Investigating the pathogenic SNPs in BLM helicase and their biological consequences by computational approach

Computational studies on the functional and structural impact of pathogenic mutations in enzymes

Enzymes are critical biological catalysts involved in maintaining the intricate balance of metabolic processes within living organisms. Mutations in enzymes can result in disruptions to their functionality that may lead to a range of diseases. This review focuses on computational studies that investigate the effects of disease-associated mutations in various enzymes. Through molecular dynamics simulations, multiscale calculations, and machine learning approaches, computational studies provide detailed insights into how mutations impact enzyme structure, dynamics, and catalytic activity. This review emphasizes the increasing impact of computational simulations in understanding molecular mechanisms behind enzyme (dis)function by highlighting the application of key computational methodologies to selected enzyme examples, aiding in the prediction of mutation effects and the development of therapeutic strategies.

TRF2-RAP1 represses RAD51-dependent homology-directed telomere repair by promoting BLM-mediated D-loop unwinding and inhibiting BLM-DNA2-dependent 5'-end resection

Inappropriate homology-directed repair (HDR) of telomeres results in catastrophic telomere loss and aberrant chromosome fusions, leading to genome instability. We have previously shown that the TRF2-RAP1 heterodimer protects telomeres from engaging in aberrant telomere HDR. Cells lacking the basic domain of TRF2 and functional RAP1 display HDR-mediated telomere clustering, resulting in the formation of ultrabright telomeres (UTs) and massive chromosome fusions. Using purified proteins, we uncover three distinct molecular pathways that the TRF2-RAP1 heterodimer utilizes to protect telomeres from engaging in aberrant HDR. We show mechanistically that TRF2-RAP1 inhibits RAD51-initiated telomeric D-loop formation. Both the TRF2 basic domain and RAP1-binding to TRF2 are required to block RAD51-mediated homology search. TRF2 recruits the BLM helicase to telomeres through its TRFH domain to promote BLM-mediated unwinding of telomere D-loops. In addition, TRF2-RAP1 inhibits BLM-DNA2-mediated 5' telomere end resection, preventing the generation of 3' single-stranded telomere overhangs necessary for RAD51-dependent HDR. Importantly, cells expressing BLM mutants unable to interact with TRF2 accumulate telomere D-loops and UTs. Our findings uncover distinct molecular mechanisms coordinated by TRF2-RAP1 to protect telomeres from engaging in aberrant HDR.

Genetic variation in the BLM gene and its expression in the ovaries is closely related to kidding number in goats

Bloom (BLM) helicase plays an important role in DNA replication and the maintenance of genome integrity. BLM protein deficiency, which plays a vital role in the sperm-egg union and germ-cell development during reproduction, can lead to severe DNA damage in goats. However, the effect of BLM protein deficiency on goat litter size has not been reported. Herein, we studied the association between the genetic variation in the BLM gene and the number of kids per litter in Guizhou white goats. We explored differences in the expression of the BLM protein in the follicles of single and multi-kid nanny goats. We also analyzed the effects of dysregulated BLM gene expression on the proliferation and apoptosis of ovarian granulosa cells and the expression of genes related to follicle development in goats. Five single nucleotide polymorphism (SNP) loci, including the non-synonymous mutations g.38179 A > G, g.40626 G > C and g.89621 T > G; the intron synonymous mutation g.56961 G > A and the exon synonymous mutation g.65796 C > T were found in the BLM gene. All SNPs loci were in Hardy-Weinberg equilibrium, and correlation analysis showed that the g.65796 C > T and g.89621 T > G loci polymorphism was strongly associated with litter size in the first three litters (P < 0.05). The diplogenotype Hap 2/2 (AAGGAACCTT) showed no significant difference in litter size between different births, indicating that the diploid genotype is stable in different litter sizes. Bioinformatics analysis showed that three non-synonymous mutation loci (p.T488A, p.A662S, and p.S1373A) could affect BLM protein stability, and mutations in p.T488A and p.S1373A led to changes in amino acid polarity and associated interactions. qPCR results showed that the expression level of the BLM gene in the uterus and ovaries of TT genotype nanny goats was significantly higher than that of GG genotype nanny goats. Indirect immunofluorescence assay (IF) showed that the BLM protein was significantly overexpressed in both the primordial and growing follicles of nanny goats with multiple kids (P < 0.01). Disrupting BLM gene expression in the ovarian granulosa cells down-regulated the expression of the Cyp19A1 gene. It also significantly inhibited the proliferation of follicles and induces early apoptosis of the granulosa cells. These findings confirm that polymorphism in the BLM gene is closely related to the littering traits of Guizhou white goats, and it affects the reproductive performance of nanny goats by regulating the development of the oocytes and granulosa cells. This work provides new evidence on the regulatory effect of the BLM gene on the litter size of nanny goats.

Design and synthesis of quinazolin-4-one derivatives as potential anticancer agents and investigation of their interaction with RecQ helicases

The upregulation of RecQ helicases has been associated with cancer cell survival and resistance to chemotherapy, making them appealing targets for therapeutic intervention. In this study, twenty-nine novel quinazolinone derivatives were designed and synthesized. The anti-proliferative activity of all compounds was evaluated against 60 cancer cell lines at the National Cancer Institute Developmental Therapeutic Program, with six compounds (11f, 11g, 11k, 11n, 11p, and 11q) being promoted to a five-dose screen. Compound 11g demonstrated high cytotoxic activity against all examined cell lines. The compounds were further assayed for Bloom syndrome (BLM) helicase inhibition, where 11g, 11q, and 11u showed moderate activity. These compounds were counter-screened against WRN and RECQ1 helicases, where 11g moderately inhibited both enzymes. An ATP competition assay confirmed that the compounds bound to the ATP site of RecQ helicases, and molecular docking simulations were used to study the binding mode within the active site of BLM, WRN, and RECQ1 helicases. Compound 11g induced apoptosis in both HCT-116 and MDA-MB-231 cell lines, but also caused an G2/M phase cell cycle arrest in HCT-116 cells. This data revealed the potential of 11g as a modulator of cell cycle dynamics and supports its interaction with RecQ helicases. In addition, compound 11g displayed non-significant toxicity against FCH normal colon cells at doses up to 100 µM, which confirming its high safety margin and selectivity on cancer cells. Overall, these findings suggest compound 11g as a potential pan RecQ helicase inhibitor with high anticancer potency and a favorable safety margin and selectivity.

Circulating interleukins and risk of colorectal cancer: a Mendelian randomization study

BACKGROUND

Recent studies have suggested a potential causal association between Interleukins (ILs) and Colorectal Cancer (CRC), and thus, it is important to examine the causal relationship between them using a Mendelian randomization (MR) approach.

METHODS

The instrumental variables were extracted for IL-1ra, IL-6, IL-6ra, IL-8, IL-16, IL-18, IL-27 from genome-wide association studies of European ancestry. Summary statistics of CRC were also retrieved. An inverse variance-weighted MR approach was implemented as the primary method to compute overall effects from multiple instruments. Additional MR approaches and sensitivity and heterogeneity pleiotropy analyses were also conducted respectively.

RESULTS

Our analysis suggested a causal effect between an increase of IL-8 and a reduced risk of CRC (odds ratio 0.65; 95% confidence interval, 0.43-0.98; p = 0.041) and did not provide evidence for causal effects of IL-1ra, IL-6, IL-6ra, IL-16, IL-18, IL-27. Sensitivity analyses suggested the robustness of MR results and that they were unlikely to be affected by unbalanced pleiotropy or significant heterogeneity.

CONCLUSIONS

This study investigated the role of ILs in the development of CRC and we found a causal effect between an increase of IL-8 and a reduced risk of CRC but not found evidence for causal effects of IL-1ra, IL-6, IL-6ra, IL-16, IL-18, IL-27. Sensitivity analyses suggested the robustness of MR results and that they were unlikely to be affected by unbalanced pleiotropy or significant heterogeneity.

BLM helicase overexpressed in human gliomas contributes to diverse responses of human glioma cells to chemotherapy

Most of anti-tumour therapies eliminate neoplastic cells by introducing DNA damage which ultimately triggers cell death. These effects are counteracted by activated DNA repair pathways to sustain tumour proliferation capacity. RECQL helicases family, including BLM, participate in DNA damage and repair, and prevent the replication stress. Glioblastoma (GBM) is a common, malignant brain tumour that inevitably recurs despite surgical resection, radiotherapy, and chemotherapy with temozolomide (TMZ). Expression and functions of the BLM helicase in GBM therapy resistance have not been elucidated. We analysed expression and localisation of BLM in human gliomas and several glioma cell lines using TCGA datasets, immunostaining and Western blotting. BLM depleted human glioma cells were generated with CRISPR/Cas9 system. Effects of chemotherapeutics on cell proliferation, DNA damage and apoptosis were determined with flow cytometry, immunofluorescence, Western blotting and RNA sequencing. We found upregulated BLM mRNA levels in malignant gliomas, increased cytosolic localisation and poor survival of GBM patients with high BLM expression. BLM deficiency in LN18 and LN229 glioma cells resulted in profound transcriptomic alterations, reduced cell proliferation, and altered cell responses to chemotherapeutics. BLM-deficient glioma cells were resistant to the TMZ and PARP inhibitor treatment and underwent polyploidy or senescence depending on the TP53 activity. Our findings of high BLM expression in GBMs and its roles in responses to chemotherapeutics provide a rationale for targeting BLM helicase in brain tumours. BLM deficiency affects responses of glioma cells to chemotherapeutics targeting PARP1 dependent pathways.

The BLM helicase is a new therapeutic target in multiple myeloma involved in replication stress survival and drug resistance

Multiple myeloma (MM) is a hematologic cancer characterized by accumulation of malignant plasma cells in the bone marrow. To date, no definitive cure exists for MM and resistance to current treatments is one of the major challenges of this disease. The DNA helicase BLM, whose depletion or mutation causes the cancer-prone Bloom's syndrome (BS), is a central factor of DNA damage repair by homologous recombination (HR) and genomic stability maintenance. Using independent cohorts of MM patients, we identified that high expression of BLM is associated with a poor outcome with a significant enrichment in replication stress signature. We provide evidence that chemical inhibition of BLM by the small molecule ML216 in HMCLs (human myeloma cell lines) leads to cell cycle arrest and increases apoptosis, likely by accumulation of DNA damage. BLM inhibition synergizes with the alkylating agent melphalan to efficiently inhibit growth and promote cell death in HMCLs. Moreover, ML216 treatment re-sensitizes melphalan-resistant cell lines to this conventional therapeutic agent. Altogether, these data suggest that inhibition of BLM in combination with DNA damaging agents could be of therapeutic interest in the treatment of MM, especially in those patients with high BLM expression and/or resistance to melphalan.

A Systems Biology and LASSO-Based Approach to Decipher the Transcriptome-Interactome Signature for Predicting Non-Small Cell Lung Cancer

The lack of precise molecular signatures limits the early diagnosis of non-small cell lung cancer (NSCLC). The present study used gene expression data and interaction networks to develop a highly accurate model with the least absolute shrinkage and selection operator (LASSO) for predicting NSCLC. The differentially expressed genes (DEGs) were identified in NSCLC compared with normal tissues using TCGA and GTEx data. A biological network was constructed using DEGs, and the top 20 upregulated and 20 downregulated hub genes were identified. These hub genes were used to identify signature genes with penalized logistic regression using the LASSO to predict NSCLC. Our model’s development involved the following steps: (i) the dataset was divided into 80% for training (TR) and 20% for testing (TD1); (ii) a LASSO logistic regression analysis was performed on the TR with 10-fold cross-validation and identified a combination of 17 genes as NSCLC predictors, which were used further for development of the LASSO model. The model’s performance was assessed on the TD1 dataset and achieved an accuracy and an area under the curve of the receiver operating characteristics (AUC-ROC) of 0.986 and 0.998, respectively. Furthermore, the performance of the LASSO model was evaluated using three independent NSCLC test datasets (GSE18842, GSE27262, GSE19804) and achieved high accuracy, with an AUC-ROC of >0.99, >0.99, and 0.95, respectively. Based on this study, a web application called NSCLCpred was developed to predict NSCLC.

Discovery of a Novel Bloom's Syndrome Protein (BLM) Inhibitor Suppressing Growth and Metastasis of Prostate Cancer

Prostate cancer (PCa) is a common cancer and a major cause of cancer-related death worldwide in men, necessitating novel targets for cancer therapy. High expression of Bloom's syndrome protein (BLM) helicase is associated with the occurrence and development of PCa. Therefore, the identification and development of new BLM inhibitors may be a new direction for the treatment of PCa. Here, we identified a novel inhibitor by molecular docking and put it to systematic evaluation via various experiments, AO/854, which acted as a competitive inhibitor that blocked the BLM-DNA interaction. Cellular evaluation indicated that AO/854-suppressed tumor growth and metastasis in PC3 cells by enhancing DNA damage, phosphorylating Chk1/Chk2, and altering the p53 signaling pathway. Collectively, the study highlights the potential of BLM as a therapeutic target in PCa and reveals a distinct mechanism by which AO/854 competitively inhibits the function of BLM.

Identification and Characterization of Novel Mutations in Chronic Kidney Disease (CKD) and Autosomal Dominant Polycystic Kidney Disease (ADPKD) in Saudi Subjects by Whole-Exome Sequencing

Background: Autosomal dominant polycystic kidney disease (ADPKD) is a condition usually caused by a single gene mutation and manifested by both renal and extrarenal features, eventually leading to end-stage renal disease (ESRD) by the median age of 60 years worldwide. Approximately 89% of ADPKD patients had either PKD1 or PKD2 gene mutations. The majority (85%) of the mutations are in the PKD1 gene, especially in the context of family history. Objectives: This study investigated the genetic basis and the undiscovered genes that are involved in ADPKD development among the Saudi population. Materials and Methods: In this study, 11 patients with chronic kidney disease were enrolled. The diagnosis of ADPKD was based on history and diagnostic images: CT images include enlargement of renal outlines, renal echogenicity, and presence of multiple renal cysts with dilated collecting ducts, loss of corticomedullary differentiation, and changes in GFR and serum creatinine levels. Next-generation whole-exome sequencing was conducted using the Ion Torrent PGM platform. Results: Of the 11 Saudi patients diagnosed with chronic kidney disease (CKD) and ADPKD, the most common heterozygote nonsynonymous variant in the PKD1 gene was exon15: (c.4264G > A). Two missense mutations were identified with a PKD1 (c.1758A > C and c.9774T > G), and one patient had a PKD2 mutation (c.1445T > G). Three detected variants were novel, identified at PKD1 (c.1758A > C), PKD2L2 (c.1364A > T), and TSC2 (deletion of a’a at the 3’UTR, R1680C) genes. Other variants in PKD1L1 (c.3813_381 4delinsTG) and PKD1L2 (c.404C > T) were also detected. The median age of end-stage renal disease for ADPK patients in Saudi Arabia was 30 years. Conclusion: This study reported a common variant in the PKD1 gene in Saudi patients with typical ADPKD. We also reported (to our knowledge) for the first time two novel missense variants in PKD1 and PKD2L2 genes and one indel mutation at the 3’UTR of the TSC2 gene. This study establishes that the reported mutations in the affected genes resulted in ADPKD development in the Saudi population by a median age of 30. Nevertheless, future protein−protein interaction studies to investigate the influence of these mutations on PKD1 and PKD2 functions are required. Furthermore, large-scale population-based studies to verify these findings are recommended.

In silico investigations identified Butyl Xanalterate to competently target CK2α (CSNK2A1) for therapy of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is an incurable malignancy of B-cells. In this study, bioinformatics analyses were conducted to identify possible pathogenic roles of CK2α, which is a protein encoded by CSNK2A1, in the progression and aggressiveness of CLL. Furthermore, various computational tools were used to search for a competent inhibitor of CK2α from fungal metabolites that could be proposed for CLL therapy. In CLL patients, high-expression of CSNK2A1 was associated with early need for therapy (n = 130, p < 0.0001) and short overall survival (OS; n = 107, p = 0.005). Consistently, bioinformatics analyses showed CSNK2A1 to associate with/play roles in CLL proliferation and survival-dependent pathways. Furthermore, PPI network analysis identified interaction partners of CK2α (PPI enrichment p value = 1 × 10^-16) that associated with early need for therapy (n = 130, p < 0.003) and have been known to heavily impact on the progression of CLL. These findings constructed a rational for targeting CK2α for CLL therapy. Consequently, computational analyses reported 35 fungal metabolites out of 5820 (filtered from 19,967 metabolites) to have lower binding energy (ΔG: - 10.9 to - 11.7 kcal/mol) and better binding affinity (Kd: 9.77 × 10⁷ M^-1 to 3.77 × 10⁸ M^-1) compared with the native ligand (ΔG: - 10.8, Kd: 8.3 × 10⁷ M-^-1). Furthermore, molecular dynamics simulation study established that Butyl Xanalterate-CK2α complex continuously remained stable throughout the simulation time (100 ns). Moreover, Butyl Xanalterate interacted with most of the catalytic residues, where complex was stabilized by more than 65% hydrogen bond interactions, and a significant hydrophobic interaction with residue Phe113. Here, high-expression of CSNK2A1 was implicated in the progression and poor prognosis of CLL, making it a potential therapeutic target in the disease. Butyl Xanalterate showed stable and strong interactions with CK2α, thus we propose it as a competitive inhibitor of CK2α for CLL therapy.

High Expression of Bloom Syndrome Helicase is a Key Factor for Poor Prognosis and Advanced Malignancy in Patients with Pancreatic Cancer: A Retrospective Study

BACKGROUND

Bloom syndrome helicase (BLM) is overexpressed in multiple types of cancers and its overexpression may induce genomic instability. This study aimed to determine the function of BLM expression in pancreatic cancer.

METHODS

BLM messenger RNA (mRNA) expression was analyzed using public datasets to determine its relationship with pancreatic cancer prognosis. Overall, 182 patients with pancreatic cancer who underwent radical resection at our institution were enrolled. BLM expression was evaluated by immunohistochemistry (IHC). We explored the effect of BLM on the proliferation, invasion, migration, and chemoresistance of pancreatic cancer cells via small-interfering RNAs and performed pathway analysis using gene set enrichment analysis.

RESULTS

BLM mRNA expression was higher in tumor tissue than in normal tissue and had a prognostic effect on overall survival (OS) and recurrence-free survival. The same results were validated by IHC. Multivariate analysis showed that high BLM expression was an independent poor prognostic factor for OS (hazard ratio [HR] 1.678, p = 0.029). In subgroup analysis, the effect of high BLM expression was more significant on OS in patients with younger age (HR 2.27, p = 0.006), male sex (HR 2.39, p = 0.002), high cancer antigen 19-9 level (HR 2.44, p = 0.001), advanced tumor stage (HR 2.25, p = 0.001), lymph node metastasis (HR 2.51, p = 0.001), nerve invasion (HR 2.07, p = 0.002), and adjuvant chemotherapy (HR 2.66, p < 0.001). In vitro, BLM suppression resulted in reduced tumor proliferation, invasion, migration, and chemoresistance. Mechanistically, BLM expression may be associated with E2F1 and E2F2.

CONCLUSION

BLM expression is a prognostic factor for patients with pancreatic cancer, especially in those with advanced malignancies and receiving chemotherapy.

In Silico Identification of Hub Genes as Observing Biomarkers for Gastric Cancer Metastasis

Perception of hub genes engaged in metastatic gastric cancer (mGC) promotes novel ways to diagnose and treat the illness. The goal of this investigation is to recognize the hub genes and reveal its molecular mechanism. In order to explore the potential facts for gastric cancer, the expression profiles of two different datasets were used (GSE161533 and GSE54129). The genes were confirmed to be part of the PPI network for gastric cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. Responsible hub genes were identified. Data from Kaplan-Meier plotter confirmed the predictive value of these distinct genes in various stages of gastric malignancy. Upregulated and downregulated genes were identified to utilize for further analysis. Positive regulation by a host of viral process, positive regulation of granulocyte differentiation, negative regulation of histone H3-K9 methylation were found in DEGs analysis. In addition, five KEGG pathways were identified as an essential enhancer that include nucleotide excision repair; base excision repair; DNA replication; homologous recombination; and complement and coagulation cascades. POLE, BUB1B, POLD4, C3, BLM, CCT7, PRPF31, APEX1, PSMA7, and CDC45 were chosen as hub genes after combining the PPI results. Our study recommends that BUB1B, CCT7, APEX1, PSMA7, and CDC45 might be potential biomarkers for gastric cancer. These biomarkers are upregulated genes. Therefore, suppression of these genes will increase the survival rate in gastric cancer patients.

Targeting of RecQ Helicases as a Novel Therapeutic Strategy for Ovarian Cancer

RecQ helicases are essential for DNA replication, recombination, DNA damage repair, and other nucleic acid metabolic pathways required for normal cell growth, survival, and genome stability. More recently, RecQ helicases have been shown to be important for replication fork stabilization, one of the major mechanisms of PARP inhibitor resistance. Cancer cells often have upregulated helicases and depend on these enzymes to repair rapid growth-promoted DNA lesions. Several studies are now evaluating the use of RecQ helicases as potential biomarkers of breast and gynecologic cancers. Furthermore, RecQ helicases have attracted interest as possible targets for cancer treatment. In this review, we discuss the characteristics of RecQ helicases and their interacting partners that may be utilized for effective treatment strategies (as cancers depend on helicases for survival). We also discuss how targeting helicase in combination with DNA repair inhibitors (i.e., PARP and ATR inhibitors) can be used as novel approaches for cancer treatment to increase sensitivity to current treatment to prevent rise of treatment resistance.

Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program

The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial intelligence (AI) in genomics are critical public issues in medical care and scientific research. The present study was aimed to examine the awareness, knowledge, and attitude of the Saudi society towards the SHGP, the sharing and privacy of genetic data resulting from the SHGP, and the role of AI in genetic data analysis and regulations. Results of a questionnaire survey with 804 respondents revealed moderate awareness and attitude towards the SHGP and minimal knowledge regarding its benefits and applications. Respondents demonstrated a low level of knowledge regarding the privacy of genetic data. A generally positive attitude was found towards the outcomes of the SHGP and genetic data sharing for medical and scientific research. The highest level of knowledge was detected regarding AI use in genetic data analysis and privacy regulation. We recommend that the SHGP’s regulators launch awareness campaigns and educational programs to increase and improve public awareness and knowledge regarding the SHGP’s benefits and applications. Furthermore, we propose a strategy for genetic data sharing which will facilitate genetic data sharing between institutions and advance Personalized Medicine in genetic diseases’ diagnosis and treatment.

Association of SNPs within TMPRSS6 and BMP2 genes with iron deficiency status in Saudi Arabia

BACKGROUND

Globally, iron-deficiency anemia (IDA) remains a major health obstacle. This health condition has been identified in 47% of pre-school students (aged 0 to 5 years), 42% of pregnant females, and 30% of non-pregnant females (aged 15 to 50 years) worldwide according to the WHO. Environmental and genetic factors play a crucial role in the development of IDA; genetic testing has revealed the association of a number of polymorphisms with iron status and serum ferritin.

AIM

The current study aims to reveal the association of TMPRSS6 rs141312 and BMP2 rs235756 with the iron status of females in Saudi Arabia.

METHODS

A cohort of 108 female university students aged 18-25 years was randomly selected to participate: 50 healthy and 58 classified as iron deficient. A 3-5 mL sample of blood was collected from each one and analyzed based on hematological and biochemical iron status followed by genotyping by PCR.

RESULTS

The genotype distribution of TMPRSS6 rs141312 was 8% (TT), 88% (TC) and 4% (CC) in the healthy group compared with 3.45% (TT), 89.66% (TC) and 6.89% (CC) in the iron-deficient group (P = 0.492), an insignificant difference in the allelic distribution. The genotype distribution of BMP2 rs235756 was 8% (TT), 90% (TC) and 2% (CC) in the healthy group compared with 3.45% (TT), 82.76% (TC) and 13.79% (CC) in iron-deficient group (P = 0.050) and was significantly associated with decreased ferritin status (P = 0.050). In addition, TMPRSS6 rs141312 is significantly (P<0.001) associated with dominant genotypes (TC+CC) and increased risk of IDA while BMP2 rs235756 is significantly (P<0.026) associated with recessive homozygote CC genotypes and increased risk of IDA.

CONCLUSION

Our finding potentially helps in the early prediction of iron deficiency in females through the genetic testing.

In silico modeling of the interaction between TEX19 and LIRE1, and analysis of TEX19 gene missense SNPs

BACKGROUND

Testis expressed 19 (TEX19) is a specific human stem cell gene identified as cancer-testis antigen (CTA), which emerged as a potential therapeutic drug target. TEX19.1, a mouse paralog of human TEX19, can interact with LINE-1 retrotransposable element ORF1 protein (LIRE1) and subsequently restrict mobilization of LINE-1 elements in the genome.

AIM

This study aimed to predict the interaction of TEX19 with LIRE1 and analyze TEX19 missense polymorphisms. TEX19 model was generated using I-TASSER and the interaction between TEX19 and LIRE1 was studied using the HADDOCK software.

METHODS

The stability of the docking formed complex was studied through the molecular dynamic simulation using GROMACS. Missense SNPs (n=102) of TEX19 were screened for their potential effects on protein structure and function using different software.

RESULTS

Outcomes of this study revealed amino acids that potentially stabilize the predicted interaction interface between TEX19 and LIRE1. Of these SNPs, 37 were predicted to play a probably damaging role for the protein, three of them (F35S, P61R, and E55L) located at the binding site of LIRE1 and could disturb this binding affinity.

CONCLUSION

This information can be verified by further in vitro and in vivo experimentations and could be exploited for potential therapeutic targets.

Nitric Oxide Synthase Potentiates the Resistance of Cancer Cell Lines to Anticancer Chemotherapeutics

BACKGROUND

Despite the advancement in the fields of medical science and molecular biology, cancer is still the leading cause of death worldwide. Chemotherapy is a choice for treatment; however, the acquisition of chemo-resistance is a major impediment to cancer management. Many mechanisms have been postulated regarding the acquisition of chemo-resistance in breast cancer the impact on cellular signaling and the induction of apoptosis in tumour cells. The mechanism of the apoptotic mutation of p53 and bcl-2 proteins is commonly associated with increased resistance to apoptosis and, therein, to chemotherapy.

OBJECTIVES

The current study was aimed to investigate A172 and MDA-MB-231 cancer cells' sensitivity against chemotherapeutic drugs, including cisplatin, doxorubicin, and paclitaxel with different doses. Moreover, it estimates the resistance of cancer cells by evaluating nitric oxide synthase (NOS) expression and evaluate its correlation with the expression profile proteins of the apoptosis regulating Bcl-2 family.

METHODS

Dose-dependent sensitivity to cisplatin, doxorubicin, or paclitaxel was evaluated on spheroid cultured A172 and MDA-MB-231 cells lines as measured by time-lapse microscopy over a 72h period. Expressions of two nitric oxides (NO) synthases isoforms (iNOS, eNOS), anti-apoptotic (Bcl-2, phospho-Bcl-2, Mcl-1, and Bcl-xL), and pro-apoptotic (BID, Bim, Bok, Bad, Puma, and Bax) were evaluated by Western blot. The effect of NO modulation on anti- and pro-apoptotic molecule expression was also studied using Western blot.

RESULT

A172 cells show more resistance to chemotherapy drugs than MDA-MB-231 cancer cells. Therefore, they need higher doses for apoptosis. Resistance of gliomas might be returned to the higher significant expression of endothelial eNOS expression. It was clear that there is not a significant effect of NO modulation on the expression of pro-and anti-apoptotic proteins on both cell lines.

CONCLUSION

The present work provides a putative mechanism for the acquisition of drug resistance in breast cancer and glioma, which might be significant for clinical outcomes.

Functions of BLM Helicase in Cells: Is It Acting Like a Double-Edged Sword?

DNA damage repair response is an important biological process involved in maintaining the fidelity of the genome in eukaryotes and prokaryotes. Several proteins that play a key role in this process have been identified. Alterations in these key proteins have been linked to different diseases including cancer. BLM is a 3′−5′ ATP-dependent RecQ DNA helicase that is one of the most essential genome stabilizers involved in the regulation of DNA replication, recombination, and both homologous and non-homologous pathways of double-strand break repair. BLM structure and functions are known to be conserved across many species like yeast, Drosophila, mouse, and human. Genetic mutations in the BLM gene cause a rare, autosomal recessive disorder, Bloom syndrome (BS). BS is a monogenic disease characterized by genomic instability, premature aging, predisposition to cancer, immunodeficiency, and pulmonary diseases. Hence, these characteristics point toward BLM being a tumor suppressor. However, in addition to mutations, BLM gene undergoes various types of alterations including increase in the copy number, transcript, and protein levels in multiple types of cancers. These results, along with the fact that the lack of wild-type BLM in these cancers has been associated with increased sensitivity to chemotherapeutic drugs, indicate that BLM also has a pro-oncogenic function. While a plethora of studies have reported the effect of BLM gene mutations in various model organisms, there is a dearth in the studies undertaken to investigate the effect of its oncogenic alterations. We propose to rationalize and integrate the dual functions of BLM both as a tumor suppressor and maybe as a proto-oncogene, and enlist the plausible mechanisms of its deregulation in cancers.

A Comprehensive Analysis of cis-Acting RNA Elements in the SARS-CoV-2 Genome by a Bioinformatics Approach

The emergence of a new coronavirus (CoV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for severe respiratory disease in humans termed coronavirus disease of 2019 (COVID-19), became a new global threat for health and the economy. The SARS-CoV-2 genome is about a 29,800-nucleotide-long plus-strand RNA that can form functionally important secondary and higher-order structures called cis-acting RNA elements. These elements can interact with viral proteins, host proteins, or other RNAs and be involved in regulating translation and replication processes of the viral genome and encapsidation of the virus. However, the cis-acting RNA elements and their biological roles in SARS-CoV-2 as well as their comparative analysis in the closely related viral genome have not been well explored, which is very important to understand the molecular mechanism of viral infection and pathogenies. In this study, we used a bioinformatics approach to identify the cis-acting RNA elements in the SARS-CoV-2 genome. Initially, we aligned the full genomic sequence of six different CoVs, and a phylogenetic analysis was performed to understand their evolutionary relationship. Next, we predicted the cis-acting RNA elements in the SARS-CoV-2 genome using the structRNAfinder tool. Then, we annotated the location of these cis-acting RNA elements in different genomic regions of SARS-CoV-2. After that, we analyzed the sequence conservation patterns of each cis-acting RNA element among the six CoVs. Finally, the presence of cis-acting RNA elements across different CoV genomes and their comparative analysis was performed. Our study identified 12 important cis-acting RNA elements in the SARS-CoV-2 genome; among them, Corona_FSE, Corona_pk3, and s2m are highly conserved across most of the studied CoVs, and Thr_leader, MAT2A_D, and MS2 are uniquely present in SARS-CoV-2. These RNA structure elements can be involved in viral translation, replication, and encapsidation and, therefore, can be potential targets for better treatment of COVID-19. It is imperative to further characterize these cis-acting RNA elements experimentally for a better mechanistic understanding of SARS-CoV-2 infection and therapeutic intervention.

A Network-Based Analysis Reveals the Mechanism Underlying Vitamin D in Suppressing Cytokine Storm and Virus in SARS-CoV-2 Infection

Background

SARS-CoV-2 causes ongoing pandemic coronavirus disease of 2019 (COVID-19), infects the cells of the lower respiratory tract that leads to a cytokine storm in a significant number of patients resulting in severe pneumonia, shortness of breathing, respiratory and organ failure. Extensive studies suggested the role of Vitamin D in suppressing cytokine storm in COVID-19 and reducing viral infection; however, the precise molecular mechanism is not clearly known. In this work, bioinformatics and systems biology approaches were used to understand SARS-CoV-2 induced cytokine pathways and the potential mechanism of Vitamin D in suppressing cytokine storm and enhancing antiviral response.

Results

This study used transcriptome data and identified 108 differentially expressed host genes (DEHGs) in SARS-CoV-2 infected normal human bronchial epithelial (NHBE) cells compared to control. Then, the DEHGs was integrated with the human protein-protein interaction data to generate a SARS-CoV-2 induced host gene regulatory network (SiHgrn). Analysis of SiHgrn identified a sub-network "Cluster 1" with the highest MCODE score, 31 up-regulated genes, and predominantly associated immune and inflammatory response. Interestingly, the iRegulone tool identified that "Cluster 1" is under the regulation of transcription factors STAT1, STAT2, STAT3, POU2F2, and NFkB1, collectively referred to as "host response signature network". Functional enrichment analysis with NDEx revealed that the "host response signature network" is predominantly associated with critical pathways, including "cytokines and inflammatory response", "non-genomic action of Vitamin D", "the human immune response to tuberculosis", and "lung fibrosis". Finally, in-depth analysis and literature mining revealed that Vitamin D binds with its receptor and could work through two different pathways: (i) it inhibits the expression of pro-inflammatory cytokines through blocking the TNF induced NFkB1 signaling pathway; and (ii) it initiates the expression of interferon-stimulating genes (ISGs) for antiviral defense program through activating the IFN-α induced Jak-STAT signaling pathway.

Conclusion

This comprehensive study identified the pathways associated with cytokine storm in SARS-CoV-2 infection. The proposed underlying mechanism of Vitamin D could be promising in suppressing the cytokine storm and inducing a robust antiviral response in severe COVID-19 patients. The finding in this study urgently needs further experimental validations for the suitability of Vitamin D in combination with IFN-α to control severe COVID-19.