Searching for the Resistance Interactome of *Pseudomonas aeruginosa*

*Diana Carolina Castaño, Juan David Patiño-Salazar and Mauricio Corredor*

#### **Abstract**

*Pseudomonas aeruginosa* is one of the most important emerging Gram-negative pathogenic bacilli worldwide. The development of antibiotic resistance and its ability to adapt to multiple environmental conditions keep triggering alarms in global hospitals since the invasion of different types of tissues. This facultative anaerobe can adapt easily to aerobic or anaerobic conditions. It invades tissues, such as the lung, gastrointestinal tract, skin, renal system, and urinary tract, to the extreme of causing a variety of punctate gangrene. The considerable size of its genome (core and accessory genome) shows that this bacterium carries a huge battery of genes that allow it to develop resistance to various antibiotics, emerging as an MDR bacterium. The most studied mechanisms for resistance development have been *quorum sensing* and biofilm formation, among others. The research of resistance genes has been a long and timeconsuming task. Genes such as CARB-3, CARB-4, PSE-1 (CARB-2), PSE-4 (CARB-1), OXA-18, OXA-2, OXA-21, OXA-10 (PSE-2), GyrA, GyrB, OprM, OprJ, OprN, MexB, MODx, MexF, and MexY, are among the best-characterized genes in *P. aeruginosa*. Another group of not-so-conventional genes is the methyltransferases, which have been negligible studied in *P. aeruginosa*. In this article, we propose to give a state of the art of the most important resistance genes of *P. aeruginosa* and their relationship with the interactome-resistome.

**Keywords:** *Pseudomonas aeruginosa*, interactome, resistome, antibiotic resistance genes, pangenomics

#### **1. Introduction**

In the past years, antibiotic resistance of *Pseudomonas aeruginosa* has been reported as an emerging global health problem by the WHO [1]. P. aeruginosa is one of the most prevalent nosocomial pathogens, responsible for 57% of overall hospitalacquired infections because it is a ubiquitous pathogen [2]. In the twentieth century, this bacterium was not a global health problem and, in many hospitals worldwide, was treated locally with aminoglycosides. Although, antibiotic resistance made it necessary to replace them with b-lactams, fluoroquinolones, and polymyxins. *P. aeruginosa* causes infections in the blood as septicemia, in the lungs as pneumonia for respiratory complications, in cystic fibrosis patients, and in the skin as epidermolysis bullosa or folliculitis [3, 4]. It can contaminate any part of the body after surgery. Now, it needs to be studied more seriously, precisely because the treatment with antibiotics has not only developed rapidly antibiotic-resistant bacteria (ARB), since it has a rapid dispersion, and it becomes multidrug-resistant (MDR) [5]. Resistant strains spread from one person to another through the infection of the mouth, lips, hair, saliva, hands, skin, and nails, likewise by infected apparatus or surfaces, but also through wind, water, and soil [6], yield a rapid spread and the development of multidrug resistant (MDR) [5], **Figure 1**.

Genomics emerges as a fundamental tool to give us a new hand to combat ARB [7]. Nonetheless, to better know the complex gene interactions, the genome size of P. aeruginosa complicates the task of identifying different genes responsible for specific antibiotic resistance. This approach has been used for years but is nowadays outdated. New strategies such as the omics allowed decoding of sequences, gene organization, and synteny; likewise, as quorum sensing communication [8, 9], epigenetic labeling on DNA and RNA, and resistome interactions [10]. This evidence is a multifaceted problem that cannot continue to be focused as a reductionist manner. Genes and proteins are arranged in an intricate chain of events to simplify the cellular activity in a discrete compartment of a pair of genes. Genes and proteins network could be the strategy of cellular events giving success to living beings, including pathogen bacteria.

The genes and proteins interactions are fundamental elements to breakthrough biological processes. The comprehensive identification of the gene-protein interaction, messenger RNA-protein association, and protein-protein interactions (PPIs) is well-known today as the interactome [11]. The research of antibiotic interactome (resistome) provides a bioinformatics framework to understand the organisms as an integrated system (system biology). In other words, the resistome is the part of the

#### **Figure 1.**

*Resistant genes of antibiotics coming from* Pseudomonas aeruginosa *strains (all strains or core genome) and the environment (some strains with accessory and unique genomes) as horizontal genes transfer, HGT.*

interactome that manages antibiotic resistance [12]. Resistome could be part of the core or accessory genome in the whole bacteria species [13–15]. However, it is not enough to study resistome using specific antibiotic resistance genes. Innovative approaches are necessary to understand the tangle of intricate steps of cellular regulation and predicting gene and protein networks.

### **2. Interactome-resistome**

Computational advances allow the deep study of protein-protein interactions (PPIs), but this is not possible for all species. Some species have been more observed than others, as in the case of *P. aeruginosa,* given the clinical interest in recent years. Resistome genes comprise essential and nonessential genes and are part of the accessory or core genome, including unique genes. Some of these genes are gained by horizontal transfer. Most of the genome or the full set of genes is not related to drug resistance. Many resistant genes are for extreme cold or heat, high salt concentration, toxic compounds, UV, or radioactivity exposition, etc. [16]. However, the resistome can include many genes related to different challenges. The network between genes or proteins represents biological data, whereas nodes represent biological entities connected by edges, meaning associations between them, which can be diagrammed and computed [17].

Despite the few works in interactomics, new results are arising. The *P. aeruginosa* protein-protein interaction (PPI) network was developed 10 years ago [18]. This study integrated various traits of genes and proteins at the genome level using a machine learning approach to predict a genome-scale PPI network of *P. aeruginosa*. A total of 54,107 interactions spanning 4,181 proteins were predicted. Using a highconfidence network that combines high-throughput predicted interactions, the author found 3,343 proteins and 19,416 potential interactions.

One of the best summaries of interactomes is PseudomonasNet (http://www.inetb io.org/pseudomonasnet/index.php). As they said: this is a database of genome-wide co-functional networks for *P. aeruginosa*. By integrating nine distinct data types, PseudomonasNet covers more than 98% of the 5,572 coding genes of the PAO1 strain with 203,118 co-functional links [19].

The interactome is not just a protein-protein interaction. For example, the RNAbinding protein Hfq interacts with mRNAs, affecting mRNA translation, either alone or together, with the small regulatory noncoding RNAs, and its degradation in *P. aeruginosa* [15]. The authors find that most of the Hfq interactions are not conserved between the different strains studied, and the strain-specific interactions are due to diverse sets of accessory genes.

#### **3. Antibiotics resistance genes and mechanisms in** *P. aeruginosa*

In *P. aeruginosa*, the antibiotic resistance can be classified into five distinct categories according to action mechanisms: inactivation of antibiotics by modifying enzymes, modification of antibiotics target, global response efflux pumps conferring multidrug resistance, antibiotic resistance by alterations in the cell wall charge, and porins modulating reduction of permeability to antibiotics. The genes associated with these mechanisms are listed in **Table 1**.


*Searching for the Resistance Interactome of* Pseudomonas aeruginosa *DOI: http://dx.doi.org/10.5772/intechopen.108245*



#### **Table 1.**

P. aeruginosa *genes confer resistance to specific antibiotics, confer resistance to multiple antibiotics or confer multi-drug resistance (MDR); with the description of the product, and classification for each gene. Some networks in the third column were downloaded from STRING (https://string-db.org/) and analyzed with Cytoscape (https://cytoscape.org/).*

#### **3.1 Inactivation of antibiotics by modifying enzymes**

The first important mechanism that *P. aeruginosa* displays to elude the inhibitory effect of antibiotics is drug inactivation through enzymes such as aminoglycosidemodifying enzymes and β-lactamases.
