Materials and construction methods of nests vary between bird species and at present, very little is known about the relationships between architecture and function in these structures. This study combines computational and experimental techniques to study the structural biology of nests fabricated by the edible nest swiftlet Aerodramus fuciphagus on vertical rock walls using threaded saliva. Utilizing its own saliva as a construction material allows the swiftlets full control over the structural features at a very high resolution in a process similar to additive manufacturing. It was hypothesized that the mechanical properties would vary between the structural regions of the nest (i.e. anchoring to the wall, center of the cup, and rim) mainly by means of architecture to offer structural support and bear the natural loads of birds and eggs. We generated numerical models of swiftlet nests from μCT scans based on collected swiftlet nests, which we loaded with a force of birds and eggs. This was done in order to study and assess the stress distribution that characterizes the specific nest’s architecture, evaluate its strength and weak points if any, as well as to understand the rationale and benefits that underlie this natural structure. We show that macro- and micro-scale structural patterns are identical in all nests, suggesting that their construction is governed by specific design principles. The nests’ response to applied loads of birds and eggs in finite element simulations suggests a mechanical overdesign strategy, which ensures the stresses experienced by its components in any loading scenario are actively minimized to be significantly smaller than the tensile fracture strength of the nests’ material. These findings highlight mechanical overdesign as a biological strategy for resilient, single-material constructions designed to protect eggs and hatchlings.

The wide variety of nest architectural designs exhibited by passerine birds allowed them to diversify into a wide variety of ecological niches and terrestrial habitats. At present, very little is known about the mechanics of building these structures. Digitizing natural biological structures such as bird nests provides the opportunity to explore their structural properties and behavior under specific conditions by means of computational manipulations, simulations, and analyses. This study describes a generic algorithm for the digitization and exploration of complex interlocked bird nests, and validates it on nests built by the Dead-Sea Sparrow (Passer moabiticus) in branches of trees using stiff dry branches. This algorithm takes as input computerized tomographic scans of the nest, identifies and isolates each branch entity within the three-dimensional data, and finally extracts the characteristics of each branch. The result is a reliable three-dimensional digital model of the nest that contains a complete geometric dataset per each of its components, e.g. dimensions and contact points with neighboring components, as well as global properties, e.g. density distribution and network structure. Based on these, we were able to simulate various models of the nest construction process. Altogether, the described algorithm and possible derivatives thereof could be a valuable tool in studying the structure-function relationships of similarly complex biological objects, and may provide further insights into the potential selective mechanisms underlying historical evolution of this distinct nest form.

The ability to manipulate and selectively position cells into patterns or distinct microenvironments is an important component of many single cell experimental methods and biological engineering applications. Although a variety of particles and cell patterning methods have been demonstrated, most of them deal with the patterning of cell populations, and are either not suitable or difficult to implement for the patterning of single cells. Here, we describe a bottom-up strategy for the micropatterning of cells and cell-sized particles. We have configured a micromanipulator system, in which a pneumatic microinjector is coupled to a holding pipette capable of physically isolating single particles and cells from different types, and positioning them with high accuracy in a predefined position, with a resolution smaller than 10 µm. Complementary DNA sequences were used to stabilize and hold the patterns together. The system is accurate, flexible, and easy-to-use, and can be automated for larger-scale tasks. Importantly, it maintains the viability of live cells. We provide quantitative measurements of the process and offer a file format for such assemblies.

13Natural biological structures are often complex and cannot be mapped directly to 14 genes, being therefore impossible to explore by traditional biological tools. In contrast, 15 digitizing these structures enables to explore their properties and behavior under specific 16 conditions, by means of computational manipulations, simulations, and analyses. We 17 describe a generic algorithm for the digitization and exploration of the complex structures 18 exhibited by common, interwoven bird nests. This algorithm takes as input computerized 19 tomographic scans of the studied Dead-Sea Sparrow (Passer moabiticus) nest, identifies and 20 isolates each branch entity within the three-dimensional data and finally extracts the 21 characteristics of each branch. The result is a reliable three-dimensional numerical model 22 of the nest that contains a complete geometric dataset per each of its components, e.g. 23 dimensions and contact points with neighboring components, as well as global properties, 24 e.g. density distribution and network structure. Based on these, we were able to simulate 25 various models of the nest construction process. Altogether, the described algorithm and 26 possible derivatives thereof could be a valuable tool in studying the structure-function 27 relationships of similarly complex biological objects. 28 29 Introduction 30The field of structural biology is concerned with the relationships between structure and 31 function of biological objects, mainly at the molecular level. Testing specific hypotheses 32 regarding these relationships is typically done by altering the structures using traditional 33 experimental techniques such as genetic mutations, and measuring the consequent behavior of 34 the object under study 1 . However, complex biological structures at the macro-scale level, such as 35 animal made structures, e.g termite mounds 2 , orb webs 3 , and bird nests 4 , that presumably have a 36 genetic basis, are challenging and often impossible to explore this way, since there is no simple 37 injective mapping between genotype and phenotype. 38While such macro-scale biological structures cannot be studied by traditional biological 39 tools, their structure-function relationships can be studied in-silico in digital formats. Digitizing 40 complex structures by converting the objects using three dimensional (3D) imaging techniques,