Integrative systems biology reveals NKG2A-biased immune responses correlate with protection in infectious disease, autoimmune disease, and cancer.

Infection, autoimmunity, and cancer are principal human health challenges of the 21st century. Often regarded as distinct ends of the immunological spectrum, recent studies hint at potential overlap between these diseases. For example, inflammation can be pathogenic in infection and autoimmunity. T resident memory (TRM) cells can be beneficial in infection and cancer. However, these findings are limited by size and scope; exact immunological factors shared across diseases remain elusive. Here, we integrate large-scale deeply clinically and biologically phenotyped human cohorts of 526 patients with infection, 162 with lupus, and 11,180 with cancer. We identify an NKG2A+ immune bias as associative with protection against disease severity, mortality, and autoimmune/post-acute chronic disease. We reveal that NKG2A+ CD8+ T cells correlate with reduced inflammation and increased humoral immunity and that they resemble TRM cells. Our results suggest NKG2A+ biases as a cross-disease factor of protection, supporting suggestions of immunological overlap between infection, autoimmunity, and cancer.

Acute cholecystitis, obesity, and steatohepatitis constitute the lethal triad for bile duct injury (BDI) during laparoscopic cholecystectomy.

OBJECTIVE: The most feared complication during laparoscopic cholecystectomy remains a bile duct injury (BDI). Accurately risk-stratifying patients for a BDI remains difficult and imprecise. This study evaluated if the lethal triad of acute cholecystitis, obesity, and steatohepatitis is a prognostic measure for BDI. METHODS: A retrospective review of the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) registry was performed. All laparoscopic cholecystectomy cases within the main NSQIP database for 2012-2019 were queried. Two study cohorts were constructed. One with the lethal triad of acute cholecystitis, BMI ≥ 30, and steatohepatitis. The other cohort did not have the full triad present. Multivariate analysis was performed via logistic regression modeling with calculation of odds ratios (OR) to identify independent factors for BDI. An uncontrolled and controlled propensity score match analysis was performed. RESULTS: A total of 387,501 cases were analyzed. 36,887 cases contained the lethal triad, the remaining 350,614 cases did not have the full triad. 860 BDIs were identified resulting in an overall incidence rate 0.22%. There were 541 BDIs within the lethal triad group with 319 BDIs in the other cohort and an incidence rate of 1.49% vs 0.09% (P < 0.001). Multivariate analysis identified the lethal triad as an independent risk factor for a BDI by over 15-fold (OR 16.35, 95%CI 14.28-18.78, P < 0.0001) on the uncontrolled analysis. For the controlled propensity score match there were 29,803 equivalent pairs identified between the cohorts. The BDI incidence rate remained significantly higher with lethal triad cases at 1.65% vs 0.04% (P < 0.001). The lethal triad was an even more significant independent risk factor for BDI on the controlled analysis (OR 40.13, 95%CI 7.05-356.59, P < 0.0001). CONCLUSIONS: The lethal triad of acute cholecystitis, obesity, and steatohepatitis significantly increases the risk of a BDI. This prognostic measure can help better counsel patients and potentially alter management.

T cell receptor sequences are the dominant factor contributing to the phenotype of CD8+ T cells with specificities against immunogenic viral antigens.

Antigen-specific CD8+ T cells mediate pathogen clearance. T cell phenotype is influenced by T cell receptor (TCR) sequences and environmental signals. Quantitative comparisons of these factors in human disease, while challenging to obtain, can provide foundational insights into basic T cell biology. Here, we investigate the phenotype kinetics of 679 CD8+ T cell clonotypes, each with specificity against one of three immunogenic viral antigens. Data were collected from a longitudinal study of 68 COVID-19 patients with antigens from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cytomegalovirus (CMV), and influenza. Each antigen is associated with a different type of immune activation during COVID-19. We find TCR sequence to be by far the most important factor in shaping T cell phenotype and persistence for populations specific to any of these antigens. Our work demonstrates the important relationship between TCR sequence and T cell phenotype and persistence and helps explain why T cell phenotype often appears to be determined early in an infection.

Large libraries of single-chain trimer peptide-MHCs enable antigen-specific CD8+ T cell discovery and analysis.

The discovery and characterization of antigen-specific CD8+ T cell clonotypes typically involves the labor-intensive synthesis and construction of peptide-MHC tetramers. We adapt single-chain trimer (SCT) technologies into a high throughput platform for pMHC library generation, showing that hundreds can be rapidly prepared across multiple Class I HLA alleles. We use this platform to explore the impact of peptide and SCT template mutations on protein expression yield, thermal stability, and functionality. SCT libraries were an efficient tool for identifying T cells recognizing commonly reported viral epitopes. We then construct SCT libraries to capture SARS-CoV-2 specific CD8+ T cells from COVID-19 participants and healthy donors. The immunogenicity of these epitopes is validated by functional assays of T cells with cloned TCRs captured using SCT libraries. These technologies should enable the rapid analyses of peptide-based T cell responses across several contexts, including autoimmunity, cancer, or infectious disease.

Multiple early factors anticipate post-acute COVID-19 sequelae.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Artificial image objects for classification of breast cancer biomarkers with transcriptome sequencing data and convolutional neural network algorithms.

BACKGROUND: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expression between individual genes. METHODS: We proposed a method to transform RNA sequencing data into artificial image objects (AIOs) and applied convolutional neural network (CNN) algorithms to classify these AIOs. With the AIO technique, we considered each gene as a pixel in an image and its expression level as pixel intensity. Using the GSE96058 (n = 2976), GSE81538 (n = 405), and GSE163882 (n = 222) datasets, we created AIOs for the subjects and designed CNN models to classify biomarker Ki67 and Nottingham histologic grade (NHG). RESULTS: With fivefold cross-validation, we accomplished a classification accuracy and AUC of 0.821 ± 0.023 and 0.891 ± 0.021 for Ki67 status. For NHG, the weighted average of categorical accuracy was 0.820 ± 0.012, and the weighted average of AUC was 0.931 ± 0.006. With GSE96058 as training data and GSE81538 as testing data, the accuracy and AUC for Ki67 were 0.826 ± 0.037 and 0.883 ± 0.016, and that for NHG were 0.764 ± 0.052 and 0.882 ± 0.012, respectively. These results were 10% better than the results reported in the original studies. For Ki67, the calls generated from our models had a better power for prediction of survival as compared to the calls from trained pathologists in survival analyses. CONCLUSIONS: We demonstrated that RNA sequencing data could be transformed into AIOs and be used to classify Ki67 status and NHG with CNN algorithms. The AIO method could handle high-dimensional data with highly correlated variables, and there was no need for variable selection. With the AIO technique, a data-driven, consistent, and automation-ready model could be developed to classify biomarkers with RNA sequencing data and provide more efficient care for cancer patients.

Artificial image objects for classification of schizophrenia with GWAS-selected SNVs and convolutional neural network.

In this article, we propose a new approach to analyze large genomics data. We considered individual genetic variants as pixels in an image and transformed a collection of variants into an artificial image object (AIO), which could be classified as a regular image by CNN algorithms. Using schizophrenia as a case study, we demonstrate the principles and their applications with 3 datasets. With 4,096 SNVs, the CNN models achieved an accuracy of 0.678 ± 0.007 and an AUC of 0.738 ± 0.008 for the diagnosis phenotype. With 44,100 SNVs, the models achieved class-specific accuracies of 0.806 ± 0.032 and 0.820 ± 0.049, and AUCs of 0.930 ± 0.017 and 0.867 ± 0.040 for the bottom and top classes stratified by the patient's polygenic risk scores. These results suggest that, once transformed to images, large genomics data can be analyzed effectively with image classification algorithms.

The Trypanosoma brucei dihydroxyacetonephosphate acyltransferase TbDAT is dispensable for normal growth but important for synthesis of ether glycerophospholipids.

Glycerophospholipids are the most abundant constituents of biological membranes in Trypanosoma brucei, which causes sleeping sickness in humans and nagana in cattle. They are essential cellular components that fulfill various important functions beyond their structural role in biological membranes such as in signal transduction, regulation of membrane trafficking or control of cell cycle progression. Our previous studies have established that the glycerol-3-phosphate acyltransferase TbGAT is dispensable for growth, viability, and ester lipid biosynthesis suggesting the existence of another initial acyltransferase(s). This work presents the characterization of the alternative, dihydroxyacetonephosphate acyltransferase TbDAT, which acylates primarily dihydroxyacetonephosphate and prefers palmitoyl-CoA as an acyl-CoA donor. TbDAT restores the viability of a yeast double null mutant that lacks glycerol-3-phosphate and dihydroxyacetonephosphate acyltransferase activities. A conditional null mutant of TbDAT in T. brucei procyclic form was created and characterized. TbDAT was important for survival during stationary phase and synthesis of ether lipids. In contrast, TbDAT was dispensable for normal growth. Our results show that in T. brucei procyclic forms i) TbDAT but not TbGAT is the physiologically relevant initial acyltransferase and ii) ether lipid precursors are primarily made by TbDAT.

Contemporary Pharyngeal and Invasive emm1 and Invasive emm12 Group A Streptococcus Isolates Exhibit Similar In Vivo Selection for CovRS Mutants in Mice.

Group A Streptococcus (GAS) causes diverse infections ranging from common pharyngitis to rare severe invasive infections. Invasive GAS isolates can have natural mutations in the virulence regulator CovRS, which result in enhanced expression of multiple virulence genes, suppressed the expression of the protease SpeB, and increased virulence. It is believed that CovRS mutations arise during human infections with GAS carrying wild-type CovRS and are not transmissible. CovRS mutants of invasive GAS of the emm1 genotype arise readily during experimental infection in mice. It is possible that invasive GAS arises from pharyngeal GAS through rare genetic mutations that confer the capacity of mutated GAS to acquire covRS mutations during infection. The objective of this study was to determine whether contemporary pharyngeal emm1 GAS isolates have a reduced propensity to acquire CovRS mutations in vivo compared with invasive emm1 GAS and whether emm3, emm12, and emm28 GAS acquire CovRS mutants in mouse infection. The propensity of invasive and pharyngeal emm1 and invasive emm3, emm12, and emm28 SpeBA+ isolates to acquire variants with the SpeBA- phenotype was determined during subcutaneous infection of mice. The majority of both invasive and pharyngeal emm1 SpeBA+ isolates and two of three emm12 isolates, but not emm3 and emm28 isolates, were found to acquire SpeBA- variants during skin infection in mice. All analyzed SpeBA- variants of emm1 and emm12 GAS from the mouse infection acquired covRS mutations and produced more platelet-activating factor acetylhydrolase SsE. Thus, contemporary invasive and pharyngeal emm1 GAS isolates and emm12 GAS have a similar capacity to acquire covRS mutations in vivo. The rarity of severe invasive infections caused by GAS does not appear to be attributable to a reduced ability of pharyngeal isolates to acquire CovRS mutations.

The Glycerol-3-Phosphate Acyltransferase TbGAT is Dispensable for Viability and the Synthesis of Glycerolipids in Trypanosoma brucei.

Glycerolipids are the main constituents of biological membranes in Trypanosoma brucei, which causes sleeping sickness in humans. Importantly, they occur as a structural component of the glycosylphosphatidylinositol lipid anchor of the abundant cell surface glycoproteins procyclin in procyclic forms and variant surface glycoprotein in bloodstream form, that play crucial roles for the development of the parasite in the insect vector and the mammalian host, respectively. The present work reports the characterization of the glycerol-3-phosphate acyltransferase TbGAT that initiates the biosynthesis of ester glycerolipids. TbGAT restored glycerol-3-phosphate acyltransferase activity when expressed in a Leishmania major deletion strain lacking this activity and exhibited preference for medium length, unsaturated fatty acyl-CoAs. TbGAT localized to the endoplasmic reticulum membrane with its N-terminal domain facing the cytosol. Despite that a TbGAT null mutant in T. brucei procyclic forms lacked glycerol-3-phosphate acyltransferase activity, it remained viable and exhibited similar growth rate as the wild type. TbGAT was dispensable for the biosynthesis of phosphatidylcholine, phosphatidylinositol, phosphatidylserine, and GPI-anchored protein procyclin. However, the null mutant exhibited a slight decrease in phosphatidylethanolamine biosynthesis that was compensated with a modest increase in production of ether phosphatidylcholine. Our data suggest that an alternative initial acyltransferase takes over TbGAT's function in its absence.