Ultra-bright Raman dots for multiplexed optical imaging

Imaging the spatial distribution of biomolecules is at the core of modern biology. The development of fluorescence techniques has enabled researchers to investigate subcellular structures with nanometer precision. However, multiplexed imaging, i.e. observing complex biological networks and interactions, is mainly limited by the fundamental ‘spectral crowding’ of fluorescent materials. Raman spectroscopy-based methods, on the other hand, have a much greater spectral resolution, but often lack the required sensitivity for practical imaging of biomarkers. Addressing the pressing need for new Raman probes, herein we present a series of Raman-active nanoparticles (Rdots) that exhibit the combined advantages of ultra-brightness and compact sizes (~20 nm). When coupled with the emerging stimulated Raman scattering (SRS) microscopy, these Rdots are brighter than previously reported Raman-active organic probes by two to three orders of magnitude. We further obtain evidence supporting for SRS imaging of Rdots at single particle level. The compact size and ultra-brightness of Rdots allows immunostaining of specific protein targets (including cytoskeleton and low-abundant surface proteins) in mammalian cells and tissue slices with high imaging contrast. These Rdots thus offer a promising tool for a large range of studies on complex biological networks.

Closing the gap between formats for storing layout information in systems biology

The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.

mully: An R Package to Create, Modify and Visualize Multilayered Graphs

The modelling of complex biological networks such as pathways has been a necessity for scientists over the last decades. The study of these networks also imposes a need to investigate different aspects of nodes or edges within the networks, or other biomedical knowledge related to it. Our aim is to provide a generic modelling framework to integrate multiple pathway types and further knowledge sources influencing these networks. This framework is defined by a multi-layered model allowing automatic network transformations and documentation. By providing a tool that generates this model, we aim to facilitate the data integration, boost the reproducibility and increase the interoperability between different sources and databases in the field of pathways. We present mully R package that allows the user to create, modify and visualize graphs with multi-layers. The package is implemented with features to specifically handle multilayered graphs.