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Construction of Protein Expression Network

Afiqah-Aleng N, Mohamed-Hussein ZA

Methods Mol Biol, 2021;2189:119-132.
PMID: 33180298 DOI: 10.1007/978-1-0716-0822-7_10

In this post-genomic era, protein network can be used as a complementary way to shed light on the growing amount of data generated from current high-throughput technologies. Protein network is a powerful approach to describe the molecular mechanisms of the biological events through protein-protein interactions. Here, we describe the computational methods used to construct the protein network using expression data. We provide a list of available tools and databases that can be used in constructing the network.
Graph cluster approach in identifying novel proteins and significant pathways involved in polycystic ovary syndrome

Afiqah-Aleng N, Altaf-Ul-Amin M, Kanaya S, Mohamed-Hussein ZA

Reprod Biomed Online, 2020 Feb;40(2):319-330.
PMID: 32001161 DOI: 10.1016/j.rbmo.2019.11.012

RESEARCH QUESTION: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with diverse clinical implications, such as infertility, metabolic disorders, cardiovascular diseases and psychological problems among others. The heterogeneity of conditions found in PCOS contribute to its various phenotypes, leading to difficulties in identifying proteins involved in this abnormality. Several studies, however, have shown the feasibility in identifying molecular evidence underlying other diseases using graph cluster analysis. Therefore, is it possible to identify proteins and pathways related to PCOS using the same approach?
METHODS: Known PCOS-related proteins (PCOSrp) from PCOSBase and DisGeNET were integrated with protein-protein interactions (PPI) information from Human Integrated Protein-Protein Interaction reference to construct a PCOS PPI network. The network was clustered with DPClusO algorithm to generate clusters, which were evaluated using Fisher's exact test. Pathway enrichment analysis using gProfileR was conducted to identify significant pathways.
RESULTS: The statistical significance of the identified clusters has successfully predicted 138 novel PCOSrp with 61.5% reliability and, based on Cronbach's alpha, this prediction is acceptable. Androgen signalling pathway and leptin signalling pathway were among the significant PCOS-related pathways corroborating the information obtained from the clinical observation, where androgen signalling pathway is responsible in producing male hormones in women with PCOS, whereas leptin signalling pathway is involved in insulin sensitivity.
CONCLUSIONS: These results show that graph cluster analysis can provide additional insight into the pathobiology of PCOS, as the pathways identified as statistically significant correspond to earlier biological studies. Therefore, integrative analysis can reveal unknown mechanisms, which may enable the development of accurate diagnosis and effective treatment in PCOS.
Fulltext Protein-Protein Interaction Network Analysis Reveals Several Diseases Highly Associated with Polycystic Ovarian Syndrome

Ramly B, Afiqah-Aleng N, Mohamed-Hussein ZA

Int J Mol Sci, 2019 Jun 18;20(12).
PMID: 31216618 DOI: 10.3390/ijms20122959

Based on clinical observations, women with polycystic ovarian syndrome (PCOS) are prone to developing several other diseases, such as metabolic and cardiovascular diseases. However, the molecular association between PCOS and these diseases remains poorly understood. Recent studies showed that the information from protein-protein interaction (PPI) network analysis are useful in understanding the disease association in detail. This study utilized this approach to deepen the knowledge on the association between PCOS and other diseases. A PPI network for PCOS was constructed using PCOS-related proteins (PCOSrp) obtained from PCOSBase. MCODE was used to identify highly connected regions in the PCOS network, known as subnetworks. These subnetworks represent protein families, where their molecular information is used to explain the association between PCOS and other diseases. Fisher's exact test and comorbidity data were used to identify PCOS-disease subnetworks. Pathway enrichment analysis was performed on the PCOS-disease subnetworks to identify significant pathways that are highly involved in the PCOS-disease associations. Migraine, schizophrenia, depressive disorder, obesity, and hypertension, along with twelve other diseases, were identified to be highly associated with PCOS. The identification of significant pathways, such as ribosome biogenesis, antigen processing and presentation, and mitophagy, suggest their involvement in the association between PCOS and migraine, schizophrenia, and hypertension.
Fulltext Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach

Harun S, Afiqah-Aleng N, Karim MB, Altaf Ul Amin M, Kanaya S, Mohamed-Hussein ZA

PeerJ, 2021;9:e11876.
PMID: 34430080 DOI: 10.7717/peerj.11876

Background: Glucosinolates (GSLs) are plant secondary metabolites that contain nitrogen-containing compounds. They are important in the plant defense system and known to provide protection against cancer in humans. Currently, increasing the amount of data generated from various omics technologies serves as a hotspot for new gene discovery. However, sometimes sequence similarity searching approach is not sufficiently effective to find these genes; hence, we adapted a network clustering approach to search for potential GSLs genes from the Arabidopsis thaliana co-expression dataset.
Methods: We used known GSL genes to construct a comprehensive GSL co-expression network. This network was analyzed with the DPClusOST algorithm using a density of 0.5. 0.6. 0.7, 0.8, and 0.9. Generating clusters were evaluated using Fisher's exact test to identify GSL gene co-expression clusters. A significance score (SScore) was calculated for each gene based on the generated p-value of Fisher's exact test. SScore was used to perform a receiver operating characteristic (ROC) study to classify possible GSL genes using the ROCR package. ROCR was used in determining the AUC that measured the suitable density value of the cluster for further analysis. Finally, pathway enrichment analysis was conducted using ClueGO to identify significant pathways associated with the GSL clusters.
Results: The density value of 0.8 showed the highest area under the curve (AUC) leading to the selection of thirteen potential GSL genes from the top six significant clusters that include IMDH3, MVP1, T19K24.17, MRSA2, SIR, ASP4, MTO1, At1g21440, HMT3, At3g47420, PS1, SAL1, and At3g14220. A total of Four potential genes (MTO1, SIR, SAL1, and IMDH3) were identified from the pathway enrichment analysis on the significant clusters. These genes are directly related to GSL-associated pathways such as sulfur metabolism and valine, leucine, and isoleucine biosynthesis. This approach demonstrates the ability of the network clustering approach in identifying potential GSL genes which cannot be found from the standard similarity search.
Fulltext PCOSBase: a manually curated database of polycystic ovarian syndrome

Afiqah-Aleng N, Harun S, A-Rahman MRA, Nor Muhammad NA, Mohamed-Hussein ZA

Database (Oxford), 2017 Jan 01;2017.
PMID: 31725861 DOI: 10.1093/database/bax098

Polycystic ovarian syndrome (PCOS) is one of the main causes of infertility and affects 5-20% women of reproductive age. Despite the increased prevalence of PCOS, the mechanisms involved in its pathogenesis and pathophysiology remains unclear. The expansion of omics on studying the mechanisms of PCOS has lead into vast amounts of proteins related to PCOS resulting to a challenge in collating and depositing this deluge of data into one place. A knowledge-based repository named as PCOSBase was developed to systematically store all proteins related to PCOS. These proteins were compiled from various online databases and published expression studies. Rigorous criteria were developed to identify those that were highly related to PCOS. They were manually curated and analysed to provide additional information on gene ontologies, pathways, domains, tissue localizations and diseases that associate with PCOS. Other proteins that might interact with PCOS-related proteins identified from this study were also included. Currently, 8185 PCOS-related proteins were identified and assigned to 13 237 gene ontology vocabulary, 1004 pathways, 7936 domains, 29 disease classes, 1928 diseases, 91 tissues and 320 472 interactions. All publications related to PCOS are also indexed in PCOSBase. Data entries are searchable in the main page, search, browse and datasets tabs. Protein advanced search is provided to search for specific proteins. To date, PCOSBase has the largest collection of PCOS-related proteins. PCOSBase aims to become a self-contained database that can be used to further understand the PCOS pathogenesis and towards the identification of potential PCOS biomarkers. Database URL: http://pcosbase.org.
Current trends of host-pathogen relationship in shrimp infectious disease via computational protein-protein interaction: A bibliometric analysis

Rosilan NF, Waiho K, Fazhan H, Sung YY, Zakaria NH, Afiqah-Aleng N, et al.

Fish Shellfish Immunol, 2023 Nov;142:109171.
PMID: 37858788 DOI: 10.1016/j.fsi.2023.109171

Protein-protein interactions (PPIs) are essential for understanding cell physiology in normal and pathological conditions, as they might involve in all cellular processes. PPIs have been widely used to elucidate the pathobiology of human and plant diseases. Therefore, they can also be used to unveil the pathobiology of infectious diseases in shrimp, which is one of the high-risk factors influencing the success or failure of shrimp production. PPI network analysis, specifically host-pathogen PPI (HP-PPI), provides insights into the molecular interactions between the shrimp and pathogens. This review quantitatively analyzed the research trends within this field through bibliometric analysis using specific keywords, countries, authors, organizations, journals, and documents. This analysis has screened 206 records from the Scopus database for determining eligibility, resulting in 179 papers that were retrieved for bibliometric analysis. The analysis revealed that China and Thailand were the driving forces behind this specific field of research and frequently collaborated with the United States. Aquaculture and Diseases of Aquatic Organisms were the prominent sources for publications in this field. The main keywords identified included "white spot syndrome virus," "WSSV," and "shrimp." We discovered that studies on HP-PPI are currently quite scarce. As a result, we further discussed the significance of HP-PPI by highlighting various approaches that have been previously adopted. These findings not only emphasize the importance of HP-PPI but also pave the way for future researchers to explore the pathogenesis of infectious diseases in shrimp. By doing so, preventative measures and enhanced treatment strategies can be identified.
Gonadal transcriptomic analysis of the mud crab Scylla olivacea infected with rhizocephalan parasite Sacculina beauforti

Waiho K, Fazhan H, Zhang Y, Afiqah-Aleng N, Moh JHZ, Ikhwanuddin M, et al.

Genomics, 2020 09;112(5):2959-2969.
PMID: 32437851 DOI: 10.1016/j.ygeno.2020.05.007

Infection by the rhizocephalan parasite Sacculina beauforti can have detrimental effects on mud crab Scylla olivacea. However, the molecular changes that occur during rhizocephalan infection are poorly understood. Due to the disruption in the reproductive system after infection, the gonadal transcriptomic profiles of non-infected and infected Scylla olivacea were compared. A total of 686 and 843 unigenes were differentially expressed between non-infected and infected males, and females, respectively. The number of DEGs increased after infection. By comparing shared DEGs of non-infected and infected individuals, potential immune- and reproduction-related of host, and immune- and metabolism-related genes of parasite are highlighted. The only shared KEGG pathway between non-infected and infected individuals was the ribosome pathway. In summary, findings in this study provide new insights into the host-parasite relationship of rhizocephalan parasites and their crustacean hosts.
Fulltext Applications of Next-Generation Sequencing Technologies and Computational Tools in Molecular Evolution and Aquatic Animals Conservation Studies: A Short Review

Tan MP, Wong LL, Razali SA, Afiqah-Aleng N, Mohd Nor SA, Sung YY, et al.

Evol Bioinform Online, 2019;15:1176934319892284.
PMID: 31839703 DOI: 10.1177/1176934319892284

Aquatic ecosystems that form major biodiversity hotspots are critically threatened due to environmental and anthropogenic stressors. We believe that, in this genomic era, computational methods can be applied to promote aquatic biodiversity conservation by addressing questions related to the evolutionary history of aquatic organisms at the molecular level. However, huge amounts of genomics data generated can only be discerned through the use of bioinformatics. Here, we examine the applications of next-generation sequencing technologies and bioinformatics tools to study the molecular evolution of aquatic animals and discuss the current challenges and future perspectives of using bioinformatics toward aquatic animal conservation efforts.
Fulltext Bridging the gap between sustainability and profitability: unveiling the untapped potential of sea cucumber viscera

Muhsin MF, Fujaya Y, Hidayani AA, Fazhan H, Wan Mahari WA, Lam SS, et al.

PeerJ, 2023;11:e16252.
PMID: 37842055 DOI: 10.7717/peerj.16252

Sea cucumbers have high economic value, and in most forms of trade, their body wall is typically the only part that is harvested and sold. The organs of the sea cucumber, collectively known as the viscera, are frequently discarded, contributing to land and water pollution. However, discarded sea cucumber viscera contain various nutrients that can be used in many applications. Therefore, this review highlights the biological and economic aspects of sea cucumbers, followed by a critical discussion of the nutritional value of their internal organs and possible applications, including as functional feed additives in the aquaculture industry, sources of natural testosterone for application in sex reversal and production of monosex population, of neuroprotective agents against central nervous system disorders and of cosmetic ingredients, especially for skin whitening and anti-ageing products. The review further highlights the valorisation potential of viscera to maximize their economic potential, thus providing an enormous prospect for reusing sea cucumber waste, thereby reducing the negative impact of the sea cucumber fishery sector on the environment.
Fulltext Molecular docking and dynamics simulation studies uncover the host-pathogen protein-protein interactions in Penaeus vannamei and Vibrio parahaemolyticus

Rosilan NF, Jamali MAM, Sufira SA, Waiho K, Fazhan H, Ismail N, et al.

PLoS One, 2024;19(1):e0297759.
PMID: 38266027 DOI: 10.1371/journal.pone.0297759

Shrimp aquaculture contributes significantly to global economic growth, and the whiteleg shrimp, Penaeus vannamei, is a leading species in this industry. However, Vibrio parahaemolyticus infection poses a major challenge in ensuring the success of P. vannamei aquaculture. Despite its significance in this industry, the biological knowledge of its pathogenesis remains unclear. Hence, this study was conducted to identify the interaction sites and binding affinity between several immune-related proteins of P. vannamei with V. parahaemolyticus proteins associated with virulence factors. Potential interaction sites and the binding affinity between host and pathogen proteins were identified using molecular docking and dynamics (MD) simulation. The P. vannamei-V. parahaemolyticus protein-protein interaction of Complex 1 (Ferritin-HrpE/YscL family type III secretion apparatus protein), Complex 2 (Protein kinase domain-containing protein-Chemotaxis CheY protein), and Complex 3 (GPCR-Chemotaxis CheY protein) was found to interact with -4319.76, -5271.39, and -4725.57 of the docked score and the formation of intermolecular bonds at several interacting residues. The docked scores of Complex 1, Complex 2, and Complex 3 were validated using MD simulation analysis, which revealed these complexes greatly contribute to the interactions between P. vannamei and V. parahaemolyticus proteins, with binding free energies of -22.50 kJ/mol, -30.20 kJ/mol, and -26.27 kJ/mol, respectively. This finding illustrates the capability of computational approaches to search for molecular binding sites between host and pathogen, which could increase the knowledge of Vibrio spp. infection on shrimps, which then can be used to assist in the development of effective treatment.

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