Adhesion and host cell modulation: critical pathogenicity determinants of Bartonella henselae

Four decades of experience of prosthetic valve endocarditis reflect a high variety of diverse pathogens

Prosthetic valve endocarditis (PVE) remains a serious condition with a high mortality rate. Precise identification of the PVE-associated pathogen/s and their virulence is essential for successful therapy, and patient survival. The commonly described PVE-associated pathogens are staphylococci, streptococci and enterococci, with Staphylococcus aureus being the most frequently diagnosed species. Furthermore, multi-drug resistance pathogens are increasing in prevalence, and continue to pose new challenges mandating a personalized approach. Blood cultures in combination with echocardiography are the most common methods to diagnose PVE, often being the only indication, it exists. In many cases, the diagnostic strategy recommended in the clinical guidelines does not identify the precise microbial agent and to frequently, false negative blood cultures are reported. Despite the fact that blood culture findings are not always a good indicator of the actual PVE agent in the valve tissue, only a minority of re-operated prostheses are subjected to microbiological diagnostic evaluation. In this review, we focus on the diversity and the complete spectrum of PVE-associated bacterial, fungal and viral pathogens in blood, and prosthetic heart valve, their possible virulence potential, and their challenges in making a microbial diagnosis. We are curious to understand if the unacceptable high mortality of PVE is associated with the high number of negative microbial findings in connection with a possible PVE. Herein, we discuss the possibilities and limits of the diagnostic methods conventionally used and make recommendations for enhanced pathogen identification. We also show possible virulence factors of the most common PVE-associated pathogens and their clinical effects. Based on blood culture, molecular biological diagnostics, and specific valve examination, better derivations for the antibiotic therapy as well as possible preventive intervention can be established in the future.

Development of a Multiplex Droplet Digital PCR Assay for the Detection of Babesia, Bartonella, and Borrelia Species

We describe the development, optimization, and validation of a multiplex droplet digital PCR (ddPCR) assay for the simultaneous detection of Babesia, Bartonella, and Borrelia spp. DNA from several sample matrices, including clinical blood samples from animals and humans, vectors, in-vitro infected human and animal cell lines, and tissues obtained from animal models (infected with Bartonella and/or B. burgdorferi). The multiplex ddPCR assay was able to detect 31 Bartonella, 13 Borrelia, and 24 Babesia species, including Theileria equi, T. cervi, and Cytauxzoon felis. No amplification of Treponema or Leptospira spp. was observed. Sensitivity of 0.2-5 genome equivalent DNA copies per microliter was achieved for different members of the Bartonella and Borrelia genus, depending on the species or matrix type (water or spiked blood DNA) tested. The ddPCR assay facilitated the simultaneous detection of co-infections with two and three vector-borne pathogens comprising four different genera (Babesia, Bartonella, Borrelia, and Theileria) from clinical and other sample sources.

Development and validation of a droplet digital PCR assay for the detection and quantification of Bartonella species within human clinical samples

This report describes the development, optimization, and validation of a ddPCR assay for the detection of Bartonella spp. DNA within several sample matrices, including clinical blood samples from patients with or without documented Bartonella spp. bacteremia. The Bartonella spp. ddPCR assay was developed based upon previously published TaqMan-based qPCR assays that can amplify DNA of over 25 Bartonella spp. Host DNA (housekeeping gene) amplification serves as a reference target to facilitate quantification. The efficiency, sensitivity, and specificity of the Bartonella spp. ddPCR assay was assessed by direct comparison with the current qPCR methods used by the Intracellular Pathogens Research Laboratory (North Carolina State University, North Carolina, USA), and Galaxy Diagnostics (Research Triangle Park, North Carolina, USA). Bartonella spp. ddPCR assay parameters were successfully optimized to detect Bartonella concentrations equivalent to 0.5 bacterial genome copies per microliter of blood (0.001 pg/ul of bacterial DNA). The number of droplets detected (resolution) for each concentration was consistent across each of four assessed time points. The Bartonella spp. ddPCR assay detected 16 species/strains including B. henselae; B. quintana; B. vinsonii subsp. berkhoffii (genotypes I, II, III and IV); B. vinsonii subsp. vinsonii; B. melophagi; B. volans; B. monaki; B. alsatica; B. bovis; B. elizabethae; B. clarridgeiae; and B. koehlerae. Bartonella DNA was detected in only one previously negative patient sample (119/120 negative; 99% specificity). The ddPCR sensitivity (53/112) was significantly better than qPCR (6/112) when testing patient blood and enrichment blood culture samples. The development of commercial ddPCR systems with integrated technologies has significantly streamlined the DNA detection process, making it more efficient and standardized for clinical diagnostic testing. The assay described in this work is the first step toward the development of a multiplex ddPCR assay (i.e., using the QX One from Bio-Rad) for the simultaneous detection and absolute quantification of multiple vector-borne pathogens (such as Babesia, Bartonella and Borrelia) within clinical samples.

Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism

Proteomics data provide unique insights into biological systems, including the predominant subcellular localization (SCL) of proteins, which can reveal important clues about their functions. Here we analyzed data of a complete prokaryotic proteome expressed under two conditions mimicking interaction of the emerging pathogen Bartonella henselae with its mammalian host. Normalized spectral count data from cytoplasmic, total membrane, inner and outer membrane fractions allowed us to identify the predominant SCL for 82% of the identified proteins. The spectral count proportion of total membrane versus cytoplasmic fractions indicated the propensity of cytoplasmic proteins to co-fractionate with the inner membrane, and enabled us to distinguish cytoplasmic, peripheral inner membrane and bona fide inner membrane proteins. Principal component analysis and k-nearest neighbor classification training on selected marker proteins or predominantly localized proteins, allowed us to determine an extensive catalog of at least 74 expressed outer membrane proteins, and to extend the SCL assignment to 94% of the identified proteins, including 18% where in silico methods gave no prediction. Suitable experimental proteomics data combined with straightforward computational approaches can thus identify the predominant SCL on a proteome-wide scale. Finally, we present a conceptual approach to identify proteins potentially changing their SCL in a condition-dependent fashion.

BIOLOGICAL SIGNIFICANCE

The work presented here describes the first prokaryotic proteome-wide subcellular localization (SCL) dataset for the emerging pathogen B. henselae (Bhen). The study indicates that suitable subcellular fractionation experiments combined with straight-forward computational analysis approaches assessing the proportion of spectral counts observed in different subcellular fractions are powerful for determining the predominant SCL of a large percentage of the experimentally observed proteins. This includes numerous cases where in silico prediction methods do not provide any prediction. Avoiding a treatment with harsh conditions, cytoplasmic proteins tend to co-fractionate with proteins of the inner membrane fraction, indicative of close functional interactions. The spectral count proportion (SCP) of total membrane versus cytoplasmic fractions allowed us to obtain a good indication about the relative proximity of individual protein complex members to the inner membrane. Using principal component analysis and k-nearest neighbor approaches, we were able to extend the percentage of proteins with a predominant experimental localization to over 90% of all expressed proteins and identified a set of at least 74 outer membrane (OM) proteins. In general, OM proteins represent a rich source of candidates for the development of urgently needed new therapeutics in combat of resurgence of infectious disease and multi-drug resistant bacteria. Finally, by comparing the data from two infection biology relevant conditions, we conceptually explore methods to identify and visualize potential candidates that may partially change their SCL in these different conditions. The data are made available to researchers as a SCL compendium for Bhen and as an assistance in further improving in silico SCL prediction algorithms.

Directed shotgun proteomics guided by saturated RNA-seq identifies a complete expressed prokaryotic proteome

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ∼90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.

The expanding bacterial type IV secretion lexicon

The bacterial type IV secretion systems (T4SSs) comprise a biologically diverse group of translocation systems functioning to deliver DNA or protein substrates from donor to target cells generally by a mechanism dependent on establishment of direct cell-to-cell contact. Members of one T4SS subfamily, the conjugation systems, mediate the widespread and rapid dissemination of antibiotic resistance and virulence traits among bacterial pathogens. Members of a second subfamily, the effector translocators, are used by often medically-important pathogens to deliver effector proteins to eukaryotic target cells during the course of infection. Here we summarize our current understanding of the structural and functional diversity of T4SSs and of the evolutionary processes shaping this diversity. We compare mechanistic and architectural features of T4SSs from Gram-negative and -positive species. Finally, we introduce the concept of the 'minimized' T4SSs; these are systems composed of a conserved set of 5-6 subunits that are distributed among many Gram-positive and some Gram-negative species.

Bartonella henselae trimeric autotransporter adhesin BadA expression interferes with effector translocation by the VirB/D4 type IV secretion system

The Gram-negative, zoonotic pathogen Bartonella henselae is the aetiological agent of cat scratch disease, bacillary angiomatosis and peliosis hepatis in humans. Two pathogenicity factors of B. henselae - each displaying multiple functions in host cell interaction - have been characterized in greater detail: the trimeric autotransporter Bartonella adhesin A (BadA) and the type IV secretion system VirB/D4 (VirB/D4 T4SS). BadA mediates, e.g. binding to fibronectin (Fn), adherence to endothelial cells (ECs) and secretion of vascular endothelial growth factor (VEGF). VirB/D4 translocates several Bartonella effector proteins (Beps) into the cytoplasm of infected ECs, resulting, e.g. in uptake of bacterial aggregates via the invasome structure, inhibition of apoptosis and activation of a proangiogenic phenotype. Despite this knowledge of the individual activities of BadA or VirB/D4 it is unknown whether these major virulence factors affect each other in their specific activities. In this study, expression and function of BadA and VirB/D4 were analysed in a variety of clinical B. henselae isolates. Data revealed that most isolates have lost expression of either BadA or VirB/D4 during in vitro passages. However, the phenotypic effects of coexpression of both virulence factors was studied in one clinical isolate that was found to stably coexpress BadA and VirB/D4, as well as by ectopic expression of BadA in a strain expressing VirB/D4 but not BadA. BadA, which forms a dense layer on the bacterial surface, negatively affected VirB/D4-dependent Bep translocation and invasome formation by likely preventing close contact between the bacterial cell envelope and the host cell membrane. In contrast, BadA-dependent Fn binding, adhesion to ECs and VEGF secretion were not affected by a functional VirB/D4 T4SS. The obtained data imply that the essential virulence factors BadA and VirB/D4 are likely differentially expressed during different stages of the infection cycle of Bartonella.