Biology subjects

Mathews, D.

Publications and source records attributed to Mathews, D..

17 recordsLinked to original sources

bioRxiv2026

Finding dugongs through environmental DNA: a complementary tool for population surveillance

Detecting dugongs at low densities remains a major challenge for conservation monitoring, particularly in remote or turbid coastal habitats where conventional surveys are difficult. Environmental DNA (eDNA) offers a complementary approach, but robust species-specific tools are needed before it can be confidently applied to dugong surveillance. We developed and analytically validated a quantitative PCR TaqMan assay for detecting dugong (Dugong dugon) eDNA and evaluated its performance across controlled aquarium conditions in Australia and Abu Dhabi, and wild populations in northern Australia and the Arabian/Persian Gulf. The assay detected dugong eDNA in aquarium and field samples, with Sanger sequencing confirming amplification of dugong mitochondrial DNA from positive field detections. Our assay provides a robust and geographically transferable tool for targeted dugong eDNA detection, performing reliably across contrasting coastal environments and widely separated populations. This approach can strengthen local-scale surveillance of low-density or difficult-to-detect dugong populations.

genetics↗

bioRxiv2026

Reparameterization of the Amber RNA Force Field Non-Bonded Terms

All-atom simulations of RNA using molecular dynamics have the promise of modeling conformational preferences, folding thermodynamics, conformational change kinetics, and binding affinities of small molecule therapeutics. These simulations rely on a force field, a set of equations and parameters that model the potential energy as a function of conformation using classical mechanics. One popular force field for RNA is Amber OL3, with the most recent iteration derived in 1999 and with subsequent updates to backbone dihedral parameters. The Amber force field, while frequently used, is known to have limitations; for example, it does not properly stabilize native structures against alternative structures. Here, we provide a new approach to fitting the non-bonded parameters for the force field, specifically atom-centered point charges for electrostatics and the Lennard-Jones parameters. The parameters are fit to quantum mechanics (QM) interaction energies calculated with symmetry-adapted perturbation theory (SAPT), including embedded point charges to represent the electrostatic field from solvent and adjacent nucleotides. In this pilot study with a limited set of fitting data, we use the Amber ff99 equations and atom types unchanged. With the revised parameters, we observe improvement in the stability of native structures relative to alternative structures. Native tetraloop conformations, which unfold with the Amber OL3 force field, are stable on the microsecond timescale with our new force field parameters. We also see improvement in the conformational preferences of tetramers. Crucially, A-form helices are still well-modeled, but we observe additional flexibility in an internal loop that is not consistent with NMR data. Overall, we provide evidence that this new approach to fitting RNA force field parameters to SAPT interaction energies with native-structure context represented as embedded point charges is promising. It offers a flexible solution for revising the equations in future work or for extension to other molecules that interact with RNA, such as proteins and small molecules. We call this new set of force field parameters Amber RNA.ROC26.

biochemistry↗

bioRxiv2025

An oligo walk to identify siRNAs against the circular Tau 12->7 RNA

Circular RNAs are associated with numerous diseases and recent evidence shows that they can be translated into proteins after undergoing RNA modification. Circular RNAs differ from their linear mRNA counterparts in their backsplice site, allowing selective targeting using RNA interference, which however limits the options to place the siRNA. We tested all possible siRNAs against the backsplice site of the circTau 12->7 RNA after it was subjected to adenosine to inosine RNA editing, a modification that promotes translation of the circRNA. Most siRNAs reduced the circRNA and protein abundance, which however did not correlate. We identified an siRNA with an IC50 of 750 pmol efficacy on protein expression. This circRNA fulfilled six of the eight criteria for siRNAs targeting mRNAs. Thus, modified circRNAs expressing protein can be targeted with siRNAs, but their optimal sequence needs to be determined empirically.

molecular biology↗

bioRxiv2025

40S ribosomal subunits scan mRNA for the start codon by one-dimensional diffusion

During eukaryotic translation initiation, the small (40S) ribosomal subunit is recruited to the 5' cap and subsequently scans the 5' untranslated region (5' UTR) of mRNA in search of the start codon. The molecular mechanism of mRNA scanning remains unclear. Here, using GFP reporters in Saccharomyces cerevisiae cells, we show that order-of-magnitude variations in the lengths of unstructured 5' UTRs have a modest effect on protein synthesis. These observations indicate that mRNA scanning is not rate limiting in yeast cells. Conversely, the presence of secondary structures in the 5' UTR strongly inhibits translation. Loss-of-function mutations in translational RNA helicases eIF4A and Ded1, as well as mutations in other initiation factors implicated in mRNA scanning, namely eIF4G, eIF4B, eIF3g and eIF3i, produced a similar decrease in translation of GFP reporters with short and long unstructured 5' UTRs. As expected, mutations in Ded1, eIF4B and eIF3i severely diminished translation of the reporters with structured 5' UTRs. Evidently, while RNA helicases eIF4A and Ded1 facilitate 40S recruitment and secondary structure unwinding, they are not rate-limiting for the 40S movement along the 5' UTR. Hence, our data indicate that, instead of helicase-driven translocation, one-dimensional diffusion predominately drives mRNA scanning by the 40S subunits in yeast cells.

genetics↗

bioRxiv2024

Structural determinants of inverted Alu-mediated backsplicing revealed by -MaP and -JuMP

Biogenesis of circular RNA usually involves a backsplicing reaction where the downstream donor site is ligated to the upstream acceptor site by the spliceosome. For this reaction to occur, it is hypothesized that these sites must be in proximity. Inverted repeat sequences, such as Alu elements, in the upstream and downstream introns are predicted to base-pair and represent one mechanism for inducing proximity. Here, we investigate the pre-mRNA structure of the human HIPK3 gene at exon 2, which forms a circular RNA via backsplicing. We leverage multiple chemical probing techniques, including the recently developed SHAPE- JuMP strategy, to characterize secondary and tertiary interactions in the pre- mRNA that govern backsplicing. Our data confirm that the antisense Alu elements, AluSz(-) and AluSq2(+) in the upstream and downstream introns, form a highly- paired interaction. Circularization requires formation of long-range Alu-mediated base pairs but does not require the full-length AluSq2(+). In addition to confirming long-range base pairs, our SHAPE-JuMP data identified multiple long-range interactions between non-pairing nucleotides. Genome-wide analysis of inverted repeats flanking circular RNAs confirm that their presence favors circularization, but the overall effect is modest. Together these results suggest that secondary structure considerations alone cannot fully explain backsplicing and additional interactions are key.

molecular biology↗

bioRxiv2024

Structural impact of 3-methylcytosine modification on the anticodon stem of a neuronally-enriched arginine tRNA

All tRNAs undergo a series of chemical modifications to fold and function correctly. In mammals, the C32 nucleotide in the anticodon loop of tRNA-Arg-CCU and UCU is methylated to form 3-methylcytosine (m3C). Deficiency of m3C in arginine tRNAs has been linked to human neurodevelopmental disorders, indicating a critical biological role for m3C modification. However, the structural repercussions of m3C modification are not well understood. Here, we examine the structural effects of m3C32 modification on the anticodon stem loop (ASL) of human tRNA-Arg-UCU-4-1, a unique tRNA with enriched expression in the central nervous system. Optical melting experiments demonstrate that m3C modification can locally disrupt nearby base pairing within the ASL while simultaneously stabilizing the ASL electrostatically, resulting in little net change thermodynamically. The isoenergetic nature of the C32 - A38 pair vs the m3C32 - A38 pair may help discriminate against structures not adopting canonical C32 - A38 pairings, as most other m3C pairings are unfavorable. Furthermore, multidimensional NMR reveals that after m3C modification there are changes in hairpin loop structure and dynamics, the structure of A37, and the neighboring A31 - U39 base pair. However, these structural changes after modification are made while maintaining the shape of the C32 - A38 pairing, which is essential for efficient tRNA function in translation. These findings suggests that m3C32 modification could alter interactions of tRNA-Arg isodecoders with one or more binding partners while simultaneously maintaining the tRNAs ability to function in translation.

biochemistry↗

bioRxiv2023

Secondary structures that regulate mRNA translation provide insights for ASO-mediated modulation of cardiac hypertrophy

Translation of upstream open reading frames (uORFs) typically abrogates translation of main (m)ORFs. The molecular mechanism of uORF regulation in cells is not well understood. Here, we identified a double-stranded RNA (dsRNA) structure residing within the GATA4 uORF that augments uORF translation and inhibits mORF translation. Antisense oligonucleotides (ASOs) that disrupt this dsRNA structure promote mORF translation, while ASOs that base-pair immediately downstream (i.e., forming a bimolecular double-stranded region) of either the uORF or mORF start codon enhance uORF or mORF translation, respectively. Human cardiomyocytes and mice treated with a uORF-enhancing ASO showed reduced cardiac GATA4 protein levels and increased resistance to cardiomyocyte hypertrophy. We further show the general utility of uORF-dsRNA- or mORF- targeting ASO to regulate mORF translation for other mRNAs. Our work demonstrates a regulatory paradigm that controls translational efficiency and a useful strategy to alter protein expression and cellular phenotypes by targeting or generating dsRNA downstream of a uORF or mORF start codon. Bullet points for discoveriesO_LIdsRNA within GATA4 uORF activates uORF translation and inhibits mORF translation. C_LIO_LIASOs that target the dsRNA can either inhibit or enhance GATA4 mORF translation. C_LIO_LIASOs can be used to impede hypertrophy in human cardiomyocytes and mouse hearts. C_LIO_LIuORF- and mORF-targeting ASOs can be used to control translation of multiple mRNAs. C_LI

molecular biology↗

bioRxiv2023

DNA Structure Design Is Improved Using an Artificially Expanded Alphabet of Base Pairs Including Loop and Mismatch Thermodynamic Parameters

We show that in silico design of DNA secondary structures is improved by extending the base pairing alphabet beyond A-T and G-C to include the pair between 2-amino-8-(1-{beta}-D-2-deoxyribofuranosyl)-imidazo-[1,2-a]-1,3,5-triazin-(8H)-4-one and 6-amino-3-(1-{beta}-D-2-deoxyribofuranosyl)-5-nitro-(1H)-pyridin-2-one, simply P and Z. To obtain the thermodynamic parameters needed to include P-Z pairs in the designs, we performed 47 optical melting experiments and combined the results with previous work to fit a new set of free energy and enthalpy nearest neighbor folding parameters for P-Z pairs and G-Z wobble pairs. We find that G-Z pairs have stability comparable to A-T pairs and therefore should be considered quantitatively by structure prediction and design algorithms. Additionally, we extrapolated the set of loop, terminal mismatch, and dangling end parameters to include P and Z nucleotides. These parameters were incorporated into the RNAstructure software package for secondary structure prediction and analysis. Using the RNAstructure Design program, we solved 99 of the 100 design problems posed by Eterna using the ACGT alphabet or supplementing with P-Z pairs. Extending the alphabet reduced the propensity of sequences to fold into off-target structures, as evaluated by the normalized ensemble defect (NED). The NED values were improved relative to those from the Eterna example solutions in 91 of 99 cases where Eterna-player solutions were provided. P-Z-containing designs had average NED values of 0.040, significantly below the 0.074 of standard-DNA-only designs, and inclusion of the P-Z pairs decreased the time needed to converge on a design. This work provides a sample pipeline for inclusion of any expanded alphabet nucleotides into prediction and design workflows.

biophysics↗

bioRxiv2022

Deep learning models for RNA secondary structure prediction (probably) do not generalise across families

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSThe secondary structure of RNA is of importance to its function. Over the last few years, several papers attempted to use machine learning to improve de novo RNA secondary structure prediction. Many of these papers report impressive results for intra-family predictions, but seldom address the much more difficult (and practical) inter-family problem. ResultsWe demonstrate it is nearly trivial with convolutional neural networks to generate pseudo-free energy changes, modeled after structure mapping data, that improve the accuracy of structure prediction for intra-family cases. We propose a more rigorous method for inter-family cross-validation that can be used to assess the performance of learning-based models. Using this method, we further demonstrate that intra-family performance is insufficient proof of generalisation despite the widespread assumption in the literature, and provide strong evidence that many existing learning-based models have not generalised inter-family. AvailabilitySource code and data is available at https://github.com/marcellszi/dl-rna.

bioinformatics↗

bioRxiv2021

Genetic basis of body shape variation along the benthic-pelagic axis in cichlid fishes

Divergence along the benthic-pelagic axis is one of the most widespread and repeated patterns of morphological variation in fishes, producing body shape diversity associated with ecology and swimming mechanics. This ecological shift is also the first stage of the explosive adaptive radiation of cichlid fishes in the East African Rift Lakes. We use two hybrid crosses of cichlids (Metriaclima sp. x Aulonocara sp. and Labidochromis sp. x Labeotropheus sp., >975 animals total) along the benthic-pelagic ecomorphological axis to determine the genetic basis of body shape diversification. Using a series of both linear and geometric shape measurements, we identify 55 quantitative trait loci (QTL) that underlie various aspects of body shape variation associated with benthic-pelagic divergence. These QTL are spread throughout the genome, each explain 3.0-7.2% of phenotypic variation, and are largely modular. Further, QTL are distinct both between these two crosses of Lake Malawi cichlids and compared to previously identified QTL for body shape in fishes such as sticklebacks. We find that body shape is controlled by many genes of small effects. In all, we find that convergent benthic and pelagic body phenotypes commonly observed across fish clades are most likely due to distinct genetic and molecular mechanisms.

evolutionary biology↗

bioRxiv2021

Quantitative prediction of variant effects on alternative splicing using endogenous pre-messenger RNA structure probing

Splicing is a highly regulated process that depends on numerous factors. It is particularly challenging to quantitatively predict how a mutation will affect precursor messenger RNA (mRNA) structure and the subsequent functional consequences. Here we use a novel Mutational Profiling (-MaP) methodology to obtain highly reproducible endogenous precursor and mature mRNA structural probing data in vivo. We use these data to estimate Boltzmann suboptimal ensembles, and predict the structural consequences of mutations on precursor mRNA structure. Together with a structural analysis of recent cryo-EM spliceosome structures at different stages of the splicing cycle, we determined that the footprint of the Bact complex on precursor mRNA is best able to predict splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene. However, structure alone only achieves 74% accuracy. We therefore developed a {beta}-regression weighting framework that incorporates splice site strength, structure and exonic/intronic splicing regulatory elements which together achieves 90% accuracy for 47 known and six newly discovered splice-altering variants. This combined experimental/computational framework represents a path forward for accurate prediction of splicing related disease-causing variants.

genomics↗

bioRxiv2021

Specific length and structure rather than high thermodynamic stability enable regulatory mRNA stem-loops to pause translation

Translating ribosomes unwind mRNA secondary structures by three basepairs each elongation cycle. Despite the ribosome helicase, certain mRNA stem-loops stimulate programmed ribosomal frameshift by inhibiting translation elongation. Here, using mutagenesis, biochemical and single-molecule experiments, we examine whether high stability of three basepairs, which are unwound by the translating ribosome, is critical for inducing ribosome pauses. We find that encountering frameshift-inducing mRNA stem-loops from the E. coli dnaX mRNA and the gag-pol transcript of Human Immunodeficiency Virus (HIV) hinders A-site tRNA binding and slows down ribosome translocation by 15-20 folds. By contrast, unwinding of first three basepairs adjacent to the mRNA entry channel slows down the translating ribosome by only 2-3 folds. Rather than high thermodynamic stability, specific length and structure enable regulatory mRNA stem-loops to stall translation by forming inhibitory interactions with the ribosome. Our data provide the basis for rationalizing transcriptome-wide studies of translation and searching for novel regulatory mRNA stem-loops.

biochemistry↗

bioRxiv2020

LinearSampling: Linear-Time Stochastic Sampling of RNA Secondary Structure with Applications to SARS-CoV-2

Many RNAs fold into multiple structures at equilibrium. The classical stochastic sampling algorithm can sample secondary structures according to their probabilities in the Boltzmann ensemble, and is widely used. However, this algorithm, consisting of a bottom-up partition function phase followed by a top-down sampling phase, suffers from three limitations: (a) the formulation and implementation of the sampling phase are unnecessarily complicated; (b) the sampling phase repeatedly recalculates many redundant recursions already done during the partition function phase; (c) the partition function runtime scales cubically with the sequence length. These issues prevent stochastic sampling from being used for very long RNAs such as the full genomes of SARS-CoV-2. To address these problems, we first adopt a hypergraph framework under which the sampling algorithm can be greatly simplified. We then present three sampling algorithms under this framework, among which the LazySampling algorithm is the fastest by eliminating redundant work in the sampling phase via on-demand caching. Based on LazySampling, we further replace the cubic-time partition function by a linear-time approximate one, and derive LinearSampling, an end-to-end linear-time sampling algorithm that is orders of magnitude faster than the standard one. For instance, LinearSampling is 176x faster (38.9s vs. 1.9h) than Vienna RNAsubopt on the full genome of Ebola virus (18,959 nt). More importantly, LinearSampling is the first RNA structure sampling algorithm to scale up to the full-genome of SARS-CoV-2 without local window constraints, taking only 69.2 seconds on its reference sequence (29,903 nt). The resulting sample correlates well with the experimentally-guided structures. On the SARS-CoV-2 genome, LinearSampling finds 23 regions of 15 nt with high accessibilities, which are potential targets for COVID-19 diagnostics and drug design. See code: https://github.com/LinearFold/LinearSampling

bioinformatics↗

bioRxiv2020

Making ends meet: new functions of mRNA secondary structure

The 5 cap and 3 poly(A) tail of mRNA are known to synergistically regulate mRNA translation and stability. Recent computational and experimental studies revealed that both protein-coding and non-coding RNAs will fold with extensive intramolecular secondary structure, which will result in close distances between the sequence ends. This proximity of the ends is a sequence-independent, universal property of most RNAs. Only low-complexity sequences without guanosines are without secondary structure and exhibit end-to-end distances expected for RNA random coils. The innate proximity of RNA ends might have important biological implications that remain unexplored. In particular, the inherent compactness of mRNA might regulate translation initiation by facilitating the formation of protein complexes that bridge mRNA 5 and 3 ends. Additionally, the proximity of mRNA ends might mediate coupling of 3' deadenylation to 5' end mRNA decay.

biochemistry↗

bioRxiv2019

CRISPR/Cas9-based mutagenesis frequently provokes on-target mRNA misregulation

The introduction of insertion-deletions (INDELs) by activation of the error-prone non-homologous end-joining (NHEJ) pathway underlies the mechanistic basis of CRISPR/Cas9-directed genome editing. The ability of CRISPR/Cas9 to achieve gene elimination (knockouts) is largely attributed to the emergence of a pre-mature termination codon (PTC) from a frameshift-inducing INDEL that elicits non-sense mediated decay (NMD) of the mutant mRNA. Yet, the impact on gene expression as a consequence of CRISPR/Cas9-introduced INDELs into RNA regulatory sequences has been largely left uninvestigated. By tracking DNA-mRNA-protein relationships in a collection of CRISPR/Cas9-edited cell lines that harbor frameshift-inducing INDELs in various targeted genes, we detected the production of foreign mRNAs or proteins in [~]50% of the cell lines. We demonstrate that these aberrant protein products are derived from the introduction of INDELs that promote internal ribosomal entry, convert pseudo-mRNAs into protein encoding molecules, or induce exon skipping by disruption of exon splicing enhancers (ESEs). Our results using CRISPR/Cas9-introduced INDELs reveal facets of an epigenetic genome buffering apparatus that likely evolved to mitigate the impact of such mutations introduced by pathogens and aberrant DNA damage repair, and that more recently pose challenges to manipulating gene expression outcomes using INDEL-based mutagenesis.

molecular biology↗

bioRxiv2018

Chemically Accurate Relative Folding Stability of RNA Hairpins from Molecular Simulations

This study describes a comparison between melts and simulated stabilities of the same RNAs that could be used to benchmark RNA force fields, and potentially to determine future melt-ing experiments. Using umbrella sampling molecular simulations of three 12-nucleotide RNA hairpin stem loops, for which there are experimentally determined free energies of unfold-ing, we projected unfolding onto the reaction coordinate of end to end (5' to 3' hydroxyl oxygen) distance. We estimate the free energy change of the transition from the native con-formation to a fully extended conformation--the stretched state--with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AM-BER FF99+bsc0+{chi}OL3 force field and each window, spaced at 1 [A] intervals, was sampled for 1 s, for a total of 552 s of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using ther-modynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence independent. The differences between experimental and simulated {Delta}{Delta}G{degrees} are on average 1.00 {+/-} 0.66 kcal/mol, which is chemically accurate and suggests analo-gous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along the reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform such simulations.

biophysics↗

bioRxiv2018

LinearFold: Linear-Time Prediction of RNA Secondary Structures

Predicting the secondary structure of an RNA sequence with speed and accuracy is useful in many applications such as drug design. The state-of-the-art predictors have a fundamental limitation: they have a run time that scales cubically with the length of the input sequence, which is slow for longer RNAs and limits the use of secondary structure prediction in genome-wide applications. To address this bottleneck, we designed the first linear-time algorithm for this problem. which can be used with both thermodynamic and machine-learned scoring functions. Our algorithm, like previous work, is based on dynamic programming (DP), but with two crucial differences: (a) we incrementally process the sequence in a left-to-right rather than in a bottom-up fashion, and (b) because of this incremental processing, we can further employ beam search pruning to ensure linear run time in practice (with the cost of exact search). Even though our search is approximate, surprisingly, it results in even higher overall accuracy on a diverse database of sequences with known structures. More interestingly, it leads to significantly more accurate predictions on the longest sequence families in that database (16S and 23S Ribosomal RNAs), as well as improved accuracies for long-range base pairs (500+ nucleotides apart).

bioinformatics↗