Integrated single-cell analysis of multicellular immune dynamics during hyperacute HIV-1 infection

Epi-Clock: A sensitive platform to help understand pathogenic disease outbreaks and facilitate the response to future outbreaks of concern

To predict potential epidemic outbreaks, we tested our strategy, Epi-Clock, which applies the novel ZHU algorithm to different SARS-CoV-2 datasets before outbreaks to search for significant mutational accumulation patterns correlated with outbreak events. Surprisingly, some inter-species genetic distances in Coronaviridae may represent intermediate states of different species or subspecies in the evolutionary history of Coronaviridae. The insertions and deletions in whole-genome sequences between different hosts were separately associated with important roles in host transmission and shifts in Coronaviridae. Furthermore, we believe that non-nucleosomal DNA may play a dominant role in the divergence of different lineages of SARS-CoV-2 in different regions of the world owing to the lack of nucleosome protection. We suggest that strong selective variation among different lineages of SARS-CoV-2 is required to produce strong codon usage bias, which appears in B.1.640.2 and B.1.617.2 (Delta). Notably, we found that an increasing number of other types of substitutions, such as those resulting from the hitchhiking effect, accumulated, especially in the pre-breakout phase, although some of the previous substitutions were replaced by other dominant genotypes. From most validations, we could accurately predict the potential pre-phase of outbreaks with a median interval of 5 days.

FixNCut: A Practical Guide to Sample Preservation by Reversible Fixation for Single Cell Assays

The quality of standard single-cell experiments often depends on the immediate processing of cells or tissues post-harvest to preserve fragile and vulnerable cell populations, unless the samples are adequately fixed and stored. Despite the recent rise in popularity of probe-based and aldehyde-fixed RNA assays, these methods face limitations in species and target availability and are not suitable for immunoprofiling or assessing chromatin accessibility. Recently, a reversible fixation strategy known as FixNCut has been successfully deployed to separate sampling from downstream applications in a reproducible and robust manner, avoiding stress or necrosis-related artifacts. In this article, we present an optimized and robust practical guide to the FixNCut protocol to aid the end-to-end adaptation of this versatile method. This protocol not only decouples tissue or cell harvesting from single-cell assays but also enables a flexible and decentralized workflow that unlocks the potential for single-cell analysis as well as unconventional study designs that were previously considered unfeasible. Key features • Reversible fixation: Preserves cellular and molecular structures with the option to later reverse the fixation for downstream applications, maintaining cell integrity • Compatibility with single-cell assays: Supports single-cell genomic assays such as scRNA-seq and ATAC-seq, essential for high-resolution analysis of cell function and gene expression • Flexibility in sample handling: Allows immediate fixation post-collection, decoupling sample processing from analysis, beneficial in settings where immediate processing is impractical • Preservation of RNA and DNA integrity: Effectively preserves RNA and DNA, reducing degradation to ensure accurate transcriptomic and genomic profiling • Suitability for various biological samples: Applicable to a wide range of biological samples, including tissues and cell suspensions, whether freshly isolated or post-dissociated • Enables multi-center studies: Facilitates collaborative research across multiple centers by allowing sample fixation at the point of collection, enhancing research scale and diversity • Avoidance of artifacts: Minimizes stress or necrosis-related artifacts, preserving the natural cellular physiology for accurate genomic and transcriptomic analysis.

Delving deeper into the mechanisms fundamental to HIV-associated immunopathology using single-cell sequencing techniques: A scoping review of current literature

Human immunodeficiency virus (HIV) infection has evolved into an established global pandemic over the past four decades; however, despite massive research investment globally, the precise underlying mechanisms which are fundamental to HIV-related pathogenesis remain unclear. Single cell ribonucleic acid (RNA) sequencing methods are increasingly being used for the identification of specific cell-type transcriptional changes in HIV infection. In this scoping review, we have considered information extracted from fourteen published HIV-associated single-cell RNA sequencing-related studies, hoping to throw light on the underlying mechanisms of HIV infection and pathogenesis, and to explore potential candidate biomarkers for HIV disease progression and antiviral treatment. Generally, HIV positive individuals tend to manifest disturbances of frequency of multiple cellular types, and specifically exhibit diminished levels of CD4+ T-cells and enriched numbers of CD8+ T-cells. Cell-specific transcriptional changes tend to be linked to cell permissiveness, hyperacute or acute HIV infection, viremia, and cell productivity. The transcriptomes of CD4+ T-cell and CD8+ T-cell subpopulations are also observed to change in HIV-positive diabetic individuals, spontaneous HIV controllers, individuals with high levels of HIV viremia, and those in an acute phase of HIV infection. The transcriptional changes seen in B cells, natural killer (NK) cells, and myeloid dendritic cells (mDCs) of HIV-infected individuals demonstrate that the humoral immune response, antiviral response, and immune response regulation, respectively, are all altered following HIV infection. Antiretroviral therapy (ART) plays a crucial role in achieving immune reconstitution, in improving immunological disruption, and in mitigating immune system imbalances in HIV-infected individuals, while not fully restoring inherent cellular transcription to levels seen in HIV-negative individuals. The preceding observations not only illustrate compelling advances in the understanding of HIV-associated immunopathogenesis, but also identify specific cell-type transcriptional changes that may serve as potential biomarkers for HIV disease monitoring and therapeutic targeting.

Pan-cancer single-cell dissection reveals phenotypically distinct B cell subtypes

Characterizing the compositional and phenotypic characteristics of tumor-infiltrating B cells (TIBs) is important for advancing our understanding of their role in cancer development. Here, we establish a comprehensive resource of human B cells by integrating single-cell RNA sequencing data of B cells from 649 patients across 19 major cancer types. We demonstrate substantial heterogeneity in their total abundance and subtype composition and observe immunoglobulin G (IgG)-skewness of antibody-secreting cell isotypes. Moreover, we identify stress-response memory B cells and tumor-associated atypical B cells (TAABs), two tumor-enriched subpopulations with prognostic potential, shared in a pan-cancer manner. In particular, TAABs, characterized by a high clonal expansion level and proliferative capacity as well as by close interactions with activated CD4 T cells in tumors, are predictive of immunotherapy response. Our integrative resource depicts distinct clinically relevant TIB subsets, laying a foundation for further exploration of functional commonality and diversity of B cells in cancer.

A comparison of scRNA-seq annotation methods based on experimentally labeled immune cell subtype dataset

Cell-type annotation is a critical step in single-cell data analysis. With the development of numerous cell annotation methods, it is necessary to evaluate these methods to help researchers use them effectively. Reference datasets are essential for evaluation, but currently, the cell labels of reference datasets mainly come from computational methods, which may have computational biases and may not reflect the actual cell-type outcomes. This study first constructed an experimentally labeled immune cell-subtype single-cell dataset of the same batch and systematically evaluated 18 cell annotation methods. We assessed those methods under five scenarios, including intra-dataset validation, immune cell-subtype validation, unsupervised clustering, inter-dataset annotation, and unknown cell-type prediction. Accuracy and ARI were evaluation metrics. The results showed that SVM, scBERT, and scDeepSort were the best-performing supervised methods. Seurat was the best-performing unsupervised clustering method, but it couldn't fully fit the actual cell-type distribution. Our results indicated that experimentally labeled immune cell-subtype datasets revealed the deficiencies of unsupervised clustering methods and provided new dataset support for supervised methods.

scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning

Single-cell sequencing is a crucial tool for dissecting the cellular intricacies of complex diseases. Its prohibitive cost, however, hampers its application in expansive biomedical studies. Traditional cellular deconvolution approaches can infer cell type proportions from more affordable bulk sequencing data, yet they fall short in providing the detailed resolution required for single-cell-level analyses. To overcome this challenge, we introduce "scSemiProfiler", an innovative computational framework that marries deep generative models with active learning strategies. This method adeptly infers single-cell profiles across large cohorts by fusing bulk sequencing data with targeted single-cell sequencing from a few rigorously chosen representatives. Extensive validation across heterogeneous datasets verifies the precision of our semi-profiling approach, aligning closely with true single-cell profiling data and empowering refined cellular analyses. Originally developed for extensive disease cohorts, "scSemiProfiler" is adaptable for broad applications. It provides a scalable, cost-effective solution for single-cell profiling, facilitating in-depth cellular investigation in various biological domains.

NKp30 and NKG2D contribute to natural killer recognition of HIV-infected cells

Natural killer (NK) cells respond rapidly in early HIV-1 infection. HIV-1 prevention and control strategies harnessing NK cells could be enabled by mechanistic understanding of how NK cells recognize HIV-infected T cells. Here, we profiled the phenotype of human primary NK cells responsive to autologous HIV-1-infected CD4 + T cells in vitro. We characterized the patterns of NK cell ligand expression on CD4 + T cells at baseline and after infection with a panel of transmitted/founder HIV-1 strains to identify key receptor-ligand pairings. CRISPR editing of CD4 + T cells to knockout the NKp30 ligand B7-H6, or the NKG2D ligands MICB or ULBP2 reduced NK cell responses to HIV-infected cells in some donors. In contrast, overexpression of NKp30 or NKG2D in NK cells enhanced their targeting of HIV-infected cells. Collectively, we identified receptor-ligand pairs including NKp30:B7-H6 and NKG2D:MICB/ULBP2 that contribute to NK cell recognition of HIV-infected cells.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

HIV-1 infection is associated with depletion of germinal center B cells and a decrease in IgA + plasma cells in the GI tract

Gastrointestinal (GI) B cells and plasma cells (PCs), critical to mucosal homeostasis, play an important role in the host response to HIV-1 infection. Here, high resolution mapping of human B cells and PCs from colon and ileum during both viremic and suppressed HIV-1 infection identified a significant reduction in germinal center (GC) B cells and Follicular Dendritic Cells (FDCs) during HIV-1 viremia. Further, IgA + PCs, the major cellular output of intestinal GCs were significantly reduced during viremic HIV-1 infection. PC-associated transcriptional perturbations, including type I interferon signaling persisted in antiretroviral therapy (ART) treated individuals, suggesting ongoing disruption of the intestinal immune milieu during ART. GI humoral immune perturbations associated with changes in intestinal microbiome composition and systemic inflammation. Herein, we highlight a key immune defect in the GI mucosa due to HIV-1 viremia, with major implications.

One Sentence Summary

Major perturbations in intestinal GC dynamics in viremic HIV-1 infection relate to reduced IgA + plasma cells, systemic inflammation and microbiota changes.

Adaptive NK Cells Rapidly Expand during Acute HIV Infection and Persist Despite Early Initiation of Antiretroviral Therapy

HIV is associated with NK cell dysfunction and expansion of adaptive-like NK cells that persist despite antiretroviral therapy (ART). We investigated the timing of NK cell perturbations during acute HIV infection and the impact of early ART initiation. PBMCs and plasma were obtained from people with HIV (PWH; all men who have sex with men; median age, 26.0 y) diagnosed during Fiebig stages I, II, III, or IV/V. Participants initiated ART a median of 3 d after diagnosis, and immunophenotyping was performed at diagnosis and longitudinally after ART. Anti-CMV Abs were assessed by ELISA. Samples from matched HIV-uninfected males were also analyzed. Proportions of adaptive NK cells (A-NKs; defined as Fcε-Receptor-1γ-) were expanded at HIV diagnosis at all Fiebig stages (pooled median 66% versus 25% for controls; p < 0.001) and were not altered by early ART initiation. Abs to CMV immediate early protein were elevated in PWH diagnosed in Fiebig stages III and IV/V (p < 0.03 for both). Proportions of A-NKs defined as either Fcε-Receptor-1γ- or NKG2C+/CD57+ were significantly associated with HIV DNA levels at diagnosis (p = 0.046 and 0.029, respectively) and trended toward an association after 48 wk of ART. Proportions of activated HLA-DR+/CD38+ NK cells remained elevated in PWH despite early ART initiation. NK cell activation and A-NK expansion occur very early after HIV transmission, before T cell activation, and are not altered by ART initiation during acute infection. A-NKs may contribute to HIV control and thus be useful for HIV cure.

Peripheral priming induces plastic transcriptomic and proteomic responses in circulating neutrophils required for pathogen containment

Neutrophils rapidly respond to inflammation and infection, but to which degree their functional trajectories after mobilization from the bone marrow are shaped within the circulation remains vague. Experimental limitations have so far hampered neutrophil research in human disease. Here, using innovative fixation and single-cell-based toolsets, we profile human and murine neutrophil transcriptomes and proteomes during steady state and bacterial infection. We find that peripheral priming of circulating neutrophils leads to dynamic shifts dominated by conserved up-regulation of antimicrobial genes across neutrophil substates, facilitating pathogen containment. We show the TLR4/NF-κB signaling-dependent up-regulation of canonical neutrophil activation markers like CD177/NB-1 during acute inflammation, resulting in functional shifts in vivo. Blocking de novo RNA synthesis in circulating neutrophils abrogates these plastic shifts and prevents the adaptation of antibacterial neutrophil programs by up-regulation of distinct effector molecules upon infection. These data underline transcriptional plasticity as a relevant mechanism of functional neutrophil reprogramming during acute infection to foster bacterial containment within the circulation.

Comparative analysis of cell-cell communication at single-cell resolution

Inference of cell-cell communication from single-cell RNA sequencing data is a powerful technique to uncover intercellular communication pathways, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell-level information. Here we present Scriabin, a flexible and scalable framework for comparative analysis of cell-cell communication at single-cell resolution that is performed without cell aggregation or downsampling. We use multiple published atlas-scale datasets, genetic perturbation screens and direct experimental validation to show that Scriabin accurately recovers expected cell-cell communication edges and identifies communication networks that can be obscured by agglomerative methods. Additionally, we use spatial transcriptomic data to show that Scriabin can uncover spatial features of interaction from dissociated data alone. Finally, we demonstrate applications to longitudinal datasets to follow communication pathways operating between timepoints. Our approach represents a broadly applicable strategy to reveal the full structure of niche-phenotype relationships in health and disease.

Bispecific antibodies promote natural killer cell-mediated elimination of HIV-1 reservoir cells

The persistence of CD4+ T cells carrying latent human immunodeficiency virus-1 (HIV-1) proviruses is the main barrier to a cure. New therapeutics to enhance HIV-1-specific immune responses and clear infected cells will probably be necessary to achieve reduction of the latent reservoir. In the present study, we report two single-chain diabodies (scDbs) that target the HIV-1 envelope protein (Env) and the human type III Fcγ receptor (CD16). We show that the scDbs promoted robust and HIV-1-specific natural killer (NK) cell activation and NK cell-mediated lysis of infected cells. Cocultures of CD4+ T cells from people with HIV-1 on antiretroviral therapy (ART) with autologous NK cells and the scDbs resulted in marked elimination of reservoir cells that was dependent on latency reversal. Treatment of human interleukin-15 transgenic NSG mice with one of the scDbs after ART initiation enhanced NK cell activity and reduced reservoir size. Thus, HIV-1-specific scDbs merit further evaluation as potential therapeutics for clearance of the latent reservoir.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Harnessing immune cells to eliminate HIV reservoirs

PURPOSE OF REVIEW

Despite decades of insights about how CD8 + T cells and natural killer (NK) cells contribute to natural control of infection, additional hurdles (mutational escape from cellular immunity, sequence diversity, and hard-to-access tissue reservoirs) will need to be overcome to develop a cure. In this review, we highlight recent findings of novel mechanisms of antiviral cellular immunity and discuss current strategies for therapeutic deisgn.

RECENT FINDINGS

Of note are the apparent converging roles of viral antigen-specific MHC-E-restricted CD8 + T cells and NK cells, interleukin (IL)-15 biologics to boost cytotoxicity, and broadly neutralizing antibodies in their native form or as anitbody fragments to neutralize virus and engage cellular immunity, respectively. Finally, renewed interest in myeloid cells as relevant viral reservoirs is an encouraging sign for designing inclusive therapeutic strategies.

SUMMARY

Several studies have shown promise in many preclinical models of disease, including simian immunodeficiency virus (SIV)/SHIV infection in nonhuman primates and HIV infection in humanized mice. However, each model comes with its own limitations and may not fully predict human responses. We eagerly await the results of clinical trails assessing the efficacy of these strategies to achieve reductions in viral reservoirs, delay viral rebound, or ultimately elicit immune based control of infection without combination antiretroviral therapy (cART).

Pro-inflammatory feedback loops define immune responses to pathogenic Lentivirus infection

BACKGROUND

The Lentivirus human immunodeficiency virus (HIV) causes chronic inflammation and AIDS in humans, with variable rates of disease progression between individuals driven by both host and viral factors. Similarly, simian lentiviruses vary in their pathogenicity based on characteristics of both the host species and the virus strain, yet the immune underpinnings that drive differential Lentivirus pathogenicity remain incompletely understood.

METHODS

We profile immune responses in a unique model of differential lentiviral pathogenicity where pig-tailed macaques are infected with highly genetically similar variants of SIV that differ in virulence. We apply longitudinal single-cell transcriptomics to this cohort, along with single-cell resolution cell-cell communication techniques, to understand the immune mechanisms underlying lentiviral pathogenicity.

RESULTS

Compared to a minimally pathogenic lentiviral variant, infection with a highly pathogenic variant results in a more delayed, broad, and sustained activation of inflammatory pathways, including an extensive global interferon signature. Conversely, individual cells infected with highly pathogenic Lentivirus upregulated fewer interferon-stimulated genes at a lower magnitude, indicating that highly pathogenic Lentivirus has evolved to partially escape from interferon responses. Further, we identify CXCL10 and CXCL16 as important molecular drivers of inflammatory pathways specifically in response to highly pathogenic Lentivirus infection. Immune responses to highly pathogenic Lentivirus infection are characterized by amplifying regulatory circuits of pro-inflammatory cytokines with dense longitudinal connectivity.

CONCLUSIONS

Our work presents a model of lentiviral pathogenicity where failures in early viral control mechanisms lead to delayed, sustained, and amplifying pro-inflammatory circuits, which in turn drives disease progression.

Early cellular and molecular signatures correlate with severity of West Nile virus infection

Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

Development trends of human organoid-based COVID-19 research based on bibliometric analysis

Coronavirus disease 2019 (COVID-19), a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed a catastrophic threat to human health worldwide. Human stem cell-derived organoids serve as a promising platform for exploring SARS-CoV-2 infection. Several review articles have summarized the application of human organoids in COVID-19, but the research status and development trend of this field have seldom been systematically and comprehensively studied. In this review, we use bibliometric analysis method to identify the characteristics of organoid-based COVID-19 research. First, an annual trend of publications and citations, the most contributing countries or regions and organizations, co-citation analysis of references and sources and research hotspots are determined. Next, systematical summaries of organoid applications in investigating the pathology of SARS-CoV-2 infection, vaccine development and drug discovery, are provided. Lastly, the current challenges and future considerations of this field are discussed. The present study will provide an objective angle to identify the current trend and give novel insights for directing the future development of human organoid applications in SARS-CoV-2 infection.

Single-Cell RNA Sequencing Reveals That Adaptation of Human Aortic Endothelial Cells to Antiproliferative Therapies Is Modulated by Flow-Induced Shear Stress

BACKGROUND

Endothelial cells (ECs) are capable of quickly responding in a coordinated manner to a wide array of stresses to maintain vascular homeostasis. Loss of EC cellular adaptation may be a potential marker for cardiovascular disease and a predictor of poor response to endovascular pharmacological interventions such as drug-eluting stents. Here, we report single-cell transcriptional profiling of ECs exposed to multiple stimulus classes to evaluate EC adaptation.

METHODS

Human aortic ECs were costimulated with both pathophysiological flows mimicking shear stress levels found in the human aorta (laminar and turbulent, ranging from 2.5 to 30 dynes/cm2) and clinically relevant antiproliferative drugs, namely paclitaxel and rapamycin. EC state in response to these stimuli was defined using single-cell RNA sequencing.

RESULTS

We identified differentially expressed genes and inferred the TF (transcription factor) landscape modulated by flow shear stress using single-cell RNA sequencing. These flow-sensitive markers differentiated previously identified spatially distinct subpopulations of ECs in the murine aorta. Moreover, distinct transcriptional modules defined flow- and drug-responsive EC adaptation singly and in combination. Flow shear stress was the dominant driver of EC state, altering their response to pharmacological therapies.

CONCLUSIONS

We showed that flow shear stress modulates the cellular capacity of ECs to respond to paclitaxel and rapamycin administration, suggesting that while responding to different flow patterns, ECs experience an impairment in their transcriptional adaptation to other stimuli.

γδ T cells: origin and fate, subsets, diseases and immunotherapy

The intricacy of diseases, shaped by intrinsic processes like immune system exhaustion and hyperactivation, highlights the potential of immune renormalization as a promising strategy in disease treatment. In recent years, our primary focus has centered on γδ T cell-based immunotherapy, particularly pioneering the use of allogeneic Vδ2+ γδ T cells for treating late-stage solid tumors and tuberculosis patients. However, we recognize untapped potential and optimization opportunities to fully harness γδ T cell effector functions in immunotherapy. This review aims to thoroughly examine γδ T cell immunology and its role in diseases. Initially, we elucidate functional differences between γδ T cells and their αβ T cell counterparts. We also provide an overview of major milestones in γδ T cell research since their discovery in 1984. Furthermore, we delve into the intricate biological processes governing their origin, development, fate decisions, and T cell receptor (TCR) rearrangement within the thymus. By examining the mechanisms underlying the anti-tumor functions of distinct γδ T cell subtypes based on γδTCR structure or cytokine release, we emphasize the importance of accurate subtyping in understanding γδ T cell function. We also explore the microenvironment-dependent functions of γδ T cell subsets, particularly in infectious diseases, autoimmune conditions, hematological malignancies, and solid tumors. Finally, we propose future strategies for utilizing allogeneic γδ T cells in tumor immunotherapy. Through this comprehensive review, we aim to provide readers with a holistic understanding of the molecular fundamentals and translational research frontiers of γδ T cells, ultimately contributing to further advancements in harnessing the therapeutic potential of γδ T cells.

Identification of drug candidates targeting monocyte reprogramming in people living with HIV

Introduction

People living with HIV (PLHIV) are characterized by functional reprogramming of innate immune cells even after long-term antiretroviral therapy (ART). In order to assess technical feasibility of omics technologies for application to larger cohorts, we compared multiple omics data layers.

Methods

Bulk and single-cell transcriptomics, flow cytometry, proteomics, chromatin landscape analysis by ATAC-seq as well as ex vivo drug stimulation were performed in a small number of blood samples derived from PLHIV and healthy controls from the 200-HIV cohort study.

Results

Single-cell RNA-seq analysis revealed that most immune cells in peripheral blood of PLHIV are altered in their transcriptomes and that a specific functional monocyte state previously described in acute HIV infection is still existing in PLHIV while other monocyte cell states are only occurring acute infection. Further, a reverse transcriptome approach on a rather small number of PLHIV was sufficient to identify drug candidates for reversing the transcriptional phenotype of monocytes in PLHIV.

Discussion

These scientific findings and technological advancements for clinical application of single-cell transcriptomics form the basis for the larger 2000-HIV multicenter cohort study on PLHIV, for which a combination of bulk and single-cell transcriptomics will be included as the leading technology to determine disease endotypes in PLHIV and to predict disease trajectories and outcomes.

Single cell transcriptomics shows that malaria promotes unique regulatory responses across multiple immune cell subsets

Plasmodium falciparum malaria drives immunoregulatory responses across multiple cell subsets, which protects from immunopathogenesis, but also hampers the development of effective anti-parasitic immunity. Understanding malaria induced tolerogenic responses in specific cell subsets may inform development of strategies to boost protective immunity during drug treatment and vaccination. Here, we analyse the immune landscape with single cell RNA sequencing during P. falciparum malaria. We identify cell type specific responses in sub-clustered major immune cell types. Malaria is associated with an increase in immunosuppressive monocytes, alongside NK and γδ T cells which up-regulate tolerogenic markers. IL-10-producing Tr1 CD4 T cells and IL-10-producing regulatory B cells are also induced. Type I interferon responses are identified across all cell types, suggesting Type I interferon signalling may be linked to induction of immunoregulatory networks during malaria. These findings provide insights into cell-specific and shared immunoregulatory changes during malaria and provide a data resource for further analysis.

Single-cell epigenetic, transcriptional, and protein profiling of latent and active HIV-1 reservoir revealed that IKZF3 promotes HIV-1 persistence

Understanding how HIV-1-infected cells proliferate and persist is key to HIV-1 eradication, but the heterogeneity and rarity of HIV-1-infected cells hamper mechanistic interrogations. Here, we used single-cell DOGMA-seq to simultaneously capture transcription factor accessibility, transcriptome, surface proteins, HIV-1 DNA, and HIV-1 RNA in memory CD4+ T cells from six people living with HIV-1 during viremia and after suppressive antiretroviral therapy. We identified increased transcription factor accessibility in latent HIV-1-infected cells (RORC) and transcriptionally active HIV-1-infected cells (interferon regulatory transcription factor [IRF] and activator protein 1 [AP-1]). A proliferation program (IKZF3, IL21, BIRC5, and MKI67 co-expression) promoted the survival of transcriptionally active HIV-1-infected cells. Both latent and transcriptionally active HIV-1-infected cells had increased IKZF3 (Aiolos) expression. Distinct epigenetic programs drove the heterogeneous cellular states of HIV-1-infected cells: IRF:activation, Eomes:cytotoxic effector differentiation, AP-1:migration, and cell death. Our study revealed the single-cell epigenetic, transcriptional, and protein states of latent and transcriptionally active HIV-1-infected cells and cellular programs promoting HIV-1 persistence.

Lymph node dendritic cells harbor inducible replication-competent HIV despite years of suppressive ART

Although gut and lymph node (LN) memory CD4 T cells represent major HIV and simian immunodeficiency virus (SIV) tissue reservoirs, the study of the role of dendritic cells (DCs) in HIV persistence has long been limited to the blood due to difficulties to access lymphoid tissue samples. In this study, we show that LN migratory and resident DC subpopulations harbor distinct phenotypic and transcriptomic profiles. Interestingly, both LN DC subpopulations contain HIV intact provirus and inducible replication-competent HIV despite the expression of the antiviral restriction factor SAMHD1. Notably, LN DC subpopulations isolated from HIV-infected individuals treated for up to 14 years are transcriptionally silent but harbor replication-competent virus that can be induced upon TLR7/8 stimulation. Taken together, these results uncover a potential important contribution of LN DCs to HIV infection in the presence of ART.

Single-Cell Transcriptomics of Mtb/HIV Co-Infection

Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection continues to pose a significant healthcare burden. HIV co-infection during TB predisposes the host to the reactivation of latent TB infection (LTBI), worsening disease conditions and mortality. There is a lack of biomarkers of LTBI reactivation and/or immune-related transcriptional signatures to distinguish active TB from LTBI and predict TB reactivation upon HIV co-infection. Characterizing individual cells using next-generation sequencing-based technologies has facilitated novel biological discoveries about infectious diseases, including TB and HIV pathogenesis. Compared to the more conventional sequencing techniques that provide a bulk assessment, single-cell RNA sequencing (scRNA-seq) can reveal complex and new cell types and identify more high-resolution cellular heterogeneity. This review will summarize the progress made in defining the immune atlas of TB and HIV infections using scRNA-seq, including host-pathogen interactions, heterogeneity in HIV pathogenesis, and the animal models employed to model disease. This review will also address the tools needed to bridge the gap between disease outcomes in single infection vs. co-infection. Finally, it will elaborate on the translational benefits of single-cell sequencing in TB/HIV diagnosis in humans.

Cellular state landscape and herpes simplex virus type 1 infection progression are connected

Prediction, prevention and treatment of virus infections require understanding of cell-to-cell variability that leads to heterogenous disease outcomes, but the source of this heterogeneity has yet to be clarified. To study the multimodal response of single human cells to herpes simplex virus type 1 (HSV-1) infection, we mapped high-dimensional viral and cellular state spaces throughout the infection using multiplexed imaging and quantitative single-cell measurements of viral and cellular mRNAs and proteins. Here we show that the high-dimensional cellular state scape can predict heterogenous infections, and cells move through the cellular state landscape according to infection progression. Spatial information reveals that infection changes the cellular state of both infected cells and of their neighbors. The multiplexed imaging of HSV-1-induced cellular modifications links infection progression to changes in signaling responses, transcriptional activity, and processing bodies. Our data show that multiplexed quantification of responses at the single-cell level, across thousands of cells helps predict infections and identify new targets for antivirals.

NK cell phenotypic profile during active TB in people living with HIV-evolution during TB treatment and implications for bacterial clearance and disease severity

Natural killer (NK) cells, key effector cells of the innate immune system, play an important role in the clearance and control of Mycobacterium tuberculosis and HIV infections. Here, we utilized peripheral blood specimens from the Improving Retreatment Success CAPRISA 011 study to characterize NK cell phenotypes during active TB in individuals with or without HIV co-infection. We further assessed the effects of TB treatment on NK cell phenotype, and characterized the effects of NK cell phenotypes during active TB on mycobacterial clearance and TB disease severity measured by the presence of lung cavitation. TB/HIV co-infection led to the expansion of functionally impaired CD56neg NK cell subset. TB treatment completion resulted in restoration of total NK cells, NK cell subset redistribution and downregulation of several NK cell activating and inhibitory receptors. Higher percentage of peripheral CD56bright cells was associated with longer time to culture conversion, while higher expression of NKp46 on CD56dim NK cells was associated with lower odds of lung cavitation in the overall cohort and the TB/HIV co-infected participants. Together these results provide a detailed description of peripheral NK cells in TB and TB/HIV co-infection and yield insights into their role in TB disease pathology.

Transcriptome-based measurement of CD8+ T cell age and its applications

The ability of T cells to undergo robust cell division in response to antigenic stimulation is essential for competent T cell function. However, this ability is reduced with aging and contributes to increased susceptibility to infectious diseases, cancers, and other diseases among older adults. To better understand T cell aging, improved measurements of age-related cellular changes in T cells are necessary. The recent development of machine learning (ML)-assisted transcriptome-based quantification of individual CD8+ T cell age represents a significant step forward in this regard. It reveals both prominent and subtle changes in gene expression and points to potential functional alterations of CD8+ T cells with aging. I argue that single-cell transcriptome-based age prediction in the immune system may have promising future applications.

Single-cell profiling of lncRNA expression during Ebola virus infection in rhesus macaques

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and are pivotal mediators of the immune response, yet little is known about their properties at the single-cell level. Here, we generate a multi-tissue bulk RNAseq dataset from Ebola virus (EBOV) infected and not-infected rhesus macaques and identified 3979 novel lncRNAs. To profile lncRNA expression dynamics in immune circulating single-cells during EBOV infection, we design a metric, Upsilon, to estimate cell-type specificity. Our analysis reveals that lncRNAs are expressed in fewer cells than protein-coding genes, but they are not expressed at lower levels nor are they more cell-type specific when expressed in the same number of cells. In addition, we observe that lncRNAs exhibit similar changes in expression patterns to those of protein-coding genes during EBOV infection, and are often co-expressed with known immune regulators. A few lncRNAs change expression specifically upon EBOV entry in the cell. This study sheds light on the differential features of lncRNAs and protein-coding genes and paves the way for future single-cell lncRNA studies.

Brain volumetrics differ by Fiebig stage in acute HIV infection

OBJECTIVE

People with chronic HIV exhibit lower regional brain volumes compared to people without HIV (PWOH). Whether imaging alterations observed in chronic infection occur in acute HIV infection (AHI) remains unknown.

DESIGN

Cross-sectional study of Thai participants with AHI.

METHODS

One hundred and twelve Thai males with AHI (age 20-46) and 18 male Thai PWOH (age 18-40) were included. Individuals with AHI were stratified into early (Fiebig I-II; n  = 32) and late (Fiebig III-V; n  = 80) stages of acute infection using validated assays. T1-weighted scans were acquired using a 3 T MRI performed within five days of antiretroviral therapy (ART) initiation. Volumes for the amygdala, caudate nucleus, hippocampus, nucleus accumbens, pallidum, putamen, and thalamus were compared across groups.

RESULTS

Participants in late Fiebig stages exhibited larger volumes in the nucleus accumbens (8% larger; P  = 0.049) and putamen (19%; P  < 0.001) when compared to participants in the early Fiebig. Compared to PWOH, participants in late Fiebig exhibited larger volumes of the amygdala (9% larger; P  = 0.002), caudate nucleus (11%; P  = 0.005), nucleus accumbens (15%; P  = 0.004), pallidum (19%; P  = 0.001), and putamen (31%; P  < 0.001). Brain volumes in the nucleus accumbens, pallidum, and putamen correlated modestly with stimulant use over the past four months among late Fiebig individuals ( P s < 0.05).

CONCLUSIONS

Findings indicate that brain volume alterations occur in acute infection, with the most prominent differences evident in the later stages of AHI. Additional studies are needed to evaluate mechanisms for possible brain disruption following ART, including viral factors and markers of neuroinflammation.

Gene dysregulation in acute HIV-1 infection – early transcriptomic analysis reveals the crucial biological functions affected

Introduction

Transcriptomic analyses from early human immunodeficiency virus (HIV) infection have the potential to reveal how HIV causes widespread and lasting damage to biological functions, especially in the immune system. Previous studies have been limited by difficulties in obtaining early specimens.

Methods

A hospital symptom-based screening approach was applied in a rural Mozambican setting to enrol patients with suspected acute HIV infection (Fiebig stage I-IV). Blood samples were collected from all those recruited, so that acute cases and contemporaneously recruited, uninfected controls were included. PBMC were isolated and sequenced using RNA-seq. Sample cellular composition was estimated from gene expression data. Differential gene expression analysis was completed, and correlations were determined between viral load and differential gene expression. Biological implications were examined using Cytoscape, gene set enrichment analysis, and enrichment mapping.

Results

Twenty-nine HIV infected subjects one month from presentation and 46 uninfected controls were included in this study. Subjects with acute HIV infection demonstrated profound gene dysregulation, with 6131 (almost 13% of the genome mapped in this study) significantly differentially expressed. Viral load was correlated with 1.6% of dysregulated genes, in particular, highly upregulated genes involved in key cell cycle functions, were correlated with viremia. The most profoundly upregulated biological functions related to cell cycle regulation, in particular, CDCA7 may drive aberrant cell division, promoted by overexpressed E2F family proteins. Also upregulated were DNA repair and replication, microtubule and spindle organization, and immune activation and response. The interferome of acute HIV was characterized by broad activation of interferon-stimulated genes with antiviral functions, most notably IFI27 and OTOF. BCL2 downregulation alongside upregulation of several apoptotic trigger genes and downstream effectors may contribute to cycle arrest and apoptosis. Transmembrane protein 155 (TMEM155) was consistently highly overexpressed during acute infection, with roles hitherto unknown.

Discussion

Our study contributes to a better understanding of the mechanisms of early HIV-induced immune damage. These findings have the potential to lead to new earlier interventions that improve outcomes.

The immune cell landscape and response of Marek's disease resistant and susceptible chickens infected with Marek's disease virus

Genetically resistant or susceptible chickens to Marek's disease (MD) have been widely used models to identify the molecular determinants of these phenotypes. However, these prior studies lacked the basic identification and understanding of immune cell types that could be translated toward improved MD control. To gain insights into specific immune cell types and their responses to Marek's disease virus (MDV) infection, we used single-cell RNA sequencing (scRNAseq) on splenic cells from MD resistant and susceptible birds. In total, 14,378 cells formed clusters that identified various immune cell types. Lymphocytes, specifically T cell subtypes, were the most abundant with significant proportional changes in some subtypes upon infection. The largest number of differentially expressed genes (DEG) response was seen in granulocytes, while macrophage DEGs differed in directionality by subtype and line. Among the most DEG in almost all immune cell types were granzyme and granulysin, both associated with cell-perforating processes. Protein interactive network analyses revealed multiple overlapping canonical pathways within both lymphoid and myeloid cell lineages. This initial estimation of the chicken immune cell type landscape and its accompanying response will greatly aid efforts in identifying specific cell types and improving our knowledge of host response to viral infection.

HIV Infection Elicits Differential Transcriptomic Remodeling in CD4+ T Cells with Variable Proliferative Responses to the T Cell Receptor Stimulus

Identification of a cellular biomarker of latent HIV infection will facilitate the latent reservoir detection, quantification, and targeting for elimination. Unfortunately, the latency biomarkers reported in the literature define only a fraction of the entire reservoir. The latent HIV reservoir may be established in dividing cells that subsequently return to quiescence and in resting cells. The strength of the T cell receptor (TCR) signaling at the time of infection affects characteristics of the established reservoir, such as the ability to reactivate with latency reversing agents. To better understand the cellular environments before latency establishment, we characterized transcriptomic remodeling induced by the initial HIV infection in cells with differential proliferative responses to the TCR stimulus. Cell proliferation was monitored using the viable dye carboxyfluorescein diacetate succinimidyl ester. Cells that divided many times, a few times, or remained non-dividing were subjected to single-cell RNA sequencing. A subset of identified transcriptional changes induced by HIV infection was independent of the number of cell divisions; however, responses unique to different cell subsets were also detected. Some of these early gene expression changes were consistent with reported markers of latently infected cells. We pose that the latency biomarkers may depend on the cellular proliferative state at the time of infection.

Multi-organ single-cell analysis reveals an on/off switch system with potential for personalized treatment of immunological diseases

Prioritization of disease mechanisms, biomarkers, and drug targets in immune-mediated inflammatory diseases (IMIDs) is complicated by altered interactions between thousands of genes. Our multi-organ single-cell RNA sequencing of a mouse IMID model, namely collagen-induced arthritis, shows highly complex and heterogeneous expression changes in all analyzed organs, even though only joints showed signs of inflammation. We organized those into a multi-organ multicellular disease model, which shows predicted molecular interactions within and between organs. That model supports that inflammation is switched on or off by altered balance between pro- and anti-inflammatory upstream regulators (URs) and downstream pathways. Meta-analyses of human IMIDs show a similar, but graded, on/off switch system. This system has the potential to prioritize, diagnose, and treat optimal combinations of URs on the levels of IMIDs, subgroups, and individual patients. That potential is supported by UR analyses in more than 600 sera from patients with systemic lupus erythematosus.

A single-cell atlas reveals shared and distinct immune responses and metabolic profiles in SARS-CoV-2 and HIV-1 infections

Introduction: Within the inflammatory immune response to viral infection, the distribution and cell type-specific profiles of immune cell populations and the immune-mediated viral clearance pathways vary according to the specific virus. Uncovering the immunological similarities and differences between viral infections is critical to understanding disease progression and developing effective vaccines and therapies. Insight into COVID-19 disease progression has been bolstered by the integration of single-cell (sc)RNA-seq data from COVID-19 patients with data from related viruses to compare immune responses. Expanding this concept, we propose that a high-resolution, systematic comparison between immune cells from SARS-CoV-2 infection and an inflammatory infectious disease with a different pathophysiology will provide a more comprehensive picture of the viral clearance pathways that underscore immunological and clinical differences between infections. Methods: Using a novel consensus single-cell annotation method, we integrate previously published scRNA-seq data from 111,566 single PBMCs from 7 COVID-19, 10 HIV-1+, and 3 healthy patients into a unified cellular atlas. We compare in detail the phenotypic features and regulatory pathways in the major immune cell clusters. Results: While immune cells in both COVID-19 and HIV-1+ cohorts show shared inflammation and disrupted mitochondrial function, COVID-19 patients exhibit stronger humoral immunity, broader IFN-I signaling, elevated Rho GTPase and mTOR pathway activity, and downregulated mitophagy. Discussion: Our results indicate that differential IFN-I signaling regulates the distinct immune responses in the two diseases, revealing insight into fundamental disease biology and potential therapeutic candidates.

Single-cell RNA-seq analysis reveals dual sensing of HIV-1 in blood Axl+ dendritic cells

Sensing of incoming viruses is a pivotal task of dendritic cells (DCs). Human primary blood DCs encompass various subsets that are diverse in their susceptibility and response to HIV-1. The recent identification of the blood Axl⁺DC subset, endowed with unique capacities to bind, replicate, and transmit HIV-1 prompted us to evaluate its anti-viral response. We demonstrate that HIV-1 induced two main broad and intense transcriptional programs in different Axl⁺DCs potentially induced by different sensors; an NF-κB-mediated program that led to DC maturation and efficient CD4⁺ T cell activation, and a program mediated by STAT1/2 that activated type I IFN and ISG responses. These responses were absent from cDC2 exposed to HIV-1 except when viral replication was allowed. Finally, Axl⁺DCs actively replicating HIV-1 identified by quantification of viral transcripts exhibited a mixed NF-κB/ISG innate response. Our results suggest that the route of HIV-1 entry may dictate different innate sensing pathways by DCs.

Single-cell RNA-seq methods to interrogate virus-host interactions

The twenty-first century has seen the emergence of many epidemic and pandemic viruses, with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate intracellular parasites, viruses rely on host cells to replicate and produce progeny, resulting in complex virus and host dynamics during an infection. Single-cell RNA sequencing (scRNA-seq), by enabling broad and simultaneous profiling of both host and virus transcripts, represents a powerful technology to unravel the delicate balance between host and virus. In this review, we summarize technological and methodological advances in scRNA-seq and their applications to antiviral immunity. We highlight key scRNA-seq applications that have enabled the understanding of viral genomic and host response heterogeneity, differential responses of infected versus bystander cells, and intercellular communication networks. We expect further development of scRNA-seq technologies and analytical methods, combined with measurements of additional multi-omic modalities and increased availability of publicly accessible scRNA-seq datasets, to enable a better understanding of viral pathogenesis and enhance the development of antiviral therapeutics strategies.

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.

Titration of 124 antibodies using CITE-Seq on human PBMCs

Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies will improve the analysis and may reduce costs. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.

T-cell activation and B-cell interaction signatures in rectal tissues are associated with HIV replication in ex-vivo model of infection

OBJECTIVE

The rectal mucosa is a critical site of HIV vulnerability. We sought to identify transcriptomic features of rectal mucosal tissue prior to exposure associated with support or restriction of HIV replication.

DESIGN

Rectal tissue from HIV-negative cis gender men ( n  = 57) underwent concurrent RNAseq transcriptomic analyses (two biopsies/participant) and challenge with HIV in the ex-vivo explant model of infection (three biopsies challenged/participant) as part of a larger cohort study to understand the rectal mucosal immune environment among MSM.

METHODS

P24 was quantified in the explant supernatants over a culture period of 18 days via ELISA. Participant median p24 log area under the curve was correlated with bulk transcriptomic data (Illumina HiSeq3000) to identify associations between gene expression and p24 production. Significant differentially expressed genes (DEGs) were identified via DESeq2 analysis and analyzed with Reactome to identify pathways of interest.

RESULTS

In total, 183 DEG (181 upregulated, two downregulated) were associated with higher p24 accumulation in the ex-vivo challenge model, including T-cell activation, B-cell function, and chemokine DEG. Reactome analysis of the upregulated genes identified 'Adaptive Immune System', 'Cytokine Signaling in Immune System', and 'Innate Immune System' as significantly upregulated pathways.

CONCLUSION

For the first time, we identified rectal tissue transcriptomic signatures associated with increased p24 production utilizing an ex-vivo model. Our findings are highly relevant to HIV transmission and the early establishment of HIV reservoirs in humans, and future studies should examine the identified pathways as targets for new or improved biomedical prevention or treatment interventions.

Natural killer cells during acute HIV-1 infection: clues for HIV-1 prevention and therapy

Despite progress in preexposure prophylaxis, the number of newly diagnosed cases with HIV-1 remains high, highlighting the urgent need for preventive and therapeutic strategies to reduce HIV-1 acquisition and limit disease progression. Early immunological events, occurring during acute infection, are key determinants of the outcome and course of disease. Understanding early immune responses occurring before viral set-point is established, is critical to identify potential targets for prophylactic and therapeutic approaches. Natural killer (NK) cells represent a key cellular component of innate immunity and contribute to the early host defence against HIV-1 infection, modulating the pathogenesis of acute HIV-1 infection (AHI). Emerging studies have identified tools for harnessing NK cell responses and expanding specialized NK subpopulations with adaptive/memory features, paving the way for development of novel HIV-1 therapeutics. This review highlights the knowns and unknowns regarding the role of NK cell subsets in the containment of acute HIV-1 infection, and summarizes recent advances in selectively augmenting NK cell functions through prophylactic and therapeutic interventions.

Single-cell analysis of immune cell transcriptome during HIV-1 infection and therapy

BACKGROUND

Cellular immune responses are phenotypically and functionally perturbed during HIV-1 infection, with the majority of function restored upon antiretroviral therapy (ART). Despite ART, residual inflammation remains that can lead to HIV-related co-morbidities and mortality, indicating that ART does not fully restore normal immune cell function. Thus, understanding the dynamics of the immune cell landscape during HIV-1 infection and ART is critical to defining cellular dysfunction that occurs during HIV-1 infection and imprints during therapy.

RESULTS

Here, we have applied single-cell transcriptome sequencing of peripheral blood immune cells from chronic untreated HIV-1 individuals, HIV-1-infected individuals receiving ART and HIV-1 negative individuals. We also applied single-cell transcriptome sequencing to a primary cell model of early HIV-1 infection using CD4+ T cells from healthy donors. We described changes in the transcriptome at high resolution that occurred during HIV-1 infection, and perturbations that remained during ART. We also determined transcriptional differences among T cells expressing HIV-1 transcripts that identified key regulators of HIV-1 infection that may serve as targets for future therapies to block HIV-1 infection.

CONCLUSIONS

This work identified key molecular pathways that are altered in immune cells during chronic HIV-1 infection that could remain despite therapy. We also identified key genes that are upregulated during early HIV-1 infection that provide insights on the mechanism of HIV-1 infection and could be targets for future therapy.

Executable models of immune signaling pathways in HIV-associated atherosclerosis

Atherosclerosis (AS)-associated cardiovascular disease is an important cause of mortality in an aging population of people living with HIV (PLWH). This elevated risk has been attributed to viral infection, anti-retroviral therapy, chronic inflammation, and lifestyle factors. However, the rates at which PLWH develop AS vary even after controlling for length of infection, treatment duration, and for lifestyle factors. To investigate the molecular signaling underlying this variation, we sequenced 9368 peripheral blood mononuclear cells (PBMCs) from eight PLWH, four of whom have atherosclerosis (AS+). Additionally, a publicly available dataset of PBMCs from persons before and after HIV infection was used to investigate the effect of acute HIV infection. To characterize dysregulation of pathways rather than just measuring enrichment, we developed the single-cell Boolean Omics Network Invariant Time Analysis (scBONITA) algorithm. scBONITA infers executable dynamic pathway models and performs a perturbation analysis to identify high impact genes. These dynamic models are used for pathway analysis and to map sequenced cells to characteristic signaling states (attractor analysis). scBONITA revealed that lipid signaling regulates cell migration into the vascular endothelium in AS+ PLWH. Pathways implicated included AGE-RAGE and PI3K-AKT signaling in CD8+ T cells, and glucagon and cAMP signaling pathways in monocytes. Attractor analysis with scBONITA facilitated the pathway-based characterization of cellular states in CD8+ T cells and monocytes. In this manner, we identify critical cell-type specific molecular mechanisms underlying HIV-associated atherosclerosis using a novel computational method.

CellDrift: inferring perturbation responses in temporally sampled single-cell data

Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.

CD8 + T-cell responses in HIV controllers: potential implications for novel HIV remission strategies

PURPOSE OF REVIEW

Immunological studies of spontaneous HIV and simian virus (SIV) controllers have identified virus-specific CD8 +  T cells as a key immune mechanism of viral control. The purpose of this review is to consider how knowledge about the mechanisms that are associated with CD8 +  T cell control of HIV/SIV in natural infection can be harnessed in HIV remission strategies.

RECENT FINDINGS

We discuss characteristics of CD8 +  T-cell responses that may be critical for suppressing HIV replication in spontaneous controllers comprising HIV antigen recognition including specific human leukocyte antigen types, broadly cross-reactive T cell receptors and epitope targeting, enhanced expansion and antiviral functions, and localization of virus-specific T cells near sites of reservoir persistence. We also discuss the need to better understand the timing of CD8 +  T-cell responses associated with viral control of HIV/SIV during acute infection and after treatment interruption as well as the mechanisms by which HIV/SIV-specific CD8 +  T cells coordinate with other immune responses to achieve control.

SUMMARY

We propose implications as to how this knowledge from natural infection can be applied in the design and evaluation of CD8 +  T-cell-based remission strategies and offer questions to consider as these strategies target distinct CD8 +  T-cell-dependent mechanisms of viral control.

Combined protein and transcript single-cell RNA sequencing in human peripheral blood mononuclear cells

BACKGROUND

Cryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single-cell (sc)RNA sequencing (scRNA-seq) in PBMCs.

RESULTS

Among 31 participants in the Women's Interagency HIV Study (WIHS), we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs (tool for visualizing high-dimensional data) and Louvain clustering, we identified 50 subsets among CD4+ T, CD8+ T, B, NK cells, and monocytes. This resolution was superior to flow cytometry, mass cytometry, or scRNA-seq without antibodies. Combined protein and transcript scRNA-seq allowed for the assessment of disease-related changes in transcriptomes and cell type proportions. As a proof-of-concept, we showed such differences between healthy and matched individuals living with HIV with and without cardiovascular disease.

CONCLUSIONS

In conclusion, combined protein and transcript scRNA sequencing is a suitable and powerful method for clinical investigations using PBMCs.

Heterogeneity and transcriptome changes of human CD8+ T cells across nine decades of life

The decline of CD8⁺ T cell functions contributes to deteriorating health with aging, but the mechanisms that underlie this phenomenon are not well understood. We use single-cell RNA sequencing with both cross-sectional and longitudinal samples to assess how human CD8⁺ T cell heterogeneity and transcriptomes change over nine decades of life. Eleven subpopulations of CD8⁺ T cells and their dynamic changes with age are identified. Age-related changes in gene expression result from changes in the percentage of cells expressing a given transcript, quantitative changes in the transcript level, or a combination of these two. We develop a machine learning model capable of predicting the age of individual cells based on their transcriptomic features, which are closely associated with their differentiation and mutation burden. Finally, we validate this model in two separate contexts of CD8⁺ T cell aging: HIV infection and CAR T cell expansion in vivo.

The characterisation of T cells during aging is important to predict functional outcomes in vaccination or infection. Here the authors use flow cytometry and scRNA sequencing to transcriptionally age CD8 T cells and then use a machine learning model to interpret cell age from transcriptional profiles.

Comparative analysis of cell-cell communication at single-cell resolution

Inference of cell-cell communication (CCC) from single-cell RNA-sequencing data is a powerful technique to uncover putative axes of multicellular coordination, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell level information. Here we present Scriabin â€" a flexible and scalable framework for comparative analysis of CCC at single-cell resolution. We leverage multiple published datasets to show that Scriabin recovers expected CCC edges and use spatial transcriptomic data, genetic perturbation screens, and direct experimental manipulation of receptor-ligand interactions to validate that the recovered edges are biologically meaningful. We then apply Scriabin to uncover co-expressed programs of CCC from atlas-scale datasets, validating known communication pathways required for maintaining the intestinal stem cell niche and revealing species-specific communication pathways. Finally, we utilize single-cell communication networks calculated using Scriabin to follow communication pathways that operate between timepoints in longitudinal datasets, highlighting bystander cells as important initiators of inflammatory reactions in acute SARS-CoV-2 infection. Our approach represents a broadly applicable strategy to leverage single-cell resolution data maximally toward uncovering CCC circuitry and rich niche-phenotype relationships in health and disease.

Cell landscape of larval and adult Xenopus laevis at single-cell resolution

The rapid development of high-throughput single-cell RNA sequencing technology offers a good opportunity to dissect cell heterogeneity of animals. A large number of organism-wide single-cell atlases have been constructed for vertebrates such as Homo sapiens, Macaca fascicularis, Mus musculus and Danio rerio. However, an intermediate taxon that links mammals to vertebrates of more ancient origin is still lacking. Here, we construct the first Xenopus cell landscape to date, including larval and adult organs. Common cell lineage-specific transcription factors have been identified in vertebrates, including fish, amphibians and mammals. The comparison of larval and adult erythrocytes identifies stage-specific hemoglobin subtypes, as well as a common type of cluster containing both larval and adult hemoglobin, mainly at NF59. In addition, cell lineages originating from all three layers exhibits both antigen processing and presentation during metamorphosis, indicating a common regulatory mechanism during metamorphosis. Overall, our study provides a large-scale resource for research on Xenopus metamorphosis and adult organs.

Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization

Dimension reduction (DR) algorithms project data from high dimensions to lower dimensions to enable visualization of interesting high-dimensional structure. DR algorithms are widely used for analysis of single-cell transcriptomic data. Despite widespread use of DR algorithms such as t-SNE and UMAP, these algorithms have characteristics that lead to lack of trust: they do not preserve important aspects of high-dimensional structure and are sensitive to arbitrary user choices. Given the importance of gaining insights from DR, DR methods should be evaluated carefully before trusting their results. In this paper, we introduce and perform a systematic evaluation of popular DR methods, including t-SNE, art-SNE, UMAP, PaCMAP, TriMap and ForceAtlas2. Our evaluation considers five components: preservation of local structure, preservation of global structure, sensitivity to parameter choices, sensitivity to preprocessing choices, and computational efficiency. This evaluation can help us to choose DR tools that align with the scientific goals of the user.