Regenerating aggregates of hydra display unique cytoskeletal organisation that is absent in a regeneration-deficient strain

Hydra has the unique ability to regenerate from aggregates of dissociated single cells that lack positional information. We compared two strains of hydra, a strain of hydra that was capable of regenerating from aggregates and a strain of hydra that was deficient in this type of regeneration. We observed unique actin cytoskeletal arrangements that were present in the regenerates of regeneration-competent strain but not in the regeneration-deficient strain. Concomitantly, the regeneration-deficient strain failed to organise the extracellular cytoskeleton of laminin and collagen between ectodermal and endodermal epithelial cells. These interesting preliminary observations highlight the importance of the cytoskeletal organisation in regeneration of hydra and suggest that regeneration from the aggregates of dissociated cells through de novo patterning requires correct structural organisation of cytoskeletal elements.

Model of ‘implant-host’ neural circuits in a microfluidic chip in vitro

In this study, we developed a new model of neuronal cells plating into a developed neural network to study functional integration using microfluidic methods. The integration was modeled in a three-chamber microfluidic chip by growing two weakly coupled neuronal networks and enhancing its connectivity by plating new dissociated cells. The direction of connections was formed by the asymmetric design of the chip. Such technology can be used to develop a new type of scaffold to recover the modular structure of the network.

Kinematic self-replication in reconfigurable organisms

All living systems perpetuate themselves via growth in or on the body, followed by splitting, budding, or birth. We find that synthetic multicellular assemblies can also replicate kinematically by moving and compressing dissociated cells in their environment into functional self-copies. This form of perpetuation, previously unseen in any organism, arises spontaneously over days rather than evolving over millennia. We also show how artificial intelligence methods can design assemblies that postpone loss of replicative ability and perform useful work as a side effect of replication. This suggests other unique and useful phenotypes can be rapidly reached from wild-type organisms without selection or genetic engineering, thereby broadening our understanding of the conditions under which replication arises, phenotypic plasticity, and how useful replicative machines may be realized.

Cell Interaction by Multiplet sequencing (CIM-seq) v2

Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions. Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.

Dissociated forms of moraxella isolated from the affected eyes of cattle

The dissociation phenomenon of epizootic cultures of Moraxella was studied. The study was conducted in economic entities of Almaty region of the Republic of Kazakhstan for 233 heads of cattle with clinical signs of keratoconjunctivitis. Isolation of the causative agent of Moraxella was performed by bacteriological washes from the conjunctival sacs of the eyes of animals. The laboratory study was carried out according to the approved methodological guidelines. It was found that bacteria of the genus Moraxella dissociate when grown on a solid nutrient medium for more than 6 hours in a thermostat at 37 °C. The bacteria were studied by the following methods: staining according to White-Wilson, thermoagglutination and acriflavine assay. When evaluating the grown colonies according to White-Wilson, the optimal dilution for crystal violet was found to be 1 : 2000, and for gentian violet stain 1 : 1000. In this case, the colonies in the S-form have a dark purple color with a metallic tint, and the dissociated colonies in the R-form do not stain. In the presence of dissociated cells, precipitation (thermoagglutination), sediment formation and clearing of the supernatant fluid at 90 °C for 30 minutes were noted. The suspension of undissociated colonies remained cloudy. When weighing microbial cells isolated by a bacterial loop from individual grown colonies in a solution of acriflavine, dissociated bacteria stick together to form conglomerates. When studying the antigenic activity of the S-, R- forms of Moraxella, it was revealed that the activity of the S-antigen significantly exceeded that of the R-forms. Data on the dissociation of Moraxella cultures can be used for the development of diagnostic and prophylactic drugs against moraxellosis in cattle.

SIRV: Spatial inference of RNA velocity at the single-cell resolution

Studying cellular differentiation using single-cell RNA sequencing (scRNA-seq) rapidly expands our understanding of cellular development processes. Recently, RNA velocity has created new possibilities in studying these cellular differentiation processes, as differentiation dynamics can be obtained from measured spliced and unspliced mRNA expression. However, to map these differentiation processes to developments within a tissue, the spatial context of the tissue should be taken into account, which is not possible with current approaches as they start from dissociated cells. We present SIRV (Spatially Inferred RNA Velocity), a method to infer spatial differentiation trajectories within the spatial context of a tissue at the single-cell resolution. SIRV integrates spatial transcriptomics data with reference scRNA-seq data, to enrich the spatially measured genes with spliced and unspliced expressions from the scRNA-seq data. Next, SIRV calculates RNA velocity vectors for every spatially measured cell and maps these vectors to the spatial coordinates within the tissue. We tested SIRV on the Developing Mouse Brain Atlas data and obtained biologically relevant spatial differentiation trajectories. Additionally, SIRV annotates spatial cells with cellular identities and the region of origin which are transferred from the annotated reference scRNA-seq data. Altogether, with SIRV, we introduce a new tool to enrich spatial transcriptomics data that can assist in understanding how tissues develop.

Robust Acquisition of High Resolution Spatial Transcriptomes from Preserved Tissues with Immunofluorescence Based Laser Capture Microdissection

The functioning of tissues is fundamentally dependent upon not only the phenotypes of the constituent cells but also their spatial organization in the tissue. However, obtaining comprehensive transcriptomic data based on established phenotypes while retaining this spatial information has been challenging. Here we present a general and robust method based on immunofluorescence-guided laser capture microdissection (immuno-LCM-RNAseq) to enable acquisition of finely resolved spatial transcriptomes with as few as tens of cells from snap-frozen or RNAlater-treated tissues, overcoming the long-standing problem of significant RNA degradation during this lengthy process. The efficacy of this approach is exemplified by the characterization of differences at the transcript isoform level between cells at the tip versus the main capillary body of the mouse small intestine lacteal. With the extensive repertoire of phenotype-specific antibodies that are presently available, our method provides a powerful means by which spatially resolved cellular states can be delineated in situ with preserved tissues. Moreover, such high quality spatial transcriptomes defined by immuno-markers can be used to compare with clusters obtained from single-cell RNAseq studies of dissociated cells as well as applied to bead-based spatial transcriptomics approaches that require such information a priori for cell identification.

Progressive Cellular Senescence Mediates Renal Dysfunction in Ischemic Nephropathy

Background: Peripheral vascular diseases may induce chronic ischemia and cellular injury distal to the arterial obstruction. Cellular senescence involves proliferation arrest in response to stress, which can damage neighboring cells. Renal artery stenosis (RAS) induces stenotic-kidney dysfunction and injury, but whether these arise from cellular senescence and their temporal pattern remain unknown. Methods and Results: Chronic renal ischemia was induced in transgenic INK-ATTAC mice by unilateral RAS, and kidney function (in vivo micro-MRI) and tissue damage assessed. Selective clearance of highly p16Ink4a-expressing cells using intraperitoneal AP20187 starting 1, 2, or 4 weeks after RAS attenuated cellular senescence and improved stenotic-kidney function, whereas starting immediately after RAS induction was unsuccessful. Broader clearance of senescent cells using the oral senolytic combination Dasatinib and Quercetin in C57BL/6 RAS mice was more effective in clearing p21 (Cdkn1a)-positive cells and alleviating renal dysfunction and damage. Unbiased single-cell RNA-sequencing in freshly-dissociated cells from healthy and stenotic mouse kidneys identified stenotic-kidney epithelial cells undergoing both mesenchymal transition and senescence. Like mice, injured human stenotic kidneys exhibited cellular senescence, suggesting that this process is conserved. Conclusions: Maladaptive tubular cell senescence, involving upregulated p16 (Cdkn2a), p19 (Cdkn2d), and p21 (Cdkn1a) expression, is associated with renal dysfunction and injury in chronic ischemia. These findings support development of senolytic strategies to delay chronic ischemic renal injury.

Experimental Platform to Study Spiking Pattern Propagation in Modular Networks In Vitro

The structured organization of connectivity in neural networks is associated with highly efficient information propagation and processing in the brain, in contrast with disordered homogeneous network architectures. Using microfluidic methods, we engineered modular networks of cultures using dissociated cells with unidirectional synaptic connections formed by asymmetric microchannels. The complexity of the microchannel geometry defined the strength of the synaptic connectivity and the properties of spiking activity propagation. In this study, we developed an experimental platform to study the effects of synaptic plasticity on a network level with predefined locations of unidirectionally connected cellular assemblies using multisite extracellular electrophysiology.

A head-to-head comparison of ribodepletion and polyA selection approaches for C. elegans low input RNA-sequencing libraries

A recent and powerful technique is to obtain transcriptomes from rare cell populations, such as single neurons in C. elegans, by enriching dissociated cells using fluorescent sorting. However, these cell samples often have low yields of RNA that present challenges in library preparation. This can lead to PCR duplicates, noisy gene expression for lowly expressed genes, and other issues that limit endpoint analysis. Further, some common resources, such as sequence specific kits for removing ribosomal RNA, are not optimized for non-mammalian samples. To advance library construction for such challenging samples, we compared two approaches for building RNAseq libraries from less than 10 nanograms of C. elegans RNA: SMARTSeq V4 (Takara), a widely used kit for selecting poly-adenylated transcripts; and SoLo Ovation (Tecan Genomics), a newly developed ribodepletion-based approach. For ribodepletion, we used a custom kit of 200 probes designed to match C. elegans rRNA gene sequences. We found that SoLo Ovation, in combination with our custom C. elegans probe set for rRNA depletion, detects an expanded set of noncoding RNAs, shows reduced noise in lowly expressed genes, and more accurately counts expression of long genes. The approach described here should be broadly useful for similar efforts to analyze transcriptomics when RNA is limiting.