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bioRxiv2020

A Pseudo-Temporal Causality Approach to Identifying miRNA-mRNA Interactions During Biological Processes

AbstractMotivation microRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA-mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using “pseudo-time” concept have inspired us to develop a pseudo-time based method to infer the miRNA-mRNA relationships characterising a biological process by taking into account the temporal aspect of the process.Results We have developed a novel approach, called pseudo-time causality (PTC), to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition (EMT), a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA-mRNA interactions in both single cell and bulk data. The results suggest that utilising the pseudo-temporal information from the data helps reveal the gene regulation in a biological process much better than using the static information.Availability R scripts and datasets can be found at https://github.com/AndresMCB/PTCCompeting Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2015

Measuring and modeling diffuse scattering in protein X-ray crystallography

X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations must be measured. Until now measurement of diffuse scattering from protein crystals has been scarce, due to the extra effort of collecting diffuse data. Here, we present three-dimensional measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested Translation-Libration-Screw (TLS), Liquid-Like Motions (LLM), and coarse-grained Normal Modes (NM) models of protein motions. The LLM model provides a global picture of motions and were refined against the diffuse data, while the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that NM-based refinement can generate dynamics-inspired structural models that simultaneously agree with both Bragg and diffuse scattering.\n\nSignificanceThe structural details of protein motions are critical to understanding many biological processes, but they are often hidden to conventional biophysical techniques. Diffuse X-ray scattering can reveal details of the correlated movements between atoms; however, the data collection historically has required extra effort and dedicated experimental protocols. We have measured three-dimensional diffuse intensities in X-ray diffraction from CypA and trypsin crystals using standard crystallographic data collection techniques. Analysis of the resulting data is consistent with the protein motions resembling diffusion in a liquid or vibrations of a soft solid. Our results show that using diffuse scattering to model protein motions can become a component of routine crystallographic analysis through the extension of commonplace methods.

Biophysics↗