Preprint
Article

Some Transmembrane Proteins Of Salmonella Typhimurium Are Potential Drug Targets: An In Silico Analysis

Altmetrics

Downloads

96

Views

34

Comments

0

Submitted:

10 May 2024

Posted:

15 May 2024

You are already at the latest version

Alerts
Abstract
Salmonella sp. is a globally prevalent organism responsible for causing salmonellosis, a foodborne illness. Salmonella Typhimurium represents a type of Salmonella sp. not associated with typhoid fever but capable of causing stomach and intestinal inflammation or severe infection. In the present study, 150 uncharacterized proteins of S. Typhimurium were randomly selected from UniProtKB and analyzed using TMHMM, PROSITE, STRING, DEG, and BLASTp. Results indicated that 32 uncharacterized proteins (21%) were predicted to be transmembrane proteins involved in various biological pathways. Among them, 30 transmembrane proteins were predicted to be essential and non-host homologous. This study's findings suggest their potential as drug targets against salmonellosis.
Keywords: 
Subject: Biology and Life Sciences  -   Immunology and Microbiology

1. Introduction

Salmonella sp. is the worldwide pathogen that causes salmonellosis, a foodborne disease. Salmonella typhimurium is a nontyphoidal salmonella that can cause gastroenteritis or invasive disease. Invasive nontyphoidal salmonellosis often involves immunocompromised individuals, especially those who suffered with HIV infection. Salmonella sp. infection can be transmitted either by contact or by ingestion of contaminated food. The presence of multidrug resistance Salmonella sp. is a serious issue for disease spread. Salmonella enterica serovar has been divided into two groups which is typhoidal and non-typhoidal (NTS) (Okoro et al., 2015). In general, Salmonella sp. is a Gram-negative, facultative anaerobic bacterium under Phylum Proteobacteria with peritrichous flagella for locomotion. It also has fimbriae that helps S. typhimurium adhere to cell surfaces, increasing the probability of disease production. Additionally, S. typhimurium has specialized sex pili for genetic information exchange between cells. It inhabits the intestinal tracts of humans and animals, especially poultry and cattle. The infection can be transmitted through person-to-person contact via saliva or mouth-to-mouth contact with an infected person (Fernandes et al., 2016). S. Typhimurium invades the intestinal mucosa, multiplies within vesicles inside cells, and crosses epithelial cell membranes to enter the lymphatic system and bloodstream, causing acute intestinal inflammation in humans (Hapfelmeier & Hardt, 2005). Biofilm formation by S. Typhimurium has been reported over many decades (Armon et al. 1997; Lapidot et al. 2006; Yahya et al. 2017; Johari et al. 2023).
Transmembrane proteins confer particular properties to the membrane, including signal transduction and the transport of ions or small molecules across it. Some transmembrane proteins bind to hormone or neurotransmitter receptors, altering their structure and triggering specific reactions. Additionally, they selectively transport substances such as ions or molecules across the membrane, establishing concentration gradients or energy potentials between intracellular and extracellular environments via active or passive transport. Due to their unique features, transmembrane proteins are under extensive research for various applications in sensors, screening, water purification, and energy harvesting (Ryu et al., 2019). Identifying transmembrane proteins in pathogenic microorganisms involves employing bioinformatic tools and computational approaches to predict and analyze protein structures and functions. Sequence-based bioinformatics tools are utilized to detect potential transmembrane domains within protein sequences, employing algorithms like Hidden Markov Models (HMMs) and Position-Specific Scoring Matrices (PSSMs) to recognize characteristic patterns indicative of transmembrane regions (Khan & Uddin 2022). Subsequently, structural bioinformatics tools are employed to model the three-dimensional structure of identified proteins, enabling visualization of transmembrane domains and their orientation within the lipid bilayer.
Bioinformatics plays a crucial role in identifying drug targets in Salmonella through diverse computational methods and data analysis techniques. It facilitates the analysis of genomic and proteomic data from Salmonella strains, aiding in pinpointing potential drug targets (Khan & Uddin 2022). By comparing genomes of drug-resistant strains with susceptible ones, bioinformatics detects genetic variations linked to resistance, thus highlighting potential intervention targets (Jalal et al. 2021). Additionally, bioinformatic tools predict the function and structure of proteins encoded by Salmonella genes, assisting in selecting targets with druggable properties. This study aims to analyze uncharacterized proteins of S. typhimurium for potential drug targets.

2. Materials and Methods

A total of 150 uncharacterized proteins of S. Typhimurium were randomly selected and retrieved from UniprotKB database. They were analyzed using TMHMM, PROSITE, STRING, DEG and BLASTp.

3. Results

Figure 1 shows the classification of uncharacterized proteins from Salmonella Typhimurium based on their biological pathways, molecular functions, subcellular localization, and identification as transmembrane proteins. The majority of the proteins are involved in biosynthesis (16%) and DNA binding (21.3%) and located in the cytoplasm (64.7%) for their biological pathway and subcellular localization, respectively. Only 21.3% of the uncharacterized proteins were predicted to be transmembrane proteins.
Table 1 lists the identified transmembrane proteins from S. Typhimurium along with details about the number of transmembrane domains, their predicted biological pathways, molecular functions, and subcellular localization. Protein A0A2J0RKS1 showed the highest number of predicted transmembrane domains.
Table 2 summarizes the BLASTp analysis results, showing the presence or absence of homologous proteins in various hosts (human, cattle, sheep, goat, and horses) for the identified transmembrane proteins from S. Typhimurium. Most of the proteins showed no homolog in the tested hosts, except for A0A0F7JDX1, which had a homolog in sheep, and A0A717VZE3, which had a homolog in humans. The protein A0A610AT56 is marked as a non-essential protein. A total of 29 transmembrane proteins were predicted to be essential and non-host homologous.
Figure 2A shows the number of predicted transmembrane helices (TMHs) for the protein A0A2J0RKS1, which is 9. Figure 2B displays the potential post-translational modification sites identified in the protein A0A2J0RKS1, including protein kinase C phosphorylation sites, N-glycosylation sites, and N-myristoylation sites. This network visualization represents the potential activities and functional linkages of the protein A0A2J0RKS1 based on protein-protein interactions (Figure 2C). The predicted activities include protein transport, virulence, cyclic-guanylate-specific phosphodiesterase activity, and undecaprenyl-phosphate 4-deoxy-4-formamido-L-arabinose transferase activity.

4. Discussion

Studying proteins in pathogens, particularly those involved in biofilm formation, is crucial as biofilms are complex communities of microorganisms encased in a self-produced extracellular matrix, enabling bacteria to adhere to surfaces and form resilient structures resistant to antimicrobials and host immune responses (Yaacob et al. 2021; Kamaruzzaman et al. 2022; Johari et al. 2023). Understanding transmembrane proteins may provide insight into their functions and therapeutic potential (Attwood & Schiöth 2021; Saches et al. 2021). Most identified transmembrane proteins of S. Typhimurium were predicted to be essential and non-host homologous to humans, cattle, sheep, goats, and horses. These proteins, crucial for bacterial survival and virulence but absent in host organisms, are potential therapeutic targets (Yahya et al. 2014, Othman and Yahya 2019; Nogueira et al. 2021). Protein A0A2J0RKS1, with the highest number of transmembrane domains, was predicted to have numerous functional linkages, establishing it as a significant hub protein in S. Typhimurium. Identifying essential hub proteins in pathogenic microorganisms via protein-protein interaction networks has been reported in several studies (Abd Rashid et al. 2022; Isa et al. 2022; Zulkiply et al. 2022; Bajire et al. 2023; Nithya et al. 2023).

5. Conclusions

We have shown that numerous uncharacterized proteins of S. Typhimurium hold promise as drug targets. Thirty transmembrane proteins identified in this study are essential and non-host homologous. Ongoing analysis of these transmembrane proteins is crucial to aid in the creation of effective drugs targeting Salmonella infection.

References

  1. Abd Rashid, S.A.; Yaacob, M.F.; Raihanah, N.; Anuar, T.; Johari, N.; Kamaruzzaman, A.N.A.; Yahya, M.F.Z. R.; et al. A combination of in silico subtractive and reverse vaccinology approaches reveals potential vaccine targets in Corynebacterium pseudotuberculosis. Journal of Sustainability Science and Management 2022, 17, 99–109. [Google Scholar] [CrossRef]
  2. Armon, R.; Starosvetzky, J.; Arbel, T.; Green, M. Survival of Legionella pneumophila and Salmonella typhimurium in biofilm systems. Water Science and Technology 1997, 35, 293–300. [Google Scholar] [CrossRef]
  3. Attwood, M.M.; Schiöth, H.B. Characterization of five transmembrane proteins: With focus on the Tweety, sideroflexin, and yip1 domain families. Frontiers in Cell and Developmental Biology 2021, 9. [Google Scholar] [CrossRef] [PubMed]
  4. Bajire, S.K.; Ghate, S.D.; Shetty, S.; Banerjee, S.; Rao RS, P.; Shetty, V.; Shastry, R.P. Unveiling the role of hub proteins in controlling quorum sensing regulated virulence through analogues in Pseudomonas aeruginosa PAO1: A functional protein-protein network biology approach. Biochemical and Biophysical Research Communications 2023, 660, 13–20. [Google Scholar] [CrossRef]
  5. Fernandes, L.; Centeno, M.M.; Couto, N.; Nunes, T.; Almeida, V.; Alban, L.; Pomba, C. Longitudinal characterization of monophasic salmonella typhimurium throughout the pig’s life cycle. Veterinary Microbiology 2016, 192, 231–237. [Google Scholar] [CrossRef] [PubMed]
  6. Hapfelmeier, S.; Hardt, W.-D. A mouse model for S. typhimurium-induced enterocolitis. Trends in Microbiology 2005, 13, 497–503. [Google Scholar] [CrossRef]
  7. Isa SF, M.; Abdul Hamid, U.M.; Zaman Raja Yahya, M.F. Treatment with the combined antimicrobials triggers proteomic changes in P. aeruginosa-C. albicans polyspecies biofilms. ScienceAsia 2022, 48. [Google Scholar]
  8. Jalal, K.; Khan, K.; Hassam, M.; Abbas, M.N.; Uddin, R.; Khusro, A.; Gajdács, M.; et al. Identification of a novel therapeutic target against XDR Salmonella Typhi H58 using genomics driven approach followed up by natural products virtual screening. Microorganisms 2021, 9, 2512. [Google Scholar] [CrossRef] [PubMed]
  9. Johari, N.A.; Aazmi, M.S.; Yahya, M.F.Z.R. FTIR Spectroscopic Study of Inhibition of Chloroxylenol-Based Disinfectant Against Salmonella enterica serovar Thyphimurium Biofilm. Malaysian Applied Biology 2023, 52, 97–107. [Google Scholar] [CrossRef]
  10. Kamaruzzaman, A.N.A.; Mulok, T.E.T.Z.; Nor, N.H.M.; Yahya, M.F.Z.R. FTIR spectral changes in Candida albicans biofilm following exposure to antifungals. Malaysian Applied Biology 2022, 51, 57–66. [Google Scholar] [CrossRef]
  11. Khan, K.; Uddin, R. Integrated bioinformatics based subtractive genomics approach to decipher the therapeutic function of hypothetical proteins from Salmonella typhi XDR H-58 strain. Biotechnology Letters 2022, 1–20. [Google Scholar] [CrossRef]
  12. Lapidot, A.; Romling, U.; Yaron, S. Biofilm formation and the survival of Salmonella Typhimurium on parsley. International journal of food microbiology 2006, 109, 229–233. [Google Scholar] [CrossRef]
  13. Mohammed, B.T. Identification and bioinformatic analysis of invA gene of Salmonella in free range chicken. Brazilian Journal of Biology 2022, 84, e263363. [Google Scholar] [CrossRef] [PubMed]
  14. Nithya, C.; Kiran, M.; Nagarajaram, H.A. Dissection of hubs and bottlenecks in a protein-protein interaction network. Computational Biology and Chemistry 2023, 102, 107802. [Google Scholar] [CrossRef] [PubMed]
  15. Nogueira, W.G.; Jaiswal, A.K.; Tiwari, S.; Ramos, R.T.; Ghosh, P.; Barh, D.; Soares, S.C.; et al. Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium. Genomics 2021, 113, 2730–2743. [Google Scholar] [CrossRef]
  16. Okoro, C.K.; Barquist, L.; Connor, T.R.; Harris, S.R.; Clare, S.; Stevens, M.P.; Arends, M.J.; Hale, C.; Kane, L.; Pickard, D.J.; Hill, J.; Harcourt, K.; Parkhill, J.; Dougan, G.; Kingsley, R.A. Signatures of adaptation in human invasive salmonella typhimurium ST313 populations from Sub-Saharan africa. PLOS Neglected Tropical Diseases 2015, 9. [Google Scholar]
  17. Othman, N.A.; Yahya, M.F.Z.R. In silico analysis of essential gene and non-homologous proteins in Salmonella typhimurium biofilm. Journal of Physics: Conference Series 2019, 1349, 012133. [Google Scholar]
  18. Ryu, H.; Fuwad, A.; Yoon, S.; Jang, H.; Lee, J.; Kim, S.; Jeon, T.-J. Biomimetic membranes with transmembrane proteins: State-of-the-art in transmembrane protein applications. International Journal of Molecular Sciences 2019, 20, 1437. [Google Scholar] [CrossRef]
  19. Sanches, R.C.; Tiwari, S.; Ferreira, L.C.; Oliveira, F.M.; Lopes, M.D.; Passos, M.J.; Lopes, D.O.; et al. Immunoinformatics design of multi-epitope peptide-based vaccine against Schistosoma mansoni using transmembrane proteins as a target. Frontiers in immunology 2021, 12, 621706. [Google Scholar] [CrossRef]
  20. Yaacob, M.F.; Murata, A.; Nor, N.H.M.; Jesse, F.F.A.; Yahya, M.F.Z.R. Biochemical composition, morphology and antimicrobial susceptibility pattern of Corynebacterium pseudotuberculosis biofilm. Journal of King Saud University-Science 2021, 33, 101225. [Google Scholar] [CrossRef]
  21. Yahya, M.F.Z.R.; Hamid, U.M.A.; Norfatimah, M.Y.; Kambol, R. In silico analysis of essential tricarboxylic acid cycle enzymes from biofilm-forming bacteria. Trends in Bioinformatics 2014, 7, 19–26. [Google Scholar] [CrossRef]
  22. Yahya, M.F.; Alias, Z.; Karsani, S.A. Subtractive protein profiling of Salmonella typhimurium biofilm treated with DMSO. The Protein Journal 2017, 36, 286–298. [Google Scholar] [CrossRef] [PubMed]
  23. Zhang, R. DEG: A database of essential genes. Nucleic Acids Research 2004, 32. [Google Scholar] [CrossRef]
  24. Zulkiply, N.; Ramli, M.E.; Yahya, M.F.Z.R. In silico identification of antigenic proteins in Staphylococcus aureus. Journal of Sustainability Science and Management 2022, 17, 18–26. [Google Scholar] [CrossRef]
Figure 1. Classification of uncharacterized proteins of S. Typhimurium. A) Biological pathway; B) Molecular function; C) Subcellular localization; D) Transmembrane proteins.
Figure 1. Classification of uncharacterized proteins of S. Typhimurium. A) Biological pathway; B) Molecular function; C) Subcellular localization; D) Transmembrane proteins.
Preprints 106158 g001aPreprints 106158 g001b
Figure 2. A) Transmembrane domains of A0A2J0RKS1; B) Functional motifs of A0A2J0RKS1; C) Protein-protein interaction network of A0A2J0RKS1 (STM0557).
Figure 2. A) Transmembrane domains of A0A2J0RKS1; B) Functional motifs of A0A2J0RKS1; C) Protein-protein interaction network of A0A2J0RKS1 (STM0557).
Preprints 106158 g002
Table 1. Identified transmembrane proteins of S. Typhimurium.
Table 1. Identified transmembrane proteins of S. Typhimurium.
Accession No. of TM domain Biological pathway Molecular function Subcellular localization
A0A2J0RKS1 9 Conjugation Porin activity Cell outer membrane
A0A1P8DMP4 1 Unknown ATP binding Plasma membrane
A0A3Z7JEV9 1 DNA repair DNA ligase activity Cytosol
A0A2J0RFX8 1 Catabolic process D-aminoacyl-tRNA deacylase activity Cytoplasm
A0A2J0RDC1 1 Translocation Unknown Nucleus
A0A3T3ZZV4 1 tRNA processing ATP binding Cytoplasm
A0A3V6H1D5 1 Pathogenesis Unknown Plasma membrane
A0A0D6HCE5 2 Lipoprotein biosynthesis phosphatidylglycerol-prolipoprotein diacylglyceryl transferase activity Plasma membrane
A0A2J0RDS6 1 Host-virus interaction Unknown Host membrane
A0A3V7XF93 1 Carbohydrate metabolic process Carbohydrate binding Extracellular region or secreted
A0A3V7X7Z5 2 Host-virus interaction ATP binding Cell membrane
A0A5Z7LRR5 4 Proteolysis Metal ion binding Cell membrane
A0A5Z7LRA6 1 Cell cycle ATP binding Nucleus
A0A0F7J9G5 1 DNA packaging Metal ion binding viral terminase complex
A0A0F7JGQ1 1 Cell adhesion Protein-containing complex binding Extracellular region or secreted
A0A0F7JFI2 1 Differentiation Zinc ion binding Extracellular region or secreted
A0A0F7JDX1 2 Establishment of competence for transformation Unknown Plasma membrane
A0A5Y2HQY6 1 Amino acid biosynthesis ATP binding Cytoplasm
A0A0F7J982 1 Protein biosynthesis GTP binding Cytoplasm
A0A6C8WQJ4 3 inorganic anion transport Chloride channel activity Plasma membrane
A0A735ZTN8 7 Transmembrane transport Porin activity Plasma membrane
A0A731QU75 2 Chemical synaptic transmission G-protein coupled receptor activity [serotonin] Plasma membrane
A0A607WTJ3 6 Phospholipid biosynthetic process Transferase activity Plasma membrane
A0A705WX69 1 Oxidative phosphorylation Translocase Plasma membrane
A0A707YZC5 1 Cytochrome complex assembly heme transmembrane transporter activity Plasma membrane
A0A706T8K4 2 Transmembrane transport transmembrane transporter activity Vacuole
A0A717VZE3 1 DNA replication DNA binding Plasma membrane
A0A736JL85 2 Folate biosynthesis metal ion binding Inner membrane
A0A610AT56 3 Phospholipid biosynthetic process Transferase activity Plasma membrane
A0A705WZ57 1 Transmembrane transport Transmembrane transporter activity Plasma membrane
A0A701H8E2 4 Cytochrome c-type biogenesis Heme binding Plasma membrane
A0A7G2DIQ3 2 Viral tail assembly Unknown Host cell cytoplasm
Table 2. List of essential and non-host homologous proteins of Salmonella Typhimurium.
Table 2. List of essential and non-host homologous proteins of Salmonella Typhimurium.
Protein Human Cattle Sheep Goat Horses
A0A2J0RKS1 0 0 0 0 0
A0A1P8DMP4 0 0 0 0 0
A0A3Z7JEV9 0 0 0 0 0
A0A2J0RFX8 0 0 0 0 0
A0A2J0RDC1 0 0 0 0 0
A0A3T3ZZV4 0 0 0 0 0
A0A3V6H1D5 0 0 0 0 0
A0A0D6HCE5 0 0 0 0 0
A0A2J0RDS6 0 0 0 0 0
A0A3V7XF93 0 0 0 0 0
A0A3V7X7Z5 0 0 0 0 0
A0A5Z7LRR5 0 0 0 0 0
A0A5Z7LRA6 0 0 0 0 0
A0A0F7J9G5 0 0 0 0 0
A0A0F7JGQ1 0 0 0 0 0
A0A0F7JFI2 0 0 0 0 0
A0A0F7JDX1 0 0 1 0 0
A0A5Y2HQY6 0 0 0 0 0
A0A0F7J982 0 0 0 0 0
A0A6C8WQJ4 0 0 0 0 0
A0A735ZTN8 0 0 0 0 0
A0A731QU75 0 0 0 0 0
A0A607WTJ3 0 0 0 0 0
A0A705WX69 0 0 0 0 0
A0A707YZC5 0 0 0 0 0
A0A706T8K4 0 0 0 0 0
A0A717VZE3 1 0 0 0 0
A0A736JL85 0 0 0 0 0
A0A610AT56 * 0 0 0 0 0
A0A705WZ57 0 0 0 0 0
A0A701H8E2 0 0 0 0 0
A0A7G2DIQ3 0 0 0 0 0
(0) = absence homologues; (1) = presence homologue; (*) refer to non-essential protein.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated