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Gomez-Varela, D.

Publications and source records attributed to Gomez-Varela, D..

4 recordsLinked to original sources

Proximity labelling reveals the compartmental proteome of murine sensory neurons

IntroductionUnderstanding the molecular architecture of peripheral sensory neurons is critical as we pursue novel drug targets against pain and neuropathy. Sensory neurons in the dorsal root ganglion (DRG) show extensive compartmentalization, thus understanding each compartment - from the peripheral to central terminals - is key to this effort. MethodsTo systematically profile this spatial complexity, we generated a TurboIDfl/fl transgenic mouse line (ROSA26em1(TurboID)Bros), enabling targeted proximity labelling and deep proteomic profiling of DRG neuron compartments via Tg(Advillin-Cre)+. ResultsOur data reveal distinct proteomic signatures across neuronal compartments that reflect specialized neuronal functions. We provide proteomic insights into previously inaccessible nerve terminals both in the periphery (innervating the skin) and in the spinal cord. Further, using a DRG explant model of chemotherapy-induced peripheral neuropathy, we uncover novel and discrete proteome changes, highlighting neuronal vulnerability. ConclusionTogether, our findings provide a unique proteome atlas of the sensory neuron proteome across anatomical domains and demonstrate the utility of proximity labelling proteomics for detecting compartment-specific molecular alterations in a disease model.

neuroscience↗

Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics

Metaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications of mouse gut microbiota and, importantly, also of the host proteome. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.

microbiology↗

Transcriptomic and proteomic profiling of NaV1.8-expressing mouse nociceptors

Nociceptors play an essential role in both acute pain and chronic pain conditions. and have recently been classified into distinct subsets using single-cell transcriptional profiling. In this study, we examined protein levels in dorsal root ganglia using DIA Mass-spectrometry technologies with NaV1.8Cre+/-; ROSA26-flox-stop-flox-DTA (Diphtheria toxin fragment A) mutant mice (NaV1.8Cre-DTA), in which NaV1.8-expressing neurons (mainly nociceptors) in dorsal root ganglia (DRG) were ablated. The results show that 353 transcripts and 78 proteins, including nociceptor-specific sodium channels NaV1.8 (Scn10a) and NaV1.9 (Scn11a), were specifically expressed in nociceptors of DRG. A comparative analysis revealed that about 40% of nociceptor-specific proteins are shared within the nociceptor-specific transcript dataset. Scatter plots show that the proteome and transcriptome datasets in nociceptors have a moderate correlation (r = 0.4825), indicating the existence of post-transcriptional and post-translational gene regulation in nociceptors. This combined profiling study provides a unique resource for sensory studies, especially for pain research.

neuroscience↗

Species-specific cutaneous protein signatures upon incision injury and correlation with distinct pain-related phenotypes in humans

Pain after surgery is common, and its management remains a clinical challenge. Severe acute and prolonged post-surgical pain impairs immediate recovery and leads to long-term consequences like chronic pain, opioid dependency, and reduced quality of life. Althought rodent pain incision models exist, translation to patients is still hampered. To bridge this gap, we combined sensory phenotyping with quantitative proteomics and protein networks in humans and mice after skin incision representing an established model for surgical pain. Initially, we revealed, for the first time, similarities and differences of protein-protein interaction (PPI) networks across both species. Next, we comprehensively phenotyped humans for pain-related symptoms and observed phenotypes with incision-induced proteome changes. Remarkably, post-incision PPI-networks differed between volunteers with small incision-related hyperalgesic areas ("Low responder") versus those with large areas ("High responder"). The latter exhibited a pronounced proteolytic environment associated with persistent inflammation, while an anti-inflammatory protein signature was observed in Low responders. Taken together, we provide unprecedented insights into peripheral processes relevant for developing hyperalgesia and pain after incision. This knowledge will immensely facilitate bidirectional translational pain studies and guide future research on the pathophysiology of pain after surgery and the discovery of novel targets for its treatment and prevention.

neuroscience↗