Characterization of Posttranslationally Modified PHF-1 Tau Peptides Using Gaussian Accelerated Molecular Dynamics Simulation.

The microtubule-associated protein, Tau, is an intrinsically disordered protein that plays a crucial role in neurodegenerative diseases like Alzheimer's disease. The posttranslational modifications across the Tau protein domains are involved in regulating Tau protein's function and disease onset. Of the various posttranslational modifications at Ser, Thr, and Tyr sites, O-GlcNAcylation and phosphorylation are the most critical ones, playing a vital role in Tau aggregation and tauopathies. To understand the function, it is essential to characterize the structural changes associated with Tau modification. Previous experimental studies have focused on high-resolution nuclear magnetic resonance techniques to structurally characterize the effect of phosphorylation, O-GlcNAcylation, and combination of both PTMs on Tau conformation in small peptides centered on the PHF-1 epitope from amino acid 392 to 411. The structural characterization using atomistic molecular dynamics simulation of such disordered peptides requires long simulation time, proper sampling method, and utilization of appropriate force fields for accurate determination of conformational ensembles, resembling the experimental data. This chapter details the protocol for the structural characterization of modified Tau peptides using the CHARMM36m force field and enhanced sampling methods like Gaussian accelerated molecular dynamics (GaMD) simulation. We have focused on a detailed explanation of the GaMD method and analyses of molecular dynamics trajectories to explain the relationship between two modifications, phospho- and glyco-, at C-terminus of Tau protein and its stable conformation over the longer simulation timeframes. The analyses involve energetics reweighting, clustering of simulation trajectories, and characterization of secondary structure using circular dichroism data from the simulation. The reader can utilize this protocol to investigate the structures of complex proteins, especially the disordered ones.

Dynamics and recognition of homeodomain containing protein-DNA complex of IRX4.

Iroquois Homeobox 4 (IRX4) belongs to a family of homeobox TFs having roles in embryogenesis, cell specification, and organ development. Recently, large scale genome-wide association studies and epigenetic studies have highlighted the role of IRX4 and its associated variants in prostate cancer. No studies have investigated and characterized the structural aspect of the IRX4 homeodomain and its potential to bind to DNA. The current study uses sequence analysis, homology modeling, and molecular dynamics simulations to explore IRX4 homeodomain-DNA recognition mechanisms and the role of somatic mutations affecting these interactions. Using publicly available databases, gene expression of IRX4 was found in different tissues, including prostate, heart, skin, vagina, and the protein expression was found in cancer cell lines (HCT166, HEK293), B cells, ascitic fluid, and brain. Sequence conservation of the homeodomain shed light on the importance of N- and C-terminal residues involved in DNA binding. The specificity of IRX4 homodimer bound to consensus human DNA sequence was confirmed by molecular dynamics simulations, representing the role of conserved amino acids including R145, A194, N195, S190, R198, and R199 in binding to DNA. Additional N-terminal residues like T144 and G143 were also found to have specific interactions highlighting the importance of N-terminus of the homeodomain in DNA recognition. Additionally, the effects of somatic mutations, including the conserved Arginine (R145, R198, and R199) residues on DNA binding elucidated the importance of these residues in stabilizing the protein-DNA complex. Secondary structure and hydrogen bonding analysis showed the roles of specific residues (R145, T191, A194, N195, R198, and R199) in maintaining the homogeneity of the structure and its interaction with DNA. The differences in relative binding free energies of all the mutants shed light on the structural modularity of this protein and the dynamics behind protein-DNA interaction. We also have predicted that the C-terminal sequence of the IRX4 homeodomain could act as a potential cell-penetrating peptide, emphasizing the role these small peptides could play in targeting homeobox TFs.

Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes.

OBJECTIVE: There is increasing use of open-source artificial pancreas systems (APS) in the management of Type 1 diabetes. Our aim was to assess the safety and efficacy of the automated insulin delivery system AndroidAPS (AAPS), compared with stand-alone pump therapy in people with type 1 diabetes. The primary outcome was the difference in the percentage of time in range (TIR, 70-180 mg/dL). Secondary aims included mean sensor glucose value and percent continuous glucose monitor (CGM) time below range (TBR, <70 mg/dL). RESEARCH DESIGN AND METHODS: This open-label single-center randomized crossover study (ANZCTR, Australian New Zealand clinical trial registry, ANZCTR-ACTRN12620001191987) comprised 20 participants with type 1 diabetes on established pump therapy, assigned to either stand-alone insulin pump therapy or the open-source AAPS hybrid closed-loop system for four weeks, with crossover to the alternate arm for the following four weeks. The CGM outcome parameters were measured by seven-day CGM at baseline and the final week of each four-week study arm. RESULTS: Twenty participants were recruited (60% women), aged 45.8 ± 15.9 years, with mean diabetes duration of 23.9 ± 13.2 years, baseline glycated hemoglobin (HbA1c) 7.5% ± 0.5% (58 ± 6 mmol/mol) and mean TIR 62.3% ± 12.9%. The change in TIR from baseline for AAPS compared with stand-alone pump therapy was 18.6% (11.4-25.9), (P < .001), TIR 76.6% ± 11.7%, 58.0% ± 15.6%, for AAPS and stand-alone pump, respectively. Time glucose <54 mg/dL was not increased (mean = -2.0%, P = .191). No serious adverse events or episodes of severe hypoglycemia were recorded. CONCLUSIONS: This clinical trial of the open-source AAPS hybrid closed-loop system performed in an at-home setting demonstrated comparable safety to stand-alone pump therapy. The glycemic outcomes of AAPS were superior with improved TIR, and there was no significant difference in TBR compared with stand-alone pump therapy.

Integrative competing endogenous RNA network analyses identify novel lncRNA and genes implicated in metastatic breast cancer.

Competing endogenous RNAs (ceRNAs) have gained attention in cancer research owing to their involvement in microRNA-mediated gene regulation. Previous studies have identified ceRNA networks of individual cancers. Nevertheless, none of these studies has investigated different cancer stages. We identify stage-specific ceRNAs in breast cancer using the cancer genome atlas data. Moreover, we investigate the molecular functions and prognostic ability of ceRNAs involved in stage I-IV networks. We identified differentially expressed candidate ceRNAs using edgeR and limma R packages. A three-step analysis was used to identify statistically significant ceRNAs of each stage. Survival analysis and functional enrichment analysis were conducted to identify molecular functions and prognostic ability. We found five genes and one long non-coding RNA unique to the stage IV ceRNA network. These genes have been described in previous breast cancer studies. Genes acted as ceRNAs are enriched in cancer-associated pathways. Two, three, and three microRNAs from stages I, II, and III were prognostic from the Kaplan-Meier survival analysis. Our results reveal a set of unique ceRNAs in metastatic breast cancer. Further experimental work is required to evaluate their role in metastasis. Moreover, identifying stage-specific ceRNAs will improve the understanding of personalised therapeutics in breast cancer.

Dehydroepiandrosterone Sulfate and Colorectal Cancer Risk: A Mendelian Randomization Analysis.

Colorectal cancer is the third most common and second most deadly type of cancer worldwide, with approximately 1.9 million cases and 0.9 million deaths worldwide in 2020. Previous studies have shown that estrogen and testosterone hormones are associated with colorectal cancer risk and mortality. However, the potential effect of their precursor, dehydroepiandrosterone sulfate (DHEAS), on colorectal cancer risk has not been investigated. Therefore, evaluating DHEAS's effect on colorectal cancer will expand our understanding of the hormonal contribution to colorectal cancer risk. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal effect of DHEAS on colorectal cancer. We obtained DHEAS and colorectal cancer genomewide association study (GWAS) summary statistics from the Leipzig Health Atlas and the GWAS catalog and conducted MR analyses using the TwoSampleMR R package. Our results suggest that higher DHEAS levels are causally associated with decreased colorectal cancer risk (odds ratio per unit increase in DHEAS levels z score = 0.70; 95% confidence interval [0.51, 0.96]), which is in line with previous observations in a case-control study of colon cancer. The outcome of this study will be beneficial in developing plasma DHEAS-based biomarkers in colorectal cancer. Further studies should be conducted to interpret the DHEAS-colorectal cancer association among different ancestries and populations.

A supervised machine learning approach identifies gene-regulating factor-mediated competing endogenous RNA networks in hormone-dependent cancers.

Competing endogenous RNAs (ceRNAs) have become an emerging topic in cancer research due to their role in gene regulatory networks. To date, traditional ceRNA bioinformatic studies have investigated microRNAs as the only factor regulating gene expression. Growing evidence suggests that genomic (e.g., copy number alteration [CNA]), transcriptomic (e.g., transcription factors [TFs]), and epigenomic (e.g., DNA methylation [DM]) factors can influence ceRNA regulatory networks. Herein, we used the Least absolute shrinkage and selection operator regression, a machine learning approach, to integrate DM, CNA, and TFs data with RNA expression to infer ceRNA networks in cancer risk. The gene-regulating factors-mediated ceRNA networks were identified in four hormone-dependent (HD) cancer types: prostate, breast, colorectal, and endometrial. The shared ceRNAs across HD cancer types were further investigated using survival analysis, functional enrichment analysis, and protein-protein interaction network analysis. We found two (BUB1 and EXO1) and one (RRM2) survival-significant ceRNA(s) shared across breast-colorectal-endometrial and prostate-colorectal-endometrial combinations, respectively. Both BUB1 and BUB1B genes were identified as shared ceRNAs across more than two HD cancers of interest. These genes play a critical role in cell division, spindle-assembly checkpoint signalling, and correct chromosome alignment. Furthermore, shared ceRNAs across multiple HD cancers have been involved in essential cancer pathways such as cell cycle, p53 signalling, and chromosome segregation. Identifying ceRNAs' roles across multiple related cancers will improve our understanding of their shared disease biology. Moreover, it contributes to the knowledge of RNA-mediated cancer pathogenesis.

Identifying Complex lncRNA/Pseudogene-miRNA-mRNA Crosstalk in Hormone-Dependent Cancers.

The discovery of microRNAs (miRNAs) has fundamentally transformed our understanding of gene regulation. The competing endogenous RNA (ceRNA) hypothesis postulates that messenger RNAs and other RNA transcripts, such as long non-coding RNAs and pseudogenes, can act as natural miRNA sponges. These RNAs influence each other's expression levels by competing for the same pool of miRNAs through miRNA response elements on their target transcripts, thereby modulating gene expression and protein activity. In recent years, these ceRNA regulatory networks have gained considerable attention in cancer research. Several studies have identified cancer-specific ceRNA networks. Nevertheless, prior bioinformatic analyses have focused on long-non-coding RNA-associated ceRNA networks. Here, we identify an extended ceRNA network (including both long non-coding RNAs and pseudogenes) shared across a group of five hormone-dependent (HD) cancers, i.e., prostate, breast, colon, rectal, and endometrial cancers, using data from The Cancer Genome Atlas (TCGA). We performed a functional enrichment analysis for differentially expressed genes in the shared ceRNA network of HD cancers, followed by a survival analysis to determine their prognostic ability. We identified two long non-coding RNAs, nine genes, and seventy-four miRNAs in the shared ceRNA network across five HD cancers. Among them, two genes and forty-one miRNAs were associated with at least one HD cancer survival. This study is the first to investigate pseudogene-associated ceRNAs across a group of related cancers and highlights the value of this approach to understanding the shared molecular pathogenesis in a group of related diseases.

Integrative Transcriptome-Wide Analyses Uncover Novel Risk-Associated MicroRNAs in Hormone-Dependent Cancers.

BACKGROUND: Hormone-dependent cancers (HDC) are among the leading causes of death worldwide among both men and women. Some of the established risk factors of HDC include unhealthy lifestyles, environmental factors, and genetic influences. Numerous studies have been conducted to understand gene-cancer associations. Transcriptome-wide association studies (TWAS) integrate data from genome-wide association studies (GWAS) and gene expression (expression quantitative trait loci - eQTL) to yield meaningful information on biological pathways associated with complex traits/diseases. Recently, TWAS have enabled the identification of novel associations between HDC risk and protein-coding genes. METHODS: In the present study, we performed a TWAS analysis using the summary data-based Mendelian randomization (SMR)-heterogeneity in dependent instruments (HEIDI) method to identify microRNAs (miRNAs), a group of non-coding RNAs (ncRNAs) associated with HDC risk. We obtained eQTL and GWAS summary statistics from the ncRNA-eQTL database and the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog. RESULTS: We identified 13 TWAS-significant miRNAs at cis regions (±1 Mb) associated with HDC risk (two, five, one, two, and three miRNAs for prostate, breast, ovarian, colorectal, and endometrial cancers, respectively). Among them, eight novel miRNAs were recognized in HDC risk. Eight protein-coding genes targeted by TWAS-identified miRNAs (SIRT1, SOX4, RUNX2, FOXA1, ABL2, SUB1, HNRNPH1, and WAC) are associated with HDC functions and signaling pathways. CONCLUSION: Overall, identifying risk-associated miRNAs across a group of related cancers may help to understand cancer biology and provide novel insights into cancer genetic mechanisms. This customized approach can be applied to identify significant miRNAs in any trait/disease of interest.