ALVIS: interactive non-aggregative visualization and explorative analysis of multiple sequence alignments

ggmsa: a visual exploration tool for multiple sequence alignment and associated data

The identification of the conserved and variable regions in the multiple sequence alignment (MSA) is critical to accelerating the process of understanding the function of genes. MSA visualizations allow us to transform sequence features into understandable visual representations. As the sequence-structure-function relationship gains increasing attention in molecular biology studies, the simple display of nucleotide or protein sequence alignment is not satisfied. A more scalable visualization is required to broaden the scope of sequence investigation. Here we present ggmsa, an R package for mining comprehensive sequence features and integrating the associated data of MSA by a variety of display methods. To uncover sequence conservation patterns, variations and recombination at the site level, sequence bundles, sequence logos, stacked sequence alignment and comparative plots are implemented. ggmsa supports integrating the correlation of MSA sequences and their phenotypes, as well as other traits such as ancestral sequences, molecular structures, molecular functions and expression levels. We also design a new visualization method for genome alignments in multiple alignment format to explore the pattern of within and between species variation. Combining these visual representations with prime knowledge, ggmsa assists researchers in discovering MSA and making decisions. The ggmsa package is open-source software released under the Artistic-2.0 license, and it is freely available on Bioconductor (https://bioconductor.org/packages/ggmsa) and Github (https://github.com/YuLab-SMU/ggmsa).

Theta-Defensins to Counter COVID-19 as Furin Inhibitors: In Silico Efficiency Prediction and Novel Compound Design

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was characterized as a pandemic by the World Health Organization (WHO) in Dec. 2019. SARS-CoV-2 binds to the cell membrane through spike proteins on its surface and infects the cell. Furin, a host-cell enzyme, possesses a binding site for the spike protein. Thus, molecules that block furin could potentially be a therapeutic solution. Defensins are antimicrobial peptides that can hypothetically inhibit furin because of their arginine-rich structure. Theta-defensins, a subclass of defensins, have attracted attention as drug candidates due to their small size, unique structure, and involvement in several defense mechanisms. Theta-defensins could be a potential treatment for COVID-19 through furin inhibition and an anti-inflammatory mechanism. Note that inflammatory events are a significant and deadly condition that could happen at the later stages of COVID-19 infection. Here, the potential of theta-defensins against SARS-CoV-2 infection was investigated through in silico approaches. Based on docking analysis results, theta-defensins can function as furin inhibitors. Additionally, a novel candidate peptide against COVID-19 with optimal properties regarding antigenicity, stability, electrostatic potential, and binding strength was proposed. Further in vitro/in vivo investigations could verify the efficiency of the designed novel peptide.

Hotspots for mutations in the SARS-CoV-2 spike glycoprotein: a correspondence analysis

Spike glycoprotein (Sgp) is liable for binding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the host receptors. Since Sgp is the main target for vaccine and drug designing, elucidating its mutation pattern could help in this regard. This study is aimed at investigating the correspondence of specific residues to the SgpSARS-CoV-2 functionality by explorative interpretation of sequence alignments. Centrality analysis of the Sgp dissects the importance of these residues in the interaction network of the RBD-ACE2 (receptor-binding domain) complex and furin cleavage site. Correspondence of RBD to threonine500 and asparagine501 and furin cleavage site to glutamine675, glutamine677, threonine678, and alanine684 was observed; all residues are exactly located at the interaction interfaces. The harmonious location of residues dictates the RBD binding property and the flexibility, hydrophobicity, and accessibility of the furin cleavage site. These species-specific residues can be assumed as real targets of evolution, while other substitutions tend to support them. Moreover, all these residues are parts of experimentally identified epitopes. Therefore, their substitution may affect vaccine efficacy. Higher rate of RBD maintenance than furin cleavage site was predicted. The accumulation of substitutions reinforces the probability of the multi-host circulation of the virus and emphasizes the enduring evolutionary events.

Plant expression of NifD protein variants resistant to mitochondrial degradation

Engineering nitrogenase in plants may help alleviate economic and environmental issues due to the use of nitrogen fertilizer. Mitochondria have shown promise in supporting the function of nitrogenase, including electron donation and metallocluster assembly. Despite these successes, formation of the catalytic unit, NifDK, has proven difficult. Here, we find that when relocated to plant mitochondria, NifD is subject to errant peptidase-based cleavage and is insoluble. Guided by NifD sequence variation amongst bacteria and structural modeling, we designed NifD variants that avoided cleavage and retained function in bacterial assays. Fusion of NifK to degradation-resistant NifD also improved solubility, and the polyprotein retained function in bacterial assays. This work advances efforts to produce crops less reliant on nitrogen fertilizer.

To engineer Mo-dependent nitrogenase function in plants, expression of the structural proteins NifD and NifK will be an absolute requirement. Although mitochondria have been established as a suitable eukaryotic environment for biosynthesis of oxygen-sensitive enzymes such as NifH, expression of NifD in this organelle has proven difficult due to cryptic NifD degradation. Here, we describe a solution to this problem. Using molecular and proteomic methods, we found NifD degradation to be a consequence of mitochondrial endoprotease activity at a specific motif within NifD. Focusing on this functionally sensitive region, we designed NifD variants comprising between one and three amino acid substitutions and distinguished several that were resistant to degradation when expressed in both plant and yeast mitochondria. Nitrogenase activity assays of these resistant variants in Escherichia coli identified a subset that retained function, including a single amino acid variant (Y100Q). We found that other naturally occurring NifD proteins containing alternate amino acids at the Y100 position were also less susceptible to degradation. The Y100Q variant also enabled expression of a NifD(Y100Q)–linker–NifK translational polyprotein in plant mitochondria, confirmed by identification of the polyprotein in the soluble fraction of plant extracts. The NifD(Y100Q)–linker–NifK retained function in bacterial nitrogenase assays, demonstrating that this polyprotein permits expression of NifD and NifK in a defined stoichiometry supportive of activity. Our results exemplify how protein design can overcome impediments encountered when expressing synthetic proteins in novel environments. Specifically, these findings outline our progress toward the assembly of the catalytic unit of nitrogenase within mitochondria.

Tasks, Techniques, and Tools for Genomic Data Visualization

Genomic data visualization is essential for interpretation and hypothesis generation as well as a valuable aid in communicating discoveries. Visual tools bridge the gap between algorithmic approaches and the cognitive skills of investigators. Addressing this need has become crucial in genomics, as biomedical research is increasingly data-driven and many studies lack well-defined hypotheses. A key challenge in data-driven research is to discover unexpected patterns and to formulate hypotheses in an unbiased manner in vast amounts of genomic and other associated data. Over the past two decades, this has driven the development of numerous data visualization techniques and tools for visualizing genomic data. Based on a comprehensive literature survey, we propose taxonomies for data, visualization, and tasks involved in genomic data visualization. Furthermore, we provide a comprehensive review of published genomic visualization tools in the context of the proposed taxonomies.

Handling FMRP and its molecular partners: Structural insights into Fragile X Syndrome

Fragile X Mental Retardation Protein (FMRP) is a RNA-binding protein (RBP) known to control different steps of mRNA metabolism, even though its complete function is not fully understood yet. Lack or mutations of FMRP lead to Fragile X Syndrome (FXS), the most common form of inherited intellectual disability and a leading monogenic cause of autism spectrum disorder (ASD). It is well established that FMRP has a multi-domain architecture, a feature that allows this RBP to be engaged in a large interaction network with numerous proteins and mRNAs or non-coding RNAs. Insights into the three-dimensional (3D) structure of parts of its three domains (N-terminus, central domain and C-terminus) were obtained using Nuclear Magnetic Resonance and X-ray diffraction, but the complete 3D arrangement of each domain with respect to the others is still missing. Here, we review the structural features of FMRP and of the network of its protein and RNA interactions. Understanding these aspects is the first necessary step towards the design of novel compounds for new therapeutic interventions in FXS.