A history of studies that examine the interactions of Toxoplasma with its host cell: Emphasis on in vitro models

This review is a historical look at work carried out over the past 50 years examining interactions of Toxoplasma with the host cell and attempts to focus on some of the seminal experiments in the field. This early work formed the foundation for more recent studies aimed at identifying the host and parasite factors mediating key Toxoplasma-host cell interactions. We focus especially on those studies that were performed in vitro and provide discussions of the following general areas: (i) establishment of the parasitophorous vacuole, (ii) the requirement of specific host cell molecules for parasite replication, (iii) the scenarios under which the host cell can resist parasite replication and/or persistence, (iv) host species-specific and host strain-specific responses to Toxoplasma infection, and (v) Toxoplasma-induced immune modulation.     

The evolutionary consequences of plasticity in host-pathogen interactions

Interactions between individuals such as hosts and pathogens are often characterized by substantial phenotypic plasticity. Pathogens sometimes alter their exploitation strategies in response to defensive strategies adopted by their host and vice versa. Nevertheless, most game-theoretic models developed to explain the evolution of pathogen and host characteristics assume that no such plasticity occurs. Allowing for phenotypic plasticity in these models is difficult because one must focus on the evolution of pathogen and host reaction norms, and then allow for the potentially indefinite reciprocal changes in pathogen and host behaviour that occur during an infection as a result of their interacting reaction norms. Here, we begin to address these issues for a simple host-pathogen system in which the pathogen exhibits a level of virulence and the host exhibits a level of immune clearance. We find, quite generally, that plasticity promotes the evolution of higher levels of cooperation, in this case leading to reduced levels of both virulence and clearance.     

Mouse pathogenicity studies of Nocardia asteroides complex species and clinical correlation with human isolates

Abstract Nocardia asteroides complex organisms derived from human specimens between 1979 and 1992 were identified on the species level. Of 117 N. asteroides complex organisms, 34 (29%) were N. farcinica , 28 (24%) were N. nova , and 55 (47%) were N. asteroides sensu stricto . An analysis of the specimen sites from which the organisms were derived showed that isolates derived from blood, brain, or bone marrow were more likely to be N. farcinica than the other two species. A study of the virulence of ten strains of each species was undertaken, using a mouse model with intravenous inoculation. The 50% lethal doses (LD₅₀) for N. farcinica were significantly lower than those of the other two species. LD₅₀ values for N. nova and N. asteroides were not significantly different. The above data confirming the greater virulence of N. farcinica support the identification of species within the N. asteroides complex.     

Illuminating the host – How RNAi screens shed light on host-pathogen interactions

Over millions of years pathogens have coevolved with their respective hosts utilizing host cell functions for survival and replication. Despite remarkable progress in developing antibiotics and vaccination strategies in the last century, infectious diseases still remain a severe threat to human health. Meanwhile, genomic research offers a new era of data-generating platforms that will dramatically enhance our knowledge of pathogens and the diseases they cause. Improvements in gene knockdown studies by RNA interference (RNAi) combined with recent developments in instrumentation and image analysis enable the use of high-throughput screening approaches to elucidate host gene functions exploited by pathogens. Although only a few RNAi-based screens focusing on host genes have been reported so far, these studies have already uncovered hundreds of genes not previously known to be involved in pathogen infection. This review describes recent progress in RNAi screening approaches, highlighting both the limitations and the tremendous potential of RNAi-based screens for the identification of essential host cell factors during infection.     

A Bayesian mixture model for metaanalysis of microarray studies

The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs control. A recent Bayesian metaanalysis model used a prior distribution for the mean log-expression ratios that was a mixture of two normal distributions. This model centered the prior distribution of differential expression at zero, and separated genes into two groups only: expressed and nonexpressed. Here, we introduce a Bayesian three-component truncated normal mixture prior model that more flexibly assigns prior distributions to the differentially expressed genes and produces three groups of genes: up and downregulated, and nonexpressed. We found in simulations of two and five studies that the three-component model outperformed the two-component model using three comparison measures. When analyzing biological data of Bacillus subtilis, we found that the three-component model discovered more genes and omitted fewer genes for the same levels of posterior probability of differential expression than the two-component model, and discovered more genes for fixed thresholds of Bayesian false discovery. We assumed that the data sets were produced from the same microarray platform and were prescaled.     

Design considerations for efficient and effective microarray studies

This article describes the theoretical and practical issues in experimental design for gene expression microarrays. Specifically, this article 1) discusses the basic principles of design (randomization, replication, and blocking) as they pertain to microarrays, and 2) provides some general guidelines for statisticians designing microarray studies.     

Using ANOVA for gene selection from microarray studies of the nervous system

Methods are presented for detecting differential expression using statistical hypothesis testing methods including analysis of variance (ANOVA). Practicalities of experimental design, power, and sample size are discussed. Methods for multiple testing correction and their application are described. Instructions for running typical analyses are given in the R programming environment. R code and the sample data set used to generate the examples are available at http://microarray.cpmc.columbia.edu/pavlidis/pub/aovmethods/.     

Host pathogen protein interactions predicted by comparative modeling

Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host-pathogen interactions involve protein-protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host-pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for "neglected" human diseases. The method was assessed by (1) comparison to a set of known host-pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host-pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host-pathogen protein interactions.     

Presence of cna, emp and pls genes and pathogenicity of methicillin-resistant Staphylococcus aureus strains

Methicillin-resistant strains of Staphylococcus aureus (MRSA) are important etiological factors responsible for hospital-acquired infections. The aim of this study was to analyze the influence of the presence of emp, pls and cna genes on the pathogenicity of MRSA strains. The presence of these genes was tested by PCR in 302 MRSA strains isolated from hospitalized patients and from carriers. For each tested gene, proportions of positive and negative strains were similar among the infected patients and carriers. We did not find any obvious correlation between the presence of the three tested genes and the infectivity of strains. Our results may also suggest that a lack of emp and presence of pls may correlate with reduced virulence of these strains.     

Coevolutionary cycling of host sociality and pathogen virulence in contact networks

Infectious diseases may place strong selection on the social organization of animals. Conversely, the structure of social systems can influence the evolutionary trajectories of pathogens. While much attention has focused on the evolution of host sociality or pathogen virulence separately, few studies have looked at their coevolution. Here we use an agent-based simulation to explore host-pathogen coevolution in social contact networks. Our results indicate that under certain conditions, both host sociality and pathogen virulence exhibit continuous cycling. The way pathogens move through the network (e.g., their interhost transmission and probability of superinfection) and the structure of the network can influence the existence and form of cycling.     

Distant interactions in bacteria

Exchange of information between bacteria via physical signals, referred to as “distant interactions” (DI), is the subject of this review. All cases of DI reported to date are discussed, as well as the history of these studies and the place of DI in bacterial communication. Bacterial DI are a particular case of DI occurring in nature (in plants, animals, and fungi). Along with the chemical signals of intracellular communications, DI play a significant role in the life of microorganisms, especially during critical and transitional periods.     

Definitions of pathogenicity and virulence in invertebrate pathology

Accurate definition and usage of terminology are critical to effective communication in science. In a recently published article, the clarity and consistency of the terms pathogenicity and virulence as used in invertebrate pathology were called into question, and a revision of these terms was proposed. Our objective was to examine definitions of pathogenicity and virulence and their use in invertebrate pathology, and respond to this article. Although usage of the terms pathogenicity and virulence varies, we found considerable consistency in the published definitions of these terms in the invertebrate pathology literature throughout the history of the discipline, as well as among related disciplines such as medicine and microbiology. We did not find the established definitions to be lacking in clarity or utility. Therefore, we recommend that the definition and use of these terms adhere to precedence. Specifically, pathogenicity is the quality or state of being pathogenic, the potential ability to produce disease, whereas virulence is the disease producing power of an organism, the degree of pathogenicity within a group or species. Pathogenicity is a qualitative term, an “all-or-none” concept, whereas virulence is a term that quantifies pathogenicity.     

Study of stem cell function using microarray experiments

DNA Microarrays are used to simultaneously measure the levels of thousands of mRNAs in a sample. We illustrate here that a collection of such measurements in different cell types and states is a sound source of functional predictions, provided the microarray experiments are analogous and the cell samples are appropriately diverse. We have used this approach to study stem cells, whose identity and mechanisms of control are not well understood, generating Affymetrix microarray data from more than 200 samples, including stem cells and their derivatives, from human and mouse. The data can be accessed online (StemBase; http://www.scgp.ca:8080/StemBase/).     

Lipidomics of host-pathogen interactions

The cell biology of intracellular pathogens (viruses, bacteria, eukaryotic parasites) has provided us with molecular information of host-pathogen interactions. As a result it is becoming increasingly evident that lipids play important roles at various stages of host-pathogen interactions. They act in first line recognition and host cell signaling during pathogen docking, invasion and intracellular trafficking. Lipid metabolism is a housekeeping function in energy homeostasis and biomembrane synthesis during pathogen replication and persistence. Lipids of enormous chemical diversity play roles as immunomodulatory factors. Thus, novel biochemical analytics in combination with cell and molecular biology are a promising recipe for dissecting the roles of lipids in host-pathogen interactions.     

Bacteriocin‐mediated interactions within and between coexisting species

Bacteriocins are bacteriocidal toxins released by almost all bacteria. They are thought to have a narrow range of killing, but as bacteriocin‐mediated interactions have been rarely studied at biologically relevant scales, whether this narrow range of action falls mostly within or mostly between coexisting species in natural communities is an open question with important ecological and evolutionary implications. In a previous study, we systematically sampled Xenorhabdus bacteria along a hillside and found evidence for genotypic variability and bacteriocin‐mediated interactions within Xenorhabdus bovienii and X. koppenhoeferi colonies that were collected only a few meters apart. In contrast, colonies that were isolated from the same soil sample were always genetically similar and showed no inhibitions. Here, we conducted pairwise growth‐inhibition assays within and between seven X. bovienii and five X. koppenhoeferi colonies that were isolated from different soil samples; all seven X. bovienii colonies and at least three of the X. koppenhoeferi have been distinguished as distinct genotypes based on coarse‐grain genomic markers. We found signatures for both conspecific and heterospecific bacteriocin inhibitions in this natural community of Xenorhabdus bacteria, but intraspecific inhibitions were significantly more common than interspecific inhibitions. These results suggest that bacteriocins have a major role in intraspecific competition in nature, but also suggest that bacterocins are important in mediating interspecific interactions among coexisting species in natural communities.     

Observations on interactions between naturally-collected bacteria and several species of algae

Interactions between a naturally-collected algal species and strains of bacteria with which it was closely associated were examined under controlled conditions. Three strains of bacteria, Pseudomonas, Xanthomonas and Flavobacterium, were isolated from Oscillatoria. These bacteria were grown in combination with axenic cultures of the Oscillatoria culture as well as with several additional algal species. Oscillatoria growth was stimulated by all of the bacteria, but other algal species varied in their response. Some were stimulated, but others were inhibited or unaffected by exposure to the bacterial strains. There were also observations indicating that some algae may be able to develop resistance to antagonistic bacteria. These data suggest that succession and dominance of individual algal species may be influenced by interactions with bacteria.     

Gene expression profiling of candidate virulence factors in the laminated root rot pathogen Phellinus sulphurascens

Background

Phellinus sulphurascens is a fungal pathogen that causes laminar root rot in conifers, one of the most damaging root diseases in western North America. Despite its importance as a forest pathogen, this fungus is still poorly studied at the genomic level. An understanding of the molecular events involved in establishment of the disease should help to develop new methods for control of this disease.

Results

We generated over 4600 expressed sequence tags from two cDNA libraries constructed using either mycelia grown on cellophane sheets and exposed to Douglas-fir roots or tissues from P. sulphurascens-infected Douglas-fir roots. A total of 890 unique genes were identified from the two libraries, and functional classification of 636 of these genes was possible using the Functional Catalogue (FunCat) annotation scheme. cDNAs were identified that encoded 79 potential virulence factors, including numerous genes implicated in virulence in a variety of phytopathogenic fungi. Many of these putative virulence factors were also among 82 genes identified as encoding putatively secreted proteins. The expression patterns of 86 selected fungal genes over 7 days of infection of Douglas-fir were examined using real-time PCR, and those significantly up-regulated included rhamnogalacturonan acetylesterase, 1,4-benzoquinone reductase, a cyclophilin, a glucoamylase, 3 hydrophobins, a lipase, a serine carboxypeptidase, a putative Ran-binding protein, and two unknown putatively secreted proteins called 1 J04 and 2 J12. Significantly down-regulated genes included a manganese-superoxide dismutase, two metalloproteases, and an unknown putatively secreted protein called Ps0058.

Conclusions

This first collection of Phellinus sulphurascens EST sequences and its annotation provide an important resource for future research aimed at understanding key virulence factors of this forest pathogen. We examined the expression patterns of numerous fungal genes with potential roles in virulence, and found a collection of functionally diverse genes that are significantly up- or down-regulated during infection of Douglas-fir seedling roots by P. sulphurascens.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-603) contains supplementary material, which is available to authorized users.     

Optimization of fragmentation conditions for microarray analysis of viral RNA

An important consideration in microarray analysis of nucleic acids is the efficiency with which the target molecule is captured by, or hybridized to, surface-immobilized oligos. For RNA, secondary and tertiary structure of the target strand can significantly decrease capture efficiency. To overcome this limitation, RNA is often fragmented to reduce structural effects. In this study, the metal ion-catalyzed base hydrolysis fragmentation conditions for viral RNA extracted from influenza viruses were evaluated and the hybridization efficiency of the resulting fragments was determined as a function of fragment length. The amount of RNA captured was evaluated qualitatively by fluorescence intensity normalized to an internal standard. Optimized conditions for influenza RNA were determined to include a fragmentation time of 20-30 min at 75 degrees C. These conditions resulted in a maximum concentration of fragments between 38 and 150 nt in length and a maximum in the capture and label efficiency.