The Molecular Landscape of Medulloblastoma in Teenagers and Young Adults

Medulloblastoma (MB) is a childhood malignant brain tumour but also occurs in teenagers and young adults (TYA). Considering that MB is heterogeneous, this study aimed to define the molecular landscape of MBs in TYAs. We collated more than 2000 MB samples that included 287 TYA patients (13–24 years). We performed computational analyses consisting of genome-wide methylation and transcriptomic profiles and developed a prognostics model for the TYAs with MB. We identified that TYAs predominantly comprised of Group 4 (40%) and Sonic Hedgehog (SHH)-activated (33%) tumours, with Wingless-type (WNT, 17%) and Group 3 (10%) being less common. TYAs with SHH tumours displayed significantly more gene expression alterations, whereas no gene was detected in the Group 4 tumours. Across MB subgroups, we identified unique and shared sets of TYA-specific differentially methylated probes and DNA-binding motifs. Finally, a 22-gene signature stratified TYA patients into high- and low-risk groups, and the prognostic significance of these risk groups persisted in multivariable regression models (P = 0.001). This study is an important step toward delineating the molecular landscape of TYAs with MB. The emergence of novel genes and pathways may provide a basis for improved clinical management of TYA with MB.

Computational analyses of mechanism of action (MoA): data, methods and integration

This review summarises different data, data resources and methods for computational mechanism of action (MoA) analysis, and highlights some case studies where integration of data types and methods enabled MoA elucidation on the systems-level.

Substrate Specificity for Human Histidine Methyltransferase SETD3

Histidine methyltransferase SETD3 plays an important role in human biology and diseases. Previously, we showed that SETD3 catalyzes N3-methylation of histidine 73 in β-actin (Kwiatkowski et al., 2018). Here we report integrated synthetic, biocatalytic, biostructural and computational analyses on human SETD3-catalyzed methylation of β-actin peptides possessing histidine and its structurally and chemically diverse mimics. Our enzyme assays supported by biostructural analyses demonstrate that SETD3 has a broader substrate scope beyond histidine, including N-nucleophiles on the aromatic and aliphatic side chains. Quantum mechanical/molecular mechanical (QM/MM) molecular dynamics and free-energy simulations provide insight into binding geometries and the free energy barrier for the enzymatic methyl transfer to histidine mimics, further supporting experimental data that histidine is the superior SETD3 substrate over its analogs. This work demonstrates that human SETD3 has a potential to catalyze efficient methylation of several histidine mimics, overall providing mechanistic, biocatalytic and functional insight into β-actin histidine methylation by SETD3.

Structural insights into the ion selectivity of the MgtE channel for Mg2+ over Ca2+

MgtE is a Mg2+-selective ion channel whose orthologs are widely distributed from prokaryotes to eukaryotes, including humans, and play an important role in the maintenance of cellular Mg2+ homeostasis. Previous functional analyses showed that MgtE transports divalent cations with high selectivity for Mg2+ over Ca2+. Whereas the high-resolution structure determination of the MgtE transmembrane (TM) domain in complex with Mg2+ ions revealed a Mg2+ recognition mechanism of MgtE, the previous Ca2+-bound structure of the MgtE TM domain was determined only at moderate resolution (3.2 angstrom resolution), which was insufficient to visualize the water molecules coordinated to Ca2+ ions. Thus, the structural basis of the ion selectivity of MgtE for Mg2+ over Ca2+ has remained unclear. Here, we showed that the metal-binding site of the MgtE TM domain binds to Mg2+ ~500-fold more strongly than Ca2+. We then determined the crystal structure of the MgtE TM domain in complex with Ca2+ ions at a higher resolution (2.5 angstrom resolution), allowing us to reveal hexahydrated Ca2+, which is similarly observed in the previously determined Mg2+-bound structure but with extended metal-oxygen bond lengths. Our structural, biochemical, and computational analyses provide mechanistic insights into the ion selectivity of MgtE for Mg2+ over Ca2+.

Advancing genomic technologies and clinical awareness accelerates discovery of disease-associated tandem repeat sequences

Expansions of gene-specific DNA tandem repeats (TRs), first described in 1991 as a disease-causing mutation in humans, are now known to cause >60 phenotypes, not just disease, and not only in humans. TRs are a common form of genetic variation with biological consequences, observed, so far, in humans, dogs, plants, oysters, and yeast. Repeat diseases show atypical clinical features, genetic anticipation, and multiple and partially penetrant phenotypes among family members. Discovery of disease-causing repeat expansion loci accelerated through technological advances in DNA sequencing and computational analyses. Between 2019 and 2021, 17 new disease-causing TR expansions were reported, totaling 63 TR loci (>69 diseases), with a likelihood of more discoveries, and in more organisms. Recent and historical lessons reveal that properly assessed clinical presentations, coupled with genetic and biological awareness, can guide discovery of disease-causing unstable TRs. We highlight critical but underrecognized aspects of TR mutations. Repeat motifs may not be present in current reference genomes but will be in forthcoming gapless long-read references. Repeat motif size can be a single nucleotide to kilobases/unit. At a given locus, repeat motif sequence purity can vary with consequence. Pathogenic repeats can be “insertions” within nonpathogenic TRs. Expansions, contractions, and somatic length variations of TRs can have clinical/biological consequences. TR instabilities occur in humans and other organisms. TRs can be epigenetically modified and/or chromosomal fragile sites. We discuss the expanding field of disease-associated TR instabilities, highlighting prospects, clinical and genetic clues, tools, and challenges for further discoveries of disease-causing TR instabilities and understanding their biological and pathological impacts—a vista that is about to expand.

Green by Design: Convergent Synthesis, Computational Analyses, and Activity Evaluation of New FXa Inhibitors Bearing Peptide Triazole Linking Units

Green chemistry implementation has led to promising results in waste reduction in the pharmaceutical industry. However, the early sustainable development of pharmaceutically active compounds and ingredients remains a considerable challenge. Herein, we wish to report a green synthesis of new pharmaceutically active peptide triazoles as potent factor Xa inhibitors, an important drug target associated with the treatment of diverse cardiovascular diseases. The new inhibitors were synthesized in three steps, featuring cycloaddition reactions (high atom economy), microwave-assisted organic synthesis (energy efficiency), and copper nanoparticle catalysis, thus featuring Earth-abundant metals. The molecules obtained showed FXa inhibition, with IC50-values as low as 17.2 μM and no associated cytotoxicity in HEK293 and HeLa cells. These results showcase the environmental potential and chemical implications of the applied methodologies for the development of new molecules with pharmacological potential.

Ancient Metagenomic Studies: Considerations for the Wider Scientific Community

Like modern metagenomics, ancient metagenomics is a highly data-rich discipline, with the added challenge that the DNA of interest is degraded and, depending on the sample type, in low abundance. This requires the application of specialized measures during molecular experiments and computational analyses.

nf-rnaSeqCount: A Nextflow pipeline for obtaining raw read counts from RNA-seq data

The rate of raw sequence production through Next-Generation Sequencing (NGS) has been growing exponentially due to improved technology and reduced costs. This has enabled researchers to answer many biological questions through ``multi-omics'' data analyses. Even though such data promises new insights into how biological systems function and understanding disease mechanisms, computational analyses performed on such large datasets comes with its challenges and potential pitfalls. The aim of this study was to develop a robust portable and reproducible bioinformatic pipeline for the automation of RNA sequencing (RNA-seq) data analyses. Using Nextflow as a workflow management system and Singularity for application containerisation, the nf-rnaSeqCount pipeline was developed for mapping raw RNA-seq reads to a reference genome and quantifying abundance of identified genomic features for differential gene expression analyses. The pipeline provides a quick and efficient way to obtain a matrix of read counts that can be used black with tools such as DESeq2 and edgeR for differential expression analysis. Robust and flexible bioinformatic and computational pipelines for RNA-seq data analysis, from QC to sequence alignment and comparative analyses, will reduce analysis time, and increase accuracy and reproducibility of findings to promote transcriptome research.