Reconstructing microvascular network skeletons from 3D images: What is the ground truth?

Structural changes to microvascular networks are increasingly highlighted as markers of pathogenesis in a wide range of disease, e.g. Alzheimer's disease, vascular dementia and tumour growth. This has motivated the development of dedicated 3D imaging techniques, alongside the creation of computational modelling frameworks capable of using 3D reconstructed networks to simulate functional behaviours such as blood flow or transport processes. Extraction of 3D networks from imaging data broadly consists of two image processing steps: segmentation followed by skeletonisation. Much research effort has been devoted to segmentation field, and there are standard and widely-applied methodologies for creating and assessing gold standards or ground truths produced by manual annotation or automated algorithms. The Skeletonisation field, however, lacks widely applied, simple to compute metrics for the validation or optimisation of the numerous algorithms that exist to extract skeletons from binary images. This is particularly problematic as 3D imaging datasets increase in size and visual inspection becomes an insufficient validation approach. In this work, we first demonstrate the extent of the problem by applying 4 widely-used skeletonisation algorithms to 3 different imaging datasets. In doing so we show significant variability between reconstructed skeletons of the same segmented imaging dataset. Moreover, we show that such a structural variability propagates to simulated metrics such as blood flow. To mitigate this variability we introduce a new, fast and easy to compute super metric that compares the volume, connectivity, medialness, bifurcation point identification and homology of the reconstructed skeletons to the original segmented data. We then show that such a metric can be used to select the best performing skeletonisation algorithm for a given dataset, as well as to optimise its parameters. Finally, we demonstrate that the super metric can also be used to quickly identify how a particular skeletonisation algorithm could be improved, becoming a powerful tool in understanding the complex implication of small structural changes in a network.

Emergent mechanical control of vascular morphogenesis.

Vascularization is driven by morphogen signals and mechanical cues that coordinately regulate cellular force generation, migration, and shape change to sculpt the developing vascular network. However, it remains unclear whether developing vasculature actively regulates its own mechanical properties to achieve effective vascularization. We engineered tissue constructs containing endothelial cells and fibroblasts to investigate the mechanics of vascularization. Tissue stiffness increases during vascular morphogenesis resulting from emergent interactions between endothelial cells, fibroblasts, and ECM and correlates with enhanced vascular function. Contractile cellular forces are key to emergent tissue stiffening and synergize with ECM mechanical properties to modulate the mechanics of vascularization. Emergent tissue stiffening and vascular function rely on mechanotransduction signaling within fibroblasts, mediated by YAP1. Mouse embryos lacking YAP1 in fibroblasts exhibit both reduced tissue stiffness and develop lethal vascular defects. Translating our findings through biology-inspired vascular tissue engineering approaches will have substantial implications in regenerative medicine.

Quantitative Image Processing for Three-Dimensional Episcopic Images of Biological Structures: Current State and Future Directions.

Episcopic imaging using techniques such as High Resolution Episcopic Microscopy (HREM) and its variants, allows biological samples to be visualized in three dimensions over a large field of view. Quantitative analysis of episcopic image data is undertaken using a range of methods. In this systematic review, we look at trends in quantitative analysis of episcopic images and discuss avenues for further research. Papers published between 2011 and 2022 were analyzed for details about quantitative analysis approaches, methods of image annotation and choice of image processing software. It is shown that quantitative processing is becoming more common in episcopic microscopy and that manual annotation is the predominant method of image analysis. Our meta-analysis highlights where tools and methods require further development in this field, and we discuss what this means for the future of quantitative episcopic imaging, as well as how annotation and quantification may be automated and standardized across the field.

Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes.

Advances in biological imaging have accelerated our understanding of human physiology in both health and disease. As these advances have developed, the opportunities gained by integrating with cutting-edge mathematical models have become apparent yet remain challenging. Combined imaging-modelling approaches provide unprecedented opportunity to correlate data on tissue architecture and function, across length and time scales, to better understand the mechanisms that underpin fundamental biology and also to inform clinical decisions. Here we discuss the opportunities and challenges of such approaches, providing literature examples across a range of organ systems. Given the breadth of the field we focus on the intersection of continuum modelling and in vivo imaging applied to the vasculature and blood flow, though our rationale and conclusions extend widely. We propose three key research pillars (image acquisition, image processing, mathematical modelling) and present their respective advances as well as future opportunity via better integration. Multidisciplinary efforts that develop imaging and modelling tools concurrently, and share them open-source with the research community, provide exciting opportunity for advancing these fields.

Modular type I polyketide synthase acyl carrier protein domains share a common N-terminally extended fold.

Acyl carrier protein (ACP) domains act as interaction hubs within modular polyketide synthase (PKS) systems, employing specific protein-protein interactions to present acyl substrates to a series of enzyme active sites. Many domains from the multimodular PKS that generates the toxin mycolactone display an unusually high degree of sequence similarity, implying that the few sites which vary may do so for functional reasons. When domain boundaries based on prior studies were used to prepare two isolated ACP segments from this system for studies of their interaction properties, one fragment adopted the expected tertiary structure, but the other failed to fold, despite sharing a sequence identity of 49%. Secondary structure prediction uncovered a previously undetected helical region (H0) that precedes the canonical helix-bundle ACP topology in both cases. This article reports the NMR solution structures of two N-terminally extended mycolactone mACP constructs, mH0ACPa and mH0ACPb, both of which possess an additional α-helix that behaves like a rigid component of the domain. The interactions of these species with a phosphopantetheinyl transferase and a ketoreductase domain are unaffected by the presence of H0, but a shorter construct that lacks the H0 region is shown to be substantially less thermostable than mH0ACPb. Bioinformatics analysis suggests that the extended H0-ACP motif is present in 98% of type I cis-acyltransferase PKS chain-extension modules. The polypeptide linker that connects an H0-ACP motif to the preceding domain must therefore be ~12 residues shorter than previously thought, imposing strict limits on ACP-mediated substrate delivery within and between PKS modules.

Challenges in the Structural-Functional Characterization of Multidomain, Partially Disordered Proteins CBP and p300: Preparing Native Proteins and Developing Nanobody Tools.

The structural and functional characterization of large multidomain signaling proteins containing long disordered linker regions represents special methodological and conceptual challenges. These proteins show extreme structural heterogeneity and have complex posttranslational modification patterns, due to which traditional structural biology techniques provide results that are often difficult to interpret. As demonstrated through the example of two such multidomain proteins, CREB-binding protein (CBP) and its paralogue, p300, even the expression and purification of such proteins are compromised by their extreme proteolytic sensitivity and structural heterogeneity. In this chapter, we describe the effective expression of CBP and p300 in a eukaryotic host, Sf9 insect cells, followed by their tandem affinity purification based on two terminal tags to ensure their structural integrity. The major focus of this chapter is on the development of novel accessory tools, single-domain camelid antibodies (nanobodies), for structural-functional characterization. Specific nanobodies against full-length CBP and p300 can specifically target their different regions and can be used for their marking, labeling, and structural stabilization in a broad range of in vitro and in vivo studies. Here, we describe four high-affinity nanobodies binding to the KIX and the HAT domains, either mimicking known interacting partners or revealing new functionally relevant conformations. As immunization of llamas results in nanobody libraries with a great sequence variation, deep sequencing and interaction analysis with different regions of the proteins provide a novel approach toward developing a panel of specific nanobodies.