Typhimurium host cell invasion and assigned a novel role for COPI in controlling mammalian plasma membrane composition. It should be noted that other viral and bacterial pathogens do show a similar dependency on host cellular COPI and plasma membrane lipids. This includes notorious pathogens such as Staphylococcus aureus (Ramet et al, 2002; Potrich et al, 2009), Listeria monocytogenes (Seveau et al, 2004; Agaisse et al, 2005; Cheng et al, 2005; Gekara et al, 2005), Mycobacterium tuberculosis (Munoz et al, 2009), Chlamydia trachomatis (Elwell et al, 2008), influenza virus (Hao et al, 2008; Konig et al, 2010), hepatitis C virus (Tai et al, 2009; Popescu and Dubuisson, 2010) and the vesicular stomatitis virus (presented study) and suggests that COPI-mediated control of host cell plasma membrane composition might be of broad importance for pathogenesis. Future work will have to address whether this might offer starting points for developing anti-infective therapeutics with a very broad spectrum of activity.
The pathogen Salmonella Typhimurium is a common cause of diarrhea and invades the gut tissue by injecting a cocktail of virulence factors into epithelial cells, triggering actin rearrangements, membrane ruffling and pathogen entry. One of these factors is SopE, a G-nucleotide exchange factor for the host cellular Rho GTPases Rac1 and Cdc42. How SopE mediates cellular invasion is incompletely understood. Using genome-scale RNAi screening we identified 72 known and novel host cell proteins affecting SopE-mediated entry. Follow-up assays assigned these ‘hits' to particular steps of the invasion process; i.e., binding, effector injection, membrane ruffling, membrane closure and maturation of the Salmonella-containing vacuole. Depletion of the COPI complex revealed a unique effect on virulence factor injection and membrane ruffling. Both effects are attributable to mislocalization of cholesterol, sphingolipids, Rac1 and Cdc42 away from the plasma membrane into a large intracellular compartment. Equivalent results were obtained with the vesicular stomatitis virus. Therefore, COPI-facilitated maintenance of lipids may represent a novel, unifying mechanism essential for a wide range of pathogens, offering opportunities for designing new drugs.
doi:10.1038/msb.2011.7
PMCID: PMC3094068  PMID: 21407211
coatomer; HeLa; Salmonella; siRNA; systems biology
3.  Dissecting Inflammatory Complications in Critically Injured Patients by Within-Patient Gene Expression Changes: A Longitudinal Clinical Genomics Study 
PLoS Medicine  2011;8(9):e1001093.
By studying gene expression changes over time in a cohort of trauma patients, Keyur Desai and colleagues identify genes and pathways strongly associated with longer-term complications, which could lead to improved outcome prediction in the first 80 hours after injury.
Background
Trauma is the number one killer of individuals 1–44 y of age in the United States. The prognosis and treatment of inflammatory complications in critically injured patients continue to be challenging, with a history of failed clinical trials and poorly understood biology. New approaches are therefore needed to improve our ability to diagnose and treat this clinical condition.
Methods and Findings
We conducted a large-scale study on 168 blunt-force trauma patients over 28 d, measuring ∼400 clinical variables and longitudinally profiling leukocyte gene expression with ∼800 microarrays. Marshall MOF (multiple organ failure) clinical score trajectories were first utilized to organize the patients into five categories of increasingly poor outcomes. We then developed an analysis framework modeling early within-patient expression changes to produce a robust characterization of the genomic response to trauma. A quarter of the genome shows early expression changes associated with longer-term post-injury complications, captured by at least five dynamic co-expression modules of functionally related genes. In particular, early down-regulation of MHC-class II genes and up-regulation of p38 MAPK signaling pathway were found to strongly associate with longer-term post-injury complications, providing discrimination among patient outcomes from expression changes during the 40–80 h window post-injury.
Conclusions
The genomic characterization provided here substantially expands the scope by which the molecular response to trauma may be characterized and understood. These results may be instrumental in furthering our understanding of the disease process and identifying potential targets for therapeutic intervention. Additionally, the quantitative approach we have introduced is potentially applicable to future genomics studies of rapidly progressing clinical conditions.
Trial Registration
ClinicalTrials.gov NCT00257231
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Trauma—a serious injury to the body caused by violence or by an accident—is a major global health problem. Every year, events that include traffic collisions, falls, blows, and fires cause injuries that kill more than 5 million people (9% of annual global deaths). Road traffic accidents alone are responsible for 1.3 million deaths a year and, if current trends continue, will be the fifth leading cause of death worldwide by 2030. Moreover, in many countries, including the US, trauma is the number one killer of individuals aged 1–44 y. Trauma can kill people rapidly through loss of blood or serious physical damage to internal organs, but it can also lead to localized infections and to sepsis, an infection of the bloodstream that is characterized by an amplified, body-wide (systemic) inflammatory response. Inflammation—redness, pain, and swelling—is an immune system response that normally provides protection against infections, but systemic inflammation can result in multiple organ failure (MOF) and death.
Why Was This Study Done?
Inflammatory complications of trauma are responsible for more than half of late trauma deaths, but at present it is impossible to predict which patients with major injuries will recover and which will spiral down into MOF and death, because the biological processes that underlie post-injury inflammatory complications are poorly understood. If the changes in gene expression (the process that converts the information encoded in genes into functional proteins) that accompany systemic inflammation could be elucidated, it might be possible to improve the diagnosis of MOF and to develop better treatments for post-trauma inflammatory complications. In this prospective, longitudinal clinical genomics study (part of the Inflammation and Host Response to Injury multi-disciplinary research program [IHRI]), the researchers developed an approach to associate early within-patient gene expression changes with later clinical outcomes. A prospective study is one in which patients with a specific condition are enrolled and then followed to see how various factors affect their outcomes; a longitudinal study analyzes multiple samples taken at different times from individual patients; a clinical genomics study investigates how genes and gene expression affect clinical outcomes.
What Did the Researchers Do and Find?
The researchers followed 168 patients for up to 28 d after they experienced blunt-force trauma (injuries caused when the human body hits or is hit by a large object such as a car). Using a molecular biology tool called a DNA microarray, they determined gene expression patterns in leukocytes (a type of immune system cell) isolated from multiple blood samples collected from each patient during the first few days after injury. Using clinical information collected by trained nurses, they organized the patients into five outcome categories based on a measure of MOF known as the Marshall score. Finally, they developed a statistical method (an analysis framework) to associate the early changes in gene expression with clinical outcomes.
A quarter of the patients' genes showed early expression changes that were associated with longer-term post-injury inflammatory complications. Among the associations revealed by this analysis, down-regulation (reduced expression) of MHC-class II genes (which encode proteins involved in antigen presentation, the process by which molecules from foreign invaders are presented to immune cells to initiate an immune response) and up-regulation of genes encoding components of the p38 MAPK signaling pathway (which helps to drive inflammatory responses) between 40 and 80 h post-injury were particularly strongly associated with longer-term post-injury complications and provided the strongest discrimination between patient outcomes.
What Do These Findings Mean?
The statistical approach used in this study to link the early changes in gene expression that occur after trauma to clinical outcomes provides a detailed picture of genome-wide gene expression responses to trauma. These findings could help scientists understand why some patients develop inflammatory complications of trauma while others do not, and they could help to identify those patients most at risk of developing complications. They could also help to identify targets for therapy, although further studies are needed to confirm and extend these findings. Importantly, the quantitative approach developed by the researchers for analyzing associations between within-patient gene changes over time and clinical outcomes should provide more robust predictions of outcomes than single measurements of gene expression and could be applicable to genomic studies of other rapidly progressing clinical conditions.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001093.
More details about the Inflammation and Host Response to Injury research program are available; the program's website includes a link to an article that explains how genomics can be used to understand the inflammatory complications of trauma
The World Health Organization provides information on injuries and on violence and injury prevention (in several languages)
The US National Institutes of Health has a factsheet on burns and traumatic injury in the USA
The US Centers for Disease Control and Prevention has information on injury and violence prevention and control
MedlinePlus provides links to further resources on injuries
doi:10.1371/journal.pmed.1001093
PMCID: PMC3172280  PMID: 21931541
4.  Genome-Scale Identification of Legionella pneumophila Effectors Using a Machine Learning Approach 
PLoS Pathogens  2009;5(7):e1000508.
A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF) was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine learning algorithms for the identification and characterization of bacterial pathogenesis determinants.
Author Summary
Many pathogenic bacteria exert their function by translocating a set of proteins, termed effectors, into the cytoplasm of their host cell. These effectors subvert various host cell processes for the benefit of the bacteria. Our goal in this study was to identify novel effectors in a genomic scale, towards a better understanding of the molecular mechanisms of bacterial pathogenesis. We developed a computational approach for the detection of new effectors in the intracellular pathogen Legionella pneumophila, the causative agent of the Legionnaires' disease, a severe pneumonia-like disease. The novelty of our approach for detecting effectors is the combination of state-of-the-art machine learning classification algorithms with broad biological knowledge on effector biology in a genomic scale. Applying this method, we detected and experimentally validated dozens of new effectors. Notably, our computational predictions had an exceedingly high accuracy of over 90%. In analyzing these effectors we were able to obtain new insights into the molecular mechanism of the pathogenesis system. Our results suggest, for the first time, that over 10% of the Legionella genome is dedicated to pathogenesis. Finally, our approach is general and can be utilized to study effectors in many other human pathogens.
doi:10.1371/journal.ppat.1000508
PMCID: PMC2701608  PMID: 19593377
5.  Multiserotype Enzyme-Linked Immunosorbent Assay as a Diagnostic Aid for Periodontitis in Large-Scale Studies 
Journal of Clinical Microbiology  2002;40(2):512-518.
Periodontitis is a common chronic oral infection caused by gram-negative bacteria, including Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis. Periodontitis evokes inflammatory host response locally in the periodontium but also systemically. The systemic humoral antibody response against oral pathogens can conveniently be measured by an immunoassay. The aim of the study was to measure serum immunoglobulin G class antibodies against A. actinomycetemcomitans and P. gingivalis by an enzyme-linked immunosorbent assay (ELISA) in which mixtures of several serotypes of the pathogens were used as antigens to avoid biasing of the results in favor of a particular strain. For A. actinomycetemcomitans the antigen consisted of six strains representing serotypes a, b, c, d, and e and one nonserotypeable strain. In the P. gingivalis ELISA, antigens representing serotypes a, b, and c were used. Serum samples from 90 subjects, including 35 samples from patients with diagnosed periodontitis, 10 samples from periodontally healthy controls, and 45 samples from randomly selected apparently healthy volunteers (referred to as “healthy subjects”), were tested. For both pathogens the antibody levels (means ± standard deviations) of the patients—expressed as area under the dilution curve—were significantly higher than those for healthy controls or healthy subjects, with values for A. actinomycetemcomitans and P. gingivalis, respectively, as follows: patients, 22.60 ± 9.94 mm2 and 26.72 ± 11.13 mm2; healthy controls, 9.99 ± 3.92 mm2 and 6.90 ± 3.38 mm2; and healthy subjects, 16.85 ± 6.67 mm2 and 8.51 ± 4.23 mm2. The serotype mixture ELISA is suitable for measuring antibodies against periodontal pathogens in large epidemiological studies in order to evaluate the role of periodontitis as a risk factor for other diseases.
doi:10.1128/JCM.40.2.512-518.2002
PMCID: PMC153358  PMID: 11825965
6.  Phylodynamic Inference for Structured Epidemiological Models 
PLoS Computational Biology  2014;10(4):e1003570.
Coalescent theory is routinely used to estimate past population dynamics and demographic parameters from genealogies. While early work in coalescent theory only considered simple demographic models, advances in theory have allowed for increasingly complex demographic scenarios to be considered. The success of this approach has lead to coalescent-based inference methods being applied to populations with rapidly changing population dynamics, including pathogens like RNA viruses. However, fitting epidemiological models to genealogies via coalescent models remains a challenging task, because pathogen populations often exhibit complex, nonlinear dynamics and are structured by multiple factors. Moreover, it often becomes necessary to consider stochastic variation in population dynamics when fitting such complex models to real data. Using recently developed structured coalescent models that accommodate complex population dynamics and population structure, we develop a statistical framework for fitting stochastic epidemiological models to genealogies. By combining particle filtering methods with Bayesian Markov chain Monte Carlo methods, we are able to fit a wide class of stochastic, nonlinear epidemiological models with different forms of population structure to genealogies. We demonstrate our framework using two structured epidemiological models: a model with disease progression between multiple stages of infection and a two-population model reflecting spatial structure. We apply the multi-stage model to HIV genealogies and show that the proposed method can be used to estimate the stage-specific transmission rates and prevalence of HIV. Finally, using the two-population model we explore how much information about population structure is contained in genealogies and what sample sizes are necessary to reliably infer parameters like migration rates.
Author Summary
Mathematical models play an important role in our understanding of what processes drive the complex population dynamics of infectious pathogens. Yet developing statistical methods for fitting models to epidemiological data is difficult. Epidemiological data is often noisy, incomplete, aggregated across different scales and generally provides only a partial picture of the underlying disease dynamics. Using nontraditional sources of data, like molecular sequences of pathogens, can provide additional information about epidemiological dynamics. But current “phylodynamic” inference methods for fitting models to genealogies reconstructed from sequence data have a number of major limitations. We present a statistical framework that builds upon earlier work to address two of these limitations: population structure and stochasticity. By incorporating population structure, our framework can be applied in cases where the host population is divided into different subpopulations, such as by spatial isolation. Our framework also takes into consideration stochastic noise and can therefore capture the inherent variability of epidemiological dynamics. These advances allow for a much wider class of epidemiological models to be fit to genealogies in order to estimate key epidemiological parameters and to reconstruct past disease dynamics.
doi:10.1371/journal.pcbi.1003570
PMCID: PMC3990497  PMID: 24743590
7.  Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing 
We developed analytical models of DNA replication that include probabilistic initiation of origins, fork progression, passive replication, and asynchrony.We fit the model to budding yeast genome-wide microarray data probing the replication fraction and found that initiation times correlate with the precision of timing.We extracted intrinsic origin properties, such as potential origin efficiency and firing-time distribution, which cannot be done using phenomenological approaches.We propose that origin timing is controlled by stochastically activated initiators bound to origin sites rather than explicit time-measuring mechanisms.
The kinetics of DNA replication must be controlled for cells to develop properly. Although the biochemical mechanisms of origin initiations are increasingly well understood, the organization of initiation timing as a genome-wide program is still a mystery. With the advance of technology, researchers have been able to generate large amounts of data revealing aspects of replication kinetics. In particular, the use of microarrays to probe the replication fraction of budding yeast genome wide has been a successful first step towards unraveling the details of the replication program (Raghuraman et al, 2001; Alvino et al, 2007; McCune et al, 2008). On the surface, the microarray data shows apparent patterns of early and late replicating regions and seems to support the prevailing picture of eukaryotic replication—origins are positioned at defined sites and initiated at defined, preprogrammed times (Donaldson, 2005). Molecular combing, a single-molecule technique, however, showed that the initiation of origins is stochastic (Czajkowsky et al, 2008). Motivated by these conflicting viewpoints, we developed a model that is flexible enough to describe both deterministic and stochastic initiation.
We modeled origin initiation as probabilistic events. We first propose a model where each origin is allowed to have its distinct ‘firing-time distribution.' Origins that have well-determined initiation times have narrow distributions, whereas more stochastic origins have wider distributions. Similar models based on simulations have previously been proposed (Lygeros et al, 2008; Blow and Ge, 2009; de Moura et al, 2010); however, our model is novel in that it is analytic. It is much faster than simulations and allowed us, for the first time, to fit genome-wide microarray data and extract parameters that describe the replication program in unprecedented detail (Figure 2).
Our main result is this: origins that fire early, on average, have precisely defined initiation times, whereas origins that fire late, on average, do not have a well-defined initiation time and initiate throughout S phase. What kind of global controlling mechanism can account for this trend? We propose a second model where an origin is composed of multiple initiators, each of which fires independently and identically. A good candidate for the initiator is the minichromosome maintenance (MCM) complex, as it is found to be associated with origin firing and loaded in abundance (Hyrien et al, 2003). We show that the aforementioned relationship can be explained quantitatively if the earlier-firing origins have more MCM complexes. This model offers a new view of replication: controlled origin timing can emerge from stochastic firing and does not need an explicit time-measuring mechanism, a ‘clock.' This model provides a new, detailed, plausible, and testable mechanism for replication timing control.
Our models also capture the effects of passive replication, which is often neglected in phenomenological approaches (Eshaghi et al, 2007). There are two ways an origin site can be replicated. The site can be replicated by the origin binding to it but can also be passively replicated by neighboring origins. This complication makes it difficult to extract the intrinsic properties of origins. By modeling passive replication, we can separate the contribution from each origin and extract the potential efficiency of origins, i.e., the efficiency of the origin given that there is no passive replication. We found that while most origins are potentially highly efficient, their observed efficiency varies greatly. This implies that many origins, though capable of initiating, are often passively replicated and appear dormant. Such a design makes the replication process robust against replication stress such as fork stalling (Blow and Ge, 2009). If two approaching forks stall, normally dormant origins in the region, not being passively replicated, will initiate to replicate the gap.
With the advance of the microarray and molecular-combing technology, experiments have been done to probe many different types of cells, and large amounts of replication fraction data have been generated. Our model can be applied to spatiotemporally resolved replication fraction data for any organism, as the model is flexible enough to capture a wide range of replication kinetics. The analytical model is also much faster than simulation-based models. For these reasons, we believe that the model is a powerful tool for analyzing these large datasets. This work opens the possibility for understanding the replication program across species in more rigor and detail (Goldar et al, 2009).
Microarrays are powerful tools to probe genome-wide replication kinetics. The rich data sets that result contain more information than has been extracted by current methods of analysis. In this paper, we present an analytical model that incorporates probabilistic initiation of origins and passive replication. Using the model, we performed least-squares fits to a set of recently published time course microarray data on Saccharomyces cerevisiae. We extracted the distribution of firing times for each origin and found that the later an origin fires on average, the greater the variation in firing times. To explain this trend, we propose a model where earlier-firing origins have more initiator complexes loaded and a more accessible chromatin environment. The model demonstrates how initiation can be stochastic and yet occur at defined times during S phase, without an explicit timing program. Furthermore, we hypothesize that the initiators in this model correspond to loaded minichromosome maintenance complexes. This model is the first to suggest a detailed, testable, biochemically plausible mechanism for the regulation of replication timing in eukaryotes.
doi:10.1038/msb.2010.61
PMCID: PMC2950085  PMID: 20739926
DNA replication program; genome-wide analysis; microarray data; replication-origin efficiency; stochastic modeling
8.  Metabolite Cross-Feeding Enhances Virulence in a Model Polymicrobial Infection 
PLoS Pathogens  2011;7(3):e1002012.
Microbes within polymicrobial infections often display synergistic interactions resulting in enhanced pathogenesis; however, the molecular mechanisms governing these interactions are not well understood. Development of model systems that allow detailed mechanistic studies of polymicrobial synergy is a critical step towards a comprehensive understanding of these infections in vivo. In this study, we used a model polymicrobial infection including the opportunistic pathogen Aggregatibacter actinomycetemcomitans and the commensal Streptococcus gordonii to examine the importance of metabolite cross-feeding for establishing co-culture infections. Our results reveal that co-culture with S. gordonii enhances the pathogenesis of A. actinomycetemcomitans in a murine abscess model of infection. Interestingly, the ability of A. actinomycetemcomitans to utilize L-lactate as an energy source is essential for these co-culture benefits. Surprisingly, inactivation of L-lactate catabolism had no impact on mono-culture growth in vitro and in vivo suggesting that A. actinomycetemcomitans L-lactate catabolism is only critical for establishing co-culture infections. These results demonstrate that metabolite cross-feeding is critical for A. actinomycetemcomitans to persist in a polymicrobial infection with S. gordonii supporting the idea that the metabolic properties of commensal bacteria alter the course of pathogenesis in polymicrobial communities.
Author Summary
Many bacterial infections are not the result of colonization and persistence of a single pathogenic microbe in an infection site but instead the result of colonization by several. Although the importance of polymicrobial interactions and pathogenesis has been noted by many prominent microbiologists including Louis Pasteur, most studies of pathogenic microbes have focused on single organism infections. One of the primary reasons for this oversight is the lack of robust model systems for studying bacterial interactions in an infection site. Here, we use a model co-culture system composed of the opportunistic oral pathogen Aggregatibacter actinomycetemcomitans and the common oral commensal Streptococcus gordonii to assess the impact of polymicrobial growth on pathogenesis. We found that the abilities of A. actinomycetemcomitans to persist and cause disease are enhanced during co-culture with S. gordonii. Remarkably, this enhanced persistence requires A. actinomycetemcomitans catabolism of L-lactate, the primary metabolite produced by S. gordonii. These data demonstrate that during co-culture growth, S. gordonii provides a carbon source for A. actinomycetemcomitans that is necessary for establishing a robust polymicrobial infection. This study also demonstrates that virulence of an opportunistic pathogen is impacted by members of the commensal flora.
doi:10.1371/journal.ppat.1002012
PMCID: PMC3069116  PMID: 21483753
9.  High Content Screening in Neurodegenerative Diseases 
The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency1-4. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation5. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known6, 7. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long.
There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity8. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention.
High-throughput screening (HTS) is an ideal methodology to address these issues9-12. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties13, 14. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)4, 15-17. HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS.
HCS has many advantages over HTS18, 19, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility.
Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing20 and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism21.
Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.
doi:10.3791/3452
PMCID: PMC3369774  PMID: 22257990
Medicine;  Issue 59;  High-throughput screening;  high-content screening;  neurodegeneration;  automated cell culturing;  Parkinson’s disease
10.  A Genome-Wide Integrative Genomic Study Localizes Genetic Factors Influencing Antibodies against Epstein-Barr Virus Nuclear Antigen 1 (EBNA-1) 
PLoS Genetics  2013;9(1):e1003147.
Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10−15 for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.
Author Summary
Many factors influence individual differences in susceptibility to infectious disease, including genetic factors of the host. Here we use several genome-wide investigative tools (linkage, association, joint linkage and association, and the analysis of gene expression data) to search for host genetic factors influencing Epstein-Barr virus (EBV) infection. EBV is a human herpes virus that infects up to 90% of adults worldwide, infection with which has been associated with severe complications including malignancies and autoimmune disorders. In a sample of >1,300 Mexican American family members, we found significant evidence of association of anti–EBV antibody levels with loci on chromosome 6 in the human leukocyte antigen region, which contains genes related to immune function. The top two independent loci in this region were HLA-DRB1 and HLA-DQB1, both of which are involved in the presentation of foreign antigens to T cells. This finding was specific to EBV and not to 12 other pathogens we examined. We also report an overlap of genetic factors influencing both EBV antibody level and EBV–related cancers and autoimmune disorders. This work demonstrates the presence of EBV susceptibility loci and provides impetus for further investigation to better understand the underlying mechanisms related to differences in disease progression among individuals infected with this pathogen.
doi:10.1371/journal.pgen.1003147
PMCID: PMC3542101  PMID: 23326239
11.  Quorum Sensing Coordinates Brute Force and Stealth Modes of Infection in the Plant Pathogen Pectobacterium atrosepticum 
PLoS Pathogens  2008;4(6):e1000093.
Quorum sensing (QS) in vitro controls production of plant cell wall degrading enzymes (PCWDEs) and other virulence factors in the soft rotting enterobacterial plant pathogen Pectobacterium atrosepticum (Pba). Here, we demonstrate the genome-wide regulatory role of QS in vivo during the Pba–potato interaction, using a Pba-specific microarray. We show that 26% of the Pba genome exhibited differential transcription in a QS (expI-) mutant, compared to the wild-type, suggesting that QS may make a greater contribution to pathogenesis than previously thought. We identify novel components of the QS regulon, including the Type I and II secretion systems, which are involved in the secretion of PCWDEs; a novel Type VI secretion system (T6SS) and its predicted substrates Hcp and VgrG; more than 70 known or putative regulators, some of which have been demonstrated to control pathogenesis and, remarkably, the Type III secretion system and associated effector proteins, and coronafacoyl-amide conjugates, both of which play roles in the manipulation of plant defences. We show that the T6SS and a novel potential regulator, VirS, are required for full virulence in Pba, and propose a model placing QS at the apex of a regulatory hierarchy controlling the later stages of disease progression in Pba. Our findings indicate that QS is a master regulator of phytopathogenesis, controlling multiple other regulators that, in turn, co-ordinately regulate genes associated with manipulation of host defences in concert with the destructive arsenal of PCWDEs that manifest the soft rot disease phenotype.
Author Summary
Many Gram-negative bacteria use a population density-dependent regulatory mechanism called quorum sensing (QS) to control the production of virulence factors during infection. In the bacterial plant pathogen Pectobacterium atrosepticum (formerly Erwinia carotovora subsp. atroseptica), an important model for QS, this mechanism regulates production of enzymes that physically attack the host plant cell wall. This study used a whole genome microarray-based approach to investigate the entire QS regulon during plant infection. Results demonstrate that QS regulates a much wider set of essential virulence factors than was previously appreciated. These include virulence factors similar to those in other plant and animal pathogens that have not previously been associated with QS, e.g., a Type VI secretion system (and its potential substrates), shown for the first time to be required for virulence in a plant pathogen; and the plant toxin coronafacic acid, known in other pathogens to play a role in manipulating plant defences. This study provides the first evidence that Pectobacterium may target host defences simultaneously with a physical attack on the plant cell wall. Moreover, the study demonstrates that a wide range of previously known and unknown virulence regulators lie within the QS regulon, revealing it to be the master regulator of virulence.
doi:10.1371/journal.ppat.1000093
PMCID: PMC2413422  PMID: 18566662
12.  A Functional Genomic Yeast Screen to Identify Pathogenic Bacterial Proteins  
PLoS Pathogens  2008;4(1):e9.
Many bacterial pathogens promote infection and cause disease by directly injecting into host cells proteins that manipulate eukaryotic cellular processes. Identification of these translocated proteins is essential to understanding pathogenesis. Yet, their identification remains limited. This, in part, is due to their general sequence uniqueness, which confounds homology-based identification by comparative genomic methods. In addition, their absence often does not result in phenotypes in virulence assays limiting functional genetic screens. Translocated proteins have been observed to confer toxic phenotypes when expressed in the yeast Saccharomyces cerevisiae. This observation suggests that yeast growth inhibition can be used as an indicator of protein translocation in functional genomic screens. However, limited information is available regarding the behavior of non-translocated proteins in yeast. We developed a semi-automated quantitative assay to monitor the growth of hundreds of yeast strains in parallel. We observed that expression of half of the 19 Shigella translocated proteins tested but almost none of the 20 non-translocated Shigella proteins nor ∼1,000 Francisella tularensis proteins significantly inhibited yeast growth. Not only does this study establish that yeast growth inhibition is a sensitive and specific indicator of translocated proteins, but we also identified a new substrate of the Shigella type III secretion system (TTSS), IpaJ, previously missed by other experimental approaches. In those cases where the mechanisms of action of the translocated proteins are known, significant yeast growth inhibition correlated with the targeting of conserved cellular processes. By providing positive rather than negative indication of activity our assay complements existing approaches for identification of translocated proteins. In addition, because this assay only requires genomic DNA it is particularly valuable for studying pathogens that are difficult to genetically manipulate or dangerous to culture.
Author Summary
Many bacterial pathogens promote infection and ultimately cause disease, in part, through the actions of proteins that the bacteria directly inject into host cells. These proteins subvert host cell processes to favor survival of the pathogen. The identification of such proteins can be limited since many of the injected proteins lack homology with other virulence proteins and pathogens that no longer express the proteins are often unimpaired in conventional assays of pathogenesis. Many of these proteins target cellular processes conserved from mammals to yeast, and overexpression of these proteins in yeast results in growth inhibition. We have established a high throughput growth assay amenable to systematically screening open reading frames from bacterial pathogens for those that inhibit yeast growth. We observe that yeast growth inhibition is a sensitive and specific indicator of proteins that are injected into host cells. Expression of about half of the injected bacterial proteins but almost none of the bacteria-confined proteins results in yeast growth inhibition. Since this assay only requires genomic DNA it is particularly valuable for studying pathogens that are difficult to genetically manipulate or dangerous to grow in the laboratory.
doi:10.1371/journal.ppat.0040009
PMCID: PMC2211553  PMID: 18208325
13.  Yeast Functional Genomic Screens Lead to Identification of a Role for a Bacterial Effector in Innate Immunity Regulation 
PLoS Pathogens  2007;3(2):e21.
Numerous bacterial pathogens manipulate host cell processes to promote infection and ultimately cause disease through the action of proteins that they directly inject into host cells. Identification of the targets and molecular mechanisms of action used by these bacterial effector proteins is critical to understanding pathogenesis. We have developed a systems biological approach using the yeast Saccharomyces cerevisiae that can expedite the identification of cellular processes targeted by bacterial effector proteins. We systematically screened the viable yeast haploid deletion strain collection for mutants hypersensitive to expression of the Shigella type III effector OspF. Statistical data mining of the results identified several cellular processes, including cell wall biogenesis, which when impaired by a deletion caused yeast to be hypersensitive to OspF expression. Microarray experiments revealed that OspF expression resulted in reversed regulation of genes regulated by the yeast cell wall integrity pathway. The yeast cell wall integrity pathway is a highly conserved mitogen-activated protein kinase (MAPK) signaling pathway, normally activated in response to cell wall perturbations. Together these results led us to hypothesize and subsequently demonstrate that OspF inhibited both yeast and mammalian MAPK signaling cascades. Furthermore, inhibition of MAPK signaling by OspF is associated with attenuation of the host innate immune response to Shigella infection in a mouse model. These studies demonstrate how yeast systems biology can facilitate functional characterization of pathogenic bacterial effector proteins.
Author Summary
Many bacterial pathogens use specialized secretion systems to deliver effector proteins directly into host cells. The effector proteins mediate the subversion or inhibition of host cell processes to promote survival of the pathogens. Although these proteins are critical elements of pathogenesis, relatively few are well characterized. They often lack significant homology to proteins of known function, and they present special challenges, biological and practical, to study in vivo. For example, their functions often appear to be redundant or synergistic, and the organisms that produce them can be dangerous or difficult to culture, requiring special facilities. The yeast Saccharomyces cerevisiae has recently emerged as a model system to both identify and functionally characterize effector proteins. This work describes how genome-wide phenotypic screens and mRNA profiling of yeast expressing the Shigella effector OspF led to the discovery that OspF inhibits mitogen-activated protein kinase signaling in both yeast and mammalian cells. This inhibition of mitogen-activated protein kinase signaling is associated with attenuation of the host innate immune response. This study demonstrates how yeast functional genomic studies can contribute to the understanding of pathogenic effector proteins.
doi:10.1371/journal.ppat.0030021
PMCID: PMC1797620  PMID: 17305427
14.  Association between Selected Oral Pathogens and Gastric Precancerous Lesions 
PLoS ONE  2013;8(1):e51604.
We examined whether colonization of selected oral pathogens is associated with gastric precancerous lesions in a cross-sectional study. A total of 119 participants were included, of which 37 were cases of chronic atrophic gastritis, intestinal metaplasia, or dysplasia. An oral examination was performed to measure periodontal indices. Plaque and saliva samples were tested with real-time quantitative PCR for DNA levels of pathogens related to periodontal disease (Porphyromonas gingivalis, Tannerella forsythensis, Treponema denticola, Actinobacillus actinomycetemcomitans) and dental caries (Streptococcus mutans and S. sobrinus). There were no consistent associations between DNA levels of selected bacterial species and gastric precancerous lesions, although an elevated but non-significant odds ratio (OR) for gastric precancerous lesions was observed in relation to increasing colonization of A. actinomycetemcomitans (OR = 1.36 for one standard deviation increase, 95% Confidence Interval = 0.87–2.12), P. gingivalis (OR = 1.12, 0.67–1.88) and T. denticola (OR = 1.34, 0.83–2.12) measured in plaque. To assess the influence of specific long-term infection, stratified analyses by levels of periodontal indices were conducted. A. actinomycetemcomitans was significantly associated with gastric precancerous lesions (OR = 2.51, 1.13–5.56) among those with ≥ median of percent tooth sites with PD≥3 mm, compared with no association among those below the median (OR = 0.86, 0.43–1.72). A significantly stronger relationship was observed between the cumulative bacterial burden score of periodontal disease-related pathogens and gastric precancerous lesions among those with higher versus lower levels of periodontal disease indices (p-values for interactions: 0.03–0.06). Among individuals with periodontal disease, high levels of colonization of periodontal pathogens are associated with an increased risk of gastric precancerous lesions.
doi:10.1371/journal.pone.0051604
PMCID: PMC3538744  PMID: 23308100
15.  Strain-Specific Differences in the Genetic Control of Two Closely Related Mycobacteria 
PLoS Pathogens  2010;6(10):e1001169.
The host response to mycobacterial infection depends on host and pathogen genetic factors. Recent studies in human populations suggest a strain specific genetic control of tuberculosis. To test for mycobacterial-strain specific genetic control of susceptibility to infection under highly controlled experimental conditions, we performed a comparative genetic analysis using the A/J- and C57BL/6J-derived recombinant congenic (RC) mouse panel infected with the Russia and Pasteur strains of Mycobacterium bovis Bacille Calmette Guérin (BCG). Bacillary counts in the lung and spleen at weeks 1 and 6 post infection were used as a measure of susceptibility. By performing genome-wide linkage analyses of loci that impact on tissue-specific bacillary burden, we were able to show the importance of correcting for strain background effects in the RC panel. When linkage analysis was adjusted on strain background, we detected a single locus on chromosome 11 that impacted on pulmonary counts of BCG Russia but not Pasteur. The same locus also controlled the splenic counts of BCG Russia but not Pasteur. By contrast, a locus on chromosome 1 which was indistinguishable from Nramp1 impacted on splenic bacillary counts of both BCG Russia and Pasteur. Additionally, dependent upon BCG strain, tissue and time post infection, we detected 9 distinct loci associated with bacillary counts. Hence, the ensemble of genetic loci impacting on BCG infection revealed a highly dynamic picture of genetic control that reflected both the course of infection and the infecting strain. This high degree of adaptation of host genetics to strain-specific pathogenesis is expected to provide a suitable framework for the selection of specific host-mycobacteria combinations during co-evolution of mycobacteria with humans.
Author Summary
Susceptibility to mycobacterial infection results from a complex interaction between host and bacterial genetic factors. To examine the effect of host and pathogen genetic variability on the control of mycobacterial infection, we infected a panel of genetically related recombinant congenic (RC) mouse strains with two closely related strains of Mycobacterium bovis BCG. Bacterial counts of BCG Russia and BCG Pasteur were determined in the lung and spleen at 1 and 6 weeks following infection and used for genetic analysis. A novel analytical approach was developed to perform genome-wide linkage analyses using the RC strains. Comparative linkage analysis using this model identified a strong genetic effect on chromosome 1 controlling counts of BCG Pasteur at 1 week and of BCG Russia at 1 week and 6 weeks in the spleen. A locus impacting on late BCG Russia counts in the lung and spleen was identified on chromosome 11. Nine additional loci were shown to control bacterial counts in a tissue-, time-, and BCG strain-specific manner. Our findings suggest that the host genetic control of mycobacterial infection is highly dynamic and adapted to the stage of pathogenesis and to the infecting strain. Such a high degree of genetic plasticity in the host-pathogen interplay is expected to favour evolutionary co-adaptation in mycobacterial disease.
doi:10.1371/journal.ppat.1001169
PMCID: PMC2965770  PMID: 21060820
16.  Oral Chlamydia trachomatis in Patients with Established Periodontitis 
Clinical oral investigations  2000;4(4):226-232.
Periodontitis is considered a consequence of a pathogenic microbial infection at the periodontal site and host susceptibility factors. Periodontal research supports the association of Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis, Prevotella intermedia, and Bacteroides forsythus, and periodontitis; however causality has not been demonstrated. In pursuit of the etiology of periodontitis, we hypothesized that the intracellular bacteria, Chlamydia trachomatis, may play a role. As a first step, a cross-sectional study of dental school clinic patients with established periodontitis were assessed for the presence of C. trachomatis in the oral cavity, and in particular from the lining epithelium of periodontal sites. C. trachomatis was detected using a direct fluorescent monoclonal antibody (DFA) in oral specimens from 7% (6/87) of the patients. Four patients tested positive in specimens from the lining epithelium of diseased periodontal sites, one patient tested positive in healthy periodontal sites, and one patient tested positive in the general mucosal specimen. In conclusion, this study provides preliminary evidence of C. trachomatis in the periodontal sites. Planned studies include the use of a more precise periodontal epithelial cell collection device, the newer nucleic acid amplification techniques to detect C. trachomatis, and additional populations to determine the association of C. trachomatis and periodontitis.
PMCID: PMC2760468  PMID: 11218493
Chlamydia; Chlamydia trachomatis; Fluorescent antibody technique; Periodontal diseases; Periodontitis
17.  The Streamlined Genome of Phytomonas spp. Relative to Human Pathogenic Kinetoplastids Reveals a Parasite Tailored for Plants 
PLoS Genetics  2014;10(2):e1004007.
Members of the family Trypanosomatidae infect many organisms, including animals, plants and humans. Plant-infecting trypanosomes are grouped under the single genus Phytomonas, failing to reflect the wide biological and pathological diversity of these protists. While some Phytomonas spp. multiply in the latex of plants, or in fruit or seeds without apparent pathogenicity, others colonize the phloem sap and afflict plants of substantial economic value, including the coffee tree, coconut and oil palms. Plant trypanosomes have not been studied extensively at the genome level, a major gap in understanding and controlling pathogenesis. We describe the genome sequences of two plant trypanosomatids, one pathogenic isolate from a Guianan coconut and one non-symptomatic isolate from Euphorbia collected in France. Although these parasites have extremely distinct pathogenic impacts, very few genes are unique to either, with the vast majority of genes shared by both isolates. Significantly, both Phytomonas spp. genomes consist essentially of single copy genes for the bulk of their metabolic enzymes, whereas other trypanosomatids e.g. Leishmania and Trypanosoma possess multiple paralogous genes or families. Indeed, comparison with other trypanosomatid genomes revealed a highly streamlined genome, encoding for a minimized metabolic system while conserving the major pathways, and with retention of a full complement of endomembrane organelles, but with no evidence for functional complexity. Identification of the metabolic genes of Phytomonas provides opportunities for establishing in vitro culturing of these fastidious parasites and new tools for the control of agricultural plant disease.
Author Summary
Some plant trypanosomes, single-celled organisms living in phloem sap, are responsible for important palm diseases, inducing frequent expensive and toxic insecticide treatments against their insect vectors. Other trypanosomes multiply in latex tubes without detriment to their host. Despite the wide range of behaviors and impacts, these trypanosomes have been rather unceremoniously lumped into a single genus: Phytomonas. A battery of molecular probes has been used for their characterization but no clear phylogeny or classification has been established. We have sequenced the genomes of a pathogenic phloem-specific Phytomonas from a diseased South American coconut palm and a latex-specific isolate collected from an apparently healthy wild euphorb in the south of France. Upon comparison with each other and with human pathogenic trypanosomes, both Phytomonas revealed distinctive compact genomes, consisting essentially of single-copy genes, with the vast majority of genes shared by both isolates irrespective of their effect on the host. A strong cohort of enzymes in the sugar metabolism pathways was consistent with the nutritional environments found in plants. The genetic nuances may reveal the basis for the behavioral differences between these two unique plant parasites, and indicate the direction of our future studies in search of effective treatment of the crop disease parasites.
doi:10.1371/journal.pgen.1004007
PMCID: PMC3916237  PMID: 24516393
18.  Non-inflammatory destructive periodontal disease: a clinical, microbiological, immunological and genetic investigation 
Journal of Applied Oral Science  2012;20(1):113-121.
Periodontitis comprises a group of multifactorial diseases in which periodontopathogens accumulate in dental plaque and trigger host chronic inflammatory and immune responses against periodontal structures, which are determinant to the disease outcome. Although unusual cases of non-inflammatory destructive periodontal disease (NIDPD) are described, their pathogenesis remains unknown. A unique NIDPD case was investigated by clinical, microbiological, immunological and genetic tools. The patient, a non-smoking dental surgeon with excessive oral hygiene practice, presented a generalized bone resorption and tooth mobility, but not gingival inflammation or occlusion problems. No hematological, immunological or endocrine alterations were found. No periodontopathogens (A. actinomycetemcomitans, P. gingivalis, F. nucleatum and T. denticola) or viruses (HCMV, EBV-1 and HSV-1) were detected, along with levels of IL-1β and TNF-α in GCF compatible with healthy tissues. Conversely ALP, ACP and RANKL GCF levels were similar to diseased periodontal sites. Genetic investigation demonstrated that the patient carried some SNPs, as well HLA-DR4 (*0404) and HLA-B27 alleles, considered risk factors for bone loss. Then, a less vigorous and diminished frequency of toothbrushing was recommended to the patient, resulting in the arrest of alveolar bone loss, associated with the return of ALP, ACP and RANKL in GCF to normality levels. In conclusion, the unusual case presented here is compatible with the previous description of NIDPD, and the results that a possible combination of excessive force and frequency of mechanical stimulation with a potentially bone loss prone genotype could result in the alveolar bone loss seen in NIDPD.
doi:10.1590/S1678-77572012000100020
PMCID: PMC3928782  PMID: 22437688
Periodontal diseases; Non-inflammatory destructive periodontal
19.  Application of a Diode Laser in the Reduction of Targeted Periodontal Pathogens 
Acta Informatica Medica  2013;21(4):237-240.
Introduction:
Periodontal disease belongs to a group of diseases with more than one cause, it is a disease of a multifactorial etiology. Although bacteria are the main cause of the disease, immunoinflammatory reaction of the host is responsible for the majority of destructive changes in periodontal tissue. The main issue in the evaluation of the success of periodontal therapy is the pluralism of the bacteria and their dynamic changes during the duration, on the one hand, and the possible inaccuracy of classical microbiological analysis in determination of the dominant role of a microorganism, or the success of its reduction or elimination, on the other. Thanks to advances of microbiology and technological development, it is possible to make an assessment of specific microorganisms in a large number of samples of sub-gingival plaque with extreme precision, using checkerboard DNA-DNA hybridization and method of polymerase chain reaction (PCR). The development of laser technology and the discovery of its significant antimicrobial effects have introduced and presented this treatment modality as a possible auxiliary method of periodontitis treatment.
Materials and Methods:
The sample for the study estimating the efficiency of application of diode lasers in the reduction of periodontal pockets consisted of 1164 periodontal pockets in 24 subjects of both sexes. For laser irradiation of periodontal pockets a diode laser was used, a low-power laser (SmilePro 980, Biolitec, Germany), working in a mode precisely tuned for treatment of periodontal pockets. All subjects underwent: general anamnesis, periodontal status, and orthopantogram radiograph analysis. Following a standard periodontal preparation, a sample of subgingival plaque was collected for molecular-biological analysis (real-time PCR method) prior to laser irradiation of periodontal pockets, immediately following the irradiation, and during the control examination 3 months after irradiation.
Results:
The results of the molecular-biological analysis of target periodontal pathogens Actinobacillus (Aggregatibacter) actinomycetemcomitans (AA) and Porphyromonas gingivalis (PG) isolated from periodontal pockets prior to laser irradiation, immediately after laser irradiation, and at the control examination after 3 months were processed statistically (using real-time PCR method). The results showed that there was a statistically significant decrease in CT values for the tested bacteria immediately after treatment and the control examination, compared with the level of CT values for the same bacteria before treatment.
Conclusions:
Based on the obtained results, we concluded that diode laser irradiation reduces the number of active periodontal pathogens. We believe that the use of diode lasers, as a supplementary method in the treatment of periodontal disease, is extremely useful and efficient, and can be recommended as part of standard clinical practice.
doi:10.5455/aim.2013.21.237-240
PMCID: PMC3916176  PMID: 24554796
periodontal disease; periopathogen; diode laser; laser therapy.
20.  Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease 
PLoS ONE  2012;7(6):e37919.
The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.
doi:10.1371/journal.pone.0037919
PMCID: PMC3366996  PMID: 22675498
21.  Survey of Surface Proteins from the Pathogenic Mycoplasma hyopneumoniae Strain 7448 Using a Biotin Cell Surface Labeling Approach 
PLoS ONE  2014;9(11):e112596.
The characterization of the repertoire of proteins exposed on the cell surface by Mycoplasma hyopneumoniae (M. hyopneumoniae), the etiological agent of enzootic pneumonia in pigs, is critical to understand physiological processes associated with bacterial infection capacity, survival and pathogenesis. Previous in silico studies predicted that about a third of the genes in the M. hyopneumoniae genome code for surface proteins, but so far, just a few of them have experimental confirmation of their expression and surface localization. In this work, M. hyopneumoniae surface proteins were labeled in intact cells with biotin, and affinity-captured biotin-labeled proteins were identified by a gel-based liquid chromatography-tandem mass spectrometry approach. A total of 20 gel slices were separately analyzed by mass spectrometry, resulting in 165 protein identifications corresponding to 59 different protein species. The identified surface exposed proteins better defined the set of M. hyopneumoniae proteins exposed to the host and added confidence to in silico predictions. Several proteins potentially related to pathogenesis, were identified, including known adhesins and also hypothetical proteins with adhesin-like topologies, consisting of a transmembrane helix and a large tail exposed at the cell surface. The results provided a better picture of the M. hyopneumoniae cell surface that will help in the understanding of processes important for bacterial pathogenesis. Considering the experimental demonstration of surface exposure, adhesion-like topology predictions and absence of orthologs in the closely related, non-pathogenic species Mycoplasma flocculare, several proteins could be proposed as potential targets for the development of drugs, vaccines and/or immunodiagnostic tests for enzootic pneumonia.
doi:10.1371/journal.pone.0112596
PMCID: PMC4227723  PMID: 25386928
22.  Genome-wide association studies in ADHD 
Human Genetics  2009;126(1):13-50.
Attention-deficit/hyperactivity disorder, ADHD, is a common and highly heritable neuropsychiatric disorder that is seen in children and adults. Although heritability is estimated at around 76%, it has been hard to find genes underlying the disorder. ADHD is a multifactorial disorder, in which many genes, all with a small effect, are thought to cause the disorder in the presence of unfavorable environmental conditions. Whole genome linkage analyses have not yet lead to the identification of genes for ADHD, and results of candidate gene-based association studies have been able to explain only a tiny part of the genetic contribution to disease, either. A novel way of performing hypothesis-free analysis of the genome suitable for the identification of disease risk genes of considerably smaller effect is the genome-wide association study (GWAS). So far, five GWAS have been performed on the diagnosis of ADHD and related phenotypes. Four of these are based on a sample set of 958 parent–child trio’s collected as part of the International Multicentre ADHD Genetics (IMAGE) study and genotyped with funds from the Genetic Association Information Network (GAIN). The other is a pooled GWAS including adult patients with ADHD and controls. None of the papers reports any associations that are formally genome-wide significant after correction for multiple testing. There is also very limited overlap between studies, apart from an association with CDH13, which is reported in three of the studies. Little evidence supports an important role for the ‘classic’ ADHD genes, with possible exceptions for SLC9A9, NOS1 and CNR1. There is extensive overlap with findings from other psychiatric disorders. Though not genome-wide significant, findings from the individual studies converge to paint an interesting picture: whereas little evidence—as yet—points to a direct involvement of neurotransmitters (at least the classic dopaminergic, noradrenergic and serotonergic pathways) or regulators of neurotransmission, some suggestions are found for involvement of ‘new’ neurotransmission and cell–cell communication systems. A potential involvement of potassium channel subunits and regulators warrants further investigation. More basic processes also seem involved in ADHD, like cell division, adhesion (especially via cadherin and integrin systems), neuronal migration, and neuronal plasticity, as well as related transcription, cell polarity and extracellular matrix regulation, and cytoskeletal remodeling processes. In conclusion, the GWAS performed so far in ADHD, though far from conclusive, provide a first glimpse at genes for the disorder. Many more (much larger studies) will be needed. For this, collaboration between researchers as well as standardized protocols for phenotyping and DNA-collection will become increasingly important.
doi:10.1007/s00439-009-0663-4
PMCID: PMC3774416  PMID: 19384554
23.  Whole Blood Gene Expression Profiles to Assess Pathogenesis and Disease Severity in Infants with Respiratory Syncytial Virus Infection 
PLoS Medicine  2013;10(11):e1001549.
In this study, Mejias and colleagues found that specific blood RNA profiles of infants with RSV LRTI allowed for specific diagnosis, better understanding of disease pathogenesis, and better assessment of disease severity.
Please see later in the article for the Editors' Summary
Background
Respiratory syncytial virus (RSV) is the leading cause of viral lower respiratory tract infection (LRTI) and hospitalization in infants. Mostly because of the incomplete understanding of the disease pathogenesis, there is no licensed vaccine, and treatment remains symptomatic. We analyzed whole blood transcriptional profiles to characterize the global host immune response to acute RSV LRTI in infants, to characterize its specificity compared with influenza and human rhinovirus (HRV) LRTI, and to identify biomarkers that can objectively assess RSV disease severity.
Methods and Findings
This was a prospective observational study over six respiratory seasons including a cohort of infants hospitalized with RSV (n = 135), HRV (n = 30), and influenza (n = 16) LRTI, and healthy age- and sex-matched controls (n = 39). A specific RSV transcriptional profile was identified in whole blood (training cohort, n = 45 infants; Dallas, Texas, US) and validated in three different cohorts (test cohort, n = 46, Dallas, Texas, US; validation cohort A, n = 16, Turku, Finland; validation cohort B, n = 28, Columbus, Ohio, US) with high sensitivity (94% [95% CI 87%–98%]) and specificity (98% [95% CI 88%–99%]). It classified infants with RSV LRTI versus HRV or influenza LRTI with 95% accuracy. The immune dysregulation induced by RSV (overexpression of neutrophil, inflammation, and interferon genes, and suppression of T and B cell genes) persisted beyond the acute disease, and immune dysregulation was greatly impaired in younger infants (<6 mo). We identified a genomic score that significantly correlated with outcomes of care including a clinical disease severity score and, more importantly, length of hospitalization and duration of supplemental O2.
Conclusions
Blood RNA profiles of infants with RSV LRTI allow specific diagnosis, better understanding of disease pathogenesis, and assessment of disease severity. This study opens new avenues for biomarker discovery and identification of potential therapeutic or preventive targets, and demonstrates that large microarray datasets can be translated into a biologically meaningful context and applied to the clinical setting.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Lower respiratory tract infections (LRTIs)—bacterial and viral infections of the lungs and airways (the tubes that take oxygen-rich air to the lungs)—are major causes of illness and death in children worldwide. Pneumonia (infection of the lungs) alone is responsible for 14% of all child deaths. The leading cause of viral LTRIs in children is respiratory syncytial virus (RSV), which is readily transmitted from person to person by direct contact with nasal fluids or airborne droplets. Almost all children have an RSV infection before their second birthday, but most have only minor symptoms similar to those of a common cold and are cared for at home. Unfortunately, some children develop more serious conditions when they become infected with RSV, such as pneumonia or bronchiolitis (swelling and mucus build-up in the bronchioles, the smallest air passages in the lungs). These children have to be admitted to the hospital for supportive care—there is no specific treatment for RSV infection—such as the provision of supplemental oxygen.
Why Was This Study Done?
The lack of a treatment (and of a vaccine) for RSV is largely due to our incomplete understanding of the cellular events and reactions, including the host immune response, that occur during the development of an RSV infection (disease pathogenesis). Moreover, based on physical examination and available diagnostic tools, it is impossible to predict which children infected with RSV will develop a serious condition that requires hospitalization and which ones can be safely nursed at home. Here, the researchers use microarrays to analyze the global host response to acute RSV LTRI in infants, to define gene expression patterns that are specific to RSV infection rather than infection with other common respiratory viruses, and to identify biomarkers that indicate the severity of RSV infection. “Microarray” analysis allows researchers to examine gene expression patterns (“RNA transcriptional profiles”) in, for example, whole blood; a biomarker is a molecule whose level in bodily fluids or tissues indicates how a disease might develop and helps with patient classification.
What Did the Researchers Do and Find?
The researchers compared the RNA transcriptional profile in whole blood taken from children less than two years old hospitalized with RSV, human rhinovirus, or influenza virus infection (rhinovirus and influenza are two additional viral causes of LRTI), and from healthy infants. Using “statistical group comparisons,” they identified more than 2,000 transcripts that were differentially expressed in blood from 45 infants with RSV infection and from 14 healthy matched controls. Genes related to interferon function (interferons are released by host cells in response to the presence of disease-causing organisms) and neutrophil function (neutrophils are immune system cells that, like interferons, are involved in the innate immune response, the body's first line of defense against infection) were among the most overexpressed genes in infants infected with RSV. Genes regulating T and B cells (components of the adaptive immune response, the body's second-line of defense against infection) were among the most underexpressed genes. This specific transcriptional profile, which was validated in three additional groups of infants, accurately distinguished between infants infected with RSV and those infected with human rhinovirus or influenza virus. Finally, a “molecular distance to health” score (a numerical score that quantifies the transcriptional perturbation associated with an illness) was correlated with the clinical disease severity score of the study participants, with how long they needed supplemental oxygen, and with their duration of hospitalization.
What Do These Findings Mean?
These findings suggest that it might be possible to use whole blood RNA transcriptional profiles to distinguish between infants infected with RSV and those with other viruses that commonly cause LRTI. Moreover, if these findings can be replicated in more patients (including non-hospitalized children), gene expression profiling might provide a strategy for triaging patients with RSV infections when they first present to an emergency department and for monitoring clinical changes during the course of the infection, particularly given the development of molecular tools that might soon enable the “real time” acquisition of transcriptional profiles in the clinical setting. Finally, although certain aspects of the study design limit the accuracy and generalizability of the study's findings, these data provide new insights into the pathogenesis of RSV infection and open new avenues for the discovery of biomarkers for RSV infection and for the identification of therapeutic and preventative targets.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001549.
This study is further discussed in a PLOS Medicine Perspective by Peter Openshaw
The US Centers for Disease Control and Prevention provides information about RSV infection
The US National Heart, Lung, and Blood Institute provides information about the respiratory system and about RSV infections
The UK National Health Service Choices website provides information about bronchiolitis
The British Lung Foundation also provides information on RSV and on bronchiolitis
MedlinePlus provides links to other resources about RSV infections and about pneumonia (in English and Spanish); the MedlinePlus encyclopedia has a page on bronchiolitis (in English and Spanish)
PATH is an international non-profit organization investigating new RSV vaccines
doi:10.1371/journal.pmed.1001549
PMCID: PMC3825655  PMID: 24265599
24.  Comparative Pathogenomics Reveals Horizontally Acquired Novel Virulence Genes in Fungi Infecting Cereal Hosts 
PLoS Pathogens  2012;8(9):e1002952.
Comparative analyses of pathogen genomes provide new insights into how pathogens have evolved common and divergent virulence strategies to invade related plant species. Fusarium crown and root rots are important diseases of wheat and barley world-wide. In Australia, these diseases are primarily caused by the fungal pathogen Fusarium pseudograminearum. Comparative genomic analyses showed that the F. pseudograminearum genome encodes proteins that are present in other fungal pathogens of cereals but absent in non-cereal pathogens. In some cases, these cereal pathogen specific genes were also found in bacteria associated with plants. Phylogenetic analysis of selected F. pseudograminearum genes supported the hypothesis of horizontal gene transfer into diverse cereal pathogens. Two horizontally acquired genes with no previously known role in fungal pathogenesis were studied functionally via gene knockout methods and shown to significantly affect virulence of F. pseudograminearum on the cereal hosts wheat and barley. Our results indicate using comparative genomics to identify genes specific to pathogens of related hosts reveals novel virulence genes and illustrates the importance of horizontal gene transfer in the evolution of plant infecting fungal pathogens.
Author Summary
Cereals are our most important staple crops and are subject to attack from a diverse range of fungal pathogens. A major goal of molecular plant pathology research is to understand how pathogens infect plants to allow the development of durable plant protection measures. Comparing the genomes of different pathogens of cereals and contrasting them to non-cereal pathogen genomes allows for the identification of genes important for pathogenicity toward these important crops. In this study, we sequenced the genome of the wheat and barley pathogen F. pseudograminearum responsible for crown and root-rot diseases, and compared it to those from a broad range of previously sequenced fungal genomes from cereal and non-cereal pathogens. These analyses revealed that the F. pseudograminearum genome contains a number of genes only found in fungi pathogenic on cereals. Some of these genes appear to have been horizontally acquired from other fungi and, in some cases, from plant associated bacteria. The functions of two of these genes were tested by creating strains that lacked the genes. Both genes had important roles in causing disease on cereals. This work has important implications for our understanding of pathogen specialization during the evolution of fungal pathogens infecting cereal crops.
doi:10.1371/journal.ppat.1002952
PMCID: PMC3460631  PMID: 23028337
25.  Predictive, preventive, personalised and participatory periodontology: ‘the 5Ps age’ has already started 
The EPMA Journal  2013;4(1):16.
An impressive progress in dentistry has been recorded in the last decades. In order to reconsider guidelines in dentistry, it is required to introduce new concepts of personalised patient treatments: the wave of predictive, preventive and personalised medicine is rapidly incoming in dentistry. Worldwide dentists have to make a big cultural effort in changing the actual ‘reactive’ therapeutic point of view, belonging to the last century, into a futuristic ‘predictive’ one. The first cause of tooth loss in industrialised world is periodontitis, a Gram-negative anaerobic infection whose pathogenesis is genetically determined and characterised by complex immune reactions. Chairside diagnostic tests based on saliva, gingival crevicular fluid and cell sampling are going to be routinely used by periodontists for a new approach to the diagnosis, monitoring, prognosis and management of periodontal patients. The futuristic ‘5Ps’ (predictive, preventive, personalised and participatory periodontology) focuses on early integrated diagnosis (genetic, microbiology, host-derived biomarker detection) and on the active role of the patient in which networked patients will shift from being mere passengers to responsible drivers of their health. In this paper, we intend to propose five diagnostic levels (high-tech diagnostic tools, genetic susceptibility, bacterial infection, host response factors and tissue breakdown-derived products) to be evaluated with the intention to obtain a clear picture of the vulnerability of a single individual to periodontitis in order to organise patient stratification in different categories of risk. Lab-on-a-chip (LOC) technology may soon become an important part of efforts to improve worldwide periodontal health in developed nations as well as in the underserved communities, resource-poor areas and poor countries. The use of LOC devices for periodontal inspection will allow patients to be screened for periodontal diseases in settings other than the periodontist practice, such as at general practitioners, general dentists or dental hygienists. Personalised therapy tailored with respect to the particular medical reality of the specific stratified patient will be the ultimate target to be realised by the 5Ps approach. A long distance has to be covered to reach the above targets, but the pathway has already been clearly outlined.
doi:10.1186/1878-5085-4-16
PMCID: PMC3703280  PMID: 23763842
Predictive periodontology; Preventive periodontology; Personalised periodontology; Participatory periodontology; Lab-on-a-chip; Gas chromatographs; Cone beam computed tomography; Host-derived diagnostic markers; Saliva; Gingival crevicular fluid

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