Biology subjects

Richardson, S. M.

Publications and source records attributed to Richardson, S. M..

3 recordsLinked to original sources

bioRxiv2018

Nuclear decoupling is part of a rapid protein-level cellular response to high-intensity mechanical loading

Our current understanding of cellular mechano-signalling is based on static models, which do not replicate the dynamics of living tissues. Here, we examined the time-dependent response of primary human mesenchymal stem cells (hMSCs) to cyclic tensile strain (CTS). At low-intensity strain (1 hour, 4% CTS at 1 Hz) morphological changes mimicked responses to increased substrate stiffness. As the strain regime was intensified (frequency increased to 5 Hz), we characterised rapid establishment of a broad, structured and reversible protein-level response, even as transcription was apparently downregulated. Protein abundance was quantified coincident with changes to protein conformation and post transcriptional modification. Furthermore, we characterised changes within the linker of nucleo- and cytoskeleton (LINC) complex of proteins that bridges the nuclear envelope, and specifically to levels of SUN domain-containing protein 2 (SUN2). The result of this regulation was to decouple mechano-transmission between the cytoskeleton and the nucleus, thus conferring protection to chromatin.

biophysics↗

bioRxiv2018

BayesENproteomics: Bayesian elastic nets for quantification of proteoforms in complex samples

Multivariate regression modelling provides a statistically powerful means of quantifying the effects of a given treatment while compensating for sources of variation and noise, such as variability between human donors and the behaviour of different peptides during mass spectrometry. However, methods to quantify endogenous post-translational modifications (PTMs) are typically reliant on summary statistical methods that fail to consider sources of variability such as changes in levels of the parent protein. Here, we compare three multivariate regression methods, including a novel Bayesian elastic net algorithm (BayesENproteomics) that enables assessment of relative protein abundances while also quantifying identified PTMs for each protein. We tested the ability of these methods to accurately quantify expression of proteins in a mixed-species benchmark experiment, and to quantify synthetic PTMs induced by stable isotope labelling. Finally, we extended our regression pipeline to calculate fold changes at the pathway level, providing a complement to commonly used enrichment analysis. Our results show that BayesENproteomics can quantify changes to protein levels across a broad dynamic range while also accurately quantifying PTM and pathway-level fold changes. Raw data has been deposited to the ProteomeXchange with identifiers PXD012784, PXD012782 and PXD012772. BayesENproteomics is available for Matlab: www.github.com/VenkMallikarjun/BayesENproteomics and Python3: www.github.com/VenkMallikarjun/BENPPy

bioinformatics↗

bioRxiv2018

An immortalised mesenchymal stem cell line maintains mechano-responsive behaviour and can be used as a reporter of substrate stiffness

The mechanical environment can influence cell behaviour, including changes to transcriptional and proteomic regulation, morphology and, in the case of stem cells, commitment to lineage. However, current tools for characterizing substrates mechanical properties, such as atomic force microscopy (AFM), often do not fully recapitulate the length and time scales over which cells feel substrates. Here, we show that an immortalised, clonal line of human mesenchymal stem cells (MSCs) maintained responsiveness to substrate mechanics observed in primary cells, and could be used as a reporter of stiffness. MSCs were cultured on soft and stiff polyacrylamide hydrogels. In both primary and immortalised MSCs, stiffer substrates promoted increased cell spreading, expression of lamin-A/C and translocation of mechano-sensitive proteins YAP1 and MKL1 to the nucleus. Stiffness was also found to regulate transcriptional markers of lineage. A GFP-YAP / RFP-H2B reporter construct was designed and virally delivered to the immortalised MSCs for in situ detection of substrate stiffness. MSCs with stable expression of the reporter showed GFP-YAP to be increasingly co-localized with nuclear RFP-H2B on stiffer substrates, enabling development of a cellular reporter of substrate stiffness. This will facilitate mechanical characterisation of new materials developed for applications in tissue engineering and regenerative medicine.

bioengineering↗