Single cell transcriptomics reveals opioid usage evokes widespread suppression of antiviral gene program

The single-cell opioid responses in the context of HIV (SCORCH) consortium

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

Chronic Opioid Treatment Arrests Neurodevelopment and Alters Synaptic Activity in Human Midbrain Organoids

Understanding the impact of long-term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross-species differences in animal models. Here, a human midbrain model is established that uses hiPSC-derived midbrain organoids to assess cell-type-specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single-cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single-cell level.

Single-cell transcriptomics analysis of cellular heterogeneity and immune mechanisms in neurodegenerative diseases

Single-cell transcriptomics analysis is an advanced technology that can describe the intracellular transcriptome in complex tissues. It profiles and analyses datasets by single-cell RNA sequencing. Neurodegenerative diseases are identified by the abnormal apoptosis of neurons in the brain with few or no effective therapy strategies at present, which has been a growing healthcare concern and brought a great burden to society. The transcriptome of individual cells provides deep insights into previously unforeseen cellular heterogeneity and gene expression differences in neurodegenerative disorders. It detects multiple cell subsets and functional changes during pathological progression, which deepens the understanding of the molecular underpinnings and cellular basis of neurodegenerative diseases. Furthermore, the transcriptome analysis of immune cells shows the regulation of immune response. Different subtypes of immune cells and their interaction are found to contribute to disease progression. This finding enables the discovery of novel targets and biomarkers for early diagnosis. In this review, we emphasize the principles of the technology, and its recent progress in the study of cellular heterogeneity and immune mechanisms in neurodegenerative diseases. The application of single-cell transcriptomics analysis in neurodegenerative disorders would help explore the pathogenesis of these diseases and develop novel therapeutic methods.

Neuroimmune Mechanisms of Opioid Use Disorder and Recovery: Translatability to Human Studies, and Future Research Directions

Opioid use disorder (OUD) is a major current cause of morbidity and mortality. Long-term exposure to short-acting opioids (MOP-r agonists such as heroin or fentanyl) results in complex pathophysiological changes to neuroimmune and neuroinflammatory functions, affected in part by peripheral mechanisms (e.g., cytokines in blood), and by neuroendocrine systems such as the hypothalamic-pituitary-adrenal (HPA) stress axis. There are important findings from preclinical models, but their role in the trajectory and outcomes of OUD in humans is not well understood. The goal of this narrative review is to examine available data on immune and inflammatory functions in persons with OUD, and to identify major areas for future research. Peripheral blood biomarker studies revealed a pro-inflammatory state in persons with OUD in withdrawal or early abstinence, consistent with available postmortem brain studies (which show glial activation) and diffusion tensor imaging studies (indicating white matter disruptions), with gradual abstinence-associated recovery. The mechanistic roles of these neuroimmune and neuroinflammatory changes in the trajectory of OUD (including recovery and medication management) cannot be examined practically with postmortem data. Collection of longitudinal data in larger-scale human cohorts would allow examination of these mechanisms associated with OUD stage and progression. Given the heterogeneity in presentation of OUD, a precision medicine approach integrating multi-omic peripheral biomarkers and comprehensive phenotyping, including neuroimaging, can be beneficial in risk stratification, and individually optimized selection of interventions for individuals who will benefit, and assessments under refractory therapy.

Opioids and immune checkpoint inhibitors differentially regulate a common immune network in triple-negative breast cancer

Background

Opioids are the primary analgesics for cancer pain. Recent clinical evidence suggests opioids may counteract the effect of immune checkpoint inhibition (ICI) immunotherapy, but the mechanism for this interaction is unknown. The following experiments study how opioids and immunotherapy modulate a common RNA expression pathway in triple negative breast cancer (TNBC), a cancer subtype in which immunotherapy is increasingly used. This study identifies a mechanism by which opioids may decrease ICI efficacy, and compares ketamine, a non-opioid analgesic with emerging use in cancer pain, for potential ICI interaction.

Methods

Tumor RNA expression and clinicopathologic data from a large cohort with TNBC (N=286) was used to identify RNA expression signatures of disease. Various drug-induced RNA expression profiles were extracted from multimodal RNA expression datasets and analyzed to estimate the RNA expression effects of ICI, opioids, and ketamine on TNBC.

Results

We identified a RNA expression network in CD8+ T-cells that was relevant to TNBC pathogenesis and prognosis. Both opioids and anti-PD-L1 ICI regulated RNA expression in this network, suggesting a nexus for opioid-ICI interaction. Morphine and anti-PD-L1 therapy regulated RNA expression in opposing directions. By contrast, there was little overlap between the effect of ketamine and anti-PD-L1 therapy on RNA expression.

Conclusions

Opioids and ICI may target a common immune network in TNBC and regulate gene expression in opposing fashion. No available evidence supports a similar interaction between ketamine and ICI.

sccomp: Robust differential composition and variability analysis for single-cell data

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.

Beyond the Syndemic of Opioid Use Disorders and HIV: The Impact of Opioids on Viral Reservoirs

People with HIV are more likely to have opioid use disorder and to be prescribed opioids for chronic pain than the general population; however, the effects of opioids on the immune system and HIV persistence have not been fully elucidated. Opioids may affect HIV reservoirs during their establishment, maintenance, and reactivation by enhancing HIV infectivity and replication due to upregulation of co-receptors and impairment of innate antiviral responses. Opioids may also modulate immune cell functioning and microbial translocation and can reverse viral latency. In this review, we summarize the current findings for and against the modulating effects of opioids on HIV cellular and anatomical reservoirs, highlighting the current limitations that affect in vitro, ex vivo, and in vivo studies in the field. We propose further research targets and potential strategies to approach this topic.

Reliable Identification and Interpretation of Single-Cell Molecular Heterogeneity and Transcriptional Regulation using Dynamic Ensemble Pruning

Unsupervised clustering is an essential step in identifying cell types from single-cell RNA sequencing (scRNA-seq) data. However, a common issue with unsupervised clustering models is that the optimization direction of the objective function and the final generated clustering labels in the absence of supervised information may be inconsistent or even arbitrary. To address this challenge, a dynamic ensemble pruning framework (DEPF) is proposed to identify and interpret single-cell molecular heterogeneity. In particular, a silhouette coefficient-based indicator is developed to determine the optimization direction of the bi-objective function. In addition, a hierarchical autoencoder is employed to project the high-dimensional data onto multiple low-dimensional latent space sets, and then a clustering ensemble is produced in the latent space by the basic clustering algorithm. Following that, a bi-objective fruit fly optimization algorithm is designed to prune dynamically the low-quality basic clustering in the ensemble. Multiple experiments are conducted on 28 real scRNA-seq datasets and one large real scRNA-seq dataset from diverse platforms and species to validate the effectiveness of the DEPF. In addition, biological interpretability and transcriptional and post-transcriptional regulatory are conducted to explore biological patterns from the cell types identified, which could provide novel insights into characterizing the mechanisms.

scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) strives to capture cellular diversity with higher resolution than bulk RNA sequencing. Clustering analysis is critical to transcriptome research as it allows for further identification and discovery of new cell types. Unsupervised clustering cannot integrate prior knowledge where relevant information is widely available. Purely unsupervised clustering algorithms may not yield biologically interpretable clusters when confronted with the high dimensionality of scRNA-seq data and frequent dropout events, which makes identification of cell types more challenging.

RESULTS

We propose scSemiAAE, a semi-supervised clustering model for scRNA sequence analysis using deep generative neural networks. Specifically, scSemiAAE carefully designs a ZINB adversarial autoencoder-based architecture that inherently integrates adversarial training and semi-supervised modules in the latent space. In a series of experiments on scRNA-seq datasets spanning thousands to tens of thousands of cells, scSemiAAE can significantly improve clustering performance compared to dozens of unsupervised and semi-supervised algorithms, promoting clustering and interpretability of downstream analyses.

CONCLUSION

scSemiAAE is a Python-based algorithm implemented on the VSCode platform that provides efficient visualization, clustering, and cell type assignment for scRNA-seq data. The tool is available from https://github.com/WHang98/scSemiAAE .

High-throughput microfluidic droplets in biomolecular analytical system: A review

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches

The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson's and Alzheimer's disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.

Immunosuppression by opioids: Mechanisms of action on innate and adaptive immunity

Opioids are excellent analgesics for the clinical treatment of various types of acute and chronic pain, particularly cancer-related pain. Nevertheless, it is well known that opioids have some nasty side effects, including immunosuppression, which is commonly overlooked. As a result, the incidence of opportunistic bacterial and viral infections increases in patients with long-term opioid use. Nowadays, there are no effective medications to alleviate opioid-induced immunosuppression. Understanding the underlying molecular mechanism of opioids in immunosuppression can enable researchers to devise effective therapeutic interventions. This review comprehensively summarized the exogenous opioids-induced immunosuppressive effects and their underlying mechanisms, the regulatory roles of endogenous opioids on the immune system, the potential link between opioid immunosuppressive effect and the function of the central nervous system (CNS), and the future perspectives in this field.

Virally Suppressed People Living with HIV Who Use Opioids Have Diminished Latency Reversal

Of the 12 million people who inject drugs worldwide, 13% live with HIV. Whether opioid use impacts HIV pathogenesis and latency is an outstanding question. To gain insight into whether opioid use influences the proviral landscape and latent HIV reservoir, we performed intact proviral DNA assays (IPDA) on peripheral blood mononuclear cells (PBMCs) from antiretroviral therapy (ART)-suppressed people living with HIV (PWH) with or without current opioid use. No differences were observed between PWH with and without opioid use in the frequency of HIV intact and defective proviral genomes. To evaluate the latent reservoir, we activated PBMCs from ART-suppressed PWH with or without opioid use and assessed the induction of HIV RNA. PWH using opioids had diminished responses to ex vivo HIV reactivation, suggesting a smaller reversible reservoir of HIV-1 latently infected cells. However, in vitro studies using primary CD4+ T cells treated with morphine showed no effect of opioids on HIV-1 infection, replication or latency establishment. The discrepancy in our results from in vitro and clinical samples suggests that while opioids may not directly impact HIV replication, latency and reactivation in CD4+ T cells, opioid use may indirectly shape the HIV reservoir in vivo by modulating general immune functions.

Morphine suppresses peripheral responses and transforms brain myeloid gene expression to favor neuropathogenesis in SIV infection

The twin pandemics of opioid abuse and HIV infection can have devastating effects on physiological systems, including on the brain. Our previous work found that morphine increased the viral reservoir in the brains of treated SIV-infected macaques. In this study, we investigated the interaction of morphine and SIV to identify novel host-specific targets using a multimodal approach. We probed systemic parameters and performed single-cell examination of the targets for infection in the brain, microglia and macrophages. Morphine treatment created an immunosuppressive environment, blunting initial responses to infection, which persisted during antiretroviral treatment. Antiretroviral drug concentrations and penetration into the cerebrospinal fluid and brain were unchanged by morphine treatment. Interestingly, the transcriptional signature of both microglia and brain macrophages was transformed to one of a neurodegenerative phenotype. Notably, the expression of osteopontin, a pleiotropic cytokine, was significantly elevated in microglia. This was especially notable in the white matter, which is also dually affected by HIV and opioids. Increased osteopontin expression was linked to numerous HIV neuropathogenic mechanisms, including those that can maintain a viral reservoir. The opioid morphine is detrimental to SIV/HIV infection, especially in the brain.

Single cell transcriptomics reveals distinct transcriptional responses to oxycodone and buprenorphine by iPSC-derived brain organoids from patients with opioid use disorder

The opioid epidemic represents a national crisis. Oxycodone is one of the most prescribed opioid medications in the United States, whereas buprenorphine is currently the most prescribed medication for opioid use disorder (OUD) pharmacotherapy. Given the extensive use of prescription opioids and the global opioid epidemic, it is essential to understand how opioids modulate brain cell type function at the single-cell level. We performed single nucleus RNA-seq (snRNA-seq) using iPSC-derived forebrain organoids from three male OUD subjects in response to oxycodone, buprenorphine, or vehicle for seven days. We utilized the snRNA-seq data to identify differentially expressed genes following drug treatment using the Seurat integrative analysis pipeline. We utilized iPSC-derived forebrain organoids and single-cell sequencing technology as an unbiased tool to study cell-type-specific and drug-specific transcriptional responses. After quality control filtering, we analyzed 25787 cells and identified sixteen clusters using unsupervised clustering analysis. Our results reveal distinct transcriptional responses to oxycodone and buprenorphine by iPSC-derived brain organoids from patients with OUD. Specifically, buprenorphine displayed a significant influence on transcription regulation in glial cells. However, oxycodone induced type I interferon signaling in many cell types, including neural cells in brain organoids. Finally, we demonstrate that oxycodone, but not buprenorphine activated STAT1 and induced the type I interferon signaling in patients with OUD. These data suggest that elevation of STAT1 expression associated with OUD might play a role in transcriptional regulation in response to oxycodone. In summary, our results provide novel mechanistic insight into drug action at single-cell resolution.

Opioids and cancer survival: are we looking in the wrong place?

There is a controversial narrative in the anaesthetic literature suggesting that anaesthetic technique (including opioids) may be detrimental to survival after tumour resection. The initial observations were retrospective. Several prospective studies are ongoing; one in breast cancer has reported no adverse outcome. The evidence for an effect of opioids stems from three pieces of information: (1) opioids depress the immune system, (2) opioids potentially promote angiogenesis, and (3) opioids potentially support tumour growth. Although the evidence for (2)/(3) is unclear, combinations of these effects are beneficial to tumours and potentially promote metastatic reseeding. Accepted wisdom suggests that opioid effects are driven by opioid receptor activation but the presence of opioid receptors on immune cells for example is unlikely. Immune cells, vascular endothelium and a range of tumour cells express Toll-like receptor 4 (TLR4) receptors (for Gram-negative bacterial wall components), and there is growing evidence for opioids interacting with this alternative receptor; and for some there is paradoxical naloxone sensitivity. Is the focus on opioid receptors and cancer the wrong target? TLR4 receptor activation produces immune activation, stimulates angiogenesis, and supports tumour survival. We know that some opioids are more immune suppressive than others (there is no such comparative information for angiogenesis and tumour survival); this may correlate with TLR4 activation. If there are clusters of opioids that have more opioid than TLR4 profiles and vice versa, this may influence outcome. If this is the case, then evidence-based advice could be given for perioperative use in the oncology-anaesthesia setting.

Opioid-Use, COVID-19 Infection, and Their Neurological Implications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an imminent threat to human health and public safety. ACE2 and transmembrane serine protease 2 proteins on host cells provide the viral entry point to SARS-CoV-2. Although SARS-CoV-2 mainly infects the respiratory system, there have been reports of viral neurotropism and central nervous system injury as indicated by plasma biomarkers, including neurofilament light chain protein and glial fibrillary acidic protein. Even with a small proportion of infections leading to neurological manifestation, the overall number remains high. Common neurological manifestations of SARS-CoV-2 infection include anosmia, ageusia, encephalopathy, and stroke, which are not restricted to only the most severe infection cases. Opioids and opioid antagonists bind to the ACE2 receptor and thereby have been hypothesized to have therapeutic potential in treating COVID-19. However, in the case of other neurotropic viral infections such as human immunodeficiency virus (HIV), opioid use has been established to exacerbate HIV-mediated central nervous system pathogenesis. An analysis of electronic health record data from more than 73 million patients shows that people with Substance Use Disorders are at higher risk of contracting COVID-19 and suffer worse consequences then non-users. Our in-vivo and in-vitro unpublished studies show that morphine treatment causes increased expression of ACE2 in murine lung and brain tissue as early as 24 h post treatment. At the same time, we also observed morphine and lipopolysaccharides treatment lead to a synergistic increase in ACE2 expression in the microglial cell line, SIM-A9. This data suggests that opioid treatment may potentially increase neurotropism of SARS-CoV-2 infection. We have previously shown that opioids induce gut microbial dysbiosis. Similarly, gut microbiome alterations have been reported with SARS-CoV-2 infection and may play a role in predicting COVID-19 disease severity. However, there are no studies thus far linking opioid-mediated dysbiosis with the severity of neuron-specific COVID-19 infection.

GeneCup: mining PubMed and GWAS catalog for gene-keyword relationships

Interpreting and integrating results from omics studies typically requires a comprehensive and time consuming survey of extant literature. GeneCup is a literature mining web service that retrieves sentences containing user-provided gene symbols and keywords from PubMed abstracts. The keywords are organized into an ontology and can be extended to include results from human genome-wide association studies. We provide a drug addiction keyword ontology that contains over 300 keywords as an example. The literature search is conducted by querying the PubMed server using a programming interface, which is followed by retrieving abstracts from a local copy of the PubMed archive. The main results presented to the user are sentences where gene symbol and keywords co-occur. These sentences are presented through an interactive graphical interface or as tables. All results are linked to the original abstract in PubMed. In addition, a convolutional neural network is employed to distinguish sentences describing systemic stress from those describing cellular stress. The automated and comprehensive search strategy provided by GeneCup facilitates the integration of new discoveries from omic studies with existing literature. GeneCup is free and open source software. The source code of GeneCup and the link to a running instance is available at https://github.com/hakangunturkun/GeneCup.

Endogenous opiates and behavior: 2020

This paper is the forty-third consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2020 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

scHFC: a hybrid fuzzy clustering method for single-cell RNA-seq data optimized by natural computation

Rapid development of single-cell RNA sequencing (scRNA-seq) technology has allowed researchers to explore biological phenomena at the cellular scale. Clustering is a crucial and helpful step for researchers to study the heterogeneity of cell. Although many clustering methods have been proposed, massive dropout events and the curse of dimensionality in scRNA-seq data make it still difficult to analysis because they reduce the accuracy of clustering methods, leading to misidentification of cell types. In this work, we propose the scHFC, which is a hybrid fuzzy clustering method optimized by natural computation based on Fuzzy C Mean (FCM) and Gath-Geva (GG) algorithms. Specifically, principal component analysis algorithm is utilized to reduce the dimensions of scRNA-seq data after it is preprocessed. Then, FCM algorithm optimized by simulated annealing algorithm and genetic algorithm is applied to cluster the data to output a membership matrix, which represents the initial clustering result and is taken as the input for GG algorithm to get the final clustering results. We also develop a cluster number estimation method called multi-index comprehensive estimation, which can estimate the cluster numbers well by combining four clustering effectiveness indexes. The performance of the scHFC method is evaluated on 17 scRNA-seq datasets, and compared with six state-of-the-art methods. Experimental results validate the better performance of our scHFC method in terms of clustering accuracy and stability of algorithm. In short, scHFC is an effective method to cluster cells for scRNA-seq data, and it presents great potential for downstream analysis of scRNA-seq data. The source code is available at https://github.com/WJ319/scHFC.

Systems biological assessment of altered cytokine responses to bacteria and fungi reveals impaired immune functionality in schizophrenia

Evidence suggests that complex interactions between the immune system and brain have important etiological and therapeutic implications in schizophrenia. However, the detailed cellular and molecular basis of immune dysfunction in schizophrenia remains poorly characterized. To better understand the immune changes and molecular pathways, we systemically compared the cytokine responses of peripheral blood mononuclear cells (PBMCs) derived from patients with schizophrenia and controls against bacterial, fungal, and purified microbial ligands, and identified aberrant cytokine response patterns to various pathogens, as well as reduced cytokine production after stimulation with muramyl dipeptide (MDP) in schizophrenia. Subsequently, we performed single-cell RNA sequencing on unstimulated and stimulated PBMCs from patients and controls and revealed widespread suppression of antiviral and inflammatory programs as well as impaired chemokine/cytokine-receptor interaction networks in various immune cell subpopulations of schizophrenic patients after MDP stimulation. Moreover, serum MDP levels were elevated in these patients and correlated with the course of the disease, suggesting increased bacterial translocation along with disease progression. In vitro assays revealed that MDP pretreatment altered the functional response of normal PBMCs to its re-stimulation, which partially recapitulated the impaired immune function in schizophrenia. In conclusion, we delineated the molecular and cellular landscape of impaired immune function in schizophrenia, and proposed a mutual interplay between innate immune impairment, reduced pathogen clearance, increased MDP translocation along schizophrenia development, and blunted innate immune response. These findings provide new insights into the pathogenic mechanisms that drive systemic immune activation, neuroinflammation, and brain abnormalities in schizophrenia.

The neuroimmune response during stress: A physiological perspective

Stress is an essential adaptive response that enables the organism to cope with challenges and restore homeostasis. Different stressors require distinctive corrective responses in which immune cells play a critical role. Hence, effects of stress on immunity may vary accordingly. Indeed, epidemiologically, stress can induce either inflammation or immune suppression in an organism. However, in the absence of a conceptual framework, these effects appear chaotic, leading to confusion. Here, we examine how stressor diversity is imbedded in the neuroimmune axis. Stressors differ in the brain patterns they induce, diversifying the neuronal and endocrine mediators dispatched to the periphery and generating a wide range of potential immune effects. Uncovering this complexity and diversity of the immune response to different stressors will allow us to understand the involvement of stress in pathological conditions, identify ways to modulate it, and even harness the therapeutic potential embedded in an adaptive response to stress.

Where to Next? Research Directions after the First Hepatitis C Vaccine Efficacy Trial

Thirty years after its discovery, the hepatitis C virus (HCV) remains a leading cause of liver disease worldwide. Given that many countries continue to experience high rates of transmission despite the availability of potent antiviral therapies, an effective vaccine is seen as critical for the elimination of HCV. The recent failure of the first vaccine efficacy trial for the prevention of chronic HCV confirmed suspicions that this virus will be a challenging vaccine target. Here, we examine the published data from this first efficacy trial along with the earlier clinical and pre-clinical studies of the vaccine candidate and then discuss three key research directions expected to be important in ongoing and future HCV vaccine development. These include the following: 1. design of novel immunogens that generate immune responses to genetically diverse HCV genotypes and subtypes, 2. strategies to elicit broadly neutralizing antibodies against envelope glycoproteins in addition to cytotoxic and helper T cell responses, and 3. consideration of the unique immunological status of individuals most at risk for HCV infection, including those who inject drugs, in vaccine platform development and early immunogenicity trials.

Interfacing Seurat with the R tidy universe

Motivation

Seurat is one of the most popular software suites for the analysis of single-cell RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a large set of data display, query, manipulation, integration and visualization utilities, a great opportunity exists to interface the Seurat object with the tidyverse. This interface gives the large data science community of tidyverse users the possibility to operate with familiar grammar.

Results

To provide Seurat with a tidyverse-oriented interface without compromising efficiency, we developed tidyseurat, a lightweight adapter to the tidyverse. Tidyseurat displays cell information as a tibble abstraction, allowing intuitively interfacing Seurat with dplyr, tidyr, ggplot2 and plotly packages powering efficient data manipulation, integration and visualization. Iterative analyses on data subsets are enabled by interfacing with the popular nest-map framework.

Availability and implementation

The software is freely available at cran.r-project.org/web/packages/tidyseurat and github.com/stemangiola/tidyseurat.

Supplementary information

Supplementary data are available at Bioinformatics online.

Chronic morphine administration differentially modulates viral reservoirs in SIVmac251 infected rhesus macaque model

HIV persists in cellular reservoirs despite effective combined antiretroviral therapy (cART) and there is viremia flare up upon therapy interruption. Opioids modulate the immune system and suppress antiviral gene responses, which significantly impact people living with HIV (PLWH). However, the effect of opioids on viral reservoir dynamics remain elusive. Herein, we developed a morphine dependent SIVmac251 infected Rhesus macaque (RM) model to study the impact of opioids on HIV reservoirs. RMs on a morphine (or saline control) regimen were infected with SIVmac251. The cART was initiated in approximately half the animals five weeks post-infection, and morphine/saline administration continued until the end of the study. Among the untreated RM, we did not find any difference in plasma/CSF or in cell-associated DNA/RNA viral load in anatomical tissues. On the other hand, within the cART suppressed macaques, there was a reduction in cell-associated DNA load, intact proviral DNA levels, and in inducible SIV reservoir in lymph nodes (LNs) of morphine administered RMs. In distinction to LNs, in the CNS, the size of latent SIV reservoirs was higher in the CD11b+ microglia/macrophages in morphine dependent RMs. These results suggest that in the proposed model, morphine plays a differential role in SIV reservoirs by reducing the CD4+ T-cell reservoir in lymphoid tissues, while increasing the microglia/reservoir size in CNS tissue. The findings from this pre-clinical model will serve as a tool for screening therapeutic strategies to reduce/eliminate HIV reservoirs in opioid dependent PLWH.IMPORTANCE Identification and clearance of HIV reservoirs is a major challenge in achieving a cure for HIV. This is further complicated by co-morbidities that may alter the size of the reservoirs. There is an overlap between the risk factors for HIV and opioid abuse. Opiates have been recognized as prominent co-morbidities in HIV-infected populations. People infected with HIV also abusing opioids have immune modulatory effects and more severe neurological disease. However, the impact of opioid abuse on HIV reservoirs remains unclear. In this study, we used morphine dependent SIVmac251 infected rhesus macaque (RM) model to study the impact of opioids on HIV reservoirs. Our studies suggested that people with HIV who abuse opioids had higher reservoirs in CNS than the lymphoid system. Extrapolating the macaque findings in humans suggests that such differential modulation of HIV reservoirs among people living with HIV abusing opioids could be considered for future HIV cure research efforts.

Identifying Clear Cell Renal Cell Carcinoma Coexpression Networks Associated with Opioid Signaling and Survival

While opioids constitute the major component of perioperative analgesic regimens for surgery in general, a variety of evidence points to an association between perioperative opioid exposure and longer term oncologic outcomes. The mechanistic details underlying these effects are not well understood. In this study, we focused on clear cell renal cell carcinoma (ccRCC) and utilized RNA sequencing and outcome data from both The Cancer Genome Atlas, as well as a local patient cohort to identify survival-associated gene coexpression networks. We then projected drug-induced transcriptional profiles from in vitro cancer cells to predict drug effects on these networks and recurrence-free, cancer-specific, and overall survival. The opioid receptor agonist, leu-enkephalin, was predicted to have antisurvival effects in ccRCC, primarily through Th2 immune- and NRF2-dependent macrophage networks. Conversely, the antagonist, naloxone, was predicted to have prosurvival effects, primarily through angiogenesis, fatty acid metabolism, and hemopoesis pathways. Eight coexpression networks associated with survival endpoints in ccRCC were identified, and master regulators of the transition from the normal to disease state were inferred, a number of which are linked to opioid pathways. These results are the first to suggest a mechanism for opioid effects on cancer outcomes through modulation of survival-associated coexpression networks. While we focus on ccRCC, this methodology may be employed to predict opioid effects on other cancer types and to personalize analgesic regimens in patients with cancer for optimal outcomes. SIGNIFICANCE: This study suggests a possible molecular mechanism for opioid effects on cancer outcomes generally, with implications for personalization of analgesic regimens.

Fast and precise single-cell data analysis using a hierarchical autoencoder

A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce an analysis framework, named single-cell Decomposition using Hierarchical Autoencoder (scDHA), that reliably extracts representative information of each cell. The scDHA pipeline consists of two core modules. The first module is a non-negative kernel autoencoder able to remove genes or components that have insignificant contributions to the part-based representation of the data. The second module is a stacked Bayesian autoencoder that projects the data onto a low-dimensional space (compressed). To diminish the tendency to overfit of neural networks, we repeatedly perturb the compressed space to learn a more generalized representation of the data. In an extensive analysis, we demonstrate that scDHA outperforms state-of-the-art techniques in many research sub-fields of scRNA-seq analysis, including cell segregation through unsupervised learning, visualization of transcriptome landscape, cell classification, and pseudo-time inference.

Differential alteration in gut microbiome profiles during acquisition, extinction and reinstatement of morphine-induced CPP

Substance addiction is a chronic and complicated disease involving genetic and environmental factors. Coregulated by the above factors, perturbations of the gut microbiome have been shown to have an essential role in the development of many neuropsychiatric disorders, including addiction. However, shifts in the gut microbiome during different stages of morphine addiction remain uncharacterized. In the present study, we harvested fecal samples from mice at the acquisition (both the control and morphine groups), extinction and reinstatement stages of morphine-induced conditioned place preference (CPP). Gut microbiome profiles were detected with 16S ribosomal RNA gene sequencing. We observed an increase in community richness following morphine conditioning, and it decreased after 4 weeks of abstinence. The abundance of Verrucomicrobia increased and Bacteroides decreased at the acquisition of morphine-induced CPP, while a recovery trend was found at the extinction stage. Several discriminative genera were identified for the characterization of different stages of morphine CPP. Functional analysis of taxa with differential abundance between CPP stages was mainly enriched in the pathways of amino acid metabolism. Taken together, our findings will extend the association between dysbiosis of the gut microbiome and the opioid-induced rewarding or reinforcing behaviors.

Modeling SARS-CoV-2 infection in individuals with opioid use disorder with brain organoids

The COVID-19 pandemic has aggravated a preexisting epidemic: the opioid crisis. Much literature has shown that the circumstances imposed by COVID-19, such as social distancing regulations, medical and financial instability, and increased mental health issues, have been detrimental to those with opioid use disorder (OUD). In addition, unexpected neurological sequelae in COVID-19 patients suggest that COVID-19 compromises neuroimmunity, induces hypoxia, and causes respiratory depression, provoking similar effects as those caused by opioid exposure. Combined conditions of COVID-19 and OUD could lead to exacerbated complications. With limited human in vivo options to study these complications, we suggest that iPSC-derived brain organoid models may serve as a useful platform to investigate the physiological connection between COVID-19 and OUD. This mini-review highlights the advances of brain organoids in other neuropsychiatric and infectious diseases and suggests their potential utility for investigating OUD and COVID-19, respectively.

Effect of Opioid Use on Immune Activation and HIV Persistence on ART

While there is an emerging consensus that engagement of the Mu opioid receptor by opioids may modulate various stages the HIV life cycle (e.g.: increasing cell susceptibility to infection, promoting viral transcription, and depressing immune responses to virally-infected cells), the overall effect on latency and viral reservoirs remains unclear. Importantly, the hypothesis that the increase in immune activation observed in chronic opioid users by direct or indirect mechanisms (i.e., microbial translocation) would lead to a larger HIV reservoir after ART-suppression has not been supported to date. The potential for a subsequent decrease in reservoirs after ART-suppression has been postulated and is supported by early reports of opioid users having lower latent HIV burden. Here, we review experimental data supporting the link between opioid use and HIV modulation, as well as the scientific premise for expecting differential changes in immune activation and HIV reservoir between different medications for opioid use disorder. A better understanding of potential changes in HIV reservoirs relative to the engagement of the Mu opioid receptor and ART-mediated immune reconstitution will help guide future cure-directed studies in persons living with HIV and opioid use disorder. Graphical Abstract Review. HIV replication, immune activation and dysbiosis: opioids may affect immune reconstitution outcomes despite viral suppression.