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Bues, J.

Publications and source records attributed to Bues, J..

5 recordsLinked to original sources

Generative modeling reveals the connection between cellular morphology and gene expression

The understanding of how transcriptional programs give rise to cellular morphology, and how morphological features reflect and influence cell identity and function remains limited. This is due in part to the lack of large-scale datasets pairing the two modalities as well as the absence of computational frameworks capable of modeling their cross-modal structure. Here, we introduce COSMIC, a bidirectional generative framework that enables quantitative decomposition of transcriptional variance reflected in morphology and morphological variance explained by gene expression. COSMIC builds on a foundation model trained on over 21 million segmented nuclei and couples it with existing transcriptomic embeddings. To enable cross-modal learning, we leveraged a newly generated multimodal dataset acquired using IRIS, a technology that captures high-resolution images and transcriptomes from the same single cells at scale. COSMIC accurately modeled cell type identity, as well as continuous dynamics such as cell-cycle progression, establishing a quantitative link between morphological phenotypes and underlying gene expression. In prostate cancer cells, COSMIC identified morphological and transcriptomic differences between chemotherapy drug treatment-responsive and -resistant cells, and revealed morphology-associated genes linked to tumor state. Together, these results demonstrate that generative modeling powered by paired single-cell measurements can capture the bidirectional flow of information between cellular form and gene expression, opening new avenues for mechanistic discovery and predictive modeling in both basic and translational cell biology.

bioinformatics↗

Single-cell phenomics through integrated imaging and molecular profiling

Single-cell technologies such as transcriptomics, microscopy, and flow cytometry have revolutionized the study of cellular identity and function. While each of these technologies is powerful on its own, their full potential lies in their integration, enabling multimodal profiling of the same cell and revealing how distinct modalities influence one another. Here, we introduce IRIS (Interconnected Robotic Imaging and Single cell transcriptomics), a deterministic single-cell platform technology that seamlessly couples high-resolution microscopy with droplet-based single-cell RNA sequencing. IRIS enables precise cell positioning, multimode imaging across brightfield and fluorescent channels, and subsequent molecular capture from the same cell, directly linking high-resolution morphological features to matched transcriptomes. We validate IRIS by recovering cell cycle progression states and transcriptional programmes associated with canonical morphologies and demonstrate its discovery power by molecularly resolving two nuclear-ER architectures within naive CD8+ T cells, each defined by distinct gene expression profiles and functional markers. IRIS establishes an integrative single-cell phenomics framework, opening new avenues for dissecting how cellular form relates to molecular state and function.

immunology↗

Food texture preference reveals multisensory contributions of gustatory organs in behaviour and physiology

Food presents a multisensory experience, with visual, taste, and olfactory cues being important in allowing an animal to determine the safety and nutritional value of a given substance1. Texture, however, remains a surprisingly unexplored aspect, despite providing key information about the state of the food through properties such as hardness, liquidity, and granularity. Food perception is achieved by specialised sensory neurons, which themselves are defined by the receptor genes they express. While it was assumed that sensory neurons respond to one or few closely-related stimuli, more recent findings challenge this notion and support evidence that certain sensory neurons are more broadly tuned. In the Drosophila taste system, gustatory neurons respond to cues of opposing hedonic valence or to olfactory cues. Here, we identified that larvae ingest and navigate towards specific food substrate hardnesses, and probed the role of gustatory organs in this behaviour. By developing a genetic tool targeting specifically gustatory organs, we show that these organs are major contributors for evaluation of food texture and ingestion decision-making. We find that ablation of gustatory organs not only results in loss of chemosensation, but also navigation and ingestion preference to varied substrate textures. Furthermore, we show that certain neurons in the primary taste organ exhibit varied and concurrent physiological responses to mechanical and multimodal stimulation. We show that individual neurons house independent mechanisms for multiple sensory modalities, challenging assumptions about capabilities of sensory neurons. We propose that further investigations, across the animal kingdom, may reveal higher sensory complexity than currently anticipated.

neuroscience↗

Multimodal and multisensory coding in the Drosophila larval peripheral gustatory center

The ability to evaluate food palatability is innate in all animals, ensuring their survival. The external taste organ in Drosophila larvae is composed of only few sensory neurons but enables discrimination between a wide range of chemicals and displays high complexity in receptor gene expression and physiological response profile. It remains largely unknown how the discrepancy between a small neuronal number and the perception of a large sensory space is genetically and physiologically resolved. We tackled dissection of taste sensory coding at organ level with cellular resolution in the fruit fly larva by combining whole-organ calcium imaging and single-cell transcriptomics to map physiological properties and molecular features of individual neurons. About one third of gustatory sense neurons responded to multiple tastants, showing a rather large degree of multimodality within the taste organ. Further supporting the notion of signal integration at the periphery, we observed neuronal deactivation events within simultaneous neighboring responses, suggesting inter-cellular communication through electrical coupling and thus providing an additional level in how neurons may encode taste sensing. Interestingly, we identified neurons responding to both mechanical and taste stimulation, indicating potential multisensory integration. On a molecular level, chemosensory cells show heterogeneity in neuromodulator expression. In addition to a broad cholinergic profile, markers on dopaminergic, glutamatergic or neuropeptidergic pathways are present either in distinct cell populations or are seemingly co-expressed. Our data further extend the sensory capacity of the larval taste system pointing towards an unanticipated degree of multimodal and multisensory coding principles.

neuroscience↗

Deterministic scRNA-seq of individual intestinal organoids reveals new subtypes and coexisting distinct stem cell pools

Single-cell RNA-sequencing (scRNA-seq) has transformed our ability to resolve cellular properties across systems. However, current scRNA-seq platforms are one-size-fits-all approaches that are tailored toward large cell inputs (> 1,000 cells), rendering them inefficient and costly when processing small, individual tissue samples. This important drawback tends to be resolved by loading bulk samples, but this yields confounded mosaic cell population read-outs. To overcome these technological limitations, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo. We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics. In comparison to other microfluidics systems, the active flow control driving DisCo, enables continuous operation and processing of low-input samples (< 100 cells) at high capture efficiency (> 70%). To underscore the unique capabilities of our approach, we analyzed intestinal organoid development by "DisCo-ing" 31 individual organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a+ stem cell population which persists as symmetrical cysts even under differentiation conditions. Furthermore, we uncovered a so far uncharacterized "gobloid" subtype consisting predominantly of precursor and mature (Muc2+) goblet cells. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity among small, individual tissues.

bioengineering↗