Linking Gene Fusions to Bone Marrow Failure and Malignant Transformation in Dyskeratosis Congenita.

Dyskeratosis Congenita (DC) is a multisystem disorder intrinsically associated with telomere dysfunction, leading to bone marrow failure (BMF). Although the pathology of DC is largely driven by mutations in telomere-associated genes, the implications of gene fusions, which emerge due to telomere-induced genomic instability, remain unexplored. We meticulously analyzed gene fusions in RNA-Seq data from DC patients to provide deeper insights into DC's progression. The most significant DC-specific gene fusions were subsequently put through in silico assessments to ascertain biophysical and structural attributes, including charge patterning, inherent disorder, and propensity for self-association. Selected candidates were then analyzed using deep learning-powered structural predictions and molecular dynamics simulations to gauge their potential for forming higher-order oligomers. Our exploration revealed that genes participating in fusion events play crucial roles in upholding genomic stability, facilitating hematopoiesis, and suppressing tumors. Notably, our analysis spotlighted a particularly disordered polyampholyte fusion protein that exhibits robust higher-order oligomerization dynamics. To conclude, this research underscores the potential significance of several high-confidence gene fusions in the progression of BMF in DC, particularly through the dysregulation of genomic stability, hematopoiesis, and tumor suppression. Additionally, we propose that these fusion proteins might hold a detrimental role, specifically in inducing proteotoxicity-driven hematopoietic disruptions.

Protein sociology of ProA, Mip and other secreted virulence factors at the Legionella pneumophila surface.

The pathogenicity of L. pneumophila, the causative agent of Legionnaires' disease, depends on an arsenal of interacting proteins. Here we describe how surface-associated and secreted virulence factors of this pathogen interact with each other or target extra- and intracellular host proteins resulting in host cell manipulation and tissue colonization. Since progress of computational methods like AlphaFold, molecular dynamics simulation, and docking allows to predict, analyze and evaluate experimental proteomic and interactomic data, we describe how the combination of these approaches generated new insights into the multifaceted "protein sociology" of the zinc metalloprotease ProA and the peptidyl-prolyl cis/trans isomerase Mip (macrophage infectivity potentiator). Both virulence factors of L. pneumophila interact with numerous proteins including bacterial flagellin (FlaA) and host collagen, and play important roles in virulence regulation, host tissue degradation and immune evasion. The recent progress in protein-ligand analyses of virulence factors suggests that machine learning will also have a beneficial impact in early stages of drug discovery.

Legionella pneumophila PPIase Mip Interacts with the Bacterial Proteins SspB, Lpc2061, and FlaA and Promotes Flagellation.

The peptidyl-prolyl-cis/trans-isomerase (PPIase) macrophage infectivity potentiator (Mip) contributes to the pathogenicity and fitness of L. pneumophila, the causative agent of Legionnaires' disease. Here, we identified the stringent starvation protein SspB, hypothetical protein Lpc2061, and flagellin FlaA as bacterial interaction partners of Mip. The macrolide FK506, which inhibits the PPIase activity of Mip, interfered with the binding of Lpc2061. Moreover, we demonstrated that the N-terminal dimerization region and amino acid Y185 in the C-terminal PPIase domain of Mip are required for the binding of Lpc2061 and FlaA. The modeling of the interaction partners and global docking with Mip suggested nonoverlapping binding interfaces, and a molecular dynamic simulation predicted an increased stability for the tripartite interaction of Lpc2061, Mip, and FlaA. On the functional level, we demonstrated that Mip promotes L. pneumophila flagellation, which is positively influenced by the binding of Lpc2061 and reduced by FK506. Also, L. pneumophila mutants expressing the Y185A or the monomeric Mip variant, which bind less Lpc2061, were nonmotile, were less flagellated, and yielded less FlaA when quantified. To our knowledge, this is the first report in which a PPIase and its bacterial interaction partners were demonstrated to influence flagellation.

A Spatial and Functional Interaction of a Heterotetramer Survivin-DNA-PKcs Complex in DNA Damage Response.

Substantial evidence has shown that overexpression of the inhibitor of apoptosis protein (IAP) survivin in human tumors correlates significantly with treatment resistance and poor patient prognosis. Survivin serves as a radiation resistance factor that impacts the DNA damage response by interacting with DNA-dependent protein kinase (DNA-PKcs). However, the complexity, molecular determinants, and functional consequences of this interrelationship remain largely unknown. By applying coimmunoprecipitation and flow cytometry-based Förster resonance energy transfer assays, we demonstrated a direct involvement of the survivin baculovirus IAP repeat domain in the regulation of radiation survival and DNA repair. This survivin-mediated activity required an interaction of residues S20 and W67 with the phosphoinositide 3-kinase (PI3K) domain of DNA-PKcs. In silico molecular docking and dynamics simulation analyses, in vitro kinase assays, and large-scale mass spectrometry suggested a heterotetrameric survivin-DNA-PKcs complex that results in a conformational change within the DNA-PKcs PI3K domain. Overexpression of survivin resulted in enhanced PI3K enzymatic activity and detection of differentially abundant phosphopeptides and proteins implicated in the DNA damage response. The survivin-DNA-PKcs interaction altered the S/T-hydrophobic motif substrate specificity of DNA-PKcs with a predominant usage of S/T-P phosphorylation sites and an increase of DNA-PKcs substrates including Foxo3. These data demonstrate that survivin differentially regulates DNA-PKcs-dependent radiation survival and DNA double-strand break repair via formation of a survivin-DNA-PKcs heterotetrameric complex. SIGNIFICANCE: These findings provide insight into survivin-mediated regulation of DNA-PKcs kinase and broaden our knowledge of the impact of survivin in modulating the cellular radiation response.See related commentary by Iliakis, p. 2270 GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/9/2304/F1.large.jpg.

Loop-Mediated Isothermal Amplification Detection of SARS-CoV-2 and Myriad Other Applications.

As the second year of the COVID-19 pandemic begins, it remains clear that a massive increase in the ability to test for SARS-CoV-2 infections in a myriad of settings is critical to controlling the pandemic and to preparing for future outbreaks. The current gold standard for molecular diagnostics is the polymerase chain reaction (PCR), but the extraordinary and unmet demand for testing in a variety of environments means that both complementary and supplementary testing solutions are still needed. This review highlights the role that loop-mediated isothermal amplification (LAMP) has had in filling this global testing need, providing a faster and easier means of testing, and what it can do for future applications, pathogens, and the preparation for future outbreaks. This review describes the current state of the art for research of LAMP-based SARS-CoV-2 testing, as well as its implications for other pathogens and testing. The authors represent the global LAMP (gLAMP) Consortium, an international research collective, which has regularly met to share their experiences on LAMP deployment and best practices; sections are devoted to all aspects of LAMP testing, including preanalytic sample processing, target amplification, and amplicon detection, then the hardware and software required for deployment are discussed, and finally, a summary of the current regulatory landscape is provided. Included as well are a series of first-person accounts of LAMP method development and deployment. The final discussion section provides the reader with a distillation of the most validated testing methods and their paths to implementation. This review also aims to provide practical information and insight for a range of audiences: for a research audience, to help accelerate research through sharing of best practices; for an implementation audience, to help get testing up and running quickly; and for a public health, clinical, and policy audience, to help convey the breadth of the effect that LAMP methods have to offer.

Substitution matrix based color schemes for sequence alignment visualization.

BACKGROUND: Visualization of multiple sequence alignments often includes colored symbols, usually characters encoding amino acids, according to some (physical) properties, such as hydrophobicity or charge. Typically, color schemes are created manually, so that equal or similar colors are assigned to amino acids that share similar properties. However, this assessment is subjective and may not represent the similarity of symbols very well. RESULTS: In this article we propose a different approach for color scheme creation: We leverage the similarity information of a substitution matrix to derive an appropriate color scheme. Similar colors are assigned to high scoring pairs of symbols, distant colors are assigned to low scoring pairs. In order to find these optimal points in color space a simulated annealing algorithm is employed. CONCLUSIONS: Using the substitution matrix as basis for a color scheme is consistent with the alignment, which itself is based on the very substitution matrix. This approach allows fully automatic generation of new color schemes, even for special purposes which have not been covered, yet, including schemes for structural alphabets or schemes that are adapted for people with color vision deficiency.

StreaMD: Advanced analysis of molecular dynamics using R.

Gromacs is one of the most popular molecular simulation suites currently available. In this contribution we present streaMD, the first interface between Gromacs trajectory files and the statistical language R. The amount of data created due to ever increasing computational power renders fast and efficient analysis of trajectories into a challenge. Especially as standard approaches such as root-mean square fluctuations and the like provide only limited physical insight. In our streaMD package integration of the Gromacs I/O libraries with advanced, graph-based analysis methods as the java library Stream leads to both: improved speed and analysis depth. We benchmark our results and highlight the applicability of the package by an interesting problem in RNA design, namely the interaction of tetracycline with an aptamer. © 2018 Wiley Periodicals, Inc.