Biology subjects

Scialdone, A.

Publications and source records attributed to Scialdone, A..

30 records · Page 2Linked to original sources

bioRxiv2021

The role of cell geometry and cell-cell communication in gradient sensing

Cells can measure shallow gradients of external signals to initiate and accomplish a migration or a morphogenetic process. Recently, starting from mathematical models like the local-excitation global-inhibition (LEGI) model and with the support of empirical evidence, it has been proposed that cellular communication improves the measurement of an external gradient. However, the mathematical models that have been used have over-simplified geometries (e.g., they are uni-dimensional) or assumptions about cellular communication, which limit the possibility to analyze the gradient sensing ability of more complex cellular systems. Here, we generalize the existing models to study the effects on gradient sensing of cell number, geometry and of long-versus short-range cellular communication in 2D systems representing epithelial tissues. We find that increasing the cell number can be detrimental for gradient sensing when the communication is weak and limited to nearest neighbour cells, while it is beneficial when there is long-range communication. We also find that, with long-range communication, the gradient sensing ability improves for tissues with more disordered geometries; on the other hand, an ordered structure with mostly hexagonal cells is advantageous with nearest neighbour communication. Our results considerably extend the current models of gradient sensing by epithelial tissues, making a step further toward predicting the mechanism of communication and its putative mediator in many biological processes. Author summaryGroups of cells collectively migrate in many biological processes, ranging from development to cancer metastasis. The migration is often driven by the gradient of a signaling molecule that can be shallow and noisy, raising the question of how cells can measure it reliably. Cellular communication has recently been suggested to play a key role in gradient sensing, and mathematical models with simplified cellular geometries have been developed to help interpret and design experiments. In this work, we generalize the existing mathematical models to investigate how short- and long-range cellular communication can increase gradient sensing in two-dimensional models of epithelial tissues. We analyze various cellular geometries and tissue size, and we identify the optimal setting that corresponds to different types of communication. Our findings will help pinpoint the communication mechanisms at work in a given tissue and the properties of the molecules that mediate the communication.

biophysics↗

bioRxiv2021

Characterisation of the transcriptional dynamics underpinning the function, fate, and migration of the mouse Anterior Visceral Endoderm

During early post-implantation development of the mouse embryo, the Anterior Visceral Endoderm (AVE) differs from surrounding visceral endoderm (VE) in its migratory behaviour and ability to restrict primitive streak formation to the opposite side of the egg cylinder. In order to characterise the molecular basis for the unique properties of the AVE, we combined single-cell RNA-sequencing of the VE prior to and during AVE migration, with high-resolution imaging, short-term lineage labelling, phosphoproteomics and pharmacological intervention. This revealed the transient nature of the AVE, the emergence of heterogeneities in AVE transcriptional states relative to position of cells, and its prominence in establishing gene expression asymmetries within the spatial constraints of the embryo. We identified a previously unknown requirement of Ephrin- and Semaphorin-signalling for AVE migration. These findings point to a tight coupling of transcriptional state and position in the AVE and reveal molecular heterogeneities underpinning its migratory behaviour and function.

developmental biology↗

bioRxiv2021

Emergent Statistical Laws in Single-Cell Transcriptomic Data

Large scale data on single-cell gene expression have the potential to unravel the specific transcriptional programs of different cell types. The structure of these expression datasets suggests a similarity with several other complex systems that can be analogously described through the statistics of their basic building blocks. Transcriptomes of single cells are collections of messenger RNA abundances transcribed from a common set of genes just as books are different collections of words from a shared vocabulary, genomes of different species are specific compositions of genes belonging to evolutionary families, and ecological niches can be described by their species abundances. Following this analogy, we identify several emergent statistical laws in single-cell transcriptomic data closely similar to regularities found in linguistics, ecology or genomics. A simple mathematical framework can be used to analyze the relations between different laws and the possible mechanisms behind their ubiquity. Importantly, treatable statistical models can be useful tools in transcriptomics to disentangle the actual biological variability from general statistical effects present in most component systems and from the consequences of the sampling process inherent to the experimental technique. Author summaryGene expression profiles represent how different cells use their genetic information. Similarly, books are specific collections of words chosen from a shared vocabulary, and many complex systems can be ultimately described by the statistics of their basic components. Leveraging on this analogy, we identified several emergent statistical laws in single-cell transcriptomic data that are universally found in complex component systems. A simple mathematical description sets these laws in a treatable quantitative framework and represents a useful tool for dissecting the different sources of gene expression variability.

systems biology↗

bioRxiv2021

The anatomical logic of smell

The sense of smell helps us navigate the environment, but its molecular architecture and underlying logic remain unknown. The spatial location of odorant receptor genes (Olfrs) in the nose is widely thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we created a genome-wide 3D atlas of the mouse olfactory mucosa (OM). Topographic maps of genes differentially expressed in space reveal that both Olfrs and non-Olfrs are distributed in a continuous and overlapping fashion over five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize, providing direct evidence for the chromatographic theory of olfaction. This resource resolved the molecular architecture of the mouse OM, and will inform future studies on mechanisms underlying Olfr gene choice, axonal pathfinding, patterning of the nervous system, and basic logic for the peripheral representation of smell.

neuroscience↗

bioRxiv2020

Multiplex-GAM: genome-wide identification of chromatin contacts yields insights not captured by Hi-C

Technologies for measuring 3D genome topology are increasingly important for studying mechanisms of gene regulation, for genome assembly and for mapping of genome rearrangements. Hi-C and other ligation-based methods have become routine but have specific biases. Here, we develop multiplex-GAM, a faster and more affordable version of Genome Architecture Mapping (GAM), a ligation-free technique to map chromatin contacts genome-wide. We perform a detailed comparison of contacts obtained by multiplex-GAM and Hi-C using mouse embryonic stem (mES) cells. We find that both methods detect similar topologically associating domains (TADs). However, when examining the strongest contacts detected by either method, we find that only one third of these are shared. The strongest contacts specifically found in GAM often involve "active" regions, including many transcribed genes and super-enhancers, whereas in Hi-C they more often contain "inactive" regions. Our work shows that active genomic regions are involved in extensive complex contacts that currently go under-estimated in genome-wide ligation-based approaches, and highlights the need for orthogonal advances in genome-wide contact mapping technologies.

molecular biology↗

bioRxiv2020

A spatially resolved single cell atlas of human gastrulation

Gastrulation is the fundamental process during the embryogenesis of all multicellular animals through which the basic body plan is first laid down. It is pivotal in generating cellular diversity coordinated with spatial patterning. Gastrulation in humans occurs in the third week following fertilization. Our understanding of this process in humans is extremely limited, and based almost entirely on experimental models. Here, we characterize in a spatially resolved manner the single cell transcriptional profile of an entire gastrulating human embryo approximately 16 to 19 days after fertilization. We used these data to provide the first unequivocal demonstration that human embryonic stem cells represent the early post implantation epiblast. We identified both primordial germ cells and red blood cells, which had never been characterized so early during human development. Comparison with mouse gastrula transcriptomes revealed many commonalities between the human and mouse but also several key differences, particularly in FGF signaling, that we validated experimentally. This unique dataset offers a unique glimpse into a central but generally inaccessible stage of our development, provides new context for interpreting experiments in other model systems and represents a valuable resource for guiding directed differentiation of human cells in vitro.

developmental biology↗

bioRxiv2020

Multi-organ transcriptomic profiling reveals differential regulation of the immune system among the brain-liver-fats organ network of short-term fasted mice

Different fasting regimens are known to promote health, mitigate chronic immunological disorders, and improve age-related pathophysiological parameters in animals and humans. Indeed, several clinical trials are currently ongoing using fasting as a potential therapy for a wide range of conditions. Fasting alters metabolism by acting as a reset for energy homeostasis. However, the molecular mechanisms underlying the beneficial effects of short-term fasting (STF) are still not well understood, particularly at the systems or multi-organ level. Here, we investigated the dynamic gene expression patterns associated with six periods of STF in nine different mouse organs. We cataloged the transcriptional dynamics within and between organs during STF and discovered differential temporal effects of STF among organs. Using gene ontology enrichment analysis, we identified an organ network sharing 37 common biological pathways perturbed by STF. This network incorporates the brain, liver, interscapular brown adipose tissue, and posterior-subcutaneous white adipose tissue, hence we named it the brain-liver-fats organ network. Using Reactome pathways analysis, we identified the immune system, dominated by T cell regulation processes, as a central and prominent target of systemic modulations during STF in this organ network. The changes we identified in specific immune components point to the priming of adaptive immunity and parallel the fine-tuning of innate immune signaling. Our study provides a comprehensive multi-organ transcriptomic profiling of mice subjected to multiple periods of STF, and adds new insights into the molecular modulators involved in the systemic immuno-transcriptomic changes that occur during short-term energy loss.

systems biology↗

bioRxiv2020

Automatic identification of relevant genes from low-dimensional embeddings of single cell RNAseq data

Dimensionality reduction is a key step in the analysis of single-cell RNA sequencing data and produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single cell data. With no linear relation between genes and embedding however, there is no way to extract the identity of genes most relevant for any cells position in the low-dimensional embedding, and thus the underlying process. In this paper, we introduce the concepts of global and local gene relevance to compute an equivalent of principal component analysis loadings for non-linear low-dimensional embeddings. While global gene relevance identifies drivers of the overall embedding, local gene relevance singles out genes that change in small, possibly rare subsets of cells. We apply our method to single-cell RNAseq datasets from different experimental protocols and to different low dimensional embedding techniques, shows our methods versatility to identify key genes for a variety of biological processes. To ensure reproducibility and ease of use, our method is released as part of destiny 3.0, a popular R package for building diffusion maps from single-cell transcriptomic data. It is readily available through Bioconductor.

bioinformatics↗

bioRxiv2020

Differences in mitochondrial activity trigger cell competition during early mouse development.

Cell competition is emerging as a quality control mechanism that eliminates unfit cells in a wide range of settings from development to the adult. However, the nature of the cells normally eliminated by cell competition and what triggers their elimination remains poorly understood. In mouse, prior to gastrulation 35% of epiblast cells are eliminated. Here we have performed single cell transcriptional profiling of these cells and find that they show the hallmarks of cell competition and have mitochondrial defects. We demonstrate that mitochondrial defects are common to a range of different loser cell types and that manipulating mitochondrial function is sufficient to trigger competition. Importantly, we show that in the embryo cell competition eliminates cells with mitochondrial DNA mutations and that even non-pathological changes in mitochondrial DNA sequence can induce cell competition. Our results therefore suggest that cell competition is a purifying selection that optimises mitochondrial performance prior to gastrulation.

developmental biology↗

bioRxiv2019

COMUNET: a tool to explore and visualize intercellular communication

Intercellular communication plays an essential role in multicellular organisms and several algorithms to analyse it from single-cell transcriptional data have been recently published, but the results are often hard to visualize and interpret. We developed COMUNET (Cell cOMmunication exploration with MUltiplex NETworks), a tool that streamlines the interpretation of the results from cell-cell communication analyses. COMUNET uses multiplex networks to represent and cluster all potential communication pathways between cell types. The algorithm also enables the search for specific patterns of communication and can perform comparative analysis between two biological conditions. To exemplify its use, here we apply COMUNET to investigate cell communication patterns in single-cell transcriptomic datasets from mouse embryos and from an acute myeloid leukemia patient at diagnosis and after treatment. Our algorithm is available on GitHub, along with all the code to perform the analysis reported.

bioinformatics↗

bioRxiv2018

Epstein-Barr virus reprograms human B-lymphocytes immediately in the pre-latent phase of infection

Epstein-Barr virus (EBV) is a human tumor virus and a model of herpesviral latency. The virus efficiently infects resting human B-lymphocytes and induces their continuous proliferation in vitro, which mimics certain aspects of EBVs oncogenic potential in vivo. This seminal finding was made 50 years ago, but how EBV activates primary human B-lymphocytes and how lymphoblastoid cell lines (LCLs) evolve from the EBV-infected lymphocytes is uncertain. We conducted a systematic time-resolved longitudinal study of cellular functions and transcriptional profiles of newly infected naive primary B-lymphocytes. EBV reprograms these human cells comprehensively and globally. Rapid and extensive transcriptional changes occur within 24 hours of infection and precede any metabolic and phenotypic changes. Within the next 48 hours, the virus activates the cells, changes their phenotypes with respect to cell size, RNA and protein content and induces metabolic pathways to cope with the increased demand for energy, supporting an efficient cell cycle entry on day three post infection. The transcriptional program that EBV initiates consists of three waves of clearly discernable clusters of cellular genes that peak on day one, two, or three and regulate RNA synthesis, metabolic pathways and cell division, respectively. Upon the onset of cell doublings on day four the cellular transcriptome appears to be completely reprogrammed to support the activated and proliferating cell, but three additional clusters of EBV regulated genes adjust the infected immune cells to fine-tune cell signaling, migration, and immune response pathways, eventually. Our study reveals that more than 98 % of the 13,000 expressed genes in B-lymphocytes are regulated upon infection demonstrating that EBV governs the entire biology of its target cell.

microbiology↗

bioRxiv2018

Interspecific variation of olfactory preferences in flies, mice, and humans

Aiming to unravel interspecific differences in olfactory preferences, we performed comparative studies of odor valence in flies, mice, and humans. Our analysis revealed that odor preferences of flies correlate positively with the ones of mice and negatively with the ones of humans, but found no evidence supporting the hypothesis that humans and mice prefer the same odors. We further find that odorants eliciting the highest and lowest preferences are often advertising critical biological sources (e.g., food or oviposition sites), suggesting that evolutionary pressures reflecting the ecological needs of each species shape olfactory preferences.

neuroscience↗