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Fulltext A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

Charoenkwan P, Chotpatiwetchkul W, Lee VS, Nantasenamat C, Shoombuatong W

Sci Rep, 2021 Dec 10;11(1):23782.
PMID: 34893688 DOI: 10.1038/s41598-021-03293-w

Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.

Matched MeSH terms: Computational Biology/methods*
Fulltext Absence of evidence is not evidence of absence: Nanopore sequencing and complete assembly of the European lobster (Homarus gammarus) mitogenome uncovers the missing nad2 and a new major gene cluster duplication

Gan HM, Grandjean F, Jenkins TL, Austin CM

BMC Genomics, 2019 May 03;20(1):335.
PMID: 31053062 DOI: 10.1186/s12864-019-5704-3

BACKGROUND: The recently published complete mitogenome of the European lobster (Homarus gammarus) that was generated using long-range PCR exhibits unusual gene composition (missing nad2) and gene rearrangements among decapod crustaceans with strong implications in crustacean phylogenetics. Such atypical mitochondrial features will benefit greatly from validation with emerging long read sequencing technologies such as Oxford Nanopore that can more accurately identify structural variation.
RESULTS: We re-sequenced the H. gammarus mitogenome on an Oxford Nanopore Minion flowcell and performed a long-read only assembly, generating a complete mitogenome assembly for H. gammarus. In contrast to previous reporting, we found an intact mitochondrial nad2 gene in the H. gammarus mitogenome and showed that its gene organization is broadly similar to that of the American lobster (H. americanus) except for the presence of a large tandemly duplicated region with evidence of pseudogenization in one of each duplicated protein-coding genes.
CONCLUSIONS: Using the European lobster as an example, we demonstrate the value of Oxford Nanopore long read technology in resolving problematic mitogenome assemblies. The increasing accessibility of Oxford Nanopore technology will make it an attractive and useful tool for evolutionary biologists to verify new and existing unusual mitochondrial gene rearrangements recovered using first and second generation sequencing technologies, particularly those used to make phylogenetic inferences of evolutionary scenarios.

Matched MeSH terms: Computational Biology/methods*
Fulltext Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

Horne HN, Chung CC, Zhang H, Yu K, Prokunina-Olsson L, Michailidou K, et al.

PLoS One, 2016;11(8):e0160316.
PMID: 27556229 DOI: 10.1371/journal.pone.0160316

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

Matched MeSH terms: Computational Biology/methods
Fulltext An Immunoinformatic-Based In Silico Identification on the Creation of a Multiepitope-Based Vaccination Against the Nipah Virus

Kaur B, Karnwal A, Bansal A, Malik T

Biomed Res Int, 2024;2024:4066641.
PMID: 38962403 DOI: 10.1155/2024/4066641

The zoonotic viruses pose significant threats to public health. Nipah virus (NiV) is an emerging virus transmitted from bats to humans. The NiV causes severe encephalitis and acute respiratory distress syndrome, leading to high mortality rates, with fatality rates ranging from 40% to 75%. The first emergence of the disease was found in Malaysia in 1998-1999 and later in Bangladesh, Cambodia, Timor-Leste, Indonesia, Singapore, Papua New Guinea, Vietnam, Thailand, India, and other South and Southeast Asian nations. Currently, no specific vaccines or antiviral drugs are available. The potential advantages of epitope-based vaccines include their ability to elicit specific immune responses while minimizing potential side effects. The epitopes have been identified from the conserved region of viral proteins obtained from the UniProt database. The selection of conserved epitopes involves analyzing the genetic sequences of various viral strains. The present study identified two B cell epitopes, seven cytotoxic T lymphocyte (CTL) epitopes, and seven helper T lymphocyte (HTL) epitope interactions from the NiV proteomic inventory. The antigenic and physiological properties of retrieved protein were analyzed using online servers ToxinPred, VaxiJen v2.0, and AllerTOP. The final vaccine candidate has a total combined coverage range of 80.53%. The tertiary structure of the constructed vaccine was optimized, and its stability was confirmed with the help of molecular simulation. Molecular docking was performed to check the binding affinity and binding energy of the constructed vaccine with TLR-3 and TLR-5. Codon optimization was performed in the constructed vaccine within the Escherichia coli K12 strain, to eliminate the danger of codon bias. However, these findings must require further validation to assess their effectiveness and safety. The development of vaccines and therapeutic approaches for virus infection is an ongoing area of research, and it may take time before effective interventions are available for clinical use.

Matched MeSH terms: Computational Biology/methods
Fulltext Unsupervised Network Analysis of the Plastic Supraoptic Nucleus Transcriptome Predicts Caprin2 Regulatory Interactions

Loh SY, Jahans-Price T, Greenwood MP, Greenwood M, Hoe SZ, Konopacka A, et al.

eNeuro, 2017;4(6).
PMID: 29279858 DOI: 10.1523/ENEURO.0243-17.2017

The supraoptic nucleus (SON) is a group of neurons in the hypothalamus responsible for the synthesis and secretion of the peptide hormones vasopressin and oxytocin. Following physiological cues, such as dehydration, salt-loading and lactation, the SON undergoes a function related plasticity that we have previously described in the rat at the transcriptome level. Using the unsupervised graphical lasso (Glasso) algorithm, we reconstructed a putative network from 500 plastic SON genes in which genes are the nodes and the edges are the inferred interactions. The most active nodal gene identified within the network was Caprin2. Caprin2 encodes an RNA-binding protein that we have previously shown to be vital for the functioning of osmoregulatory neuroendocrine neurons in the SON of the rat hypothalamus. To test the validity of the Glasso network, we either overexpressed or knocked down Caprin2 transcripts in differentiated rat pheochromocytoma PC12 cells and showed that these manipulations had significant opposite effects on the levels of putative target mRNAs. These studies suggest that the predicative power of the Glasso algorithm within an in vivo system is accurate, and identifies biological targets that may be important to the functional plasticity of the SON.

Matched MeSH terms: Computational Biology/methods*
Fulltext Computational identification and binding analysis of orphan human cytochrome P450 4X1 enzyme with substrates

Kumar S

BMC Res Notes, 2015;8:9.
PMID: 25595103 DOI: 10.1186/s13104-015-0976-4

Cytochrome P450s (CYPs) are important heme-containing proteins, well known for their monooxygenase reaction. The human cytochrome P450 4X1 (CYP4X1) is categorized as "orphan" CYP because of its unknown function. In recent studies it is found that this enzyme is expressed in neurovascular functions of the brain. Also, various studies have found the expression and activity of orphan human cytochrome P450 4X1 in cancer. It is found to be a potential drug target for cancer therapy. However, three-dimensional structure, the active site topology and substrate specificity of CYP4X1 remain unclear.

Matched MeSH terms: Computational Biology/methods*
Fulltext Amino acid sequence and structural comparison of BACE1 and BACE2 using evolutionary trace method

Mirsafian H, Mat Ripen A, Merican AF, Bin Mohamad S

ScientificWorldJournal, 2014;2014:482463.
PMID: 25254246 DOI: 10.1155/2014/482463

Beta-amyloid precursor protein cleavage enzyme 1 (BACE1) and beta-amyloid precursor protein cleavage enzyme 2 (BACE2), members of aspartyl protease family, are close homologues and have high similarity in their protein crystal structures. However, their enzymatic properties differ leading to disparate clinical consequences. In order to identify the residues that are responsible for such differences, we used evolutionary trace (ET) method to compare the amino acid conservation patterns of BACE1 and BACE2 in several mammalian species. We found that, in BACE1 and BACE2 structures, most of the ligand binding sites are conserved which indicate their enzymatic property of aspartyl protease family members. The other conserved residues are more or less randomly localized in other parts of the structures. Four group-specific residues were identified at the ligand binding site of BACE1 and BACE2. We postulated that these residues would be essential for selectivity of BACE1 and BACE2 biological functions and could be sites of interest for the design of selective inhibitors targeting either BACE1 or BACE2.

Matched MeSH terms: Computational Biology/methods*
Immunoinformatics study on highly expressed Mycobacterium tuberculosis genes during infection

Nguyen Thi le T, Sarmiento ME, Calero R, Camacho F, Reyes F, Hossain MM, et al.

Tuberculosis (Edinb), 2014 Sep;94(5):475-81.
PMID: 25034135 DOI: 10.1016/j.tube.2014.06.004

The most important targets for vaccine development are the proteins that are highly expressed by the microorganisms during infection in-vivo. A number of Mycobacterium tuberculosis (Mtb) proteins are also reported to be expressed in-vivo at different phases of infection. In the present study, we analyzed multiple published databases of gene expression profiles of Mtb in-vivo at different phases of infection in animals and humans and selected 38 proteins that are highly expressed in the active, latent and reactivation phases. We predicted T- and B-cell epitopes from the selected proteins using HLAPred for T-cell epitope prediction and BCEPred combined with ABCPred for B-cell epitope prediction. For each selected proteins, regions containing both T- and B-cell epitopes were identified which might be considered as important candidates for vaccine design against tuberculosis.

Matched MeSH terms: Computational Biology*
Fulltext First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene

Mohamoud HS, Hussain MR, El-Harouni AA, Shaik NA, Qasmi ZU, Merican AF, et al.

Comput Math Methods Med, 2014;2014:904052.
PMID: 24723968 DOI: 10.1155/2014/904052

GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.

Matched MeSH terms: Computational Biology/methods
Fulltext Molecular epidemiology of coxsackievirus A16: intratype and prevalent intertype recombination identified

Chen X, Tan X, Li J, Jin Y, Gong L, Hong M, et al.

PLoS One, 2013;8(12):e82861.
PMID: 24340064 DOI: 10.1371/journal.pone.0082861

Coxsackievirus A16 (CVA16) is responsible for nearly 50% of all the conﬁrmed hand, foot, and mouth disease (HFMD) cases in mainland China, sometimes it could also cause severe complications, and even death. To clarify the genetic characteristics and the epidemic patterns of CVA16 in mainland China, comprehensive bioinfomatics analyses were performed by using 35 CVA16 whole genome sequences from 1998 to 2011, 593 complete CVA16 VP1 sequences from 1981 to 2011, and prototype strains of human enterovirus species A (EV-A). Analysis on complete VP1 sequences revealed that subgenotypes B1a and B1b were prevalent strains and have been co-circulating in many Asian countries since 2000, especially in mainland China for at least 13 years. While the prevalence of subgenotype B1c (totally 20 strains) was much limited, only found in Malaysia from 2005 to 2007 and in France in 2010. Genotype B2 only caused epidemic in Japan and Malaysia from 1981 to 2000. Both subgenotypes B1a and B1b were potential recombinant viruses containing sequences from other EV-A donors in the 5'-untranslated region and P2, P3 non-structural protein encoding regions.

Matched MeSH terms: Computational Biology/methods*
Fulltext Discovery of a new class of inhibitors for the protein arginine deiminase type 4 (PAD4) by structure-based virtual screening

Teo CY, Shave S, Chor AL, Salleh AB, Rahman MB, Walkinshaw MD, et al.

BMC Bioinformatics, 2012;13 Suppl 17:S4.
PMID: 23282142 DOI: 10.1186/1471-2105-13-S17-S4

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease with unknown etiology. Anticitrullinated protein autoantibody has been documented as a highly specific autoantibody associated with RA. Protein arginine deiminase type 4 (PAD4) is the enzyme responsible for catalyzing the conversion of peptidylarginine into peptidylcitrulline. PAD4 is a new therapeutic target for RA treatment. In order to search for inhibitors of PAD4, structure-based virtual screening was performed using LIDAEUS (Ligand discovery at Edinburgh university). Potential inhibitors were screened experimentally by inhibition assays.
RESULTS: Twenty two of the top-ranked water-soluble compounds were selected for inhibitory screening against PAD4. Three compounds showed significant inhibition of PAD4 and their IC50 values were investigated. The structures of the three compounds show no resemblance with previously discovered PAD4 inhibitors, nor with existing drugs for RA treatment.
CONCLUSION: Three compounds were discovered as potential inhibitors of PAD4 by virtual screening. The compounds are commercially available and can be used as scaffolds to design more potent inhibitors against PAD4.

Matched MeSH terms: Computational Biology/methods*
Fulltext Prediction of mycoplasma hominis proteins targeting in mitochondria and cytoplasm of host cells and their implication in prostate cancer etiology

Khan S, Zakariah M, Rolfo C, Robrecht L, Palaniappan S

Oncotarget, 2017 May 09;8(19):30830-30843.
PMID: 27027344 DOI: 10.18632/oncotarget.8306

Although the idea of bacteria causing different types of cancer has exploded about century ago, the potential mechanisms of carcinogenesis is still not well established. Many reports showed the involvement of M. hominis in the development of prostate cancer, however, mechanistic approach for growth and development of prostate cancer has been poorly understood. In the current study, we predicted M. hominis proteins targeting in the mitochondria and cytoplasm of host cells and their implication in prostate cancer. A total of 77 and 320 proteins from M. hominis proteome were predicted to target in the mitochondria and cytoplasm of host cells respectively. In particular, various targeted proteins may interfere with normal growth behaviour of host cells, thereby altering the decision of programmed cell death. Furthermore, we investigated possible mechanisms of the mitochondrial and cytoplasmic targeted proteins of M. hominis in etiology of prostate cancer by screening the whole proteome.

Matched MeSH terms: Computational Biology/methods
Fulltext Impacts of Nonsynonymous Single Nucleotide Polymorphisms of Adiponectin Receptor 1 Gene on Corresponding Protein Stability: A Computational Approach

Saleh MA, Solayman M, Paul S, Saha M, Khalil MI, Gan SH

Biomed Res Int, 2016;2016:9142190.
PMID: 27294143 DOI: 10.1155/2016/9142190

Despite the reported association of adiponectin receptor 1 (ADIPOR1) gene mutations with vulnerability to several human metabolic diseases, there is lack of computational analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the human ADIPOR1 at protein level. Therefore, sequence- and structure-based computational tools were employed in this study to functionally and structurally characterize the coding nsSNPs of ADIPOR1 gene listed in the dbSNP database. Our in silico analysis by SIFT, nsSNPAnalyzer, PolyPhen-2, Fathmm, I-Mutant 2.0, SNPs&GO, PhD-SNP, PANTHER, and SNPeffect tools identified the nsSNPs with distorting functional impacts, namely, rs765425383 (A348G), rs752071352 (H341Y), rs759555652 (R324L), rs200326086 (L224F), and rs766267373 (L143P) from 74 nsSNPs of ADIPOR1 gene. Finally the aforementioned five deleterious nsSNPs were introduced using Swiss-PDB Viewer package within the X-ray crystal structure of ADIPOR1 protein, and changes in free energy for these mutations were computed. Although increased free energy was observed for all the mutants, the nsSNP H341Y caused the highest energy increase amongst all. RMSD and TM scores predicted that mutants were structurally similar to wild type protein. Our analyses suggested that the aforementioned variants especially H341Y could directly or indirectly destabilize the amino acid interactions and hydrogen bonding networks of ADIPOR1.

Matched MeSH terms: Computational Biology/methods*
Computational prediction of Mycoplasma hominis proteins targeting in nucleus of host cell and their implication in prostate cancer etiology

Khan S, Zakariah M, Palaniappan S

Tumour Biol., 2016 Aug;37(8):10805-13.
PMID: 26874727 DOI: 10.1007/s13277-016-4970-9

Cancer has long been assumed to be a genetic disease. However, recent evidence supports the enigmatic connection of bacterial infection with the growth and development of various types of cancers. The cause and mechanism of the growth and development of prostate cancer due to Mycoplasma hominis remain unclear. Prostate cancer cells are infected and colonized by enteroinvasive M. hominis, which controls several factors that can affect prostate cancer growth in susceptible persons. We investigated M. hominis proteins targeting the nucleus of host cells and their implications in prostate cancer etiology. Many vital processes are controlled in the nucleus, where the proteins targeting M. hominis may have various potential implications. A total of 29/563 M. hominis proteins were predicted to target the nucleus of host cells. These include numerous proteins with the capability to alter normal growth activities. In conclusion, our results emphasize that various proteins of M. hominis targeted the nucleus of host cells and were involved in prostate cancer etiology through different mechanisms and strategies.

Matched MeSH terms: Computational Biology*
Fulltext Comprehensive computational target fishing approach to identify Xanthorrhizol putative targets

Shahid M, Azfaralariff A, Law D, Najm AA, Sanusi SA, Lim SJ, et al.

Sci Rep, 2021 01 15;11(1):1594.
PMID: 33452398 DOI: 10.1038/s41598-021-81026-9

Xanthorrhizol (XNT), is a bioactive compound found in Curcuma xanthorrhiza Roxb. This study aimed to determine the potential targets of the XNT via computational target fishing method. This compound obeyed Lipinski's and Veber's rules where it has a molecular weight (MW) of 218.37 gmol-1, TPSA of 20.23, rotatable bonds (RBN) of 4, hydrogen acceptor and donor ability is 1 respectively. Besides, it also has half-life (HL) values 3.5 h, drug-likeness (DL) value of 0.07, oral bioavailability (OB) of 32.10, and blood-brain barrier permeability (BBB) value of 1.64 indicating its potential as therapeutic drug. Further, 20 potential targets were screened out through PharmMapper and DRAR-CPI servers. Co-expression results derived from GeneMANIA revealed that these targets made connection with a total of 40 genes and have 744 different links. Four genes which were RXRA, RBP4, HSD11B1 and AKR1C1 showed remarkable co-expression and predominantly involved in steroid metabolic process. Furthermore, among these 20 genes, 13 highly expressed genes associated with xenobiotics by cytochrome P450, chemical carcinogenesis and steroid metabolic pathways were identified through gene ontology (GO) and KEGG pathway analysis. In conclusion, XNT is targeting multiple proteins and pathways which may be exploited to shape a network that exerts systematic pharmacological effects.

Matched MeSH terms: Computational Biology/methods*
Fulltext DeSigN: connecting gene expression with therapeutics for drug repurposing and development

Lee BK, Tiong KH, Chang JK, Liew CS, Abdul Rahman ZA, Tan AC, et al.

BMC Genomics, 2017 01 25;18(Suppl 1):934.
PMID: 28198666 DOI: 10.1186/s12864-016-3260-7

BACKGROUND: The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously.
RESULTS: We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control.
CONCLUSIONS: DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

Matched MeSH terms: Computational Biology/methods*
Fulltext Molecular study of wound healing after using biosynthesized BNC/Fe3O4 nanocomposites assisted with a bioinformatics approach

Moniri M, Boroumand Moghaddam A, Azizi S, Abdul Rahim R, Zuhainis Saad W, Navaderi M, et al.

Int J Nanomedicine, 2018;13:2955-2971.
PMID: 29861630 DOI: 10.2147/IJN.S159637

Background: Molecular investigation of wound healing has allowed better understanding about interaction of genes and pathways involved in healing progression.
Objectives: The aim of this study was to prepare magnetic/bacterial nanocellulose (Fe3O4/BNC) nanocomposite films as ecofriendly wound dressing in order to evaluate their physical, cytotoxicity and antimicrobial properties. The molecular study was carried out to evaluate expression of genes involved in healing of wounds after treatment with BNC/Fe3O4 films.
Study design materials and methods: Magnetic nanoparticles were biosynthesized by using Aloe vera extract in new isolated bacterial nanocellulose (BNC) RM1. The nanocomposites were characterized using X-ray diffraction, Fourier transform infrared, and field emission scanning electron microscopy. Moreover, swelling property and metal ions release profile of the nanocomposites were investigated. The ability of nanocomposites to promote wound healing of human dermal fibroblast cells in vitro was examined. Bioinformatics databases were used to identify genes with important healing effect. Key genes which interfered with healing were studied by quantitative real time PCR.
Results: Spherical magnetic nanoparticles (15-30 nm) were formed and immobilized within the structure of BNC. The BNC/Fe3O4 was nontoxic (IC50>500 μg/mL) with excellent wound healing efficiency after 48 hours. The nanocomposites showed good antibacterial activity ranging from 6±0.2 to 13.40±0.10 mm against Staphylococcus aureus, Staphylococcus epidermidis and Pseudomonas aeruginosa. The effective genes for the wound healing process were TGF-B1, MMP2, MMP9, Wnt4, CTNNB1, hsa-miR-29b, and hsa-miR-29c with time dependent manner. BNC/Fe3O4 has an effect on microRNA by reducing its expression and therefore causing an increase in the gene expression of other genes, which consequently resulted in wound healing.
Conclusion: This eco-friendly nanocomposite with excellent healing properties can be used as an effective wound dressing for treatment of cutaneous wounds.

Matched MeSH terms: Computational Biology/methods
In silico 'fishing' using known small regulatory RNA (sRNA) candidates as the decoy from Escherichia coli, Salmonella typhi and Salmonella typhimurium manifested 14 novel sRNA candidates in the orthologous region of Proteus mirabilis

KishanRaj S, Sumitha S, Siventhiran B, Thiviyaa O, Sathasivam KV, Xavier R, et al.

Mol Biol Rep, 2018 Dec;45(6):2333-2343.
PMID: 30284142 DOI: 10.1007/s11033-018-4397-z

Proteus mirabilis, a gram-negative bacterium of the family Enterobacteriaceae, is a leading cause of urinary tract infection (UTI) with rapid development of multi-drug resistance. Identification of small regulatory RNAs (sRNAs), which belongs to a class of RNAs that do not translate into a protein, could permit the comprehension of the regulatory roles this molecules play in mediating pathogenesis and multi-drug resistance of the organism. In this study, comparative sRNA analysis across three different members of Enterobacteriaceae (Escherichia coli, Salmonella typhi and Salmonella typhimurium) was carried out to identify the sRNA homologs in P. mirabilis. A total of 232 sRNA genes that were reported in E. coli, S. typhi and S. typhimurium were subjected to comparative analysis against P. mirabilis HI4320 genome. We report the detection of 14 sRNA candidates, conserved in the orthologous regions of P. mirabilis, that are not included in Rfam database. Northern-blot analysis was carried out for selected three sRNA candidates from the current investigation and three known sRNA from Rfam of P. mirabilis. The expression pattern of the six sRNA candidates shows that they are growth stage-dependant. To the best of our knowledge, this is the first report on the identification of sRNA candidates in P. mirabilis.

Matched MeSH terms: Computational Biology/methods
Fulltext In vitro molecular study of wound healing using biosynthesized bacteria nanocellulose/silver nanocomposite assisted by bioinformatics databases

Moniri M, Boroumand Moghaddam A, Azizi S, Abdul Rahim R, Zuhainis SW, Navaderi M, et al.

Int J Nanomedicine, 2018;13:5097-5112.
PMID: 30254435 DOI: 10.2147/IJN.S164573

Background: In recent years, bacterial nanocellulose (BNC) based nanocomposites have been developed to promote healing property and antibacterial activity of BNC wound dressing. Molecular study can help to better understanding about interaction of genes and pathways involved in healing progression.
Objectives: The aim of this study was to prepare bacterial nanocellulose/silver (BNC/Ag) nanocomposite films as ecofriendly wound dressing in order to assess their physical, cytotoxicity and antimicrobial properties. The in vitro molecular study was performed to evaluate expression of genes involved in healing of wounds after treatment with BNC/Ag biofilms.
Study design materials and methods: Silver nanoparticles were formed by using Citrullus colocynthis extract within new isolated bacterial nanocellulose (BNC) RM1. The nanocomposites were characterized using X-ray diffraction, Fourier transform infrared, and field emission scanning electron microscopy. Besides, swelling property and Ag release profile of the nanocomposites were studied. The ability of nanocomposites to promote wound healing of human dermal fibroblast cells in vitro was studied. Bioinformatics databases were used to identify genes with important healing effect. Key genes which interfered with healing were studied by quantitative real time PCR.
Results: Spherical silver nanoparticles with particle size ranging from 20 to 50 nm were synthesized and impregnated within the structure of BNC. The resulting nanocomposites showed significant antibacterial activities with inhibition zones ranging from 7±0.25 to 16.24±0.09 mm against skin pathogenic bacteria. Moreover, it was compatible with human fibroblast cells (HDF) and could promote in vitro wound healing after 48h. Based on bioinformatics databases, the genes of TGF-β1, MMP2, MMP9, CTNNB1, Wnt4, hsa-miR-29b-3p and hsa-miR-29c-3p played important role in wound healing. The nanocomposites had an effect in expression of the genes in healing. Thus, the BNC/Ag nanocomposite can be used to heal wound in a short period and simple manner.
Conclusion: This eco-friendly nanocomposite with excellent antibacterial activities and healing property confirming its utility as potential wound dressings.

Matched MeSH terms: Computational Biology*
In silico study of missense variants of FANCA, FANCC and FANCG genes reveals high risk deleterious alleles predisposing to Fanconi anemia pathogenesis

Shahid M, Azfaralariff A, Zubair M, Abdulkareem Najm A, Khalili N, Law D, et al.

Gene, 2022 Feb 20;812:146104.
PMID: 34864095 DOI: 10.1016/j.gene.2021.146104

Among the 22 Fanconi anemia (FA) reported genes, 90% of mutational spectra were found in three genes, namely FANCA (64%), FANCC (12%) and FANCG (8%). Therefore, this study aimed to identify the high-risk deleterious variants in three selected genes (FANCA, FANCC, and FANCG) through various computational approaches. The missense variant datasets retrieved from the UCSC genome browser were analyzed for their pathogenicity, stability, and phylogenetic conservancy. A total of 23 alterations, of which 16 in FANCA, 6 in FANCC and one variant in FANCG, were found to be highly deleterious. The native and mutant structures were generated, which demonstrated a profound impact on the respective proteins. Besides, their pathway analysis predicted many other pathways in addition to the Fanconi anemia pathway, homologous recombination, and mismatch repair pathways. Hence, this is the first comprehensive study that can be useful for understanding the genetic signatures in the development of FA.

Matched MeSH terms: Computational Biology/methods*

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