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.

Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.

MOTIVATION: Recent years have seen the release of several toolsets that reveal cell-cell interactions from single-cell data. However, all existing approaches leverage mean celltype gene expression values, and do not preserve the single-cell fidelity of the original data. Here, we present NICHES (Niche Interactions and Communication Heterogeneity in Extracellular Signaling), a tool to explore extracellular signaling at the truly single-cell level. RESULTS: NICHES allows embedding of ligand-receptor signal proxies to visualize heterogeneous signaling archetypes within cell clusters, between cell clusters and across experimental conditions. When applied to spatial transcriptomic data, NICHES can be used to reflect local cellular microenvironment. NICHES can operate with any list of ligand-receptor signaling mechanisms, is compatible with existing single-cell packages, and allows rapid, flexible analysis of cell-cell signaling at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: NICHES is an open-source software implemented in R under academic free license v3.0 and it is available at http://github.com/msraredon/NICHES. Use-case vignettes are available at https://msraredon.github.io/NICHES/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Longitudinal single-cell analysis of a patient receiving adoptive cell therapy reveals potential mechanisms of treatment failure.

Adoptive cell therapy (ACT) using tumor infiltrating lymphocytes (TIL) is being studied in multiple tumor types. However, little is known about clonal cell expansion in vitro and persistence of the ACT product in vivo. We performed single-cell RNA and T-Cell Receptor (TCR) sequencing on serial blood and tumor samples from a patient undergoing ACT, who did not respond. We found that clonal expansion varied during preparation of the ACT product, and only one expanded clone was preserved in the ACT product. The TCR of the preserved clone which persisted and remained activated for five months was previously reported as specific for cytomegalovirus and had upregulation of granzyme family genes and genes associated with effector functions (HLA-DQB1, LAT, HLA-DQA1, and KLRD1). Clones that contracted during TIL preparation had features of exhaustion and apoptosis. At disease progression, all previously detected clonotypes were detected. New clonotypes appearing in blood or tumor at disease progression were enriched for genes associated with cytotoxicity or stemness (FGFBP2, GNLY, GZMH, GZMK, IL7R, SELL and KLF2), and these might be harnessed for alternative cellular therapy or cytokine therapy. In-depth single-cell analyses of serial samples from additional ACT-treated patients is warranted, and viral- versus tumor-specificity should be carefully analyzed.

Organ Boundary Circuits Regulate Sox9+ Alveolar Tuft Cells During Post-Pneumonectomy Lung Regeneration.

Tissue homeostasis is controlled by cellular circuits governing cell growth, organization, and differentation. In this study we identify previously undescribed cell-to-cell communication that mediates information flow from mechanosensitive pleural mesothelial cells to alveolar-resident stem-like tuft cells in the lung. We find mesothelial cells to express a combination of mechanotransduction genes and lineage-restricted ligands which makes them uniquely capable of responding to tissue tension and producing paracrine cues acting on parenchymal populations. In parallel, we describe a large population of stem-like alveolar tuft cells that express the endodermal stem cell markers Sox9 and Lgr5 and a receptor profile making them uniquely sensitive to cues produced by pleural Mesothelium. We hypothesized that crosstalk from mesothelial cells to alveolar tuft cells might be central to the regulation of post-penumonectomy lung regeneration. Following pneumonectomy, we find that mesothelial cells display radically altered phenotype and ligand expression, in a pattern that closely tracks with parenchymal epithelial proliferation and alveolar tissue growth. During an initial pro-inflammatory stage of tissue regeneration, Mesothelium promotes epithelial proliferation via WNT ligand secretion, orchestrates an increase in microvascular permeability, and encourages immune extravasation via chemokine secretion. This stage is followed first by a tissue remodeling period, characterized by angiogenesis and BMP pathway sensitization, and then a stable return to homeostasis. Coupled with key changes in parenchymal structure and matrix production, the cumulative effect is a now larger organ including newly-grown, fully-functional tissue parenchyma. This study paints Mesothelial cells as a key orchestrating cell type that defines the boundary of the lung and exerts critical influence over the tissue-level signaling state regulating resident stem cell populations. The cellular circuits unearthed here suggest that human lung regeneration might be inducible through well-engineered approaches targeting the induction of tissue regeneration and safe return to homeostasis.

Comparative assessments of VOC emission rates and associated health risks from wastewater treatment processes.

With the growing concern regarding emission of volatile organic compounds (VOCs) from wastewater treatment plants (WWTPs), the relationship between the VOC emission rates and the associated public health risks has been rarely discussed. The objective of this study was to examine and compare the VOC emission rates and cancer and non-cancer risks by inhalation intake, using a municipal WWTP in China as an example, with respect to the effects of treatment technologies, VOC species, and seasonal variation. Given the treatment technology considered, the emission rates of VOCs in this study were estimated by means of mass balance or calculated on the molecular level. From the viewpoints of both emission rates and cancer and non-cancer risks, sedimentation was the treatment technology with the highest health risks to the workers. Slightly lower VOC emission rates and health risks than those for sedimentation were observed in anaerobic treatment. Although the aeration significantly enhanced the VOC emission rates in the aerobic treatment process, the associated health risks were limited due to the low VOC concentrations in the gas phase, which were likely attributed to the strong mixing and dilution with fresh air by aeration. Amongst the VOCs investigated, benzene was the VOC with both a relatively high emission rate and health risk, while trichloroethylene possessed a high emission rate but the lowest health risk. Without strong interfacial aeration and turbulence between the water and atmosphere, the effects of treatment technology and seasonal variation on the health risks might be connected to the VOC emission rates, while the effect of VOC species depended considerably on the respective cancer slope factors and reference concentrations; the employment of aeration provided a different conclusion in which the emission rates were enhanced without a significant increase in the related cancer risks. These findings can provide insight into future health risk management and reduction strategies for workers in WWTPs.

Computation and visualization of cell-cell signaling topologies in single-cell systems data using Connectome.

Single-cell RNA-sequencing data has revolutionized our ability to understand of the patterns of cell-cell and ligand-receptor connectivity that influence the function of tissues and organs. However, the quantification and visualization of these patterns in a way that informs tissue biology are major computational and epistemological challenges. Here, we present Connectome, a software package for R which facilitates rapid calculation and interactive exploration of cell-cell signaling network topologies contained in single-cell RNA-sequencing data. Connectome can be used with any reference set of known ligand-receptor mechanisms. It has built-in functionality to facilitate differential and comparative connectomics, in which signaling networks are compared between tissue systems. Connectome focuses on computational and graphical tools designed to analyze and explore cell-cell connectivity patterns across disparate single-cell datasets and reveal biologic insight. We present approaches to quantify focused network topologies and discuss some of the biologic theory leading to their design.

Computational Study of HCV p7 Channel: Insight into a New Strategy for HCV Inhibitor Design.

HCV p7 protein is a cation-selective ion channel, playing an essential role during the life cycle of HCV viruses. To understand the cation-selective mechanism, we constructed a hexameric model in lipid bilayers of HCV p7 protein for HCB JFH-1 strain, genotype 2a. In this structural model, His9 and Val6 were key factors for the HCV cation-selective ion channel. The histidine residues at position 9 in the hexameric model formed a first gate for HCV p7 channel, acting as a selectivity filter for cations. The valines mentioned above formed a second gate for HCV p7 channel, serving as a hydrophobic filter for the dehydrated cations. The binding pocket for the channel blockers, e.g., amantadine and rimantadine, was composed of residues 20-26 in H2 helix and 52-60 in H3 helix in i + 2 monomer. However, the molecular volumes for both amantadine and rimantadine were too small for the binding pocket of HCV p7 channel. Thus, designing a compound similar with rimantadine and having much larger volume would be an effective strategy for discovering inhibitors against HCV p7 channel. To achieve this point, we used rimantadine as a structural template to search ChEMBL database for the candidates employing favorable binding affinities to HCV p7 channel. As a result, six candidates were identified to have potential to be novel inhibitors against HCV p7 channel.

PredT4SE-Stack: Prediction of Bacterial Type IV Secreted Effectors From Protein Sequences Using a Stacked Ensemble Method.

Gram-negative bacteria use various secretion systems to deliver their secreted effectors. Among them, type IV secretion system exists widely in a variety of bacterial species, and secretes type IV secreted effectors (T4SEs), which play vital roles in host-pathogen interactions. However, experimental approaches to identify T4SEs are time- and resource-consuming. In the present study, we aim to develop an in silico stacked ensemble method to predict whether a protein is an effector of type IV secretion system or not based on its sequence information. The protein sequences were encoded by the feature of position specific scoring matrix (PSSM)-composition by summing rows that correspond to the same amino acid residues in PSSM profiles. Based on the PSSM-composition features, we develop a stacked ensemble model PredT4SE-Stack to predict T4SEs, which utilized an ensemble of base-classifiers implemented by various machine learning algorithms, such as support vector machine, gradient boosting machine, and extremely randomized trees, to generate outputs for the meta-classifier in the classification system. Our results demonstrated that the framework of PredT4SE-Stack was a feasible and effective way to accurately identify T4SEs based on protein sequence information. The datasets and source code of PredT4SE-Stack are freely available at http://xbioinfo.sjtu.edu.cn/PredT4SE_Stack/index.php.

Fates of chlorinated volatile organic compounds in aerobic biological treatment processes: the effects of aeration and sludge addition.

The emission of volatile organic compounds (VOCs) from wastewater treatment plants (WWTPs) is becoming an environmental issue of increasing concern. As biological treatment has been considered as one important approach for VOC removal, lab-scale batch experiments were conducted in this study to investigate the fates of four chlorinated hydrocarbons, including chloroform, carbon tetrachloride, trichloroethylene (TCE), and tetrachloroethylene (PERC), in the biological treatment processes with respect to the effects of aeration and sludge addition. The VOC concentrations in the phases of air, water, and sludge under four simulated treatment stages (the first sedimentation, the forepart and rear part of aerobic biological treatment, and the second sedimentation) were analyzed. The results were used to understand the three-phase partitioning of these compounds and to estimate their potentials for volatilization and biological sorption and degradation in these technologies with the concept of fugacity. It was observed that the VOCs were mainly present in the water phase through the experiments. The effects of aeration or sludge addition on the fates of these VOCs occurred but appeared to be relatively limited. The concentration distributions of the VOCs were well below the reported partitioning coefficients. It was suggested that these compounds were unsaturated in the air and sludge phases, enhancing their potentials for volatilization and biological sorption/degradation through the processes. However, the properties of these chlorinated VOCs such as the volatility, polarity, or even biodegradability caused by their structural characteristics (e.g., the number of chlorine, saturated or unsaturated) may represent more significant factors for their fates in the aerobic biological treatment processes. These findings prove the complication behind the current knowledge of VOC pollutions in WWTPs and are of help to manage the adverse impacts on the environment and public health by the VOCs from these particular sources.

Underestimated public health risks caused by overestimated VOC removal in wastewater treatment processes.

The uncontrolled release of volatile organic compounds (VOCs) from wastewater treatment plants (WWTPs) and the adverse health effects on the public have been of increasing concern. In this study, a lab-scale bioreactor was prepared to analyze the mass distribution of three aromatic (benzene, toluene, and xylenes) and four chlorinated VOCs (chloroform, carbon tetrachloride, trichloroethylene, and tetrachloroethylene) among the air, water and sludge phases in wastewater treatment processes. The VOC distribution through a full-scale WWTP in northern China was further investigated with respect to the effects of seasonal temperature variations and treatment technologies, followed by the cancer risk assessment using a steady-state Gaussian plume model (Industrial Source Complex) to simulate the atmospheric behaviors of the VOCs emitted from the WWTP. It was found that three aromatic hydrocarbons, notably benzene, were more readily released from the wastewater into the atmosphere, whereas the chlorinated compounds except chloroform were mainly present in the water phase through the treatment processes. The primary clarifier was the technology releasing high levels of VOCs into the atmosphere from the wastewater. The extents of volatilization or biodegradation, two important mechanisms to remove VOCs from wastewater, appeared to be determined by the physicochemical characteristics of the compounds, as the influence of treatment technologies (e.g., aeration) and seasonal temperature variations was rather limited. More importantly, the people living in the areas even more than 4 km away from the WWTP were still potentially exposed to cancer risks exceeding the regulatory threshold limit. The findings described the complex nature of VOC emissions from WWTPs and quantitatively indicated that the associated health impacts on the public near the WWTPs could be severely underestimated, whereas their treatment efficiencies by wastewater treatment technologies were overestimated. Instead of fully controlling the VOC release from WWTPs, the identification and abatement of important VOC species with regard to the atmospheric emission and health concerns is one possible alternative approach to effectively minimize the environmental and public health impacts by VOCs released from this particular source.

[Spectroscopy properties of dissolved organic matter in landfill leachate during corrosion cell-Fenton post-treatment].

To differentiate the transformation of dissolved organic matter (DOM) during corrosion cell-Fenton (CCF) post-treatment, the leachate was separated into five fractions by XAD-8 and XAD-4 resins (hydrophilic fraction, HPI; hydrophobic acid, HPO-A; transphilic acid, TPI-A; hydrophobic neutral, HPO-N; transphilic neutral, TPI-N). UV-Vis spectroscopy and fluorescence spectroscopy were used for the degradation analysis. Experimental results showed that DOM in landfill leachate reduced 61.8% of dissolved organic carbon (DOC). Especially for HPO-A and HPO-N, with the removal ratios were up to 74.9% and 66.5%, respectively. The predominant portion in the effluent was HPI (comprising 60.1% of DOC). Spectral analyses showed that the leachate DOM was composed of abundant condensed ring aromatic compounds and humic substances, with the HPO-A was the highest aromatic fraction. The ratio of absorbance at 253 nm and 203 nm (E253/E203) was decreased in the order of HPO-A > HPO-N > TPI-A > TPI-N > HPI. The unsaturated conjugated structures were efficiently destroyed after the CCF treatment, and the functional groups such as carbonyl, amine were also eliminated. The main fluorophores in leachate fractions were in the region of aromatic protein-like and visible fulvic-like. The fluorescence intensity of peaks in each fraction decreased after CCF treatment, especially for the fulvic-like fluorescent substances. The results indicated that the CCF treatment was efficient to remove the hydrophobic fractions and reduce the complicacy of leachate effluent.

Characterization of dissolved organic matter during landfill leachate treatment by sequencing batch reactor, aeration corrosive cell-Fenton, and granular activated carbon in series.

Landfill leachate is generally characterized as a complex recalcitrant wastewater containing high concentration of dissolved organic matter (DOM). A combination of sequencing batch reactor (SBR)+aeration corrosive cell-Fenton (ACF)+granular activated carbon (GAC) adsorption in series was proposed for the purpose of removing pollutants in the leachate. Fractionation was also performed to investigate the composition changes and characteristics of the leachate DOM in each treatment process. Experimental results showed that organic matter, in terms of chemical oxygen demand (COD), 5-day biological oxygen demand (BOD(5)), and dissolved organic carbon (DOC), was reduced by 97.2%, 99.1%, and 98.7%, respectively. To differentiate the DOM portions, leachates were separated into five fractions by XAD-8 and XAD-4 resins: hydrophobic acid (HPO-A), hydrophobic neutral (HPO-N), transphilic acid (TPI-A), transphilic neutral (TPI-N), and hydrophilic fraction (HPI). The predominant fraction in the raw leachate was HPO-A (36% of DOC), while the dominant fraction in the final effluent was HPI (53% of DOC). Accordingly, macromolecules were degraded to simpler ones in a relatively narrow range below 1000 Da. Spectral and chromatographic analyses also showed that most humic-like substances in all fractions were effectively removed during the treatments and led to a simultaneous decrease in aromaticity.