Functional modelling of planar cell polarity: an approach for identifying molecular function.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: Cells in some tissues acquire a polarisation in the plane of the tissue in addition to apical-basal polarity. This polarisation is commonly known as planar cell polarity and has been found to be important in developmental processes, as planar polarity is required to define the in-plane tissue coordinate system at the cellular level. RESULTS: We have built an in-silico functional model of cellular polarisation that includes cellular asymmetry, cell-cell signalling and a response to a global cue. The model has been validated and parameterised against domineering non-autonomous wing hair phenotypes in Drosophila. CONCLUSIONS: We have carried out a systematic comparison of in-silico polarity phenotypes with patterns observed in vivo under different genetic manipulations in the wing. This has allowed us to classify the specific functional roles of proteins involved in generating cell polarity, providing new hypotheses about their specific functions, in particular for Pk and Dsh. The predictions from the model allow direct assignment of functional roles of genes from genetic mosaic analysis of Drosophila wings

Quantifying microsatellite mutation rates from intestinal stem cell dynamics in Msh2-deficient murine epithelium

Microsatellite sequences have an enhanced susceptibility to mutation and can act as sentinels indicating elevated mutation rates and increased risk of cancer. The probability of mutant fixation within the intestinal epithelium is dictated by a combination of stem cell dynamics and mutation rate. Here we exploit this relationship to infer microsatellite mutation rates. First a sensitive, multiplexed and quantitative method for detecting somatic changes in microsatellite length was developed that allowed the parallel detection of mutant [CA]n sequences from hundreds of low-input tissue samples at up to 14 loci. The method was applied to colonic crypts in Mus musculus and enabled detection of mutant subclones down to 20% of the cellularity of the crypt (around 50 of 250 cells). By quantifying age-related increases in clone frequencies for multiple loci, microsatellite mutation rates in wild-type and Msh2- deficient epithelium were established. An average 388-fold increase in mutation per mitosis rate was observed in Msh2-deficient epithelium (2.4 x10-2) compared to wild- type epithelium (6.2 x10-5)

Impact of weight loss on cancer-related proteins in serum: results from a cluster randomised controlled trial of individuals with type 2 diabetes

\ua9 2024 The Author(s)Background: Type 2 diabetes is associated with higher risk of several cancer types. However, the biological intermediates driving this relationship are not fully understood. As novel interventions for treating and managing type 2 diabetes become increasingly available, whether they also disrupt the pathways leading to increased cancer risk is currently unknown. We investigated the effect of a type 2 diabetes intervention, in the form of intentional weight loss, on circulating proteins associated with cancer risk to gain insight into potential mechanisms linking type 2 diabetes and adiposity with cancer development. Methods: Fasting serum samples from participants with diabetes enrolled in the Diabetes Remission Clinical Trial (DiRECT) receiving the Counterweight-Plus weight-loss programme (intervention, N = 117, mean weight-loss 10 kg, 46% diabetes remission) or best-practice care by guidelines (control, N = 143, mean weight-loss 1 kg, 4% diabetes remission) were subject to proteomic analysis using the Olink Oncology-II platform (48% of participants were female; 52% male). To identify proteins which may be altered by the weight-loss intervention, the difference in protein levels between groups at baseline and 1 year was examined using linear regression. Mendelian randomization (MR) was performed to extend these results to evaluate cancer risk and elucidate possible biological mechanisms linking type 2 diabetes and cancer development. MR analyses were conducted using independent datasets, including large cancer meta-analyses, UK Biobank, and FinnGen, to estimate potential causal relationships between proteins modified during intentional weight loss and the risk of colorectal, breast, endometrial, gallbladder, liver, and pancreatic cancers. Findings: Nine proteins were modified by the intervention: glycoprotein Nmb; furin; Wnt inhibitory factor 1; toll-like receptor 3; pancreatic prohormone; erb-b2 receptor tyrosine kinase 2; hepatocyte growth factor; endothelial cell specific molecule 1 and Ret proto-oncogene (Holm corrected P-value <0.05). Mendelian randomization analyses indicated a causal relationship between predicted circulating furin and glycoprotein Nmb on breast cancer risk (odds ratio (OR) = 0.81, 95% confidence interval (CI) = 0.67–0.99, P-value = 0.03; and OR = 0.88, 95% CI = 0.78–0.99, P-value = 0.04 respectively), though these results were not supported in sensitivity analyses examining violations of MR assumptions. Interpretation: Intentional weight loss among individuals with recently diagnosed diabetes may modify levels of cancer-related proteins in serum. Further evaluation of the proteins identified in this analysis could reveal molecular pathways that mediate the effect of adiposity and type 2 diabetes on cancer risk. Funding: The main sources of funding for this work were Diabetes UK, Cancer Research UK, World Cancer Research Fund, and Wellcome

SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud

Despite the soaring use of convolutional neural networks (CNNs) in mobile applications, uniformly sustaining high-performance inference on mobile has been elusive due to the excessive computational demands of modern CNNs and the increasing diversity of deployed devices. A popular alternative comprises offloading CNN processing to powerful cloud-based servers. Nevertheless, by relying on the cloud to produce outputs, emerging mission-critical and high-mobility applications, such as drone obstacle avoidance or interactive applications, can suffer from the dynamic connectivity conditions and the uncertain availability of the cloud. In this paper, we propose SPINN, a distributed inference system that employs synergistic device-cloud computation together with a progressive inference method to deliver fast and robust CNN inference across diverse settings. The proposed system introduces a novel scheduler that co-optimises the early-exit policy and the CNN splitting at run time, in order to adapt to dynamic conditions and meet user-defined service-level requirements. Quantitative evaluation illustrates that SPINN outperforms its state-of-the-art collaborative inference counterparts by up to 2x in achieved throughput under varying network conditions, reduces the server cost by up to 6.8x and improves accuracy by 20.7% under latency constraints, while providing robust operation under uncertain connectivity conditions and significant energy savings compared to cloud-centric execution.Comment: Accepted at the 26th Annual International Conference on Mobile Computing and Networking (MobiCom), 202

Pentanol isomer synthesis in engineered microorganisms

Pentanol isomers such as 2-methyl-1-butanol and 3-methyl-1-butanol are a useful class of chemicals with a potential application as biofuels. They are found as natural by-products of microbial fermentations from amino acid substrates. However, the production titer and yield of the natural processes are too low to be considered for practical applications. Through metabolic engineering, microbial strains for the production of these isomers have been developed, as well as that for 1-pentanol and pentenol. Although the current production levels are still too low for immediate industrial applications, the approach holds significant promise for major breakthroughs in production efficiency

The structure of the C-terminal actin-binding domain of talin

Talin is a large dimeric protein that couples integrins to cytoskeletal actin. Here, we report the structure of the C-terminal actin-binding domain of talin, the core of which is a five-helix bundle linked to a C-terminal helix responsible for dimerisation. The NMR structure of the bundle reveals a conserved surface-exposed hydrophobic patch surrounded by positively charged groups. We have mapped the actin-binding site to this surface and shown that helix 1 on the opposite side of the bundle negatively regulates actin binding. The crystal structure of the dimerisation helix reveals an antiparallel coiled-coil with conserved residues clustered on the solvent-exposed face. Mutagenesis shows that dimerisation is essential for filamentous actin (F-actin) binding and indicates that the dimerisation helix itself contributes to binding. We have used these structures together with small angle X-ray scattering to derive a model of the entire domain. Electron microscopy provides direct evidence for binding of the dimer to F-actin and indicates that it binds to three monomers along the long-pitch helix of the actin filament

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

<p>Abstract</p> <p>Background</p> <p>Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.</p> <p>Results</p> <p>We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.</p> <p>Conclusions</p> <p>Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.</p

Deoxyribonucleic acid methylation profiling of single human blastocysts by methylated CpG-island amplification coupled with CpG-island microarray

Objective To study whether methylated CpG-island (CGI) amplification coupled with microarray (MCAM) can be used to generate DNA (deoxyribonucleic acid) methylation profiles from single human blastocysts. Design A pilot microarray study with methylated CpG-island amplification applied to human blastocyst genomic DNA and hybridized on CpG-island microarrays. Setting University research laboratory. Patient(s) Five cryopreserved sibling 2-pronuclear zygotes that were surplus to requirements for clinical treatment by in vitro fertilization were donated with informed consent from a patient attending Bourn Hall Clinic, Cambridge, United Kingdom. Intervention(s) None. Main Outcome Measure(s) Successful generation of genome-wide DNA methylation profiles at CpG islands from individual human blastocysts, with common genomic regions of DNA methylation identified between embryos. Result(s) Between 472 and 734 CpG islands were methylated in each blastocyst, with 121 CpG islands being commonly methylated in all 5 blastocysts. A further 159 CGIs were commonly methylated in 4 of the 5 tested blastocysts. Methylation was observed at a number of CGIs within imprinted-gene, differentially methylated regions (DMRs), including placental and preimplantation-specific DMRs. Conclusion(s) The MCAM method is capable of providing comprehensive DNA methylation data in individual human blastocysts