Unraveling Pseudomonas aeruginosa and Candida albicans Communication in Coinfection Scenarios: Insights Through Network Analysis

Abstract

Modern medicine is currently facing huge setbacks concerning infection therapeutics as microorganisms are consistently knocking down every antimicrobial wall set before them. The situation becomes more worrying when taking into account that, in both environmental and disease scenarios, microorganisms present themselves as biofilm communities that are often polymicrobial. This comprises a competitive advantage, with interactions between different species altering host responses, antimicrobial effectiveness, microbial pathogenesis and virulence, usually augmenting the severity of the infection and contributing for the recalcitrance towards conventional therapy. Pseudomonas aeruginosa and Candida albicans are two opportunistic pathogens often co-isolated from infections, mainly from mucosal tissues like the lung. Despite the billions of years of co-existence, this pair of microorganisms is a great example on how little is known about cross-kingdom interactions, particularly within the context of coinfections. Given the described scenario, this study aimed to collect, curate, and analyze all published experimental information on the molecular basis of P. aeruginosa and C. albicans interactions in biofilms, in order to shed light into key mechanisms that may affect infection prognosis, increasing this area of knowledge. Publications were optimally retrieved from PubMed and Web of Science and classified as to their relevance. Data was then systematically and manually curated, analyzed, and further reconstructed as networks. A total of 641 interactions between the two pathogens were annotated, outputting knowledge on important molecular players affecting key virulence mechanisms, such as hyphal growth, and related genes and proteins, constituting potential therapeutic targets for infections related to these bacterial-fungal consortia. Contrasting interactions were also analyzed, and quorum-sensing inhibition approaches were highlighted. All annotated data was made publicly available at www.ceb.uminho.pt/ISCTD, a database already containing similar data for P. aeruginosa and Staphylococcus aureus communication. This will allow researchers to cut on time and effort when studying this particular subject, facilitating the understanding of the basis of the inter-species and inter-kingdom interactions and how it can be modulated to help design alternative and more effective tailored therapies. Finally, data deposition will serve as base for future dataset integration, whose analysis will hopefully give insights into communications in more complex and varied biofilm communities.

Keywords: Candida albicans; Pseudomonas aeruginosa; biofilms; coinfection; database; interactions; polymicrobial.

Figure 1

Mixed P. aeruginosa-C. albicans 24 h–old biofilm. Epifluorescence image of a stained biofilm with a mixture of SYTO® BC and propidium iodide (PI) (Invitrogen™, CA, USA) shows P. aeruginosa PAO1 (PA) cells (highlighted by white arrows) surrounding and colonizing in a great extension the C. albicans SC5314 (CA) hyphae (black arrow). Cells were prepared at approximately 10⁷ CFU/mL in RPMI 1640 media and mixed in equal proportions. Mixed suspensions were transferred to Thermanox® plastic coverslips, placed in 24-well plates, and incubated at 120 rpm and 37°C for 24 h prior to biofilm analysis.

Figure 2

Searching within the ISCTD. (A) Navigation panel that allows users to jump within the webpage, including to the “Search” section. (B) Selection of the interaction direction of interest, here exemplified by the effect of P. aeruginosa on C. albicans. (C) Selection of the source entity category, which can be left unspecified by selecting the option “All”. (D) Selection of the target entity category, here exemplified by “gene”. (E) When clicking the “Search” button, a table is generated containing all the information annotated by the expert curators and sifted through the user’s selection in (B–D). (F) Users can type keywords to further specify their search, here exemplified by “biofilm”. (G) Table is narrowed down to show only interactions observed in biofilms.

Figure 3

Overview of the types of interactions and entities annotated for the effects of P. aeruginosa on C. albicans. (A) Proportional data on the types of interactions; (B) Total number of interactions annotated for each source category; (C) Total number of interactions annotated for each target category. AI, autoinducer; VM, virulence mechanism; VF, virulence factor.

Figure 4

Overview of the types of interactions and entities annotated for the effects of C. albicans on P. aeruginosa. (A) Proportional data on the types of interactions; (B) Total number of interactions annotated for each source category; (C) Total number of interactions annotated for each target category. Legend: AI, autoinducer; VM, virulence mechanism; VF, virulence factor.

Figure 5

Network of the effects of P. aeruginosa-C. albicans interactions on VF and VM. Teal nodes, P. aeruginosa; orange nodes, C. albicans; green arrows, stimulation; grey arrows, null effect; red arrows: inhibition; node and node label sizes are directly proportional to the number of related (outward and inward) edges (interactions).

Figure 6

Network of the effects of P. aeruginosa on C. albicans gene expression. Legend: Teal nodes, P. aeruginosa; orange nodes, C. albicans; green arrows, upregulation; grey arrows, null effect; red arrows: downregulation; node and node label sizes are directly proportional to the number of related (outward and inward) edges (interactions).

Figure 7

Network of the effects of P. aeruginosa on C. albicans protein expression. Legend: Teal nodes, P. aeruginosa; orange nodes, C. albicans; green arrows, upregulation; grey arrows, null effect; red arrows: downregulation; node and node label sizes are directly proportional to the number of related (outward and inward) edges (interactions).

Figure 8

Network of the effects of C. albicans on P. aeruginosa gene expression. Legend: Teal nodes, P. aeruginosa; orange nodes, C. albicans; green arrows, upregulation; grey arrows, null effect; red arrows: downregulation; node and node label sizes are directly proportional to the number of related (outward and inward) edges (interactions).

Figure 9

Network of the effects of C. albicans on P. aeruginosa protein expression. Legend: Teal nodes, P. aeruginosa; orange nodes, C. albicans; green arrows, upregulation; grey arrows, null effect; red arrows: downregulation; node and node label sizes are directly proportional to the number of related (outward and inward) edges (interactions).