Md. Ismail Hosen

Application of a subtractive genomics approach for in silico identification and characterization of novel drug targets in Mycobacterium tuberculosis F11

Extensive dead ends or host toxicity of the conventional approaches of drug development can be avoided by applying the in silico subtractive genomics approach in the designing of potential drug target against bacterial diseases. This study utilizes the advanced in silico genome subtraction methodology to design potential and pathogen specific drug targets against Mycobacterium tuberculosis, causal agent of deadly tuberculosis. The whole proteome of Mycobacterium tuberculosis F11 containing 3941 proteins have been analyzed through a series of subtraction methodologies to remove paralogous proteins and proteins that show extensive homology with human. The subsequent exclusion of these proteins ensured the absence of host cytotoxicity and cross reaction in the identified drug targets. The high stringency (expectation value 10−100) analysis of the remaining 2935 proteins against database of essential genes resulted in 274 proteins to be essential for Mycobacterium tuberculosis F11. Comparative analysis of the metabolic pathways of human and Mycobacterium tuberculosis F11 by KAAS at the KEGG server sorted out 20 unique metabolic pathways in Mycobacterium tuberculosis F11 that involve the participation of 30 essential proteins. Subcellular localization analysis of these 30 essential proteins revealed 7 proteins with outer membrane potentialities. All these proteins can be used as a potential therapeutic target against Mycobacterium tuberculosis F11 infection. 66 of the 274 essential proteins were uncharacterized (described as hypothetical) and functional classification of these proteins showed that they belonged to a wide variety of protein classes including zinc binding proteins, transferases, transmembrane proteins, other metal ion binding proteins, oxidoreductase, and primary active transporters etc. 2D and 3D structures of these 15 membrane associated proteins were predicted using PRED-TMBB and homology modeling by Swiss model workspace respectively. The identified drug targets are expected to be of great potential for designing novel anti-tuberculosis drugs and further screening of the compounds against these newly targets may result in discovery of novel therapeutic compounds that can be effective against Mycobacterium tuberculosis.

Analyses of Genetic Variations of Glutathione S-Transferase Mu1 and Theta1 Genes in Bangladeshi Tannery Workers and Healthy Controls

Glutathione S-transferases (GSTs) belong to a group of multigene detoxification enzymes, which defend cells against oxidative stress. Tannery workers are at risk of oxidative damage that is usually detoxified by GSTs. This study investigated the genotypic frequencies of GST Mu1 (GSTM1) and GST Theta1 (GSTT1) in Bangladeshi tannery workers and healthy controls followed by their status of oxidative stress and total GST activity. Of the 188 individuals, 50.0% had both GSTM1 and GSTT1 (+/+), 12.2% had GSTM1 (+/−), 31.4% had GSTT1 (−/+) alleles, and 6.4% had null genotypes (−/−) with respect to both GSTM1 and GSTT1 alleles. Among 109 healthy controls, 54.1% were double positive, 9.2% had GSTM1 allele, 32.1% had GSTT1 allele, and 4.6% had null genotypes. Out of 79 tannery workers, 44.3% were +/+, 16.8% were +/−, 30.5% were −/+, and 8.4% were −/−. Though the polymorphic genotypes or allelic variants of GSTM1 and GSTT1 were distributed among the study subjects with different frequencies, the differences between the study groups were not statistically significant. GST activity did not vary significantly between the two groups and also among different genotypes while level of lipid peroxidation was significantly higher in tannery workers compared to controls irrespective of their GST genotypes.

Application of the Subtractive Genomics and Molecular Docking Analysis for the Identification of Novel Putative Drug Targets against Salmonella enterica subsp. enterica serovar Poona

The emergence of novel pathogenic strains with increased antibacterial resistance patterns poses a significant threat to the management of infectious diseases. In this study, we aimed at utilizing the subtractive genomic approach to identify novel drug targets against Salmonella enterica subsp. enterica serovar Poona strain ATCC BAA-1673. We employed in silico bioinformatics tools to subtract the strain-specific paralogous and host-specific homologous sequences from the bacterial proteome. The sorted proteome was further refined to identify the essential genes in the pathogenic bacterium using the database of essential genes (DEG). We carried out metabolic pathway and subcellular location analysis of the essential proteins of the pathogen to elucidate the involvement of these proteins in important cellular processes. We found 52 unique essential proteins in the target proteome that could be utilized as novel targets to design newer drugs. Further, we investigated these proteins in the DrugBank databases and 11 of the unique essential proteins showed druggability according to the FDA approved drug bank databases with diverse broad-spectrum property. Molecular docking analyses of the novel druggable targets with the drugs were carried out by AutoDock Vina option based on scoring functions. The results showed promising candidates for novel drugs against Salmonella infections.

Genetic variation of the transcription factor GATA3, not STAT4, is associated with the risk of type 2 diabetes in the Bangladeshi population

Type 2 diabetes mellitus is a multifactorial metabolic disorder caused by environmental factors and has a strong association with hereditary issues. These hereditary issues result in an imbalance in CD4+T cells and a decreased level of naïve CD4+T cells, which may be critical in the pathogenesis of type 2 diabetes. Transcription factors GATA3 and STAT4 mediate the cytokine-induced development of naïve T cells into Th1 or Th2 types. In the present study, genetic analyses of GATA3 SNP rs3824662 and STAT4 SNP rs10181656 were performed to investigate the association of allelic and genotypic variations with the risk of T2D in the Bangladeshi population. A total of 297 unrelated Bangladeshi patients with type 2 diabetes and 247 healthy individuals were included in the study. The allelic and genotypic frequencies of rs10181656 located in the STAT4 gene were not found to be associated with risk of type 2 diabetes. The GATA3 rs3824662 T allele and mutant TT genotype had a significant association with the risk of T2D [OR: 1.52 (1.15–2.02), X2 = 8.66, p = 0.003 and OR: 2.98 (1.36–6.55), X2 = 7.98, p = 0.04, respectively]. Thus, the present study postulates that the genetic variation of the transcription factor GATA3, not STAT4, is associated with the risk of type 2 diabetes in the Bangladeshi population.

Investigation of the Potential Association between Clustered Regularly Interspersed Short Palindromic Repeats (CRISPR) and Antibiotic Resistance Pattern of Bacterial Strains Isolated from Medical Waste and Environmental Water

Enterobacteriaceae are important human pathogens that cause many food and waterborne illness. Rapid emergence of multi-drug resistant bacteria in Bangladesh has become a serious problem. Phage-host interaction is now considered as the major driving force for the conversion of non-pathogenic bacteria to pathogenic ones. Evolution of highly pathogenic and antibiotic resistant bacteria largely depends upon the horizontal gene transfer by means of plasmid, megaplasmid and bacteriophages. Conversely, bacteria may acquire a novel defence mechanism called CRISPR (Clustered regularly interspersed short palindromic repeats) that can restrict horizontal transfer of plasmids and bacteriophages to limit the spread of antibiotic resistance genes among bacterial species. In this study, twenty bacterial strains were isolated from water of different medical waste and Buriganga river. Therefore, CRISPR locus was investigated following various biochemical and molecular analysis of those bacterial isolates. Identification of the bacterial isolates was conducted by Polymerase Chain Reaction (PCR) based assay of 16S rDNA extracted from those isolated strains. Results indicated that most strains were identified as Proteus mirabilis and Citrobacter freundii which mainly cause septicemia, and pneumonia in human. Thereafter, antibiogram of these strains was performed by using 11 different antibiotic discs where bacterial isolates from medical drainage system showed more resistant to antibiotics than the river water. In this study, CRISPR locus was also investigated within the genome of the isolated bacterial stains but unexpectedly, we did not find any CRISPR locus in their genome. In conclusion, we confirm that multi-drug resistant bacterial strains are devoid of CRISPR locus suggesting a possible negative association between CRISPR locus and antibiotic resistance. Further studies to pinpoint are required to elucidate the underlying mechanism of the association between CRISPR and antibiotic resistance in these isolated strains.

Molecular Diagnostic Approach Prevails Superior Over Conventional GelElectrophoresis Method in Detecting Sickle Cell Anemia

Sickle cell anemia is defined as homozygosity caused by the mutation of the glutamic acid residue to valine in the β-globin gene. Sickle cell disease is an increasing global health burden with the estimated number of patients increasing in a concerning manner. Here we report a very interesting and clinically insightful case of hemoglobinopathy which was initially suspected to be Hb S/D Punjab- a rare type of hemoglobinopathy as diagnosed by the hemoglobinelectrophoresis technique. Despite the diagnosis report indicating the rare Hb S/D Punjab, the uncharacteristic clinical presentation of the patient which was not coherent with the classical symptoms of Hb S/D Punjab, forced the clinicians to turn their attention to molecular diagnosis. To clarify the etiology of the clinical case, a sequencing-based molecular diagnosis approach was adopted that revealed the mutational signature of sickle cell anemia (SCA). This case can be regarded as a prominent example where the molecular techniques lead to the correct diagnosis matching with the clinical symptoms while the conventional diagnostic approach failed.

Correction to: Functional Polymorphism Located in the microRNA Binding Site of the Insulin Receptor (INSR) Gene Confers Risk for Type 2 Diabetes Mellitus in the Bangladeshi Population

Bangladesh has the second largest number of adults with diabetes in South Asia. Compelling evidence suggest that miRNAs contribute to the etiology of Type 2 diabetes mellitus (T2DM) by regulating many aspects of glucose homeostasis. Hence, we hypothesized that genetic polymorphisms in the diabetes-related miRNA target-binding sites could be associated with the risk of T2DM in Bangladesh. The reference Single nucleotide polymorphism (SNP) data from the Insulin Receptor (INSR) gene were downloaded from the ENSEMBL genome browser release 88 and further analyzed in silico for identifying SNPs with deleterious effect and clinical relationships. Further, case–control study using the microRNA-binding site polymorphism rs1366600 (T > C) located at the 3′ UTR of the INSR gene was carried out in 217 T2DM patients and 237 healthy controls from Bangladesh. Genotyping was performed using the real time PCR based allele discrimination method. The results showed that the minor allele ‘C’ is associated with increased risk of T2DM [Odds ratio (OR) 1.87; 95% confidence intervals (CI) 1.28–2.74; P = 0.0010]. When we dissected our analysis to include the dominant model (CC + TC genotype against the TT genotype), we found that the CC and TC genotypes were associated with increased risk of T2DM in Bangladeshi population (OR 2.01; 95% CI 1.31–3.07; P = 0.0012). However, in recessive model (CC vs TT + TC); the effect was not statistically significant (OR 2.23; 95% CI 0.66–7.51; P = 0.1848). Stratification of our data based on the gender of the cases and controls showed similar degree of risk association with respect to different genotypes and alleles. Our study showed that the miRNA binding site polymorphism rs1366600 located at the 3′-UTR region of the INSR gene is associated with increased risk of T2DM in Bangladeshi individuals.

Onco-Multi-OMICS Approach: A New Frontier in Cancer Research

The acquisition of cancer hallmarks requires molecular alterations at multiple levels including genome, epigenome, transcriptome, proteome, and metabolome. In the past decade, numerous attempts have been made to untangle the molecular mechanisms of carcinogenesis involving single OMICS approaches such as scanning the genome for cancer-specific mutations and identifying altered epigenetic-landscapes within cancer cells or by exploring the differential expression of mRNA and protein through transcriptomics and proteomics techniques, respectively. While these single-level OMICS approaches have contributed towards the identification of cancer-specific mutations, epigenetic alterations, and molecular subtyping of tumors based on gene/protein-expression, they lack the resolving-power to establish the casual relationship between molecular signatures and the phenotypic manifestation of cancer hallmarks. In contrast, the multi-OMICS approaches involving the interrogation of the cancer cells/tissues in multiple dimensions have the potential to uncover the intricate molecular mechanism underlying different phenotypic manifestations of cancer hallmarks such as metastasis and angiogenesis. Moreover, multi-OMICS approaches can be used to dissect the cellular response to chemo- or immunotherapy as well as discover molecular candidates with diagnostic/prognostic value. In this review, we focused on the applications of different multi-OMICS approaches in the field of cancer research and discussed how these approaches are shaping the field of personalized oncomedicine. We have highlighted pioneering studies from “The Cancer Genome Atlas (TCGA)” consortium encompassing integrated OMICS analysis of over 11,000 tumors from 33 most prevalent forms of cancer. Accumulation of huge cancer-specific multi-OMICS data in repositories like TCGA provides a unique opportunity for the systems biology approach to tackle the complexity of cancer cells through the unification of experimental data and computational/mathematical models. In future, systems biology based approach is likely to predict the phenotypic changes of cancer cells upon chemo-/immunotherapy treatment. This review is sought to encourage investigators to bring these different approaches together for interrogating cancer at molecular, cellular, and systems levels.

Structural, functional and molecular docking study to characterize GMI1 from Arabidopsis thaliana

Abstractγ-irradiation and Mitomycin C Induced 1 (GMI1), is a member of the SMC-hinge domain-containing protein family that takes part in double stranded break repair mechanism in eukaryotic cells. In this study we hypothesize a small molecule-Adenosine Tri Phosphate (ATP) binding region of novel SMC like GM1 protein in model organism Arabidopsis thaliana using in silico modeling. Initially, analyzing sequence information for the protein indicated presence of motifs — ‘Walker A nucleotide-binding domain’ that are required to interact with nucleotides along with ‘Walker B’ motif and ABC signature sequences. This was further proven through GMI1-ATP docking experiment and results were verified by comparing the values with controls. In negative control, no binding was seen in the same binding region of GMI1 structure for small molecules randomly selected form PubChem database, whereas in positive control binding affinity of other known proteins with ATP binding potential resembled GMI1-ATP binding affinity of −5.4 kcal/mol. Furthermore we also docked small molecules that shares structural similarity with ATP to GMI1 and found that Purine Mononucleotide bound the region with the best affinity, which implies that the compound may bind the protein with strong binding and can work as a potential agonist/antagonist to GMI1. We believe that the study would shed more light into the GM1 mechanism of action. Although the computational predictions made here are based on concrete confidence, it should be mentioned that in vitro experimentation does not fall into the scopes of this study and thus the results found here have to be further validated in vitro.