The core exosome proteome of Trichomonas vaginalis

BACKGROUND

Trichomonas vaginalis is parasitic protozoan that causes human urogenital infections. Accumulated reports indicated that exosomes released by this parasite play a crucial role in transmitting information and substances between cells during host-parasite interactions. Current knowledge on the protein contents in T. vaginalis exosome is mainly generated from three previous studies that used different T. vaginalis isolates as an experimental model. Whether T. vaginalis exosomes comprise a common set of proteins (core exosome proteome) is still unclear.

METHODS

To explore the core exosome proteome in T. vaginalis, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify the contents of sucrose ultracentrifugation-enriched exosome and supernatant fractions isolated from six isolates.

RESULTS

Transmission electron microscopy (TEM) confirmed the presence of exosomes in the enriched fraction. Proteomic analysis identified a total of 1870 proteins from exosomal extracts. There were 1207 exosomal-specific proteins after excluding 436 'non-core exosomal proteins'. Among these, 72 common exosomal-specific proteins were expressed in all six isolates. Compared with three published T. vaginalis exosome proteome datasets, we identified 16 core exosomal-specific proteins. These core exosomal-specific proteins included tetraspanin (TvTSP1), the classical exosome marker, and proteins mainly involved in catalytic activity and binding such as ribosomal proteins, ras-associated binding (Rab) proteins, and heterotrimeric G proteins.

CONCLUSIONS

Our study highlighted the importance of using supernatant fraction from exosomal extract as a control to eliminate 'non-core exosomal proteins'. We compiled a reference core exosome proteome of T. vaginalis, which is essential for developing a fundamental understanding of exosome-mediated cell communication and host-parasite interaction.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

A Lean Reverse Vaccinology Pipeline with Publicly Available Bioinformatic Tools

Reverse vaccinology (RV) marked an outstanding improvement in vaccinology employing bioinformatics tools to extract effective features from protein sequences to drive the selection of potential vaccine candidates (Rappuoli, Curr Opin Microbiol 3(5):445-450, 2000). Pioneered by Rino Rappuoli and first used against serogroup B meningococcus, since then, it has been used on several other bacterial vaccines, varying during time the adopted bioinformatics tools. Based on our experience in the field of RV and following an extensive literature review, we consolidate a lean RV pipeline of publicly available bioinformatic tools whose usage is described in this contribution. The protein features, whose extraction is reported in this contribution, can be also the input in a matrix format for machine learning-based approaches.

Screening of potential vaccine candidates against pathogenic Brucella spp. using compositive reverse vaccinology

Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis in humans and various animals. The threat of brucellosis has increased, yet currently available live attenuated vaccines still have drawbacks. Therefore, subunit vaccines, produced using protein antigens and having the advantage of being safe, cost-effective and efficacious, are urgently needed. In this study, we used core proteome analysis and a compositive RV methodology to screen potential broad-spectrum antigens against 213 pathogenic strains of Brucella spp. with worldwide geographic distribution. Candidate proteins were scored according to six biological features: subcellular localization, antigen similarity, antigenicity, mature epitope density, virulence, and adhesion probability. In the RV analysis, a total 32 candidate antigens were picked out. Of these, three proteins were selected for assessment of immunogenicity and preliminary protection in a mouse model: outer membrane protein Omp19 (used as a positive control), type IV secretion system (T4SS) protein VirB8, and type I secretion system (T1SS) protein HlyD. These three antigens with a high degree of conservation could induce specific humoral and cellular immune responses. Omp19, VirB8 and HlyD could substantially reduce the organ bacterial load of B. abortus S19 in mice and provide varying degrees of protection. In this study, we demonstrated the effectiveness of this unique strategy for the screening of potential broad-spectrum antigens against Brucella. Further evaluation is needed to identify the levels of protection conferred by the vaccine antigens against wild-type pathogenic Brucella species challenge.

Proteome and carbon flux analysis of Pseudomonas aeruginosa clinical isolates from different infection sites

Pseudomonas aeruginosa is known as opportunistic pathogen frequently isolated from different infection sites. To investigate the expression rates of P. aeruginosa proteins commonly expressed by different clinical isolates, absolute protein quantities were determined employing a gel-free and data-independent LC-IMS(E) approach. Moreover, the metabolic diversity of these isolates was investigated by (13) C-metabolic flux analyses. 812 proteins were reproducibly identified and absolutely quantified for the reference strain P. aeruginosa PAO1, 363 of which were also identified and relatively quantified in all isolates. Whilst the majority of these proteins were expressed in constant amounts, expression rates of 42 proteins were highly variable between the isolates. Notably, the outer membrane protein OprH and the response regulator PhoP were strongly expressed in burned wounds isolates compared to lung/urinary tract isolates. Moreover, proteins involved in iron/amino acids uptake were found to be highly abundant in urinary tract isolates. The fluxome data revealed a conserved glycolysis, and a niche-specific divergence in fluxes through the glyoxylate shunt and the TCA cycle among the isolates. The integrated proteome/fluxome analysis did not indicate straightforward correlation between the protein amount and flux, but rather points to additional layers of regulation that mediate metabolic adaption of P. aeruginosa to different host environments. All MS data have been deposited in the ProteomeXchange with identifier PXD002373 (http://proteomecentral.proteomexchange.org/dataset/PXD002373).