Corrigendum: Single-cell RNA sequencing reveals the difference in human normal and degenerative nucleus pulposus tissue profiles and cellular interactions.

[This corrects the article DOI: 10.3389/fcell.2022.910626.].

Single-Cell RNA Sequencing Reveals the Difference in Human Normal and Degenerative Nucleus Pulposus Tissue Profiles and Cellular Interactions.

Background: The nucleus pulposus is a constituent structure of the human intervertebral disc, and its degeneration can cause intervertebral disc degeneration (IDD). However, the cellular and molecular mechanisms involved remain elusive. Methods: Through bioinformatics analysis, the single-cell transcriptome sequencing expression profiles of human normal nucleus pulposus (NNP) cells and human degenerative nucleus pulposus (DNP) cells were compared to clarify the transcriptome differential expression profiles of human NNP and DNP. The single-cell sequencing results of the two samples were analyzed using bioinformatics methods to compare the differences in histiocytosis between human NNP and DNP, map the histiocytes of NNP and DNP, perform cell differentiation trajectories for the cell populations of interest and predict cell function, and explore their heterogeneity by pathway analysis and Gene Ontology analysis. Results: Nine cell types were identified, which were chondrocyte 1, chondrocyte 2, chondrocyte 3, chondrocyte 4, chondrocyte 5, endothelial, macrophage, neutrophil, and T cells. Analysis of the proportion of chondrocytes in different tissues revealed that chondrocyte 1 accounted for a higher proportion of NNP cells and highly expressed COL2A1 compared with DNP cells; chondrocyte 2, chondrocyte 3, chondrocyte 4, and chondrocyte 5 accounted for a higher proportion of DNP cells compared with NNP cells. Among them, chondrocyte 2 was an inhibitory calcified chondrocyte with high expression of MGP, chondrocytes 3 were fibrochondrocytes with high expression of COL1A1, chondrocytes 4 were chondrocytes that highly express pain inflammatory genes such as PTGES, and chondrocytes 5 were calcified chondrocytes with high expression of FN1 (chondrocytes 4 and chondrocytes 5 were found for the first time in a study of single-cell transcriptome sequencing of disc tissue). Cell trajectory analysis revealed that chondrocyte 1 was at the beginning of the trajectory and chondrocyte 3 was at the end of the trajectory, while chondrocyte 5 appeared first in the trajectory relative to chondrocyte 2 and chondrocyte 4. Conclusion: After functional identification of the specifically expressed genes in five chondrocytes, it was found that chondrocyte 1 was a chondrocyte with high expression of COL2A1, COL9A2, COL11A2, and CHRDL2 in a high proportion of NNP cells, and chondrocyte 3 was a fibrochondrocyte with high expression of COL1A1, COL6A3, COL1A2, COL3A1, AQP1, and COL15A1 in an increased proportion during nucleus pulposus cell degeneration. Through cell trajectory analysis, it was found that chondrocytes 5 specifically expressing FN1, SESN2, and GDF15 may be the key cells leading to degeneration of nucleus pulposus cells. Chondrocytes 2 expressing MGP, MT1G, and GPX3 may play a role in reversing calcification and degeneration, and chondrocytes 4 expressing PTGES, TREM1, and TIMP1 may play a role in disc degeneration pain and inflammation.

Corrigendum: Single-cell RNA sequencing reveals the difference in human normal and degenerative nucleus pulposus tissue profiles and cellular interactions.

[This corrects the article DOI: 10.3389/fcell.2022.910626.].

Neural processing of the reward value of pleasant odorants.

Pleasant odorants are represented in the posterior olfactory bulb (pOB) in mice. How does this hedonic information generate odor-motivated behaviors? Using optogenetics, we report here that stimulating the representation of pleasant odorants in a sensory structure, the pOB, can be rewarding, self-motivating, and is accompanied by ventral tegmental area activation. To explore the underlying neural circuitry downstream of the olfactory bulb (OB), we use 3D high-resolution imaging and optogenetics and determine that the pOB preferentially projects to the olfactory tubercle, whose increased activity is related to odorant attraction. We further show that attractive odorants act as reinforcers in dopamine-dependent place preference learning. Finally, we extend those findings to humans, who exhibit place preference learning and an increase BOLD signal in the olfactory tubercle in response to attractive odorants. Thus, strong and persistent attraction induced by some odorants is due to a direct gateway from the pOB to the reward system.

Decoding communication patterns of the innate immune system by quantitative proteomics.

The innate immune system is a collective network of cell types involved in cell recruitment and activation using a robust and refined communication system. Engagement of receptor-mediated intracellular signaling initiates communication cascades by conveying information about the host cell status to surrounding cells for surveillance and protection. Comprehensive profiling of innate immune cells is challenging due to low cell numbers, high dynamic range of the cellular proteome, low abundance of secreted proteins, and the release of degradative enzymes (e.g., proteases). However, recent advances in mass spectrometry-based proteomics provides the capability to overcome these limitations through profiling the dynamics of cellular processes, signaling cascades, post-translational modifications, and interaction networks. Moreover, integration of technologies and molecular datasets provide a holistic view of a complex and intricate network of communications underscoring host defense and tissue homeostasis mechanisms. In this Review, we explore the diverse applications of mass spectrometry-based proteomics in innate immunity to define communication patterns of the innate immune cells during health and disease. We also provide a technical overview of mass spectrometry-based proteomic workflows, with a focus on bottom-up approaches, and we present the emerging role of proteomics in immune-based drug discovery while providing a perspective on new applications in the future.

Raman micro-spectroscopy study of living SH-SY5Y cells adhering on different substrates.

In this paper we test the ability of Raman micro-spectroscopy and Raman mapping to investigate the status of cells grown in adhesion on different substrates. The spectra of immortalized SH-SY5Y cells, grown on silicon and on metallic substrates are compared with those obtained for the same type of cells adhering on organic polyaniline (PANI), a memristive substrate chosen to achieve a living bio-hybrid system. Raman spectra give information on the status of the single cell, its local biochemical composition, and on the modifications induced by the substrate interaction. The good agreement between Raman spectra collected from cells adhering on different substrates confirms that the PANI, besides allowing the cell growth, doesn't strongly affect the general biochemical properties of the cell. The investigation of the cellular state in a label free condition is challenging and the obtained results confirm the Raman ability to achieve this information.

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.