Review of microarray studies for host-intracellular pathogen interactions

Mitigating the Impact of Antibacterial Drug Resistance through Host-Directed Therapies: Current Progress, Outlook, and Challenges

Increasing incidences of multidrug resistance in pathogenic bacteria threaten our ability to treat and manage bacterial infection. The development and FDA approval of novel antibiotics have slowed over the past decade; therefore, the adoption and improvement of alternative therapeutic strategies are critical for addressing the threat posed by multidrug-resistant bacteria. Host-directed therapies utilize small-molecule drugs and proteins to alter the host response to pathogen infection. Here, we highlight strategies for modulating the host inflammatory response to enhance bacterial clearance, small-molecule potentiation of innate immunity, and targeting of host factors that are exploited by pathogen virulence factors. Application of state-of-the-art "omic" technologies, including proteomics, transcriptomics, and image-omics (image-based high-throughput phenotypic screening), combined with powerful bioinformatics tools will enable the modeling of key signaling pathways in the host-pathogen interplay and aid in the identification of host proteins for therapeutic targeting and the discovery of host-directed small molecules that will regulate bacterial infection. We conclude with an outlook on research needed to overcome the challenges associated with transitioning host-directed therapies into a clinical setting.

How to Predict Molecular Interactions between Species?

Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, with the help of high-throughput experiments such as RNA-seq or microarrays. The adaptation of the gene expression to environmental changes within cells is mediated through complex gene regulatory networks. Often, our knowledge of these networks is incomplete. Network inference predicts gene regulatory interactions based on transcriptome data. An emerging application of high-throughput transcriptome studies are dual transcriptomics experiments. Here, the transcriptome of two or more interacting species is measured simultaneously. Based on a dual RNA-seq data set of murine dendritic cells infected with the fungal pathogen Candida albicans, the software tool NetGenerator was applied to predict an inter-species gene regulatory network. To promote further investigations of molecular inter-species interactions, we recently discussed dual RNA-seq experiments for host-pathogen interactions and extended the applied tool NetGenerator (Schulze et al., 2015). The updated version of NetGenerator makes use of measurement variances in the algorithmic procedure and accepts gene expression time series data with missing values. Additionally, we tested multiple modeling scenarios regarding the stimuli functions of the gene regulatory network. Here, we summarize the work by Schulze et al. (2015) and put it into a broader context. We review various studies making use of the dual transcriptomics approach to investigate the molecular basis of interacting species. Besides the application to host-pathogen interactions, dual transcriptomics data are also utilized to study mutualistic and commensalistic interactions. Furthermore, we give a short introduction into additional approaches for the prediction of gene regulatory networks and discuss their application to dual transcriptomics data. We conclude that the application of network inference on dual-transcriptomics data is a promising approach to predict molecular inter-species interactions.

The bacterial pangenome as a new tool for analysing pathogenic bacteria

The bacterial pangenome was introduced in 2005 and, in recent years, has been the subject of many studies. Thanks to progress in next-generation sequencing methods, the pangenome can be divided into two parts, the core (common to the studied strains) and the accessory genome, offering a large panel of uses. In this review, we have presented the analysis methods, the pangenome composition and its application as a study of lifestyle. We have also shown that the pangenome may be used as a new tool for redefining the pathogenic species. We applied this to the Escherichia coli and Shigella species, which have been a subject of controversy regarding their taxonomic and pathogenic position.

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Pangenome is a new way of studying pathogenic bacteria.

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Pangenome can be used as a taxonomic tool.

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This review describes pangenome in the world of pathogenic bacteria.

Early transcriptional responses of internalization defective Brucella abortus mutants in professional phagocytes, RAW 264.7

Background

Brucella abortus is an intracellular zoonotic pathogen which causes undulant fever, endocarditis, arthritis and osteomyelitis in human and abortion and infertility in cattle. This bacterium is able to invade and replicate in host macrophage instead of getting removed by this defense mechanism. Therefore, understanding the interaction between virulence of the bacteria and the host cell is important to control brucellosis. Previously, we generated internalization defective mutants and analyzed the envelope proteins. The present study was undertaken to evaluate the changes in early transcriptional responses between wild type and internalization defective mutants infected mouse macrophage, RAW 264.7.

Results

Both of the wild type and mutant infected macrophages showed increased expression levels in proinflammatory cytokines, chemokines, apoptosis and G-protein coupled receptors (Gpr84, Gpr109a and Adora2b) while the genes related with small GTPase which mediate intracellular trafficking was decreased. Moreover, cytohesin 1 interacting protein (Cytip) and genes related to ubiquitination (Arrdc3 and Fbxo21) were down-regulated, suggesting the survival strategy of this bacterium. However, we could not detect any significant changes in the mutant infected groups compared to the wild type infected group.

Conclusions

In summary, it was very difficult to clarify the alterations in host cellular transcription in response to infection with internalization defective mutants. However, we found several novel gene changes related to the GPCR system, ubiquitin-proteosome system, and growth arrest and DNA damages in response to B. abortus infection. These findings may contribute to a better understanding of the molecular mechanisms underlying host-pathogen interactions and need to be studied further.

Host gene expression and respiratory syncytial virus infection

Advances in RNA interference (RNAi) and transcription studies have facilitated the application of systematic cell-based loss- or gain-of-function and cell response screening that enable genome-wide analysis of cell factors involved in viral replication and disease. Application of both experimental and computational biology approaches have led to crucial insights into virus infection, its life cycle, and host gene targets for disease intervention. A better understanding of the spatial and temporal host gene interactions during viral infection has enabled insights into mechanisms by which viral proteins co-opt host cell function, and host regulatory mechanisms that influence disease and treatment outcome. In this chapter, approaches to host gene discovery and transcriptome profiling for respiratory syncytial virus (RSV) are discussed in the context of biological relevance for disease intervention in the clinical setting and vaccine development.

DNA microarrays for the diagnosis of infectious diseases

The diagnosis of bacterial infections relies on isolation of the bacterium, which is rarely achieved when needed for patient management. Furthermore, culture is poorly suited to the diagnosis of polymicrobial infections. Finally, a syndromic approach should target both bacteria and viruses causing the same syndrome. The detection of specific DNA sequences in clinical specimen, using DNA microarrays, is an alternative. Microarrays were first used as a diagnostic tool in 1993, to identify a hantavirus associated with an outbreak of acute respiratory diseases. The main advantage of microarrays is multiplexing, enabling exploration of the microbiota and pathogen detection in bacteremia, respiratory infections, and digestive infections: circumstance in which DNA arrays may lack sensitivity and provide false negatives. Enrichment of sampling can increase sensitivity. Furthermore, chips allow typing Streptococcus pneumoniae and detecting resistance in Staphylococcus aureus (MRSA) and Mycobacterium tuberculosis (rifampicin, isoniazid, fluoroquinolones). However, the cost and high technical requirements remain a problem for routine use of this bacterial infection diagnostic technology.

Diagnostic des infections bactériennes par les puces à ADN

Le diagnostic des infections bactériennes repose sur l’isolement du pathogène, qui ne peut pas être réalisé dans le temps du soin. Egalement, la culture est mal adaptée au diagnostic des infections polymicrobiennes. Une alternative est la détection de séquences ADN spécifiques dans l’échantillon clinique par les puces à ADN. La première utilisation des puces à ADN en tant qu’outil diagnostic date de 1995. Cette revue porte sur la mise au point de différentes puces à ADN pour la détection des bactéries pathogènes au cours des infections respiratoires, digestives et systémiques. Ces études ont permis de montrer que les puces à ADN sont un outil fiable, rapide et reproductible pour le diagnostic des maladies infectieuses d’origine bactérienne. Le coût et la technicité demeurent deux freins au déploiement en routine de cette technologie pour le diagnostic des infections bactériennes.

Effect of antibiotic treatment on the intestinal metabolome

The importance of the mammalian intestinal microbiota to human health has been intensely studied over the past few years. It is now clear that the interactions between human hosts and their associated microbial communities need to be characterized in molecular detail if we are to truly understand human physiology. Additionally, the study of such host-microbe interactions is likely to provide us with new strategies to manipulate these complex systems to maintain or restore homeostasis in order to prevent or cure pathological states. Here, we describe the use of high-throughput metabolomics to shed light on the interactions between the intestinal microbiota and the host. We show that antibiotic treatment disrupts intestinal homeostasis and has a profound impact on the intestinal metabolome, affecting the levels of over 87% of all metabolites detected. Many metabolic pathways that are critical for host physiology were affected, including bile acid, eicosanoid, and steroid hormone synthesis. Dissecting the molecular mechanisms involved in the impact of beneficial microbes on some of these pathways will be instrumental in understanding the interplay between the host and its complex resident microbiota and may aid in the design of new therapeutic strategies that target these interactions.

Subpopulation-specific metabolic pathway usage in mixed cultures as revealed by reporter protein-based 13C analysis

Most large-scale biological processes, like global element cycling or decomposition of organic matter, are mediated by microbial consortia. Commonly, the different species in such consortia exhibit mutual metabolic dependencies that include the exchange of nutrients. Despite the global importance, surprisingly little is known about the metabolic interplay between species in particular subpopulations. To gain insight into the intracellular fluxes of subpopulations and their interplay within such mixed cultures, we developed here a (13)C flux analysis approach based on affinity purification of the recombinant fusion glutathione S-transferase (GST) and green fluorescent protein (GFP) as a reporter protein. Instead of detecting the (13)C labeling patterns in the typically used amino acids from the total cellular protein, our method detects these (13)C patterns in amino acids from the reporter protein that has been expressed in only one species of the consortium. As a proof of principle, we validated our approach by mixed-culture experiments of an Escherichia coli wild type with two metabolic mutants. The reporter method quantitatively resolved the expected mutant-specific metabolic phenotypes down to subpopulation fractions of about 1%.

Coxiella burnetii transcriptional analysis reveals serendipity clusters of regulation in intracellular bacteria

Coxiella burnetii, the causative agent of the zoonotic disease Q fever, is mainly transmitted to humans through an aerosol route. A spore-like form allows C. burnetii to resist different environmental conditions. Because of this, analysis of the survival strategies used by this bacterium to adapt to new environmental conditions is critical for our understanding of C. burnetii pathogenicity. Here, we report the early transcriptional response of C. burnetii under temperature stresses. Our data show that C. burnetii exhibited minor changes in gene regulation under short exposure to heat or cold shock. While small differences were observed, C. burnetii seemed to respond similarly to cold and heat shock. The expression profiles obtained using microarrays produced in-house were confirmed by quantitative RT-PCR. Under temperature stresses, 190 genes were differentially expressed in at least one condition, with a fold change of up to 4. Globally, the differentially expressed genes in C. burnetii were associated with bacterial division, (p)ppGpp synthesis, wall and membrane biogenesis and, especially, lipopolysaccharide and peptidoglycan synthesis. These findings could be associated with growth arrest and witnessed transformation of the bacteria to a spore-like form. Unexpectedly, clusters of neighboring genes were differentially expressed. These clusters do not belong to operons or genetic networks; they have no evident associated functions and are not under the control of the same promoters. We also found undescribed but comparable clusters of regulation in previously reported transcriptomic analyses of intracellular bacteria, including Rickettsia sp. and Listeria monocytogenes. The transcriptomic patterns of C. burnetii observed under temperature stresses permits the recognition of unpredicted clusters of regulation for which the trigger mechanism remains unidentified but which may be the result of a new mechanism of epigenetic regulation.