Biology subjects

Mallikarjun, V.

Publications and source records attributed to Mallikarjun, V..

4 recordsLinked to original sources

bioRxiv2018

microRNA-dependent regulation of biomechanical genes establishes tissue stiffness homeostasis

The mechanical properties of tissues, which are determined primarily by their extracellular matrix (ECM), are largely stable over time despite continual turnover of ECM constituents 1,2. These observations imply active homeostasis, where cells sense and adjust rates of matrix synthesis, assembly and degradation to keep matrix and tissue properties within the optimal range. However, the regulatory pathways that mediate this process are essentially unknown3. Genome-wide analyses of endothelial cells revealed abundant microRNA-mediated regulation of cytoskeletal, adhesive and extracellular matrix (CAM) mRNAs. High-throughput assays showed co-transcriptional regulation of microRNA and CAM genes on stiff substrates, which buffers CAM expression. Disruption of global or individual microRNA-dependent suppression of CAM genes induced hyper-adhesive, hyper-contractile phenotypes in multiple systems in vitro, and increased tissue stiffness in the zebrafish fin-fold during homeostasis and regeneration in vivo. Thus, a network of microRNAs and CAM mRNAs mediate tissue mechanical homeostasis.

cell biology↗

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

Circadian Clock Regulation of the Secretory Pathway

Collagen is the most abundant secreted protein in vertebrates that persists throughout life without renewal. The unchanging nature of collagen contrasts with observed continued collagen synthesis throughout adulthood and with conventional transcriptional and translational homeostatic mechanisms that replace damaged proteins with new copies. Here we show circadian clock regulation of procollagen transport from ER-to-Golgi and Golgi-to-plasma membrane by sequential rhythmic expression of SEC61, TANGO1, PDE4D and VPS33B. The result is nocturnal procollagen synthesis and daytime collagen fibril assembly in mice. Rhythmic collagen degradation by CTSK maintains collagen homeostasis. This circadian cycle of collagen synthesis, assembly and degradation affects only a pool of newly-synthesized collagen whilst maintaining the persistent collagen network. Disabling the circadian clock causes collagen accumulation and abnormal fibrils in vivo. In conclusion, our study has identified a circadian clock mechanism of protein homeostasis in which a sacrificial pool of collagen is synthesized and removed to maintain tissue function.

cell biology↗

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↗