Biology subjects

Lusk, J.

Publications and source records attributed to Lusk, J..

4 recordsLinked to original sources

bioRxiv2024

The R-loop Grammar predicts R-loop formation under different topological constraints

R-loops are transient three-stranded nucleic acids that form during transcription when the nascent RNA hybridizes with the template DNA, freeing the DNA non-template strand. There is growing evidence that R-loops play important roles in physiological processes such as control of gene expression, and that they contribute to chromosomal instability and disease. It is known that R-loop formation is influenced by both the sequence and the topology of the DNA substrate, but many questions remain about how R-loops form and the 3-dimensional structures that they adopt. Here we represent an R-loop as a word in a formal grammar called the R-loop grammar and predict R-loop formation. We train the R-loop grammar on experimental data obtained by single-molecule R-loop footprinting and sequencing (SMRF-seq). Despite not containing explicit topological information, the R-loop grammar accurately predicts R-loop formation on plasmids with varying starting topologies and outperforms previous methods in R-loop prediction. Author summaryR-loops are prevalent triple helices that play regulatory roles in gene expression and are involved in various diseases. Our work improves the understanding of the relationship between the nucleotide sequence and DNA topology in R-loop formation. We use a mathematical approach from formal language theory to define an R-loop language and a set of rules to model R-loops as words in that language. We train the resulting R-loop grammar on experimental data of co-transcriptional R-loops formed on different DNA plasmids of varying topology. The model accurately predicts R-loop formation and outperforms prior methods. The R-loop grammar distills the effect of topology versus sequence, thus advancing our understanding of R-loop structure and formation.

genomics↗

bioRxiv2024

Alanine-scanning mutagenesis library of MreB reveals distinct roles for regulating cell shape and viability

The bacterial actin-homolog MreB is a crucial component of the rod-system (elongasome) that maintains rod shape in many bacteria. It is localized beneath the inner membrane where it organizes the elongasome complex. Depletion or deletion of mreB results in loss of rod shape and cell death; however, the mechanism of how MreB operates is not known, given that the protein cannot be purified in a functionally intact form. Past studies have reported mutations in mreB cause varying degrees of cell shape and size alterations based on the type and position of the substitution. To better understand the role of MreB in rod shape formation we have taken the first truly systematic approach by replacing the native copy of mreB with an alanine-scanning mutagenesis library. Surprisingly, we observed stably growing spherical mutants that have lost MreBs function(s) for shape regulation without losing viability. Hence, MreB has vital functions related to growth in addition to shape maintenance that can be separated. In support of this, rod shape suppressor analysis of these spherical mutants only revealed reversions or intragenic mreB mutations, suggesting that MreB is indispensable for rod shape. Additionally, our results imply the elongasome is no longer active in these strains, suggesting a novel way for rod shaped bacteria to synthesize cell wall.

microbiology↗

bioRxiv2023

Analyzing the link between RNA secondary structures and R-loop formation with tree polynomials

R-loops are a class of non-canonical nucleic acid structures that typically form during transcription when the nascent RNA hybridizes the DNA template strand, leaving the DNA coding strand unpaired. Co-transcriptional R-loops are abundant in nature and biologically relevant. Recent research shows that DNA sequence and topology affect R-loops, yet it remains unclear how these and other factors drive R-loop formation. In this work, we investigate a link between the secondary structure of the nascent RNA and the probability of R-loop formation. We introduce tree-polynomial representations, a class of mathematical objects that enable accurate and efficient data analysis of RNA secondary structures. With tree-polynomials, we establish a strong correlation between the secondary structure of the RNA transcript and the probability of R-loop formation. We identify that branches with short stems separated by multiple bubbles in the RNA secondary structure are associated with the strong correlation and are predictive of R-loop formation.

molecular biology↗

bioRxiv2022

Computational study of the furin cleavage domain of SARS-CoV-2: delta binds strongest of extant variants

We demonstrate that AlphaFold and AlphaFold Multimer, implemented within the ColabFold suite, can accurately predict the structures of the furin enzyme with known six residue inhibitory peptides. Noting the similarity of the peptide inhibitors to polybasic furin cleavage domain insertion region of the SARS-CoV-2, which begins at P681, we implement this approach to study the wild type furin cleavage domain for the virus and several mutants. We introduce mutations in silico for alpha, omicron, and delta variants, for several sequences which have been rarely observed, for sequences which have not yet been observed, for other coronaviruses (NL63, OC43, HUK1a, HUK1b, MERS, and 229E), and for the H5N1 flu. We show that interfacial hydrogen bonds between the furin cleavage domain and furin are a good measure of binding strength that correlate well with endpoint binding free energy estimates, and conclude that among all candidate viral sequences studied, delta is near the very top binding strength within statistical accuracy. However, the binding strength of several rare sequences match delta within statistical accuracy. We find that the furin S1 pocket is optimized for binding arginine as opposed to lysine. This residue, typically at sequence position five, contains the most hydrogen bonds to the furin, and hydrogen bond count for just this residue shows a strong positive correlation with the overall hydrogen bond count. We demonstrate that the root mean square backbone C-alpha fluctuation of the first residue in the furin cleavage domain has a strong negative correlation with the interfacial hydrogen bond count. We show by considering the variation with the number of basic residues that the maximum mean number of interfacial hydrogen bonds expected is 15.7 at 4 basic residues.

biophysics↗