Biology subjects

Martelli, C.

Publications and source records attributed to Martelli, C..

11 recordsLinked to original sources

bioRxiv2026

Acute hypercapnic stress modulates innate and learned defensive behavior

Survival depends on avoiding threats, a process shaped by experience and internal states. Notably, acute stress can induce analgesia, yet the neural mechanisms by which stress alters aversive value coding remain unclear. Using Drosophila, we show that prior noxious experience induces intensity-dependent analgesia and triggers the release of CO2, a known stress signal. Surprisingly, this effect is mediated by tracheal dendrite (td) neurons in the respiratory system rather than classic olfactory pathways. We then demonstrated that activation of td neurons induces analgesia, whereas their inhibition suppresses it and restores normal nocifensive and learned behavior. Finally, high CO2 exposure decreases dopaminergic neuron responses to electric shocks, thereby impairing aversive memory formation. Together, we propose that under hypercapnic (high CO2) stress, td neurons modulate nociceptive computation and aversive value coding in the brain to facilitate appropriate innate and learned behavioral responses.

neuroscience↗

bioRxiv2026

Spatiotemporal atlas of pro-inflammatory (NF-kB) and anti-inflammatory (STAT6) signalling using reporter mice during mRNA vaccination

The immunization process unfolds through a precisely orchestrated sequence of innate and adaptive events across distinct anatomical sites. Although many mechanisms underlying vaccination are well described, most vaccines have been developed empirically, partly due to the lack of tools enabling rapid, organ-specific analysis of immune activation. To address this gap, we developed and validated a novel STAT6 reporter mouse enabling dynamic in vivo whole-body imaging and ex vivo analysis of STAT6-mediated anti-inflammatory signalling, and combined it with an established NF-{kappa}B reporter model to dissect immune activation induced by two LNP-encapsulated mRNA vaccines encoding the same antigen but differing in RNA chemistry (unmodified versus N{superscript 1}-methyl-pseudouridine (m{superscript 1}{Psi})-modified). This dual-reporter system enabled the creation of a spatiotemporal atlas of vaccine-induced signalling, revealing chemistry-dependent immune dynamics and identifying the liver as a predominant early hub for both NF-{kappa}B and STAT6 activity following systemic administration. Integration with antibody measurements demonstrated that early STAT6 activation followed by rapid signal resolution--rather than prolonged NF-{kappa}B-mediated inflammation--correlated with robust humoral responses, suggesting that monitoring NF-{kappa}B and STAT6 dynamics could provide predictive insight into vaccine immunogenicity. Together, these findings establish NF-{kappa}B and STAT6 reporter mice as rapid in vivo screening tools for the early assessment of vaccine immunogenicity and performance. By enabling dynamic, organ-resolved immune profiling, this approach paves the way for more rational, mechanism-driven design of mRNA vaccines and underscores the importance of further investigating the effects of vaccines on the liver, both as a primary LNP target and as an immunologically tolerogenic organ.

immunology↗

bioRxiv2025

Complex Assembly and Activity States as Multifaceted Protein Attributes Explaining Phenotypic Variability

Cell function studies primarily focus on measuring overall molecular abundances while often overlooking critical clues--including protein modifications and molecular interaction networks--that critically determine the functional properties of the cell. In prior work, we introduced a suite of methods to reveal context-specific transcription factor-gene regulatory networks, kinase-substrate networks, and protein interaction networks and leveraged them to gain deeper insights into transcriptional regulation and signal transduction. However, the complex interdependencies between these networks are still elusive. To address this challenge, we introduce a multi-omics framework, aimed at harnessing measured or inferred protein activity in context-specific networks, which yields deeper functional insights into mechanisms underlying molecular phenotypes, compared to protein abundance alone. As proof of concept, we utilized progressively differentiated instances of HeLa CCL2 and Kyoto cell lines to explore the role of protein complexes and interactions in cell doubling time and susceptibility to Salmonella Typhimurium infection. Notably, this analysis underscores the pivotal role of protein interaction networks in linking molecular profiles to phenotypic outcomes, thus providing a highly generalizable framework for multi-omics dataset analysis.

systems biology↗

bioRxiv2024

Undoing of firing rate adaptation enables invariant population codes

Neural adaptation supports coding efficiency by tuning responses to prevailing stimulus statistics. However, when information is represented by neural populations, adaptation of individual units could degrade behaviorally relevant signals. Here we investigate how the fly olfactory system implements adaptation in Olfactory Receptor Neurons (ORNs) and the consequences for combinatorial coding in downstream circuits. We show that adaptation of ORN firing rate is compensated at the axon terminal, where calcium transients remain background-invariant through inhibitory presynaptic feedback. Background invariance requires an adaptation strategy that shifts ORN response amplitude rather than sensitivity, diverging from efficient coding principles in single neurons. This property supports contrast encoding in ORN populations necessary for background compensation across the glomeruli. Downstream, the modulation of presynaptic Unc13 proteins maintains postsynaptic projection neurons responses to ON stimuli background invariant. We identify a new coding strategy where olfactory neuronal populations encode asymmetrically contrast information by implementing circuit computations that compensate peripheral firing rate adaptation.

neuroscience↗

bioRxiv2024

High-throughput proteome profiling with low variation in a multi-center study using dia-PASEF

High throughput proteomics is gaining increasing traction as it facilitates screening of large sample cohorts required in clinical research and systems biology studies. Recent developments in mass spectrometry-based proteomics resulted in improved hardware and software providing deep proteome coverage, robustness, and scale accessible to a wide range of laboratories. Here, we benchmark dia-PASEF, a data-independent acquisition scheme that integrates trapped ion mobility with high scan speed, with a high-resolution time-of-flight mass analyzer (timsTOF HT) for the deep proteome analysis of a human cell line applying short 5-minute gradients. To show intra-and interlaboratory reproducibility, we performed a multi-laboratory study including 11 sites. We demonstrate that on average 7,072 protein groups and 99,835 peptides were identified in human chronic myelogenous leukemia cells on the timsTOF HT with low variation. Our results underline that dia-PASEF data acquisition combined with reproducible chromatography enables high robustness and data consistency across instruments and laboratories, which is a prerequisite for translational biomedical insights.

systems biology↗

bioRxiv2023

Metabolic constraints on growth explain how developmental temperature scales synaptic connectivity relevant for behaviour.

Environmental temperature dictates the developmental pace of poikilothermic animals. In Drosophila, brain development at lower temperature is not only slower, but it also results in different wiring outcomes. A first-principle model that imposes different metabolic constraints for the growth of the neural system and the organism explains these findings, predicts brain wiring under ecologically relevant temperature cycles and explains the non-uniform scaling of neural development across temperatures. Dissecting the circuit architecture and function of first, second and third order neurons in the olfactory system, we demonstrate that the consequences of temperature are contingent upon the availability of synaptic partners in different circuits. Despite synaptic scaling, second order neurons encode robust odor representations, while temperature dependent connectivity of third order neurons leads to differences in odor-driven behavior. Therefore some circuit specific developmental programs have evolved to support functional robustness with respect to environmental temperature, while others allow phenotypic plasticity with possible adaptive advantages.

neuroscience↗

bioRxiv2021

Rapid profiling of protein complex re-organization in perturbed systems

Protein complexes constitute the primary functional modules of cellular activity. To respond to perturbations, complexes undergo changes in their abundance, subunit composition or state of modification. Understanding the function of biological systems requires global strategies to capture this contextual state information on protein complexes and interaction networks. Methods based on co-fractionation paired with mass spectrometry have demonstrated the capability for deep biological insight but the scope of studies using this approach has been limited by the large measurement time per biological sample and challenges with data analysis. As such, there has been little uptake of this strategy beyond a few expert labs into the broader life science community despite rich biological information content. We present a rapid integrated experimental and computational workflow to assess the re-organization of protein complexes across multiple cellular states. It enables complex experimental designs requiring increased sample/condition numbers. The workflow combines short gradient chromatography and DIA/SWATH mass spectrometry with a data analysis toolset to quantify changes in complex organization. We applied the workflow to study the global protein complex rearrangements of THP-1 cells undergoing monocyte to macrophage differentiation and a subsequent stimulation of macrophage cells with lipopolysaccharide. We observed massive proteome organization in functions related to signaling, cell adhesion, and extracellular matrix during differentiation, and less pronounced changes in processes related to innate immune response induced by the macrophage stimulation. We therefore establish our integrated differential pipeline for rapid and state-specific profiling of protein complex organization with broad utility in complex experimental designs.

systems biology↗

bioRxiv2021

Identification of functional residues using machine learning provides insights into the evolution of odorant receptor gene families in solitary and social insects

The gene family of insect odorant receptors (ORs) has greatly expanded in the course of evolution. ORs allow insects to detect volatile chemicals and therefore play an important role in social interactions, the detection of enemies and preys, and during foraging. The sequences of several thousand ORs are known, but their specific function or ligands have been identified only for very few of them. To advance the functional characterization of ORs, we compiled, curated and aligned the sequences of 3,902 ORs from 21 insect species. We identified the amino acid positions that best predict the response to ligands using machine learning on sets of functionally characterized proteins from the fly Drosophila melanogaster, the mosquito Anopheles gambiae and the ant Harpegnathos saltator. We studied the conservation of these predicted relevant residues across all OR subfamilies and show that the subfamilies that expanded strongly in social insects exhibit high levels of conservation in their binding sites. This indicates that ORs of social insect families are typically finely tuned and exhibit a sensitivity to very similar odorants. Our novel approach provides a powerful tool to use functional information from a limited number of genes to investigate the functional evolution of large gene families.

bioinformatics↗

bioRxiv2021

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation, because adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing. The fruit fly Drosophila also shows nearly luminance invariant behavior for both ON and OFF stimuli. To achieve this, first-order interneurons L1, L2 and L3 all encode contrast and luminance differently, and distribute information across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2 and L3 are not distinct inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavioral performance in varying conditions.

neuroscience↗

bioRxiv2019

SECAT: Quantifying differential protein-protein interaction states by network-centric analysis

Protein-protein interactions (PPIs) play critical functional and regulatory roles in virtually all cellular processes. They are essential for the formation of macromolecular complexes, which in turn constitute the basis for extended protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we describe a computational approach that extends the analysis of data from the co-fractionation / mass spectrometric analysis of native complexes to the level of PPI networks, thus enabling a qualitative and quantitative comparison of the proteome organization between samples and states. The Size-Exclusion Chromatography Algorithmic Toolkit (SECAT) implements a novel, network-centric strategy for the scalable and robust differential analysis of PPI networks. SECAT and its underlying statistical framework elucidate differential quantitative abundance and stoichiometry attributes of proteins in the context of their PPIs. We validate algorithm predictions using publicly available datasets and demonstrate that SECAT represents a more scalable and effective methodology to assess protein-network state and that our approach thus obviates the need to explicitly infer individual protein complexes. Further, by differential analysis of PPI networks of HeLa cells in interphase and mitotic state, respectively, we demonstrate the ability of the algorithm to detect PPI network differences and to thus suggest molecular mechanisms that differentiate cellular states.

systems biology↗

bioRxiv2019

Controlling and measuring dynamic odorant stimuli in the laboratory

Animals experience complex odorant stimuli that vary widely in composition, intensity and temporal properties. However, stimuli used to study olfaction in the laboratory are much simpler. This mismatch arises from the challenges in measuring and controlling them precisely and accurately. Even simple pulses can have diverse kinetics that depend on their molecular identity. Here, we introduce a model to describe how stimulus kinetics depend on the molecular identity of the odorant and the geometry of the delivery system. We describe methods to deliver dynamic odorant stimuli of several types, including broadly distributed stimuli that reproduce some of the statistics of naturalistic plumes, in a reproducible and precise manner. Finally, we introduce a method to calibrate a Photo-Ionization Detector to any odorant it can detect, using no additional components. Our approaches are affordable and flexible and can be used to advance our understanding of how olfactory neurons encode real-world odor signals.

neuroscience↗