Biology subjects

Laine, R. F.

Publications and source records attributed to Laine, R. F..

4 recordsLinked to original sources

bioRxiv2018

Intrinsically aggregation-prone proteins form amyloid-like aggregates and contribute to tissue aging in C. elegans

Reduced protein homeostasis and increased protein instability is a common feature of aging. Yet it remains unclear whether protein instability is a cause of aging. In neurodegenerative diseases and amyloidoses, specific proteins self-assemble into amyloid fibrils and accumulate as pathological solid aggregates in a variety of tissues. More recently, widespread protein aggregation has been described during normal aging, in the absence of disease processes. Until now, an extensive characterization of the nature of age-dependent protein aggregation and its consequences for aging has been lacking. Here, we show that age-dependent aggregates are rapidly formed by newly synthesized proteins and contain amyloid-like structures similar to disease-associated protein aggregates. Moreover, we demonstrate that age-dependent protein aggregation accelerates the functional decline of different tissues in C. elegans. Together, these finding reveal that the formation of amyloid aggregates is a generic problem of aging and likely to be an important target for strategies designed to maintain physiological functions in later stages of life.

cell biology↗

bioRxiv2018

Fast fluorescence lifetime imaging reveals the maturation process of α-synuclein aggregates in ageing Caenorhabditis elegans

The nematode worm Caenorhabditis elegans has emerged as an important model organism to study the molecular mechanisms of protein misfolding diseases associated with amyloid formation because of its small size, ease of genetic manipulation and optical transparency. Obtaining a reliable and quantitative read-out of protein aggregation in this system, however, remains a challenge. To address this problem, we here present a fast time-gated fluorescence lifetime imaging (TG-FLIM) method and show that it provides functional insights into the process of protein aggregation in living animals by enabling the rapid characterisation of different types of aggregates. More specifically, in longitudinal studies of C. elegans models of Parkinsons and Huntingtons diseases, we observed marked differences in the aggregation kinetics and the nature of the protein inclusions formed by -synuclein and polyglutamine. In particular, we found that -synuclein inclusions do not display amyloid-like features until late in the life of the worms, whereas polyglutamine forms amyloid characteristics rapidly in early adulthood. Furthermore, we show that the TG-FLIM method is capable of imaging live and non-anaesthetised worms moving in specially designed agarose micro-chambers. Taken together, our results show that the TG-FLIM method enables high-throughput functional imaging of living C. elegans that can be used to study in vivo mechanisms of aggregation and that has the potential to aid the search for therapeutic modifiers of protein aggregation and toxicity.

biophysics↗

bioRxiv2018

Automating multimodal microscopy with NanoJ-Fluidics

Fluorescence microscopy can reveal all aspects of cellular mechanisms, from molecular details to dynamics, thanks to approaches such as super-resolution and live-cell imaging. Each of its modalities requires specific sample preparation and imaging conditions to obtain high-quality, artefact-free images, ultimately providing complementary information. Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows involving multiple sample preparation steps. We present a robust fluidics approach to automate complex sequences of treatment, labelling and imaging of live and fixed cells. Our open-source NanoJ-Fluidics system is based on low-cost LEGO hardware controlled by ImageJ-based software and can be directly adapted to any microscope, providing easy-to-implement high-content, multimodal imaging with high reproducibility. We demonstrate its capacity to carry out complex sequences of experiments such as super-resolved live-to-fixed imaging to study actin dynamics; highly-multiplexed STORM and DNA-PAINT acquisitions of multiple targets; and event-driven fixation microscopy to study the role of adhesion contacts in mitosis.

cell biology↗

bioRxiv2018

MiLeSIM: combining super-resolution and machine learning permits high-throughput virus structure analysis

Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools in the investigation of the structure of supramolecular assemblies such as viruses. Here, we report on a new methodology which combines Structured Illumination Microscopy (SIM) with machine learning algorithms to image and classify the structure of large populations of biopharmaceutical viruses with high resolution. The method offers information on virus morphology that can ultimately be linked with functional performance. We demonstrate the approach on viruses produced for oncolytic viriotherapy (Newcastle Disease Virus) and vaccine development (Influenza). This unique tool enables the rapid assessment of the quality of viral production with high throughput obviating the need for traditional batch testing methods which are complex and time consuming. We show that our method also works on non-purified samples from pooled harvest fluids directly from the production line.

biophysics↗