Intraoperative Bivalirudin Use in Patient Undergoing Femoral Endarterectomy with Heparin-Induced Thrombocytopenia: Case Report and Review of the Literature.

PURPOSE: To describe the intraoperative use of bivalirudin during lower extremity revascularization in the setting of heparin-induced thrombocytopenia (HIT). CASE SUMMARY: A 65 year-old man presented with left common iliac, external iliac, and femoral artery occlusion necessitating revascularization with left femoral endarterectomy and common and external iliac stent angioplasty. Three months before the femoral endarterectomy, the patient was hospitalized for a coronary artery bypass procedure. During this admission, the patient tested positive for the presence of heparin-PF4 antibody complexes. With the patient's recent history of HIT, bivalirudin was selected as the optimal agent for intraoperative anticoagulation. Bivalirudin was administered as a 50 mg bolus, followed by a continuous infusion initiated at 1.75 mg/kg/hr. Repeated bivalirudin boluses were necessary to maintain an activated clotting time (ACT) necessary for the revascularization procedures and recurrent subacute thrombi despite appropriate ACT values. DISCUSSION: Bivalirudin has been utilized for cardiopulmonary bypass and carotid endarterectomy (CEA), but data for dosing in lower extremity revascularization are lacking. As the risk for thrombosis with HIT continues for months after diagnosis, it is important to elucidate optimal dosing of non-heparin anticoagulant options, such as the direct thrombin inhibitor, bivalirudin. The absence of validated dosing strategies for bivalirudin can result in prolonged operative times, increased risk of bleeding, and inadequate anticoagulation. CONCLUSION: Bivalirudin is an appropriate agent for intraoperative anticoagulation in lower extremity revascularization. However, further investigation into the optimal intraoperative bivalirudin dosing regimen is necessary.

CD8+ lymphocytes are critical for early control of tuberculosis in macaques.

The functional role of CD8+ lymphocytes in tuberculosis remains poorly understood. We depleted innate and/or adaptive CD8+ lymphocytes in macaques and showed that loss of all CD8α+ cells (using anti-CD8α antibody) significantly impaired early control of Mycobacterium tuberculosis (Mtb) infection, leading to increased granulomas, lung inflammation, and bacterial burden. Analysis of barcoded Mtb from infected macaques demonstrated that depletion of all CD8+ lymphocytes allowed increased establishment of Mtb in lungs and dissemination within lungs and to lymph nodes, while depletion of only adaptive CD8+ T cells (with anti-CD8ß antibody) worsened bacterial control in lymph nodes. Flow cytometry and single-cell RNA sequencing revealed polyfunctional cytotoxic CD8+ lymphocytes in control granulomas, while CD8-depleted animals were unexpectedly enriched in CD4 and γδ T cells adopting incomplete cytotoxic signatures. Ligand-receptor analyses identified IL-15 signaling in granulomas as a driver of cytotoxic T cells. These data support that CD8+ lymphocytes are required for early protection against Mtb and suggest polyfunctional cytotoxic responses as a vaccine target.

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.

International Union of Basic and Clinical Pharmacology CXIII: Nuclear Receptor Superfamily-Update 2023.

The NR superfamily comprises 48 transcription factors in humans that control a plethora of gene network programs involved in a wide range of physiologic processes. This review will summarize and discuss recent progress in NR biology and drug development derived from integrating various approaches, including biophysical techniques, structural studies, and translational investigation. We also highlight how defective NR signaling results in various diseases and disorders and how NRs can be targeted for therapeutic intervention via modulation via binding to synthetic lipophilic ligands. Furthermore, we also review recent studies that improved our understanding of NR structure and signaling. SIGNIFICANCE STATEMENT: Nuclear receptors (NRs) are ligand-regulated transcription factors that are critical regulators of myriad physiological processes. NRs serve as receptors for an array of drugs, and in this review, we provide an update on recent research into the roles of these drug targets.

Protective intravenous BCG vaccination induces enhanced immune signaling in the airways.

Intradermal (ID) Bacillus Calmette-Guérin (BCG) is the most widely administered vaccine in the world. However, ID-BCG fails to achieve the level of protection needed in adults to alter the course of the tuberculosis epidemic. Recent studies in non-human primates have demonstrated high levels of protection against Mycobacterium tuberculosis ( Mtb ) following intravenous (IV) administration of BCG. However, the protective immune features that emerge following IV BCG vaccination remain incompletely defined. Here we used single-cell RNA-sequencing (scRNAseq) to transcriptionally profile 157,114 unstimulated and purified protein derivative (PPD)-stimulated bronchoalveolar lavage (BAL) cells from 29 rhesus macaques immunized with BCG across routes of administration and doses to uncover cell composition-, gene expression-, and biological network-level signatures associated with IV BCG-mediated protection. Our analyses revealed that high-dose IV BCG drove an influx of polyfunctional T cells and macrophages into the airways. These macrophages exhibited a basal activation phenotype even in the absence of PPD-stimulation, defined in part by IFN and TNF-α signaling up to 6 months following BCG immunization. Furthermore, intercellular immune signaling pathways between key myeloid and T cell subsets were enhanced following PPD-stimulation in high-dose IV BCG-vaccinated macaques. High-dose IV BCG also engendered quantitatively and qualitatively stronger transcriptional responses to PPD-stimulation, with a robust Th1-Th17 transcriptional phenotype in T cells, and augmented transcriptional signatures of reactive oxygen species production, hypoxia, and IFN-γ response within alveolar macrophages. Collectively, this work supports that IV BCG immunization creates a unique cellular ecosystem in the airways, which primes and enables local myeloid cells to effectively clear Mtb upon challenge.

A structural mechanism of nuclear receptor biased agonism.

Efforts to decrease the adverse effects of nuclear receptor (NR) drugs have yielded experimental agonists that produce better outcomes in mice. Some of these agonists have been shown to cause different, not just less intense, on-target transcriptomic effects; however, a structural explanation for such agonist-specific effects remains unknown. Here, we show that partial agonists of the NR peroxisome proliferator-associated receptor γ (PPARγ), which induce better outcomes in mice compared to clinically utilized type II diabetes PPARγ-binding drugs thiazolidinediones (TZDs), also favor a different group of coactivator peptides than the TZDs. We find that PPARγ full agonists can also be biased relative to each other in terms of coactivator peptide binding. We find differences in coactivator-PPARγ bonding between the coactivator subgroups which allow agonists to favor one group of coactivator peptides over another, including differential bonding to a C-terminal residue of helix 4. Analysis of all available NR-coactivator structures indicates that such differential helix 4 bonding persists across other NR-coactivator complexes, providing a general structural mechanism of biased agonism for many NRs. Further work will be necessary to determine if such bias translates into altered coactivator occupancy and physiology in cells.

Single-cell profiling of environmental enteropathy reveals signatures of epithelial remodeling and immune activation.

Environmental enteropathy (EE) is a subclinical condition of the small intestine that is highly prevalent in low- and middle-income countries. It is thought to be a key contributing factor to childhood malnutrition, growth stunting, and diminished oral vaccine responses. Although EE has been shown to be the by-product of a recurrent enteric infection, its full pathophysiology remains unclear. Here, we mapped the cellular and molecular correlates of EE by performing high-throughput, single-cell RNA-sequencing on 33 small intestinal biopsies from 11 adults with EE in Lusaka, Zambia (eight HIV-negative and three HIV-positive), six adults without EE in Boston, United States, and two adults in Durban, South Africa, which we complemented with published data from three additional individuals from the same clinical site. We analyzed previously defined bulk-transcriptomic signatures of reduced villus height and decreased microbial translocation in EE and showed that these signatures may be driven by an increased abundance of surface mucosal cells-a gastric-like subset previously implicated in epithelial repair in the gastrointestinal tract. In addition, we determined cell subsets whose fractional abundances associate with EE severity, small intestinal region, and HIV infection. Furthermore, by comparing duodenal EE samples with those from three control cohorts, we identified dysregulated WNT and MAPK signaling in the EE epithelium and increased proinflammatory cytokine gene expression in a T cell subset highly expressing a transcriptional signature of tissue-resident memory cells in the EE cohort. Together, our work elucidates epithelial and immune correlates of EE and nominates cellular and molecular targets for intervention.

Alveolar macrophages in early stage COPD show functional deviations with properties of impaired immune activation.

Despite its high prevalence, the cellular and molecular mechanisms of chronic obstructive pulmonary disease (COPD) are far from being understood. Here, we determine disease-related changes in cellular and molecular compositions within the alveolar space and peripheral blood of a cohort of COPD patients and controls. Myeloid cells were the largest cellular compartment in the alveolar space with invading monocytes and proliferating macrophages elevated in COPD. Modeling cell-to-cell communication, signaling pathway usage, and transcription factor binding predicts TGF-ß1 to be a major upstream regulator of transcriptional changes in alveolar macrophages of COPD patients. Functionally, macrophages in COPD showed reduced antigen presentation capacity, accumulation of cholesteryl ester, reduced cellular chemotaxis, and mitochondrial dysfunction, reminiscent of impaired immune activation.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

BACKGROUND: COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications. METHODS: In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done. FINDINGS: We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile. INTERPRETATION: A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study. FUNDING: Eric and Wendy Schmidt.

JAK inhibition in a patient with a STAT1 gain-of-function variant reveals STAT1 dysregulation as a common feature of aplastic anemia.

BACKGROUND: Idiopathic aplastic anemia is a potentially lethal disease, characterized by T cell-mediated autoimmune attack of bone marrow hematopoietic stem cells. Standard of care therapies (stem cell transplantation or immunosuppression) are effective but associated with a risk of serious toxicities. METHODS: An 18-year-old man presented with aplastic anemia in the context of a germline gain-of-function variant in STAT1. Treatment with the JAK1 inhibitor itacitinib resulted in a rapid resolution of aplastic anemia and a sustained recovery of hematopoiesis. Peripheral blood and bone marrow samples were compared before and after JAK1 inhibitor therapy. FINDINGS: Following therapy, samples showed a decrease in the plasma concentration of interferon-γ, a decrease in PD1-positive exhausted CD8+ T cell population, and a decrease in an interferon responsive myeloid population. Single-cell analysis of chromatin accessibility showed decreased accessibility of STAT1 across CD4+ and CD8+ T cells, as well as CD14+ monocytes. To query whether other cases of aplastic anemia share a similar STAT1-mediated pathophysiology, we examined a cohort of 9 patients with idiopathic aplastic anemia. Bone marrow from six of nine patients also displayed abnormal STAT1 hyper-activation. CONCLUSIONS: These findings raise the possibility that STAT1 hyperactivition defines a subset of idiopathic aplastic anemia patients for whom JAK inhibition may be an efficacious therapy. FUNDING: Funding was provided by the Massachusetts General Hospital Department of Medicine Pathways Program and NIH T32 AI007387. A trial registration is at https://clinicaltrials.gov/ct2/show/NCT03906318.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control.

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

Hypoxic, glycolytic metabolism is a vulnerability of B-acute lymphoblastic leukemia-initiating cells.

High-risk forms of B-acute lymphoblastic leukemia (B-ALL) remain a therapeutic challenge. Leukemia-initiating cells (LICs) self-renew and spark relapse and therefore have been the subject of intensive investigation; however, the properties of LICs in high-risk B-ALL are not well understood. Here, we use single-cell transcriptomics and quantitative xenotransplantation to understand LICs in MLL-rearranged (MLL-r) B-ALL. Compared with reported LIC frequencies in acute myeloid leukemia (AML), engraftable LICs in MLL-r B-ALL are abundant. Although we find that multipotent, self-renewing LICs are enriched among phenotypically undifferentiated B-ALL cells, LICs with the capacity to replenish the leukemic cellular diversity can emerge from more mature fractions. While inhibiting oxidative phosphorylation blunts blast proliferation, this intervention promotes LIC emergence. Conversely, inhibiting hypoxia and glycolysis impairs MLL-r B-ALL LICs, providing a therapeutic benefit in xenotransplantation systems. These findings provide insight into the aggressive nature of MLL-r B-ALL and provide a rationale for therapeutic targeting of hypoxia and glycolysis.

A single-cell liver atlas of Plasmodium vivax infection.

Malaria-causing Plasmodium vivax parasites can linger in the human liver for weeks to years and reactivate to cause recurrent blood-stage infection. Although they are an important target for malaria eradication, little is known about the molecular features of replicative and non-replicative intracellular liver-stage parasites and their host cell dependence. Here, we leverage a bioengineered human microliver platform to culture patient-derived P. vivax parasites for transcriptional profiling. Coupling enrichment strategies with bulk and single-cell analyses, we capture both parasite and host transcripts in individual hepatocytes throughout the course of infection. We define host- and state-dependent transcriptional signatures and identify unappreciated populations of replicative and non-replicative parasites that share features with sexual transmissive forms. We find that infection suppresses the transcription of key hepatocyte function genes and elicits an anti-parasite innate immune response. Our work provides a foundation for understanding host-parasite interactions and reveals insights into the biology of P. vivax dormancy and transmission.

PI3K activation allows immune evasion by promoting an inhibitory myeloid tumor microenvironment.

BACKGROUND: Oncogenes act in a cell-intrinsic way to promote tumorigenesis. Whether oncogenes also have a cell-extrinsic effect on suppressing the immune response to cancer is less well understood. METHODS: We use an in vivo expression screen of known cancer-associated somatic mutations in mouse syngeneic tumor models treated with checkpoint blockade to identify oncogenes that promote immune evasion. We then validated candidates from this screen in vivo and analyzed the tumor immune microenvironment of tumors expressing mutant protein to identify mechanisms of immune evasion. RESULTS: We found that expression of a catalytically active mutation in phospho-inositol 3 kinase (PI3K), PIK3CA c.3140A>G (H1047R) confers a selective growth advantage to tumors treated with immunotherapy that is reversed by pharmacological PI3K inhibition. PIK3CA H1047R-expression in tumors decreased the number of CD8+ T cells but increased the number of inhibitory myeloid cells following immunotherapy. Inhibition of myeloid infiltration by pharmacological or genetic modulation of Ccl2 in PIK3CA H1047R tumors restored sensitivity to programmed cell death protein 1 (PD-1) checkpoint blockade. CONCLUSIONS: PI3K activation enables tumor immune evasion by promoting an inhibitory myeloid microenvironment. Activating mutations in PI3K may be useful as a biomarker of poor response to immunotherapy. Our data suggest that some oncogenes promote tumorigenesis by enabling tumor cells to avoid clearance by the immune system. Identification of those mechanisms can advance rational combination strategies to increase the efficacy of immunotherapy.

Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern.

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged, resulting in repeated COVID-19 surges. With over 6 million SARS-CoV-2 genomes sequenced, there is unprecedented data to decipher the evolution of fitter SARS-CoV-2 variants. Much attention has been directed to studying the functional importance of specific mutations in the Spike protein, but there is limited knowledge of genomic signatures shared by dominant variants. Here, we introduce a method to quantify the genome-wide distinctiveness of polynucleotide fragments (3- to 240-mers) that constitute SARS-CoV-2 sequences. Compared to standard phylogenetic metrics and mutational load, the new metric provides improved separation between Variants of Concern (VOCs; Reference = 89, IQR: 65-108; Alpha = 166, IQR: 149-181; Beta 131, IQR: 114-149; Gamma = 164, IQR: 150-178; Delta = 235, IQR: 217-255; and Omicron = 459, IQR: 395-521). Omicron's high genomic distinctiveness may confer an advantage over prior VOCs and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Evaluation of 883 lineages highlights that genomic distinctiveness has increased over time (R 2 = 0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed. This study demonstrates the value of characterizing SARS-CoV-2 variants by genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that monitoring of genomic distinctiveness would facilitate rapid assessment of viral fitness.

Analysis of the Effectiveness of the Ad26.COV2.S Adenoviral Vector Vaccine for Preventing COVID-19.

Importance: Continuous assessment of the effectiveness and safety of the US Food and Drug Administration-authorized SARS-CoV-2 vaccines is critical to amplify transparency, build public trust, and ultimately improve overall health outcomes. Objective: To evaluate the effectiveness of the Johnson & Johnson Ad26.COV2.S vaccine for preventing SARS-CoV-2 infection. Design, Setting, and Participants: This comparative effectiveness research study used large-scale longitudinal curation of electronic health records from the multistate Mayo Clinic Health System (Minnesota, Arizona, Florida, Wisconsin, and Iowa) to identify vaccinated and unvaccinated adults between February 27 and July 22, 2021. The unvaccinated cohort was matched on a propensity score derived from age, sex, zip code, race, ethnicity, and previous number of SARS-CoV-2 polymerase chain reaction tests. The final study cohort consisted of 8889 patients in the vaccinated group and 88 898 unvaccinated matched patients. Exposure: Single dose of the Ad26.COV2.S vaccine. Main Outcomes and Measures: The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts, measured by SARS-CoV-2 polymerase chain reaction testing. Results: The study was composed of 8889 vaccinated patients (4491 men [50.5%]; mean [SD] age, 52.4 [16.9] years) and 88 898 unvaccinated patients (44 748 men [50.3%]; mean [SD] age, 51.7 [16.7] years). The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts was 0.26 (95% CI, 0.20-0.34) (60 of 8889 vaccinated patients vs 2236 of 88 898 unvaccinated individuals), which corresponds to an effectiveness of 73.6% (95% CI, 65.9%-79.9%) and a 3.73-fold reduction in SARS-CoV-2 infections. Conclusions and Relevance: This study's findings are consistent with the clinical trial-reported efficacy of Ad26.COV2.S and the first retrospective analysis, suggesting that the vaccine is effective at reducing SARS-CoV-2 infection, even with the spread of variants such as Alpha or Delta that were not present in the original studies, and reaffirm the urgent need to continue mass vaccination efforts globally.

Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications.

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 11 patients, 61-90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10-76, r = 0.24; cohen's D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

The cellular architecture of the antimicrobial response network in human leprosy granulomas.

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1ß. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.