Tissue surface tension influences cell sorting and tissue fusion. Earlier mechanical studies suggest that multicellular spheroids actively reinforce their surface tension with applied force. Here we study this open question through high-throughput microfluidic micropipette aspiration measurements on cell spheroids to identify the role of force duration and spheroid deformability. In particular, we aspirate spheroid protrusions of mice fibroblast NIH3T3 and human embryonic HEK293T homogeneous cell spheroids into micron-sized capillaries for different pressures and monitor their viscoelastic creep behavior. We find that larger spheroid deformations lead to faster cellular retraction once the pressure is released, regardless of the applied force. Additionally, less deformable NIH3T3 cell spheroids with an increased expression level of alpha-smooth muscle actin, a cytoskeletal protein upregulating cellular contractility, also demonstrate slower cellular retraction after pressure release for smaller spheroid deformations. Moreover, HEK293T cell spheroids only display cellular retraction at larger pressures with larger spheroid deformations, despite an additional increase in viscosity at these larger pressures. These new insights demonstrate that spheroid viscoelasticity is deformation-dependent and challenge whether surface tension truly reinforces at larger aspiration pressures.

Neuronal activity in the highly organized networks of the central nervous system is the vital basis for various functional processes, such as perception, motor control, and cognition. Understanding interneuronal connectivity and how activity is regulated in the neuronal circuits is crucial for interpreting how the brain works. Multi-electrode arrays (MEAs) are particularly useful for studying the dynamics of neuronal network activity and their development as they allow for real-time, high-throughput measurements of neural activity. At present, the key challenge in the utilization of MEA data is the sheer complexity of the measured datasets. Available software offers semi-automated analysis for a fixed set of parameters that allow for the definition of spikes, bursts and network bursts. However, this analysis remains time-consuming, user-biased, and limited by pre-defined parameters. Here, we present autoMEA, software for machine learning-based automated burst detection in MEA datasets. We exemplify autoMEA efficacy on neuronal network activity of primary hippocampal neurons from wild-type mice monitored using 24-well multi-well MEA plates. To validate and benchmark the software, we showcase its application using wild-type neuronal networks and two different neuronal networks modeling neurodevelopmental disorders to assess network phenotype detection. Detection of network characteristics typically reported in literature, such as synchronicity and rhythmicity, could be accurately detected compared to manual analysis using the autoMEA software. Additionally, autoMEA could detect reverberations, a more complex burst dynamic present in hippocampal cultures. Furthermore, autoMEA burst detection was sufficiently sensitive to detect changes in the synchronicity and rhythmicity of networks modeling neurodevelopmental disorders as well as detecting changes in their network burst dynamics. Thus, we show that autoMEA reliably analyses neural networks measured with the multi-well MEA setup with the precision and accuracy compared to that of a human expert.

Neuronal network formation is facilitated by recognition between synaptic cell adhesion molecules at the cell surface. Alternative splicing of cell adhesion molecules provides additional specificity in forming neuronal connections. For the teneurin family of cell adhesion molecules, alternative splicing of the EGF-repeats and NHL domain controls synaptic protein-protein interactions. Here we present cryo-EM structures of the compact dimeric ectodomain of two teneurin-3 isoforms that harbour the splice insert in the EGF-repeats. This dimer is stabilised by an EGF8-ABD contact between subunits. Cryo-EM reconstructions of all four splice variants, together with SAXS and negative stain EM, reveal compacted dimers for each, with variant-specific dimeric arrangements. This results in specific trans-cellular interactions, as tested in cell clustering and stripe assays. The compact conformations provide a structural basis for teneurin homo- and heterophilic interactions. Altogether, our findings demonstrate how alternative splicing results in rearrangements of the dimeric subunits, influencing neuronal recognition and likely circuit wiring.

Cell-surface expressed contactin 1 and neurofascin 155 control wiring of the nervous system and interact across cells to form and maintain paranodal myelin-axon junctions. The molecular mechanism of contactin 1 – neurofascin 155 adhesion complex formation is unresolved. Crystallographic structures of complexed and individual contactin 1 and neurofascin 155 binding regions presented here, provide a rich picture of how competing and complementary interfaces, post-translational glycosylation, splice differences and structural plasticity enable formation of diverse adhesion sites. Structural, biophysical, and cell-clustering analysis reveal how conserved Ig1-2 interfaces form competing heterophilic contactin 1 – neurofascin 155 and homophilic neurofascin 155 complexes whereas contactin 1 forms low-affinity clusters through interfaces on Ig3-6. The structures explain how the heterophilic Ig1-Ig4 horseshoe’s in the contactin 1 – neurofascin 155 complex define the 7.4 nm paranodal spacing and how the remaining six domains enable bridging of distinct intercellular distances.

Establishment of correct synaptic connections is a crucial step during neural circuitry formation. The Teneurin family of neuronal transmembrane proteins promotes cell–cell adhesion via homophilic and heterophilic interactions, and is required for synaptic partner matching in the visual and hippocampal systems in vertebrates. It remains unclear how individual Teneurins form macromolecular cis- and trans-synaptic protein complexes. Here, we present a 2.7 Å cryo-EM structure of the dimeric ectodomain of human Teneurin4. The structure reveals a compact conformation of the dimer, stabilized by interactions mediated by the C-rich, YD-shell, and ABD domains. A 1.5 Å crystal structure of the C-rich domain shows three conserved calcium binding sites, and thermal unfolding assays and SAXS-based rigid-body modeling demonstrate that the compactness and stability of Teneurin4 dimers are calcium-dependent. Teneurin4 dimers form a more extended conformation in conditions that lack calcium. Cellular assays reveal that the compact cis-dimer is compatible with homomeric trans-interactions. Together, these findings support a role for teneurins as a scaffold for macromolecular complex assembly and the establishment of cis- and trans-synaptic interactions to construct functional neuronal circuits.

Significant advances in the past decade have enabled high-resolution structure determination of a vast variety of proteins by cryogenic electron microscopy single particle analysis. Despite improved sample preparation, next-generation imaging hardware, and advanced single particle analysis algorithms, small proteins remain elusive for reconstruction due to low signal-to-noise and lack of distinctive structural features. Multiple efforts have therefore been directed at the development of size-increase techniques for small proteins. Here we review the latest methods for increasing effective molecular weight of proteins <100 ​kDa through target protein binding or target protein fusion - specifically by using nanobody-based assemblies, fusion tags, and symmetric scaffolds. Finally, we summarize these state-of-the-art techniques into a decision-tree to facilitate the design of tailored future approaches, and thus for further exploration of ever-smaller proteins that make up the largest part of the human genome.

The ability to detect specific nucleic acid sequences allows for a wide range of applications such as the identification of pathogens, clinical diagnostics, and genotyping. CRISPR-Cas proteins Cas12a and Cas13a are RNA-guided endonucleases that bind and cleave specific DNA and RNA sequences, respectively. After recognition of a target sequence, both enzymes activate indiscriminate nucleic acid cleavage, which has been exploited for sequence-specific molecular diagnostics of nucleic acids. Here, we present a label-free detection approach that uses a readout based on solution turbidity caused by liquid-liquid phase separation (LLPS). Our approach relies on the fact that the LLPS of oppositely charged polymers requires polymers to be longer than a critical length. This length dependence is predicted by the Voorn-Overbeek model, which we describe in detail and validate experimentally in mixtures of polynucleotides and polycations. We show that the turbidity resulting from LLPS can be used to detect the presence of specific nucleic acid sequences by employing the programmable CRISPR-nucleases Cas12a and Cas13a. Because LLPS of polynucleotides and polycations causes solutions to become turbid, the detection of specific nucleic acid sequences can be observed with the naked eye. We furthermore demonstrate that there is an optimal polynucleotide concentration for detection. Finally, we provide a theoretical prediction that hints towards possible improvements of an LLPS-based detection assay. The deployment of LLPS complements CRISPR-based molecular diagnostic applications and facilitates easy and low-cost nucleotide sequence detection.

Latrophilins (LPHNs) are adhesion GPCRs that are originally discovered as spider’s toxin receptors, but are now known to be involved in brain development and linked to several neuronal and non-neuronal disorders. Latrophilins act in conjunction with other cell adhesion molecules and may play a leading role in its network organization. Here, we focus on the main protein partners of latrophilins, namely teneurins, FLRTs and contactins and summarize their respective temporal and spatial expression patterns, links to neurodevelopmental disorders as well as their structural characteristics. We discuss how more recent insights into the separate cell biological functions of these proteins shed light on the central role of latrophilins in this network. We postulate that latrophilins control the refinement of synaptic properties of specific subtypes of neurons, requiring discrete combinations of proteins.