In silico investigation of the impact of synonymous variants in ABCB4 gene on mRNA stability/structure, splicing accuracy and codon usage: Potential contribution to PFIC3 disease

Abstract Synonymous single nucleotide variants (sSNVs) have been implicated in various genetic disorders through alterations of pre-mRNA splicing, mRNA structure and miRNA regulation. However, their impact on synonymous codon usage and protein translation remains to be elucidated in clinical context. Here, we explore the functional impact of sSNVs in the Sonic Hedgehog (SHH) gene, identified in patients affected by holoprosencephaly, a congenital brain defect resulting from incomplete forebrain cleavage. We identified eight sSNVs in SHH, selectively enriched in holoprosencephaly patients as compared to healthy individuals, and systematically assessed their effect at both transcriptional and translational levels using a series of in silico and in vitro approaches. Although no evidence of impact of these sSNVs on splicing, mRNA structure or miRNA regulation was found, five sSNVs introduced significant changes in codon usage and were predicted to impact protein translation. Cell assays demonstrated that these five sSNVs are associated with a significantly reduced amount of the resulting protein, ranging from 5% to 23%. Inhibition of the proteasome rescued the protein levels for four out of five sSNVs, confirming their impact on protein stability and folding. Remarkably, we found a significant correlation between experimental values of protein reduction and computational measures of codon usage, indicating the relevance of in silico models in predicting the impact of sSNVs on translation. Considering the critical role of SHH in brain development, our findings highlight the clinical relevance of sSNVs in holoprosencephaly and underline the importance of investigating their impact on translation in human pathologies.

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Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

Journal of Diabetes Science and Technology ◽

10.1177/19322968211012392 ◽

2021 ◽

pp. 193229682110123

Author(s):

Chiara Roversi ◽

Martina Vettoretti ◽

Simone Del Favero ◽

Andrea Facchinetti ◽

Pratik Choudhary ◽

...

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

In Silico ◽

Open Loop ◽

Random Errors ◽

Linear Regression Models ◽

Reference Case ◽

Counting Error ◽

The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

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Detailed Dissection and Critical Evaluation of the Pfizer/BioNTech and Moderna mRNA Vaccines

Vaccines ◽

10.3390/vaccines9070734 ◽

2021 ◽

Vol 9 (7) ◽

pp. 734

Author(s):

Xuhua Xia

Keyword(s):

Codon Usage ◽

Translation Initiation ◽

Mrna Stability ◽

Stop Codon ◽

Translation Termination ◽

Critical Evaluation ◽

Immunization Programs ◽

Translation Elongation ◽

Different Types ◽

Similarities And Differences

The design of Pfizer/BioNTech and Moderna mRNA vaccines involves many different types of optimizations. Proper optimization of vaccine mRNA can reduce dosage required for each injection leading to more efficient immunization programs. The mRNA components of the vaccine need to have a 5’-UTR to load ribosomes efficiently onto the mRNA for translation initiation, optimized codon usage for efficient translation elongation, and optimal stop codon for efficient translation termination. Both 5’-UTR and the downstream 3’-UTR should be optimized for mRNA stability. The replacement of uridine by N1-methylpseudourinine () complicates some of these optimization processes because is more versatile in wobbling than U. Different optimizations can conflict with each other, and compromises would need to be made. I highlight the similarities and differences between Pfizer/BioNTech and Moderna mRNA vaccines and discuss the advantage and disadvantage of each to facilitate future vaccine improvement. In particular, I point out a few optimizations in the design of the two mRNA vaccines that have not been performed properly.

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Insight into the impact of EGFR L792Y/F/H mutations on sensitivity to osimertinib: an in silico study

New Journal of Chemistry ◽

10.1039/d0nj05570k ◽

2021 ◽

Vol 45 (10) ◽

pp. 4756-4765

Author(s):

Daoxing Chen ◽

Liting Zhang ◽

Yanan Liu ◽

Jiali Song ◽

Jingwen Guo ◽

...

Keyword(s):

In Silico ◽

In Silico Study ◽

The Impact ◽

Insight Into

EGFR L792Y/F/H mutation makes it difficult for Osimertinib to recognize ATP pockets.

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Codon harmonization reduces amino acid misincorporation in bacterially expressed P. falciparum proteins and improves their immunogenicity

AMB Express ◽

10.1186/s13568-019-0890-6 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Neeraja Punde ◽

Jennifer Kooken ◽

Dagmar Leary ◽

Patricia M. Legler ◽

Evelina Angov

Keyword(s):

Protein Structure ◽

Amino Acid ◽

Codon Usage ◽

Dna Sequences ◽

Structural Integrity ◽

Host Cells ◽

Loss Of Function ◽

Species Specific ◽

And Function ◽

The Impact

Abstract Codon usage frequency influences protein structure and function. The frequency with which codons are used potentially impacts primary, secondary and tertiary protein structure. Poor expression, loss of function, insolubility, or truncation can result from species-specific differences in codon usage. “Codon harmonization” more closely aligns native codon usage frequencies with those of the expression host particularly within putative inter-domain segments where slower rates of translation may play a role in protein folding. Heterologous expression of Plasmodium falciparum genes in Escherichia coli has been a challenge due to their AT-rich codon bias and the highly repetitive DNA sequences. Here, codon harmonization was applied to the malarial antigen, CelTOS (Cell-traversal protein for ookinetes and sporozoites). CelTOS is a highly conserved P. falciparum protein involved in cellular traversal through mosquito and vertebrate host cells. It reversibly refolds after thermal denaturation making it a desirable malarial vaccine candidate. Protein expressed in E. coli from a codon harmonized sequence of P. falciparum CelTOS (CH-PfCelTOS) was compared with protein expressed from the native codon sequence (N-PfCelTOS) to assess the impact of codon usage on protein expression levels, solubility, yield, stability, structural integrity, recognition with CelTOS-specific mAbs and immunogenicity in mice. While the translated proteins were expected to be identical, the translated products produced from the codon-harmonized sequence differed in helical content and showed a smaller distribution of polypeptides in mass spectra indicating lower heterogeneity of the codon harmonized version and fewer amino acid misincorporations. Substitutions of hydrophobic-to-hydrophobic amino acid were observed more commonly than any other. CH-PfCelTOS induced significantly higher antibody levels compared with N-PfCelTOS; however, no significant differences in either IFN-γ or IL-4 cellular responses were detected between the two antigens.

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Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants

Journal of Personalized Medicine ◽

10.3390/jpm11020131 ◽

2021 ◽

Vol 11 (2) ◽

pp. 131

Author(s):

Laura B. Scheinfeldt ◽

Andrew Brangan ◽

Dara M. Kusic ◽

Sudhir Kumar ◽

Neda Gharani

Keyword(s):

In Silico ◽

Drug Efficacy ◽

Common Variant ◽

Genomic Research ◽

Whole Genome Sequencing Data ◽

Mendelian Disease ◽

Allele Frequency Distribution ◽

Sequencing Data ◽

Patient Race ◽

The Impact

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new ‘common treatment, common variant’ perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX’s in silico predictions.

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Genomic imbalances in the placenta are associated with poor fetal growth

Molecular Medicine ◽

10.1186/s10020-020-00253-4 ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

Giulia F. Del Gobbo ◽

Yue Yin ◽

Sanaa Choufani ◽

Emma A. Butcher ◽

John Wei ◽

...

Keyword(s):

Fetal Growth ◽

Sex Chromosome ◽

Copy Number Variants ◽

Placental Insufficiency ◽

Potential Contribution ◽

Genomic Imbalances ◽

Significant Difference ◽

Underlying Causes ◽

Risk Of Disease ◽

The Impact

Abstract Background Fetal growth restriction (FGR) is associated with increased risks for complications before, during, and after birth, in addition to risk of disease through to adulthood. Although placental insufficiency, failure to supply the fetus with adequate nutrients, underlies most cases of FGR, its causes are diverse and not fully understood. One of the few diagnosable causes of placental insufficiency in ongoing pregnancies is the presence of large chromosomal imbalances such as trisomy confined to the placenta; however, the impact of smaller copy number variants (CNVs) has not yet been adequately addressed. In this study, we confirm the importance of placental aneuploidy, and assess the potential contribution of CNVs to fetal growth. Methods We used molecular-cytogenetic approaches to identify aneuploidy in placentas from 101 infants born small-for-gestational age (SGA), typically used as a surrogate for FGR, and from 173 non-SGA controls from uncomplicated pregnancies. We confirmed aneuploidies and assessed mosaicism by microsatellite genotyping. We then profiled CNVs using high-resolution microarrays in a subset of 53 SGA and 61 control euploid placentas, and compared the load, impact, gene enrichment and clinical relevance of CNVs between groups. Candidate CNVs were confirmed using quantitative PCR. Results Aneuploidy was over tenfold more frequent in SGA-associated placentas compared to controls (11.9% vs. 1.1%; p = 0.0002, OR = 11.4, 95% CI 2.5–107.4), was confined to the placenta, and typically involved autosomes, whereas only sex chromosome abnormalities were observed in controls. We found no significant difference in CNV load or number of placental-expressed or imprinted genes in CNVs between SGA and controls, however, a rare and likely clinically-relevant germline CNV was identified in 5.7% of SGA cases. These CNVs involved candidate genes INHBB, HSD11B2, CTCF, and CSMD3. Conclusions We conclude that placental genomic imbalances at the cytogenetic and submicroscopic level may underlie up to ~ 18% of SGA cases in our population. This work contributes to the understanding of the underlying causes of placental insufficiency and FGR, which is important for counselling and prediction of long term outcomes for affected cases.

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Applying Harmonised Geothermal Life Cycle Assessment Guidelines to the Rittershoffen Geothermal Heat Plant

Energies ◽

10.3390/en14133820 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3820

Author(s):

Mélanie Douziech ◽

Lorenzo Tosti ◽

Nicola Ferrara ◽

Maria Laura Parisi ◽

Paula Pérez-López ◽

...

Keyword(s):

Life Cycle Assessment ◽

Life Cycle ◽

Heat Production ◽

Hot Spot ◽

Resource Depletion ◽

Potential Contribution ◽

Geothermal Systems ◽

Geothermal Heat ◽

The Future ◽

The Impact

Heat production from a geothermal energy source is gaining increasing attention due to its potential contribution to the decarbonization of the European energy sector. Obtaining representative results of the environmental performances of geothermal systems and comparing them with other renewables is of utmost importance in order to ensure an effective energy transition as targeted by Europe. This work presents the outputs of a Life Cycle Assessment (LCA) performed on the Rittershoffen geothermal heat plant applying guidelines that were developed within the H2020 GEOENVI project. The production of 1 kWhth from the Rittershoffen heat plant was compared to the heat produced from natural gas in Europe. Geothermal heat production performed better than the average heat production in climate change and resource use, fossil categories. The LCA identified the electricity consumption during the operation and maintenance phase as a hot spot for several impact categories. A prospective scenario analysis was therefore performed to assess the evolution of the environmental performances of the Rittershoffen heat plant associated with the future French electricity mixes. The increase of renewable energy shares in the future French electricity mix caused the impact on specific categories (e.g., land use and mineral and metals resource depletion) to grow over the years. However, an overall reduction of the environmental impacts of the Rittershoffen heat plant was observed.

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