In silico detection and characterization of novel virulence proteins of the emerging poultry pathogen Gallibacterium anatis

Article information

Genomics Inform. 2022;20.e41

Publication date (electronic) : 2022 December 30

doi : https://doi.org/10.5808/gi.22006

L. G. T. G Rajapaksha¹, C. W. R Gunasekara^2,, P. S. de Alwis²

¹Veterinary Medical Center and College of Veterinary Medicine, Jeonbuk National University, Jeonju 54596, Korea

²College of Fisheries Science, Pukyong National University, Busan 48513, Korea

^*Corresponding author: E-mail: cwikumpr@jbnu.ac.kr

Received 2022 January 17; Revised 2022 May 12; Accepted 2022 October 14.

Abstract

Introduction

Gallibacterium anatis (earlier known as Pasteurella anatis), which belongs to the family Pasteurellaceae, is an emerging disease-causing organism in poultry [1]. This bacterium has been isolated from various animals including chickens, turkeys, geese, ducks, pheasants, partridges, budgerigars, peacocks, cage birds, and wild birds [1-3]. There have been debates about whether this bacterium is pathogenic or nonpathogenic since it is found as a common part of the microbiota in upper respiratory tract and lower reproductive tract of healthy chickens [2,4,5]. However, increasing evidence indicates that G. anatis is associated with a wide range of pathological changes, leading to decreased egg production and lowered animal welfare in commercial poultry farms [6,7]. The disease is most likely to occur in intensively reared poultry farms (such as those raising broiler chickens) and incurs a high rate of mortality unless treated [1]. Therefore, determining the virulence factors of G. anatis would play an important role in proposing better control and prevention methods.

In recent years, numerous genomes have been sequenced with the help of next-generation sequencing technology and are available in public databases, such as that operated by the National Center for Biotechnology Information (NCBI) [8]. As a result, genomes with hypothetical proteins (HPs) have been deposited in sequence databases instead of experimentally confirmed facts due to their functional importance. Moreover, in some circumstances, because of limitations in illustrations (experimental validation techniques), expenditures, and the time required for the corresponding methodologies, whole-genome annotations have not been archived. Furthermore, the large amount of HPs in a genome naturally creates difficulties in data analysis [8]. This encourages in silico analysis, which utilizes and produces experimental information on HPs [9]. Establishing a structural and functional annotation for HPs may also play a significant role in elucidating protein pathways and cascades, helping to complete the currently approximate records on a variety of proteins [8,10]. Bioinformatics methods using discriminative algorithms and databases are the best approach to influence laboratory-based experimental procedures. Since these algorithms produce precise experimental results, they can be used to complete the functional and structural annotation of HPs [8].

The present study employed an in silico approach and predicted the functions of all HPs in the G. anatis reference genome (NCTC11413). Following identification, the physicochemical properties of the virulence-associated HPs were examined. Among them, a virulence protein within the pH range of 6–7 was identified as a drug target and analyzed for secondary structures, leading to the production of its first three-dimensional (3D) model by the ab initio method, and finally enabling the completion of its functional annotation. We believe that the present study provides a convenient methodology to analyze HPs and their functions in prokaryotic genomes.

Methods

Results and Discussion

Physicochemical properties, subcellular localization, and protein classification of the virulence proteins

The novel virulence proteins identified had 333–3,033 nucleotides and 111–1,011 amino acids (Table 1). Among the virulence proteins, the highest extinction coefficient (1.4 × 10⁵) was observed in the HP WP_043885272.1. The instability index indicated that WP_013745190.1, WP_013746187.1, and WP_013746977.1 were unstable proteins, whereas the others were stable proteins (Table 2). Following this, the prediction of subcellular localization using PSORT indicated that 10 virulence proteins were cytoplasmic membrane proteins, whereas PSLpred showed three cytoplasmic proteins, two extracellular proteins, and six outer or inner membrane proteins. It is well known that proteins in the cytoplasm are possible drug targets, while membrane proteins are considered to be vaccine targets [29]. Cytoplasmic proteins play a crucial role in metabolic pathways that are critical to the survival of the pathogen inside the host organism [30]. Therefore, the three proteins detected in the cytoplasm (from both PSLpred and PSORT servers) can be used as drug targets, whereas the six membrane proteins could be used as vaccine targets against the present pathogen (Table 3). Moreover, the virulence-associated HP named WP_013746977.1 was identified as a signal peptide, whereas WP_013745329.1 was identified as a lipoprotein signal peptide. The protein structure of WP_013745346.1 (protein in the pH range of 6–7 and a possible drug target).

Table 1.

Novel virulence proteins identified in the Gallibacterium anatis NCTC11413 genome by the VCMPred online server

Table 2.

Physicochemical properties of 11 virulence proteins of Gallibacterium anatis with the ProtParam online server

Table 3.

Subcellular localization and classification of 11 virulence proteins of Gallibacterium anatis with PSORT, PSLpred, and SignalP-5.0 online servers. (unknown: the PSORT server predicted the same values for all the functional categories)

Functional annotation of the virulence protein WP_013745346.1

All five employed tools indicated that the virulence protein WP_013745346.1 is an enzyme (known as methylcitrate synthase) primarily associated with the citrate cycle (Supplementary Table 3). ProFunc analysis indicated it is related to both biological processes (cellular process [74.47], cellular metabolic process [74.47], metabolic process [74.47], cofactor metabolic process [56.61]) and biochemical processes (catalytic activity [74.47], transferase activity [73.74], transferase activity/transferring acyl groups [47.82], transferase activity/ transferring acyl groups/acyl groups converted into alkyl on transfer [41.91]). The STRING protein network analysis suggested that the virulence protein WP_013745346.1 is associated with other functional proteins such as acsA and prpB (Fig. 1). The phylogenetic analysis with other reference sequences revealed that WP_013745346.1 is similar to other bacterial methylcitrate synthases (Supplementary Fig. 1). Moreover, this virulence protein was related to the biosynthesis of secondary metabolites, microbial metabolism in diverse environments, carbon metabolism, the biosynthesis of amino acids, and glyoxylate and dicarboxylate metabolism (Supplementary Fig. 2). This enzyme is a key determinant of propanoate degradation in micro-organisms [31]. Previous studies also suggested that the presence of methylcitrate synthase, malate synthase, and methylcitrate dehydrate is essential to the intercellular growth, metabolism, and virulence of bacteria, such as Mycobacterium tuberculosis [32]. Moreover, methylcitrate synthase in fungi, such as Aspergillus fumigatus, has the potential to detoxify propionyl-CoA, which is a byproduct of protein utilization; therefore, it can be used as a novel drug target [33].

Fig. 1.

A STRING database search was carried out to identify a possible functional interaction network of the virulence protein WP_013745346.1 (AEC16559.1). The identified functional protein partners with the corresponding scores were as follows: AEC16558.1 (0.997), AEC18484.1 (0.966), acsA (0.962), AEC16561.1 (0.952), prpB (0.948), AEC17475.1 (0.920), AEC17206.1 (0.908), AEC17928.1 (0.907), AEC17490.1(0.877), and AEC17673.1 (0.841).

Secondary structure of the virulence protein WP_013745346.1

The secondary structure of the protein WP_013745346.1 was predicted using the SOPMA server. Alpha helices were found to be the most predominant (53.93%), followed by random coils (32.25%) and extended strands (8.40%). Beta-turns accounted for 5.42% of the structure of this protein. The predicted secondary structure for the virulence protein WP_013745346.1 from the PSIPRED server was also similar (Fig. 2).

Fig. 2.

The secondary structure of the virulence protein WP_013745346.1 was predicted using the PSIPRED server.

Homology modeling of the virulence protein WP_013745346.1

G. anatis infections have been reported in recent years at intensively reared poultry farms. However, its virulence-related factors have not been fully elucidated so far. Previous studies have demonstrated that the identification of virulence proteins from HPs plays a significant role in understanding its pathogenesis [28,29]. In silico analysis can help determine the biological functions of virulence proteins [8]. These predictions can be further strengthened by determining the 3D structures of virulence proteins using homology modeling. Homology modeling identifies the 3D structure of a selected protein sequence through alignment to one or more proteins of other known structures [34]. To perform homology modeling, the query sequence of virulence protein WP_013745346.1 was submitted to the SWISS-MODEL server. The server performed a BLASTP search for the respective protein sequence to identify templates associated with homology modeling. The highest identity of 36% observed for this virulence protein indicated that WP_013745346.1 is novel and no similar template structure is currently present in other databases. Following this, we determined the 3D structure of the virulence protein WP_013745346.1 by the ab initio method through the Phyre2 server, which gave 99.8% confidence in the model (Fig. 3). A comparative analysis of C. burnetii and M. tuberculosis methylcitrate synthases to WP_013745346.1, showed a common structural domain (citrate synthase, C-terminal domain), cellular location (cytoplasm), and molecular functions (Supplementary Fig. 3).

Fig. 3.

Three-dimensional structural analysis and visualization of the virulence protein WP_013745346.1 with Geneious Prime version 2020.0.5.

Quality assessment and visualization

The reliability of the created protein model was assessed using the ERRAT server, which analyzes the statistics of non-bonding interactions between diverse atom types, based on characteristic atomic interactions. The overall quality factor was found as 96.096%, which was sufficient to use this model. As shown by the Verify3D program, the results indicated 86.60% of residues had an average 3D (atomic model) – 1D (amino acid) score ≥0.2, meaning that this structure was compatible and genuinely good. Next, validation through a Ramachandran plot analysis showed that the distribution of φ and ψ angles in the model were within the limits (Table 4), 90.2% of the residues are in the most favored region of the plot, indicating that the model was valid (Fig. 4).

Table 4.

Ramachandran plot statistics of the virulence protein WP_013745346.1 predicted by the PROCHECK server

Fig. 4.

Ramachandran plot of the modeled structure for the virulence protein WP_013745346.1 validated by the PROCHECK program.

Supplementary Materials

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