Neurod1 mediates the reprogramming of NG2 glial into neurons in vitro

Neuronal defect and loss are the main pathological processes of many central nervous system diseases. Cellular reprogramming is a promising method to supplement lost neurons. However, study on cellular reprogramming is still limited and its mechanism remains unclear. Herein, the effect of Neurod1 expression on differentiation of NG2 glia into neurons was investigated. In this study, we successfully isolated NG2 glial cells from mice prior to identification with immunofluorescence. Afterwards, AAV-Neurod1 virus was used to construct Neurod1 overexpression vectors in NG2 glia. Later, we detected neuronal markers expression with immunofluorescence and real time quantitative polymerase-chain reaction (qRT-PCR). Besides, expression of MAPK-signaling-pathway-related proteins were detected by western blotting technique. Through immunofluorescence and qRT-PCR techniques, we observed that Neurod1 overexpression contributed to NG2 cells differentiated into neurons. Further experiments also showed that Neurod1 overexpression induced the activation of MAPK pathway, but PD98059 (a selective inhibitor of MAPK pathway) partly inhibited the neuronal differentiation induced by Neurod1 overexpression. These findings suggest that Neurod1 could promote NG2 glia cells differentiating into neurons, wherein the mechanism under the differentiation is related to activation of MAPK pathway.     

Soluble ANPEP Released From Human Astrocytes as a Positive Regulator of Microglial Activation and Neuroinflammation: Brain Renin–Angiotensin System in Astrocyte–Microglia Crosstalk

Astrocytes are major supportive glia and immune modulators in the brain; they are highly secretory in nature and interact with other cell types via their secreted proteomes. To understand how astrocytes communicate during neuroinflammation, we profiled the secretome of human astrocytes following stimulation with proinflammatory factors. A total of 149 proteins were significantly upregulated in stimulated astrocytes, and a bioinformatics analysis of the astrocyte secretome revealed that the brain renin–angiotensin system (RAS) is an important mechanism of astrocyte communication. We observed that the levels of soluble form of aminopeptidase N (sANPEP), an RAS component that converts angiotensin (Ang) III to Ang IV in a neuroinflammatory milieu, significantly increased in the astrocyte secretome. To elucidate the role of sANPEP and Ang IV in neuroinflammation, we first evaluated the expression of Ang IV receptors in human glial cells because Ang IV mediates biological effects through its receptors. The expression of angiotensin type 1 receptor was considerably upregulated in activated human microglial cells but not in human astrocytes. Moreover, interleukin-1β release from human microglial cells was synergistically increased by cotreatment with sANPEP and its substrate, Ang III, suggesting the proinflammatory action of Ang IV generated by sANPEP. In a mouse neuroinflammation model, brain microglial activation and proinflammatory cytokine expression levels were increased by intracerebroventricular injection of sANPEP and attenuated by an enzymatic inhibitor and neutralizing antibody against sANPEP. Collectively, our results indicate that astrocytic sANPEP–induced increase in Ang IV exacerbates neuroinflammation by interacting with microglial proinflammatory receptor angiotensin type 1 receptor, highlighting an important role of indirect crosstalk between astrocytes and microglia through the brain RAS in neuroinflammation.     

More attention on glial cells to have better recovery after spinal cord injury

Functional improvement after spinal cord injury remains an unsolved difficulty. Glial scars, a major component of SCI lesions, are very effective in improving the rate of this recovery. Such scars are a result of complex interaction mechanisms involving three major cells, namely, astrocytes, oligodendrocytes, and microglia. In recent years, scientists have identified two subtypes of reactive astrocytes, namely, A1 astrocytes that induce the rapid death of neurons and oligodendrocytes, and A2 astrocytes that promote neuronal survival. Moreover, recent studies have suggested that the macrophage polarization state is more of a continuum between M1 and M2 macrophages. M1 macrophages that encourage the inflammation process kill their surrounding cells and inhibit cellular proliferation. In contrast, M2 macrophages promote cell proliferation, tissue growth, and regeneration. Furthermore, the ability of oligodendrocyte precursor cells to differentiate into adult oligodendrocytes or even neurons has been reviewed. Here, we first scrutinize recent findings on glial cell subtypes and their beneficial or detrimental effects after spinal cord injury. Second, we discuss how we may be able to help the functional recovery process after injury.     

Modeling Innate Antiviral Immunity in Physiological Context

An effective innate antiviral response is critical for the mitigation of severe disease and host survival following infection. In vivo, the innate antiviral response is triggered by cells that detect the invading pathogen and then communicate through autocrine and paracrine signaling to stimulate the expression of genes that inhibit viral replication, curtail cell proliferation, or modulate the immune response. In other words, the innate antiviral response is complex and dynamic. Notably, in the laboratory, culturing viruses and assaying viral life cycles frequently utilizes cells that are derived from tissues other than those that support viral replication during natural infection, while the study of viral pathogenesis often employs animal models. In recapitulating the human antiviral response, it is important to consider that variation in the expression and function of innate immune sensors and antiviral effectors exists across species, cell types, and cell differentiation states, as well as when cells are placed in different contexts. Thus, to gain novel insight into the dynamics of the host response and how specific sensors and effectors impact infection kinetics by a particular virus, the model system must be selected carefully. In this review, we briefly introduce key signaling pathways involved in the innate antiviral response and highlight how these differ between systems. We then review the application of tissue-engineered or 3D models for studying the antiviral response, and suggest how these in vitro culture systems could be further utilized to assay physiologically-relevant host responses and reveal novel insight into virus-host interactions.     

Functional Diversity and Evolution of the Drosophila Sperm Proteome

Spermatozoa are central to fertilization and the evolutionary fitness of sexually reproducing organisms. As such, a deeper understanding of sperm proteomes (and associated reproductive tissues) has proven critical to the advancement of the fields of sexual selection and reproductive biology. Due to their extraordinary complexity, proteome depth-of-coverage is dependent on advancements in technology and related bioinformatics, both of which have made significant advancements in the decade since the last Drosophila sperm proteome was published. Here, we provide an updated version of the Drosophila melanogaster sperm proteome (DmSP3) using improved separation and detection methods and an updated genome annotation. Combined with previous versions of the sperm proteome, the DmSP3 contains a total of 3176 proteins, and we provide the first label-free quantitation of the sperm proteome for 2125 proteins. The top 20 most abundant proteins included the structural elements α- and β-tubulins and sperm leucyl-aminopeptidases. Both gene content and protein abundance were significantly reduced on the X chromosome, consistent with prior genomic studies of X chromosome evolution. We identified 9 of the 16 Y-linked proteins, including known testis-specific male fertility factors. We also identified almost one-half of known Drosophila ribosomal proteins in the DmSP3. The role of this subset of ribosomal proteins in sperm is unknown. Surprisingly, our expanded sperm proteome also identified 122 seminal fluid proteins (Sfps), proteins originally identified in the accessory glands. We show that a significant fraction of ‘sperm-associated Sfps’ are recalcitrant to concentrated salt and detergent treatments, suggesting this subclass of Sfps are expressed in testes and may have additional functions in sperm, per se. Overall, our results add to a growing landscape of both sperm and seminal fluid protein biology and in particular provides quantitative evidence at the protein level for prior findings supporting the meiotic sex-chromosome inactivation model for male-specific gene and X chromosome evolution.     

‘Design,synthesis, and strategic use of small chemical probes toward identification of novel targets for drug development’

Chemical probes are essential tools used to study and modulate biological systems. Here, we describe some of the recent scientific advancement in the field of chemical biology, as well as how the advent of new technologies is redefining the criteria of ‘good’ chemical probes and influencing the discovery of valuable drug leads. In this review, we report selected examples of the usage of linkered and linker-free chemical probes for target identification, biological discovery, and general mechanistic understanding. We also discuss the promises of chemogenomics libraries in phenotypic screens, as well as the limitation of their usage to identify the modulation of new targets and biology.     

Comparative Analysis of T-Cell Spatial Proteomics and the Influence of HIV Expression

As systems biology approaches to virology have become more tractable, highly studied viruses such as HIV can now be analyzed in new unbiased ways, including spatial proteomics. We employed here a differential centrifugation protocol to fractionate Jurkat T cells for proteomic analysis by mass spectrometry; these cells contain inducible HIV-1 genomes, enabling us to look for changes in the spatial proteome induced by viral gene expression. Using these proteomics data, we evaluated the merits of several reported machine learning pipelines for classification of the spatial proteome and identification of protein translocations. From these analyses, we found that classifier performance in this system was organelle dependent, with Bayesian t-augmented Gaussian mixture modeling outperforming support vector machine learning for mitochondrial and endoplasmic reticulum proteins but underperforming on cytosolic, nuclear, and plasma membrane proteins by QSep analysis. We also observed a generally higher performance for protein translocation identification using a Bayesian model, Bayesian analysis of differential localization experiments, on row-normalized data. Comparative Bayesian analysis of differential localization experiment analysis of cells induced to express the WT viral genome versus cells induced to express a genome unable to express the accessory protein Nef identified known Nef-dependent interactors such as T-cell receptor signaling components and coatomer complex. Finally, we found that support vector machine classification showed higher consistency and was less sensitive to HIV-dependent noise. These findings illustrate important considerations for studies of the spatial proteome following viral infection or viral gene expression and provide a reference for future studies of HIV-gene-dropout viruses.     

Show your true color: Mammalian cell surface staining for tracking cellular identity in multiplexing and beyond

Fluorescence microscopy revolutionized cell biology and changed requirements for dyes towards higher brightness, novel capacities, and specific targets. With the need for multiplexing assays in high-throughput methodologies, surface staining gained particular interest because it allows rapid application of exogenous stains to track cellular identity in mixed populations. Indeed, the last decade has enriched the toolbox of general lipid stains, fluorescent lipid analogues, sugar-binding lectins, and protein-specific antibodies enabling the first rationally designed plasma membrane-specific dyes. Still, multiple challenges exist, and the unique properties of each dye must be considered when selecting a staining approach for a specific application. Recent advances are also promising that future dyes will provide ultimate brightness and photostability in diverse colors and reduced sizes for high-resolution imaging.     

Differential expression patterns of phospholipase D isoforms 1 and 2 in the mammalian brain and retina

Phosphatidic acid is a key signaling molecule heavily implicated in exocytosis due to its protein-binding partners and propensity to induce negative membrane curvature. One phosphatidic acid-producing enzyme, phospholipase D (PLD), has also been implicated in neurotransmission. Unfortunately, due to the unreliability of reagents, there has been confusion in the literature regarding the expression of PLD isoforms in the mammalian brain which has hampered our understanding of their functional roles in neurons. To address this, we generated epitope-tagged PLD1 and PLD2 knockin mice using CRISPR/Cas9. Using these mice, we show that PLD1 and PLD2 are both localized at synapses by adulthood, with PLD2 expression being considerably higher in glial cells and PLD1 expression predominating in neurons. Interestingly, we observed that only PLD1 is expressed in the mouse retina, where it is found in the synaptic plexiform layers. These data provide critical information regarding the localization and potential role of PLDs in the central nervous system.     

Immunopeptidomic Analyses of Colorectal Cancers With and Without Microsatellite Instability

Colorectal cancer is the second leading cause of cancer death worldwide, and the incidence of this disease is expected to increase as global socioeconomic changes occur. Immune checkpoint inhibition therapy is effective in treating a minority of colorectal cancer tumors; however, microsatellite stable tumors do not respond well to this treatment. Emerging cancer immunotherapeutic strategies aim to activate a cytotoxic T cell response against tumor-specific antigens, presented exclusively at the cell surface of cancer cells. These antigens are rare and are most effectively identified with a mass spectrometry–based approach, which allows the direct sampling and sequencing of these peptides. Although the few tumor-specific antigens identified to date are derived from coding regions of the genome, recent findings indicate that a large proportion of tumor-specific antigens originate from allegedly noncoding regions. Here, we employed a novel proteogenomic approach to identify tumor antigens in a collection of colorectal cancer–derived cell lines and biopsy samples consisting of matched tumor and normal adjacent tissue. The generation of personalized cancer databases paired with mass spectrometry analyses permitted the identification of more than 30,000 unique MHC I–associated peptides. We identified 19 tumor-specific antigens in both microsatellite stable and unstable tumors, over two-thirds of which were derived from noncoding regions. Many of these peptides were derived from source genes known to be involved in colorectal cancer progression, suggesting that antigens from these genes could have therapeutic potential in a wide range of tumors. These findings could benefit the development of T cell–based vaccines, in which T cells are primed against these antigens to target and eradicate tumors. Such a vaccine could be used in tandem with existing immune checkpoint inhibition therapies, to bridge the gap in treatment efficacy across subtypes of colorectal cancer with varying prognoses. Data are available via ProteomeXchange with identifier PXD028309.     

Spatial single cell metabolomics: Current challenges and future developments

Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell–cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.     

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.     

Myelinosome-like vesicles in human seminal plasma: A cryo-electron microscopy study

Seminal plasma is particularly rich in extracellular vesicles. Myelinosomes are membranous organelles described throughout the seminiferous epithelium of the testis but never reported in semen. Our aim was to determine the presence of myelinosomes in human seminal plasma.Transmission electron microscopy and cryo electron microscopy analysis of standard myelinosome preparation from TM4 Sertoli cells and human seminal plasma samples.We have specified by cryo-EM the morphological aspect of “standard” myelinosomes isolated from the culture media of TM4 Sertoli cells. Vesicles with the same morphological appearance were revealed in human seminal plasma samples.Human seminal plasma contains a population of large EV (average diameter 200 nm) whose morphological appearance resemble those of myelinosomes. Defining the specific biomarkers and functionalities of myelinosome in human seminal plasma are the concerns to be addressed in our further research.     

In silico reconstitution of DNA replication. Lessons from single-molecule imaging and cryo-tomography applied to single-particle cryo-EM

DNA replication has been reconstituted in vitro with yeast proteins, and the minimal system requires the coordinated assembly of 16 distinct replication factors, consisting of 42 polypeptides. To understand the molecular interplay between these factors at the single residue level, new structural biology tools are being developed. Inspired by advances in single-molecule fluorescence imaging and cryo-tomography, novel single-particle cryo-EM experiments have been used to characterise the structural mechanism for the loading of the replicative helicase. Here, we discuss how in silico reconstitution of single-particle cryo-EM data can help describe dynamic systems that are difficult to approach with conventional three-dimensional classification tools.     

MHC Class I Immunopeptidome: Past,Present, and Future

In the 35 years since the revelation that short peptides bound to major histocompatibility complex class I and II molecules are the secret of the major histocompatibility complex–restricted nature of T-cell recognition, there has been enormous progress in characterizing the immunopeptidome, the repertoire of peptide presented for immunosurveillance. Here, the major milestones in the journey are marked, the contribution of proteasome-mediated splicing to the immunopeptidome is discussed, and exciting recent findings relating the immunopeptidome to the translatome revealed by ribosome profiling (RiboSeq) is detailed. Finally, what is needed for continued progress is opined about, which includes the infusion of talented young scientists into the antigen-processing field, currently undergoing a renaissance; thanks in part to the astounding success of T-cell–based cancer immunotherapy.     

What does engram encode?: Heterogeneous memory engrams for different aspects of experience

Long-lasting synaptic changes within the neuronal network mediate memory. Neurons bearing such physical traces of memory (memory engram cells) are often equated with neurons expressing immediate early genes (IEGs) during a specific experience. However, past studies observed the expression of different IEGs in non-overlapping neurons or synaptic plasticity in neurons that do not express a particular IEG. Importantly, recent studies revealed that distinct subsets of neurons expressing different IEGs or even IEG negative-(yet active) neurons support different aspects of memory or computation, suggesting a more complex nature of memory engram cells than previously thought. In this short review, we introduce studies revealing such heterogeneous composition of the memory engram and discuss how the memory system benefits from it.     

Immune Checkpoint Blockade Augments Changes Within Oncolytic Virus-induced Cancer MHC-I Peptidome,Creating Novel Antitumor CD8 T Cell Reactivities

The combination cancer immunotherapies with oncolytic virus (OV) and immune checkpoint blockade (ICB) reinstate otherwise dysfunctional antitumor CD8 T cell responses. One major mechanism that aids such reinstatement of antitumor CD8 T cells involves the availability of new class I major histocompatibility complex (MHC-I)-bound tumor epitopes following therapeutic intervention. Thus, therapy-induced changes within the MHC-I peptidome hold the key to understanding the clinical implications for therapy-reinstated CD8 T cell responses. Here, using mass spectrometry–based immuno-affinity methods and tumor-bearing animals treated with OV and ICB (alone or in combination), we captured the therapy-induced alterations within the tumor MHC-I peptidome, which were then tested for their CD8 T cell response-stimulating activity. We found that the oncolytic reovirus monotherapy drives up- as well as downexpression of tumor MHC-I peptides in a cancer type and oncolysis susceptibility dependent manner. Interestingly, the combination of reovirus + ICB results in higher numbers of differentially expressed MHC-I-associated peptides (DEMHCPs) relative to either monotherapies. Most importantly, OV+ICB-driven DEMHCPs contain biologically active epitopes that stimulate interferon-gamma responses in cognate CD8 T cells, which may mediate clinically desired antitumor attack and cancer immunoediting. These findings highlight that the therapy-induced changes to the MHC-I peptidome contribute toward the reinstated antitumor CD8 T cell attack established following OV + ICB combination cancer immunotherapy.     

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has increasingly become more popular due to recent advancements in hardware and software. The number of cryo-EM maps deposited in the EMDataResource (formerly EMDatabase) since 2002 has been dramatically increasing and it continues to do so. De novo macromolecular complex modeling is a labor-intensive process, therefore, it is highly desirable to develop software that can automate this process. Here we discuss our automated, data-driven, and artificial intelligence approaches including map processing, feature extraction, modeling building, and target identification. Recently, we have enabled DNA/RNA modeling in our deep learning-based prediction tool, DeepTracer. We have also developed DeepTracer-ID, a tool that can identify proteins solely based on the cryo-EM map. In this paper, we will present our accumulated experiences in developing deep learning-based methods surrounding macromolecule modeling applications.     

Uniport,Not Proton-Symport,in a Non-Mammalian SLC23 Transporter

SLC23 family members are transporters of either nucleobases or ascorbate. While the mammalian SLC23 ascorbate transporters are sodium-coupled, the non-mammalian nucleobase transporters have been proposed, but not formally shown, to be proton-coupled symporters. This assignment is exclusively based on in vivo transport assays using protonophores. Here, by establishing the first in vitro transport assay for this protein family, we demonstrate that a representative member of the SLC23 nucleobase transporters operates as a uniporter instead. We explain these conflicting assignments by identifying a critical role of uracil phosphoribosyltransferase, the enzyme converting uracil to UMP, in driving uracil uptake in vivo. Detailed characterization of uracil phosphoribosyltransferase reveals that the sharp reduction of uracil uptake in whole cells in presence of protonophores is caused by acidification-induced enzyme inactivation. The SLC23 family therefore consists of both uniporters and symporters in line with the structurally related SLC4 and SLC26 families that have previously been demonstrated to accommodate both transport modes as well.