UWCScholar :: Browsing by Author "Pretorius, Ashley"

Browsing by Author "Pretorius, Ashley"

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Analysis, expression profiling and characterization of hsa-miR-5698 target genes as putative dynamic network biomarkers for prostate cancer: a combined in silico and molecular approach
(University of the Western Cape, 2019) Lombe, Chipampe Patricia; Pretorius, Ashley; Meyer, Mervin
2018, the International Agency for Research on Cancer (IARC) estimated that prostate cancer (PCa) was the second leading cause of death in males worldwide. The number of deaths are expected to raise by 50 % in the next decade. This rise is attributed to the shortcomings of the current diagnostic, prognostic, and therapeutic biomarkers used in the management of the disease. Therefore, research into more sensitive, specific and effective biomarkers is a requirement. The use of biomarkers in PCa diagnosis and management takes advantage of the genetic alterations and abnormalities that characterise the disease. In this regard, a microRNA, hsa-miR-5698 was identified in a previous study as a differentiating biomarker between prostate adenocarcinoma and bone metastasis. Six putative translational targets (CDKN1A, CTNND1, FOXC1, LRP8, ELK1 and BIRC2) of this microRNA were discovered using in silico approaches. The aim of this study was to analyse via expression profiling and characterization, the target genes of hsa-miR-5698 in order to determine their ability to act as putative dynamic network biomarkers for PCa. The study was conducted using a combined in silico and molecular approach. The in silico part of the study investigated the putative transcriptional effects of hsa-miR-5698 on the promotors of its translational targets, the correlation between hsa-miR-5698 and mRNA expression profiles as well as the co-expression analysis, pathway analysis and prognostic ability of the target genes. A number of computational software were employed for these purposes, including, R Studio, Trident algorithm, STRING, KEGG, MEME Suite, SurvExpress and ProGgene. The molecular part of the study involved expression profiling of the genes in two PCa cell line LNCaP and PC3 via qPCR.
Building HMM and molecular docking analysis for the sensitive detection of anti-viral pneumonia antimicrobial peptides (AMPs)
(Nature Research, 2021) Bakare, Olalekan Olanrewaju; Keyster, Marshall; Pretorius, Ashley
Pneumonia is the main reason for mortality among children under five years, causing 1.6 million deaths every year; late research has exhibited that mortality is increasing in the elderly. A few biomarkers used for its diagnosis need specificity and precision, as they are related to different infections, for example, pulmonary tuberculosis and Human Immunodeficiency Virus. There is a quest for new biomarkers worldwide to diagnose the disease to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) are promising indicative specialists against infection. This research work used AMPs as biomarkers to detect viral pneumonia pathogens, for example, Respiratory syncytial virus, Influenza A and B viruses utilizing in silico technologies, such as Hidden Markov Model (HMMER). HMMER was used to distinguish putative anti-viral pneumonia AMPs against the recognized receptor proteins of Respiratory syncytial virus, Influenza A, and B viruses. The physicochemical parameters of these putative AMPs were analyzed, and their 3-D structures were determined utilizing I-TASSER. Molecular docking interaction of these AMPs against the recognized viral pneumonia proteins was carried out using the PATCHDOCK and HDock servers. The results demonstrated 27 anti-viral AMPs ranked based on their E values with significant physicochemical parameters in similarity with known experimentally approved AMPs. The AMPs additionally had a high anticipated binding potential to the pneumonia receptors of these microorganisms sensitively. The tendency of the putative anti-viral AMPs to bind pneumonia proteins showed that they would be promising applicant biomarkers to identify these viral microorganisms in the point-of-care (POC) pneumonia diagnostics. The high precision observed for the AMPs legitimizes HMM’s utilization in the disease diagnostics’ discovery process
Changes in subcutaneous adipose tissue microRNA expression in response to exercise training in African women with obesity
(Nature Research, 2022) Pheiffer, Carmen; Dias, Stephanie; Pretorius, Ashley
The mechanisms that underlie exercise-induced adaptations in adipose tissue have not been elucidated, yet, accumulating studies suggest an important role for microRNAs (miRNAs). This study aimed to investigate miRNA expression in gluteal subcutaneous adipose tissue (GSAT) in response to a 12-week exercise intervention in South African women with obesity, and to assess depot-specific differences in miRNA expression in GSAT and abdominal subcutaneous adipose tissue (ASAT). In addition, the association between exercise-induced changes in miRNA expression and metabolic risk was evaluated. Women underwent 12-weeks of supervised aerobic and resistance training (n = 19) or maintained their regular physical activity during this period (n = 12). Exercise-induced miRNAs were identified in GSAT using Illumina sequencing, followed by analysis of differentially expressed miRNAs in GSAT and ASAT using quantitative real-time PCR. Associations between the changes (pre- and postexercise training) in miRNA expression and metabolic parameters were evaluated using Spearman’s correlation tests.
Characterization of ATP-binding cassette drug transporters and their role in breast cancer treatment using in silico approach
(University of the Western Cape, 2019) Hassan, Mohammed Hashim Abdalraheem; Klein, Ashwil; Pretorius, Ashley
Breast cancer is the most common cancer in women worldwide, and is the second most common cancer in the world, responsible for more than 500 000 deaths annually. Estimates are that 1 in 8 women will develop breast cancer in their lifetime. In South Africa, breast cancer in women affects about 16.6 % of the population and could see a 78 % increase in cases by 2030. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effects. The Chemotherapy resistance against anticancer drugs is an emerging concern. Biomarkers have been identified as a viable option for early detection and progression of disease. Examples of biological indicators for disease could be the ATP-binding cassette (ABC) drug transporters that utilizes the energy derived from ATP hydrolysis to efflux many chemically diverse compounds across the plasma membrane, thereby playing a critical and important physiological role in protecting cells from xenobiotics. These transporters are also implicated in the development of multidrug resistance (MDR) in cancer cells that have been treated with chemotherapeutics. High expression of these membrane proteins as a family of ABC drug transporters are one of the main reasons for drug resistance by increasing the efflux rate of the anti-cancer drug from cancer cells. ABC drug transporters are considered to be one of the largest protein families in living organisms. There are 48 genes in the human genome that encode ABC transporters, which are divided into seven subfamilies (ABCA-ABCG). Studies revealed that ABC transporter genes has been shown to be associated with tumour development, progression and response to therapy, suggesting their possible use as diagnostic, prognostic and predictive biomarkers. The aim of this study was to investigate and identify novel ABC transporter genes that could be implicated in breast cancer and MDR and potentially would be a therapeutic target for successful chemotherapy treatment and disease progression and survival in breast cancer patients. An in silico approach was used to identify 10 ABC transporter genes (ABCB2, ABCB9, ABCB10, ABCC1, ABCC4, ABCC5, ABCC10, ABCC11, ABCC12, ABCD1) implicated in breast cancer by conferring drug resistance through over-expression in cancer cells. The in silico study investigated the tissue expression specificity, protein interaction/s, pathways, and comparative toxicogenomics of the identified ABC transporter genes using several computational software such as Tissue-specific Gene Expression and Regulation (TiGER), the Human Protein Atlas (HPA), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and The Comparative Toxicogenomics Database (CTD). The 48 ABC transporter genes were shortlisted through very selective criteria that narrowed the genes down to 10. Differential expression analysis of the genes using TiGER and HPA compared expression in normal versus cancerous tissue of the candidate genes. The result showed that ABCC11 was preferentially expressed in breast tissue with an enrichment value higher than 10.0. The results also showed ABCC10 overexpressed in breast cancer tissue, making these two genes top candidates for further analysis. Result from STRING database showed a strong functional interaction network between the prioritized genes through protein homology, co-expression and text mining as evidence for the observed interactions. Furthermore, the prioritized list of genes was submitted to the CTD for intersectional analysis to obtain the toxicity relationship between the genes and the Tamoxifen as the first line chemotherapeutic treatment for breast cancer. Venn diagrams obtained from CTD showed intersectional relation between ABCB2, ABCC1, ABCC4, ABCC11, and ABCD1 genes and Tamoxifen. Furthermore, an in silico validation of the prognostic/predictive values of the 10 prioritized genes (list 2) was carried out using an online biomarker validation tool and database for cancer gene expression data using survival analysis (SurvExpress) and gene expression based survival analysis web application for multiple cancer (PROGGENE). Results obtained from the PROGGENE survival and predictive analysis showed good prognostic values for the genes ABCB2, ABCC1, ABCC4, ABCC10 and ABCC12 with their significance measured by the probability value (Pv) (0.053, 0.001118, 0.01286, 0.00604, 0.00157 respectively). From this study ABCC1, ABCC4, ABCC5, ABCC10, and ABCC11 genes could serve as putative therapeutic target biomarkers for breast cancer treatment following further in depth analysis. However, the variance in the effectiveness of individual genes suggests that the set of genes would perform better than individual gene in the management of breast cancer. The modulating roles of ABCC4, ABCC5 ABCC10, and ABCC11 in drug induced apoptosis, suggest they could probably play an important role in personalized medicine and could serve as biomarkers to monitor the prognosis and/or therapeutic outcome of chemotherapy drugs in breast cancer patients. The use of modern genomics, proteomics, bioinformatics, and systems biology approaches has resulted in a substantial increase in our ability to identify molecular mechanisms that are involved in MDR in cancer and to find drugs that may block or reverse the development of drug resistance. By using an in silico approach in this study, a list of five ABC transporter genes were identified, of which two (ABCC10 and ABCC11) could potentially serve as prognostic and predictive biomarkers for the management of breast cancer treatment.
DAMPD: a manually curated antimicrobial peptide database
(Oxford University Press, 2012) Sundararajan, Vijayaraghava S.; Gabere, Musa N.; Pretorius, Ashley; Adam, Saleem; Christoffels, Alan; Minna, Lehvaslaiho; Archer, John A.C.; Bajic, Vladimir B.
The demand for antimicrobial peptides (AMPs) is rising because of the increased occurrence of pathogens that are tolerant or resistant to conventional antibiotics. Since naturally occurring AMPs could serve as templates for the development of new anti-infectious agents to which pathogens are not resistant, a resource that contains relevant information on AMP is of great interest. To that extent, we developed the Dragon Antimicrobial Peptide Database (DAMPD, http://apps.sanbi.ac.za/dampd) that contains 1232 manually curated AMPs. DAMPD is an update and a replacement of the ANTIMIC database. In DAMPD an integrated interface allows in a simple fashion querying based on taxonomy, species, AMP family, citation, keywords and a combination of search terms and fields (Advanced Search). A number of tools such as Blast, ClustalW, HMMER, Hydrocalculator, SignalP, AMP predictor, as well as a number of other resources that provide additional information about the results are also provided and integrated into DAMPD to augment biological analysis of AMPs.
The detection of meningococcal disease through identification of antimicrobial peptides using an in silico model creation
(University of the Western Cape, 2019) Abdullah, Gadija; Pretorius, Ashley; Den Haan, Riaan
Neisseria meningitidis (the meningococcus), the causative agent of meningococcal disease (MD) was identified in 1887 and despite effective antibiotics and partially effective vaccines, Neisseria meningitidis (N. meningitidis) is the leading cause worldwide of meningitis and rapidly fatal sepsis usually in otherwise healthy individuals. Over 500 000 meningococcal cases occur every year. These numbers have made bacterial meningitis a top ten infectious cause of death worldwide. MD primarily affects children under 5 years of age, although in epidemic outbreaks there is a shift in disease to older children, adolescents and adults. MD is also associated with marked morbidity including limb loss, hearing loss, cognitive dysfunction, visual impairment, educational difficulties, developmental delays, motor nerve deficits, seizure disorders and behavioural problems. Antimicrobial peptides (AMPs) are molecules that provide protection against environmental pathogens, acting against a large number of microorganisms, including bacteria, fungi, yeast and virus. AMPs production is a major component of innate immunity against infection. The chemical properties of AMPs allow them to insert into the anionic cell wall and phospholipid membranes of microorganisms or bind to the bacteria making it easily detectable for diagnostic purposes. AMPs can be exploited for the generation of novel antibiotics, as biomarkers in the diagnosis of inflammatory conditions, for the manipulation of the inflammatory process, wound healing, autoimmunity and in the combat of tumour cells. Due to the severity of meningitis, early detection and identification of the strain of N. meningitidis is vital. Rapid and accurate diagnosis is essential for optimal management of patients and a major problem for MD is its diagnostic difficulties and experts conclude that with an early intervention the patient’ prognosis will be much improved. It is becoming increasingly difficult to confirm the diagnosis of meningococcal infection by conventional methods. Although polymerase chain reaction (PCR) has the potential advantage of providing more rapid confirmation of the presence of the bacterium than culturing, it is still time consuming as well as costly. Introduction of AMPs to bind to N. meningitidis receptors could provide a less costly and time consuming solution to the current diagnostic problems. World Health Organization (WHO) meningococcal meningitis program activities encourage laboratory strengthening to ensure prompt and accurate diagnosis to rapidly confirm the presence of MD. This study aimed to identify a list of putative AMPs showing antibacterial activity to N. meningitidis to be used as ligands against receptors uniquely expressed by the bacterium and for the identified AMPs to be used in a Lateral Flow Device (LFD) for the rapid and accurate diagnosis of MD.
Dietary effects of antimicrobial peptides in therapeutics
(Taylor & Francis, 2020-02-17) Bakare, Olalekan Olanrewaju; Fadaka, Adewale Oluwaseun; Klein, Ashwil; Pretorius, Ashley
The notable increase in drug-resistant infections and the failure of the most potent antibiotics to establish their curative effect without side effect have presented a serious need for the discovery of new therapeutic agent and the study of dietary implications on the mode of entry of these therapeutic agents in the human system. This review provides insight into the forms and modes of action, and roles of beneficial but limited and underutilized antimicrobial peptides for use in dietary formulations, with particular focus on the technologies employed for their discovery as well as their dietary efficacy. The wide spectrum of activities of these peptides will allow the opportunity to explore their benefits as dietary supplements and additives.
Functional analysis of miRNA regulated genes in prostate cancer as potential diagnostic molecules
(University of the Western Cape, 2016) Abdullah, Gadija; Pretorius, Ashley; Khan, Firdous
Prostate Cancer is the leading cause of cancer-related death in males in the Western world. It is a common biological disease originating from the reproductive system of the male namely, the prostate gland, usually in older patients (over the age of 50) and with a family history of this disease. The disease shows clinical aggressiveness due to genetic alterations of gene expression in prostate epithelial cells. Prostate cancer is currently diagnosed by biopsy and prostate cancer screening via the Prostate-Specific Antigen (PSA) blood test. Early detection is critical and although PSA was discovered to aid in the diagnoses of this cancer at its early stages, it has a disadvantage due to its low specificity thus causing unnecessary biopsies of healthy individuals and overtreatment of patients. Although various studies and efforts have been made to identify the ideal biomarker for prostate cancer and many even being applied to clinical use, it is still challenging and has not replaced the best-known biomarker PSA. PSA test has minimal invasive characteristics, at relatively low cost together with high sensitivity but low specificity. Biomarker discovery is a challenging process and a good biomarker has to be sensitive, specific and its test highly standardized and reproducible as well as identify risk for or diagnose a disease, assess disease severity or progression, predict prognosis or guide treatment. Computational biology plays a significant role in the discovery of new biomarkers, the analyses of disease states and the validation of potential biomarkers. Bioinformatic approaches are effective for the detection of potential micro ribonucleic acid (miRNA) in cancer. Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. Small non-protein coding RNA, miRNA are small regulatory RNA molecules that modulate the expression of their target genes. miRNAs influence numerous cancer-relevant processes such as proliferation, cell cycle control, apoptosis, differentiation, migration and metabolism. Discovery and existence of extracellular miRNAs that circulate in the blood of cancer patients has raised the possibility that miRNAs may serve as novel diagnostic markers. Since a single miRNA is said to be able to target several mRNAs, aberrant miRNA expression is capable of disrupting the expression of several mRNAs and proteins. Biomarker discovery for prostate cancer of mRNA and miRNA expression are strongly needed to enable more accurate detection of prostate cancer, improve prediction of tumour aggressiveness and facilitate diagnosis. The aim of this project was to focus on functional analyses of genes and their protein products regulated by previously identified miRNA in prostate cancer using bioinformatics as a tool. Most proteins function in collaboration with other proteins and therefore this study further aims to identify these protein-protein interactions and the biological relevance of these interactions as it relates to Prostate cancer. Various computational databases were used such as STRING, DAVID and GeneHub-GEPIS for functional analyses of these miRNA regulated genes. The main focus was on the 21 genes regulated by several miRNAs identified in a previous study. Results from this study identified six genes; ERP44, GP1BA, IFNG, SEPT2, TNFRSF13C and TNFSF4, as possible diagnostic biomarkers for prostate cancer. These results are promising, since the targeted biomarkers would be easily detectable in bodily fluids with the Gene Ontology (GO) analysis of these gene products showing enrichment for cell surface expression. The six genes identified in silico were associated to transcription factors (TFs) to confirm regulatory control of these TFs in cancer promoting processes and more specifically prostate cancer. The CREB, E2F, Nkx3-1 and p53 TFs were discovered to be linked to the genes IFNG, GP1BA, SEPT2 and TNFRSF13C respectively. The expression of these TFs show strong association with cancer and cancer related pathways specifically prostate cancer and thus demonstrates that these genes can be assessed as possible biomarkers for prostate cancer. The prognostic and predictive values of the candidate genes were evaluated to assess their relationship to prognosis of this disease by means of several in silico prognostic databases. The results revealed expression differences for the majority of the candidate genes were not significantly sufficient to be distinguished as strong prognostic biomarkers in several prostate cancer populations. Although one marker, GP1BA was supported as having prognostic value for prostate cancer based on it's statistical pvalue in one of the prostate cancer patient datasets used. Another candidate gene SEPT2 showed promise as it has some prognostic value in the early stages of the disease. Although the results yielded, based on the in silico analysis, were not the discovery of an ideal diagnostic marker based on the set criteria in this study, further analysis using a molecular approach qRT-PCR can be considered for a detailed followup study on selected candidate genes to evaluate their roles in disease initiation and progression of prostate cancer using cell lines as well as patient samples.
Functional analysis of the mouse RBBP6 gene using Interference RNA
(University of the Western Cape, 2007) Pretorius, Ashley; Jasper, D.; Rees, G.; Faculty of Science
The aim of this thesis was to investigate the cellular role of the mouse RBBP6 gene using the interference RNA (RNAi) gene targeting technology and also to understand the relevance of two promoters for the RBBP6 gene.
Functional prediction of candidate micrornas for CRC management using in silico approach
(MDPI, 2019) Fadaka, Adewale Oluwaseun; Pretorius, Ashley; Klein, Ashwil
Approximately 30–50% of malignant growths can be prevented by avoiding risk factors and implementing evidence-based strategies. Colorectal cancer (CRC) accounted for the second most common cancer and the third most common cause of cancer death worldwide. This cancer subtype can be reduced by early detection and patients’ management. In this study, the functional roles of the identified microRNAs were determined using an in silico pipeline. Five microRNAs identified using an in silico approach alongside their seven target genes from our previous study were used as datasets in this study. Furthermore, the secondary structure and the thermodynamic energies of the microRNAs were revealed by Mfold algorithm. The triplex binding ability of the oligonucleotide with the target promoters were analyzed by Trident. Finally, evolutionary stage-specific somatic events and co-expression analysis of the target genes in CRC were analyzed by SEECancer and GeneMANIA plugin in Cytoscape. Four of the five microRNAs have the potential to form more than one secondary structure. The ranges of the observed/expected ratio of CpG dinucleotides of these genes range from 0.60 to 1.22.
Identification and Molecular validation of Biomarkers for the accurate and sensitive diagnosis of bacterial and viral Pneumonia
(University of Western Cape, 2019) Bakare, Olalekan Olanrewaju; Pretorius, Ashley; Keyster, Marshall
Pneumonia remains the major cause of death in children and the elderly and several efforts have been intensified to reduce the rate of pneumonia infection. The major breakthrough has been the discovery of certain biomarkers for the diagnosis of pneumonia through immunogenic techniques.
Identification and validation of micrornas for diagnosing type 2 diabetes : an in silico and molecular approach
(University of the Western Cape, 2015) Anthony, Yancke; Pretorius, Ashley
Type 2 diabetes mellitus (T2DM), a metabolic disease characterized by chronic hyperglycemia, is the most prevalent form of diabetes globally, affecting approximately 95 % of the total number of people with diabetes i.e. approximately 366 million. Furthermore, it is also the most prevalent form in South Africa (SA), affecting approximately 3.5 million individuals. This disease and its adverse complications can be delayed or prevented if detected early. Standardized diagnostic tests for T2DM have a few limitations which include the inability to predict the future risk of normal glucose tolerance individuals developing T2DM, they are dependent on blood glucose concentration, its invasiveness, and they cannot specify between T1DM and T2DM. Therefore, there is a need for biomarkers which could be used as a tool for the early and specific detection of T2DM. MicroRNAs are small non-coding RNA molecules which play a key role in controlling gene expression and certain biological processes. Studies show that dysregulation of microRNAs may lead to various diseases including T2DM, and thus, may be useful biomarkers for disease detection. Therefore, identifying biomarkers like microRNAs as a tool for the early and specific detection of T2DM, have great potential for diagnostic purposes. The main focus of this investigation, therefore, is the early detection of T2DM by the identification and validation of novel biomarkers. Furthermore, based on previous studies, the aim of the investigation was to identify differentially expressed miRNAs as well as identify their potential target genes associated with the onset and progression of T2DM. An in silico approach was used to identify miRNAs found to be differentially expressed in the serum/plasma of T2DM individuals. Three publically available target prediction software were used for target gene prediction of the identified miRNA. The target genes were subjected to functional analysis using a web-based software, namely DAVID. Functions which were clustered with an enrichment score > 1.3 were considered significant. The ranked target genes mostly had gene ontologies linked with “transcription regulation”, “neuron signalling, and “metal ion binding”. The ranked target genes were then split into two lists – an up-regulated (ur) miRNA targeted gene list and a down-regulated (dr) miRNA targeted gene list. The in silico method used in this investigation produced a final total of 4 miRNAs: miR-dr-1, miR-ur-1, miR-ur-2, and miR-ur-3. Based on the bioinformatics results, miR-dr-1 and its target genes LDLR, PPARA and CAMTA1, seemed the most promising miRNA for biomarker validation, due to the function of the target genes being associated with T2DM onset and progression. The expression levels of the miRNAs were then profiled in kidney tissue of male Wistar rats that were on a high fat diet (HFD), streptozotocin (STZ)-induced T1DM, and non-diabetic control rats via qRT-PCR analysis. The hypothesis was that similar miRNA expression would be found in the HFD kidney samples compared to serum expression levels of the miRNA obtained from the two databases, since kidneys are involved in cleansing the blood from impurities. This hypothesis proved to be true for all miRNAs except for miR-ur-2. Additionally, miR-ur-1 seemed the most significant miRNA due to it having different expression ratios for T1DM and T2DM (i.e. -7.65 and 4.2 fold, respectively). Future work, therefore, include validation of the predicted target genes to the miRNAs of interest i.e. miR-dr-1: PPARA and LDLR and miR-ur-1: CACNB2, using molecular approaches such as the luciferase assays and western blots.
Identification and validation of putative therapeutic and diagnostic antimicrobial peptides against HIV: An in silico approach
(University of the Western Cape, 2013) Tincho, Marius Belmondo; Pretorius, Ashley
Background: Despite the effort of scientific research on HIV therapies and to reduce the rate of HIV infection, AIDS still remains one of the major causes of death in the world and mostly in Sub-Saharan Africa. To date, neither a cure, nor an HIV vaccine had been found and the disease can only be managed by using High Active Antiretroviral Therapy (HAART) if detected early. The need for an effective early diagnostic and non-toxic therapeutic treatment has brought about the necessity for the discovery of additional HIV diagnostic methods and treatment regimens to lower mortality rates. Antimicrobial Peptides (AMPs) are components of the first line of defence of prokaryotes and eukaryotes and have been proven to be promising therapeutic agents against HIV. Methods: With the utility of computational biology, this work proposes the use of profile search methods combined with structural modelling to identify putative AMPs with diagnostic and anti-HIV activity. Firstly, experimentally validated anti-HIV AMPs were retrieved from various publicly available AMP databases, APD, CAMP, Bactibase and UniprotKB and classified according to super-families. Hidden Markov Model (HMMER) and Gap Local Alignment of Motifs (GLAM2) profiles were built for each super-family of anti- HIV AMPs. Putative anti-HIV AMPs were identified after scanning genome sequence databases using the trained models, retrieved AMPs and ranked based on their E-values. The 3-D structures of the 10 peptides that were ranked highest were predicted using 1-TASSER. These peptides were docked against various HIV proteins using PatchDock and putative AMPs showing highest affinity and having the correct orientation to the HIV -1 proteins gp 120 and p24 were selected for future work so as to establish their function in HIV therapy and diagnosis. Results: The results of the in silica analysis showed that the constructed models using the HMMER algorithm had better performances compare to that of the models built by the GLAM2 algorithm. Furthermore, the former tool has better statistical and probability explanation compared to the latter tool. Thus only the HMMER scanning results were considered for further study. Out of 1059 species scanned by the HMMER models, 30 putative anti-HIV AMPs were identified from genome scans with the family specific profile models after elimination of duplicate peptides. Docking analysis of putative AMPs against HIV proteins showed that from the 10 best performing anti-HIV AMPs with the highest Escores, molecules 1,3, 8 and 10 firmly binds the gp120 binding pocket at the VIN2 domain and at the point of interaction between gp120 and T cells, with the 1st and 3rd highest scoring anti-HIV AMPs having the highest binding affinities. However, all 10 putative anti-HIV AMPs bind to the N-terminal domain of p24 with large surface interaction, rather than the C-terminal. Conclusion: The in silica approach has made it possible to construct computational models having high performances, and which enabled the identification of putative anti-HIV peptides from genome sequence scans. The in silica validation of these putative peptides through docking studies has shown that some of these AMPs may be involved in HIV/AIDS therapeutics and diagnostics. The molecular validation of these findings will be the way forward for the development of an early diagnostic tool and as a consequence initiate early treatment. This will prevent the invasion of the immune system by blocking the VIN2 domain and thus designing of a successful vaccine with broad neutralizing activity against this domain.
Identification of biomarkers associated with cervical cancer: a combined in silico and molecular approach
(University of the Western Cape, 2014) Ludaka, Namhla; Pretorius, Ashley; Meyer, Mervin
Cervical cancer is the leading cause of cancer mortality among black women in South Africa. It is estimated that this disease kills approximately 8 women in South Africa every day. Cervical cancer is caused by the human papillomavirus (HPV) with the most common screening method for cervical cancer being Papanicolaou (Pap) smear, test amongst others. However, less than 20% of South African women go for these tests. There are several reasons why women do not go for these tests but the invasiveness of the test is one of the major causes for the low rate of screening. Lateral flow devices offer medical diagnosis at the point- of-care, allowing for the quick initiation of the appropriate therapeutic response. These tests are more cost-effective for the healthcare delivery industry, and can potentially be used by patients to self-test in the privacy of their homes and allow them to make informed decisions about their health. Therefore, the aim of this study was to use computational methods to identify serum biomarkers for cervical cancer that can be used to develop a point-of-care diagnostic device for cervical cancer. An in silico approach was used to identify genes implicated in the initiation and development of cervical cancer. Several bioinformatics tools were employed to extract a list of genes from publicly available cancer repositories. Multiple gene enrichment analysis tools were employed to analyze the selected candidate genes. Through this pipeline, ~28190 genes were identified from the various databases and were further refined to only 10 genes. The 10 genes were identified as potential cervical cancer biomarkers. A subcellular compartmentalization analysis clustered the proteins encoded by these genes as cell surface, secretory granules and extracellular space/matrix proteins. The selected candidate genes were predicted to be specific for cervical cancer tissue in a cancer tissue specificity meta-analysis study. The expression levels of the candidate genes were compared relative to each other and a graph constructed using gene expression data generated by GeneHub-GEPIS and TiGER databases. Further gene enrichment analysis was performed such as protein-protein interactions, transcription factor analysis, pathway analysis and co-expression analysis, with 9 out of the10 of the candidate genes showing co-expression. A gene expression analysis done on cervical cancer cell lines, other cancer cell lines and normal fibroblast cell line revealed differential expression of the candidate genes. Three candidate genes were significantly expressed in cervical cancer, while the seven remaining genes showed over expression in other cancer types. The study serves as basis for future investigations to diagnosis of cervical cancer, as well as for cancers. Thus, they could also serve as potential drug targets for cancer therapeutics and diagnostics.
Identification of biomarkers for the accurate and sensitive diagnosis of three bacterial pneumonia pathogens using in silico approaches
(Springer Nature, 2020) Bakare, Olalekan Olanrewaju; Keyster, Marshall; Pretorius, Ashley
: Pneumonia ranks as one of the main infectious sources of mortality among kids under 5 years of age, killing 2500 a day; late research has additionally demonstrated that mortality is higher in the elderly. A few biomarkers, which up to this point have been distinguished for its determination lack specificity, as these biomarkers fail to build up a differentiation between pneumonia and other related diseases, for example, pulmonary tuberculosis and Human Immunodeficiency Infection (HIV). There is an inclusive global consensus of an improved comprehension of the utilization of new biomarkers, which are delivered in light of pneumonia infection for precision identification to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) have been demonstrated to be promising remedial specialists against numerous illnesses. This research work sought to identify AMPs as biomarkers for three bacterial pneumonia pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Acinetobacter baumannii using in silico technology. Hidden Markov Models (HMMER) was used to identify putative anti-bacterial pneumonia AMPs against the identified receptor proteins of Streptococcus pneumoniae, Klebsiella pneumoniae, and Acinetobacter baumannii. The physicochemical parameters of these putative AMPs were computed and their 3-D structures were predicted using I-TASSER. These AMPs were subsequently subjected to docking interaction analysis against the identified bacterial pneumonia pathogen proteins using PATCHDOCK.
Identification of microRNAs as a class of biomarkers for the early diagnosis of prostate cancer : an in silico and molecular approach
(University of the Western Cape, 2015) Lombe, Chipampe Patricia; Pretorius, Ashley; Meyer, Mervin
Prostate cancer (PCa) is the second most common form of cancer in men around the world. In many parts of Africa, data on prostate cancer is sparse. This is attributed to poor access to testing and diagnostics. The International Agency for Research on Cancer (GLOBOCAN) estimated that 28,000 deaths occurred as a result of PCa in Africa in 2008, 4500 of which were in South Africa. This figure (28,000) is predicated a rise to 57,000 over the next two decades. Currently, the most commonly used diagnostic tests for PCa are the DRE and PSA tests. The former is highly invasive and both have low specificity and poor sensitivity. Therefore, the need for a less invasive early detection method with the ability to overcome the lack of specificity and sensitivity is required. Biomarkers have recently been identified as a viable option for early detection of disease. Examples of biological indicators for disease are miRNAs. miRNAs are small non-coding RNA molecules which play a key role in controlling gene expression and certain biological processes. Studies have shown that aberrantly expressed miRNAs are a hallmark of several diseases like cancer. miRNA expression has been shown to be associated with tumour development, progression and response to therapy, suggesting their possible use as diagnostic, prognostic and predictive biomarkers. The study aimed to investigate the potential of miRNAs implicated in prostate cancer as putative biomarkers for the disease and evaluating these miRNAs in a panel of prostate as well as several other cancer cell lines using qRT-PCR. An in silico approach was used to identify 13 putative miRNAs implicated in prostate cancer of which 8 were further analysed in a parallel study and 5 in this study. Two publicly available target prediction software were used for target gene prediction of the 5 identified miRNAs. The target genes were subjected to functional analysis using web-based software, DAVID. Functions which were clustered with an enrichment score of 1.3 and greater were considered significant. Targets with gene ontologies linked to “transcription regulation”, “regulation of “apopotosis”, “extracellular region” and “metal ion binding” were considered for further analyses. Protein gene interaction analysis was performed to determine the pathways the target genes are involved in using STRING. Expression profile analysis of the genes in various tissues was also carried out using in silico methods through the TiGER and GeneHub-GEPIS databases. Analysis using DAVID resulted in 9 gene targets for the 5 miRNAs. It was found that miR3 seemed the most promising miRNA for biomarker validation based on the in silico analyses. Its target gene MNT was found to be abundantly expressed in prostate tissue from the TiGER results. The GeneHub-GEPIS results also indicated that the gene’s expression is up-regulated during prostate cancer. The expression levels of the miRNAs analysed using qRT-PCR indicated that miR3 is significantly over-expressed in prostate cancer cells when compared to the other cancer cell lines used in this study, corroborating the results observed from the in silico analyses. Another miRNA with interesting results was miR5. It was predicted to target two genes, YWHAZ and TNFSF13B. In TiGER, both were found to be expressed in prostate tissue. The genes were also found to be up regulated during prostate cancer in GeneHub-GEPIS. The expression level of miR5 in LNCaP was 15.32; it was significantly up-regulated in the cell line using qRT-PCR. However, miR5 was also present in HEPG2-7.06, MCF7-0.79, HT29-1.61 and H157-3.59. Thus, it was concluded it can be used as a biomarker in combination with other miRNAs. The miRNA miR2 was found to target the actin filament protein encoding gene AFAP1. The gene was predicted to be upregulated with a DEU of 33.25 in GeneHuB-GEPIS. The qRT-PCR analysis showed that the expression ratio in LNcaP was 8.79. However, miR2 expression was up-regulated in MCF7-0.85 and HT29-1.09 as well. The expression level of miR1 in BHP1 was found to be 4.85. It can be considered as an indicator for benign prostate hyperplasia. Future work would include investigating the expression of miR3 in a larger panel of cancer cells as well as in patient samples. In addition, analysis of the UTR sequences of the miRNAs targets experimentally to prove that the target genes identified using in silico methods, are indeed regulated by these miRNAs. Furthermore, performing gene “knock-out” studies on the genes that code for the miRNAs to study their roles in prostate cancer development.
Identification of miRNA's as specific biomarkers in prostate cancer diagnostics : a combined in silico and molecular approach
(University of the Western Cape, 2015) Khan, Firdous; Pretorius, Ashley; Meyer, M.
There are over 100 different types of cancer, and each of these cancers are classified by the type of cell that it initially affects. For the purpose of this research we will be focussing on prostate cancer (PC). Prostate cancer is the second most common form of cancer in men around the world and annually approximately 4500 men in South Africa are diagnosed making PC a global epidemic. Prostate cancer is a type of cancer which starts in the prostate it is normally a walnut-sized gland found right below the bladder. PC follows a natural course, starting as a tiny group of cancer cells that can grow into a tumour. In some men if PC is not treated it may spread to surrounding tissue by a process called direct invasion/ spread and could lead to death. Current diagnostic tests for prostate cancer have low specificity and poor sensitivity. Although many PC's are slow growing there is currently no test to distinguish between these and cancers that will become aggressive and life threatening. Therefore the need for a less invasive early detection method with the ability to overcome the lack of specificity and sensitivity of current available diagnostic test is required. Biomarkers have recently been identified as a viable option for early detection of disease for example biological indicators ie. DNA, RNA, proteins and microRNAs (miRNAs). Since first described in the 1990s, circulating miRNAs have provided an active and rapidly evolving area of research that has the potential to transform cancer diagnostics and prognostics. In particular, miRNAs could provide potentially new biomarkers for PC as diagnostic molecules. Circulating miRNAs are highly stable and are both detectable and quantifiable in a range of accessible bio-fluids, having the potential to be useful as diagnostic, prognostic and predictive biomarkers. In this study we aimed to identify miRNAs as potential biomarkers to detect and distinguish between various types of PC in its earliest stage. The major objectives of the study were to identify miRNAs and their gene targets that play a critical role in disease onset and progression to further understand their mechanism of action in PC using several in silico methods, and to validate the potential diagnostic miRNAs using qRT-PCR in several cell lines. The identification of specific miRNAs and their targets was done using an "in-house" designed pipeline. Bioinformatic analyses was done using a number of databases including STRING, DAVID, DIANA and mFold database, and these combined with programming and statistical analyses was used for the identification of potential miRNAs specific to PC. Our study identified 40 miRNAs associated with PC using our "in-house" parameters in comparison to the 20-30 miRNAs known to be involved in PC found in public databases e.g. miRBase. A comparison between our parameters and those used in public databases showed a higher degree of specificity for the identification PC-associated miRNAs. These selected miRNAs were analysed using different bioinformatics tools, and were confirmed to be novel miRNAs associated with PC. The identified miRNAs were experimentally validated using qRT-PCR to generate expression profiles for PC as well as various other cancers. Prostate lines utilised in this study included PNT2C2 (normal) which was compared to BPH1 (Benign) and LNCaP (Metastatic). In the study the expression profiles of eight potential miRNA biomarkers for the detection of PC was determined using qRT-PCR, and to distinguish PC from other cancers. QRT-PCR data showed that miRNA-3 and -5 were up-regulated in the BPH1 and LNCaP when compared to PNT2C2. In addition miRNA-8 was also shown to be up-regulated in LNCaP. Based on these results it was shown that a miRNA profile could be established to distinguish between BPH1 and the LNCaP prostate cell lines. The results suggest that one miRNA as a diagnostic marker may be sufficient to differentiate between different cancer cell lines. Furthermore by creating a unique profile for each cancer cell line by using a combination of miRNAs could be a suitable approach as well. Finally, it was shown that through the use of a single or combination of all eight miRNAs a unique profile for all the cancer cell lines tested in this study can be created. This is an important finding which could have potential diagnostic or prognostic implications in clinical practice.
Identification of novel miRNAs as diagnostic and prognostic biomarkers for prostate cancer using an in silico approach
(University of the Western Cape, 2017) Eshibona, Nasr O.M.; Pretorius, Ashley; Gabere,Musa
Cancer is known as uncontrollable cell growth which results in the formation of tumours in the areas that are affected by the cancer. There are two types of tumours: benign and malignant. This study focus is on prostate cancer (PCa) as one of the most common cancers in men around the world. A previous study has reported that there were 27,132 new cases of cancer in South Africa in 2010. Out of those, 4652 were prostate cancer cases, which make it a considerable issue. The prostate is a gland that forms part of the male reproductive system. Prostate cancer is more apparent in men over the age of 65 years however it can be present in men of a lower age. However it is rare in men under 45 years of age. Prostate cancer start as a small group of cancer cells that can grow into a mature tumour. In the advanced stages, the tumour cells can spread to other tissue by metastases and can lead to death. Current diagnostic tools include Digital Rectal Examination (DRE), the Prostate-Specific Antigen test (PSA) ultra sound, and biopsy.
Identification of novel miRNAs as diagnostic molecules for detection of breast cancer using in silico approaches
(University of the Western cape, 2017) Ferrara, Najua Ali; Pretorius, Ashley
Breast cancer (BC) is the most common cancer in women worldwide, and is the second most common cancer in the world, responsible for more than 500 000 deaths annually. Estimates are that 1 in 8 women will develop BC in their lifetime. In South Africa, BC in women affects about 16.6 % of the population and could see a 78 % increase in cases by 2030. The failure of conventional diagnostic tools to detect BC from an early onset has revealed the need for diagnostic tools that would enable early diagnosis of BC. The current diagnostic tools include breast self-examination, mammography magnetic resonance imaging, ultrasonography and serum biomarkers; BRACA1, BRACA2, HER2. These conventional methods lack sensitivity, specificity and positive predictive value, and some of these diagnostic tools may be expensive and quite invasive. Therefore, novel diagnostic tools such as microRNAs which address the short comings of current methods are required for early diagnosis as well as BC management. MicroRNAs are a class of non-coding RNA molecules, which are important in RNA stability and gene expression. Various methodologies have been employed to identify novel microRNAs for diagnostics such as bioinformatics, also referred to as in silico analysis. The aim of this study is to identify novel microRNAs that can potentially detect BC at its earliest stage.
Identification of potential biomarkers in lung cancer as possible diagnostic agents using bioinformatics and molecular approaches
(University of the Western Cape, 2015) Ahmed, Firdous; Pretorius, Ashley; Gamieldien, Kareemah; Gamieldien, Junaid
Lung cancer remains the leading cause of cancer deaths worldwide, with the majority of cases attributed to non-small cell lung carcinomas. At the time of diagnosis, a large percentage of patients present with advanced stage of disease, ultimately resulting in a poor prognosis. The identification circulatory markers, overexpressed by the tumour tissue, could facilitate the discovery of an early, specific, non-invasive diagnostic tool as well as improving prognosis and treatment protocols. The aim was to analyse gene expression data from both microarray and RNA sequencing platforms, using bioinformatics and statistical analysis tools. Enrichment analysis sought to identify genes, which were differentially expressed (p < 0.05, FC > 2) and had the potential to be secreted into the extracellular circulation, by using Gene Ontology terms of the Cellular Component. Results identified 1 657 statically significant genes between normal and early lung cancer tissue, with only 1 gene differentially expressed (DE) between the early and late stage disease. Following statistical analysis, 171 DE genes selected as potential early stage biomarkers. The overall sensitivity of RNAseq, in comparison to arrays enabled the identification of 57 potential serum markers. These genes of interest were all downregulated in the tumour tissue, and while they did not facilitate the discovery of an ideal diagnostic marker based on the set criteria in this study, their roles in disease initiation and progression require further analysis.