Enabling Technologies for Personalized and Precision Medicine

Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care.

Brain Endothelial Cells Are Exquisite Sensors of Age-Related Circulatory Cues

Brain endothelial cells (BECs) are key constituents of the blood-brain barrier (BBB), protecting the brain from pathogens and restricting access of circulatory factors. Yet, because circulatory proteins have prominent age-related effects on adult neurogenesis, neuroinflammation, and cognitive function in mice, we wondered whether BECs receive and potentially relay signals between the blood and brain. Using single-cell RNA sequencing of hippocampal BECs, we discover that capillary BECs-compared with arterial and venous BECs-undergo the greatest transcriptional changes in normal aging, upregulating innate immunity and oxidative stress response pathways. Short-term infusions of aged plasma into young mice recapitulate key aspects of this aging transcriptome, and remarkably, infusions of young plasma into aged mice exert rejuvenation effects on the capillary transcriptome. Together, these findings suggest that the transcriptional age of BECs is exquisitely sensitive to age-related circulatory cues and pinpoint the BBB itself as a promising therapeutic target to treat brain disease.

Molecular and genetic regulation of pig pancreatic islet cell development

Reliance on rodents for understanding pancreatic genetics, development and islet function could limit progress in developing interventions for human diseases such as diabetes mellitus. Similarities of pancreas morphology and function suggest that porcine and human pancreas developmental biology may have useful homologies. However, little is known about pig pancreas development. To fill this knowledge gap, we investigated fetal and neonatal pig pancreas at multiple, crucial developmental stages using modern experimental approaches. Purification of islet β-, α- and δ-cells followed by transcriptome analysis (RNA-seq) and immunohistology identified cell- and stage-specific regulation, and revealed that pig and human islet cells share characteristic features that are not observed in mice. Morphometric analysis also revealed endocrine cell allocation and architectural similarities between pig and human islets. Our analysis unveiled scores of signaling pathways linked to native islet β-cell functional maturation, including evidence of fetal α-cell GLP-1 production and signaling to β-cells. Thus, the findings and resources detailed here show how pig pancreatic islet studies complement other systems for understanding the developmental programs that generate functional islet cells, and that are relevant to human pancreatic diseases.

A single-parasite transcriptional atlas of Toxoplasma Gondii reveals novel control of antigen expression

Toxoplasma gondii, a protozoan parasite, undergoes a complex and poorly understood developmental process that is critical for establishing a chronic infection in its intermediate hosts. Here, we applied single-cell RNA-sequencing (scRNA-seq) on >5,400 Toxoplasma in both tachyzoite and bradyzoite stages using three widely studied strains to construct a comprehensive atlas of cell-cycle and asexual development, revealing hidden states and transcriptional factors associated with each developmental stage. Analysis of SAG1-related sequence (SRS) antigenic repertoire reveals a highly heterogeneous, sporadic expression pattern unexplained by measurement noise, cell cycle, or asexual development. Furthermore, we identified AP2IX-1 as a transcription factor that controls the switching from the ubiquitous SAG1 to rare surface antigens not previously observed in tachyzoites. In addition, comparative analysis between Toxoplasma and Plasmodium scRNA-seq results reveals concerted expression of gene sets, despite fundamental differences in cell division. Lastly, we built an interactive data-browser for visualization of our atlas resource.

Single-Cell Transcriptomes Reveal Diverse Regulatory Strategies for Olfactory Receptor Expression and Axon Targeting

The regulatory mechanisms by which neurons coordinate their physiology and connectivity are not well understood. The Drosophila olfactory receptor neurons (ORNs) provide an excellent system to investigate this question. Each ORN type expresses a unique olfactory receptor, or a combination thereof, and sends their axons to a stereotyped glomerulus. Using single-cell RNA sequencing, we identified 33 transcriptomic clusters for ORNs and mapped 20 to their glomerular types, demonstrating that transcriptomic clusters correspond well with anatomically and physiologically defined ORN types. Each ORN type expresses hundreds of transcription factors. Transcriptome-instructed genetic analyses revealed that (1) one broadly expressed transcription factor (Acj6) only regulates olfactory receptor expression in one ORN type and only wiring specificity in another type, (2) one type-restricted transcription factor (Forkhead) only regulates receptor expression, and (3) another type-restricted transcription factor (Unplugged) regulates both events. Thus, ORNs utilize diverse strategies and complex regulatory networks to coordinate their physiology and connectivity.

Non-invasive characterization of human bone marrow stimulation and reconstitution by cell-free messenger RNA sequencing

Circulating cell-free mRNA (cf-mRNA) holds great promise as a non-invasive diagnostic biomarker. However, cf-mRNA composition and its potential clinical applications remain largely unexplored. Here we show, using Next Generation Sequencing-based profiling, that cf-mRNA is enriched in transcripts derived from the bone marrow compared to circulating cells. Further, longitudinal studies involving bone marrow ablation followed by hematopoietic stem cell transplantation in multiple myeloma and acute myeloid leukemia patients indicate that cf-mRNA levels reflect the transcriptional activity of bone marrow-resident hematopoietic lineages during bone marrow reconstitution. Mechanistically, stimulation of specific bone marrow cell populations in vivo using growth factor pharmacotherapy show that cf-mRNA reflects dynamic functional changes over time associated with cellular activity. Our results shed light on the biology of the circulating transcriptome and highlight the potential utility of cf-mRNA to non-invasively monitor bone marrow involved pathologies.

Circulating cell-free mRNA holds great promise as a non-invasive diagnostic biomarker. Here the authors show that cell-free mRNA captures transcripts from the bone marrow and can be used to non-invasively monitor dynamic changes in bone marrow physiology.

Cell-Surface Proteomic Profiling in the Fly Brain Uncovers Wiring Regulators

Molecular interactions at the cellular interface mediate organized assembly of single cells into tissues and, thus, govern the development and physiology of multicellular organisms. Here, we developed a cell-type-specific, spatiotemporally resolved approach to profile cell-surface proteomes in intact tissues. Quantitative profiling of cell-surface proteomes of Drosophila olfactory projection neurons (PNs) in pupae and adults revealed global downregulation of wiring molecules and upregulation of synaptic molecules in the transition from developing to mature PNs. A proteome-instructed in vivo screen identified 20 cell-surface molecules regulating neural circuit assembly, many of which belong to evolutionarily conserved protein families not previously linked to neural development. Genetic analysis further revealed that the lipoprotein receptor LRP1 cell-autonomously controls PN dendrite targeting, contributing to the formation of a precise olfactory map. These findings highlight the power of temporally resolved in situ cell-surface proteomic profiling in discovering regulators of brain wiring.

Investigating Pregnancy and Its Complications Using Circulating Cell-Free RNA in Women's Blood During Gestation

In recent years, there have been major advances in the application of non-invasive techniques to predict pregnancy-related complications, for example by measuring cell-free RNA (cfRNA) in maternal blood. In contrast to cell-free DNA (cfDNA), which is already in clinical use to diagnose fetal aneuploidy, circulating RNA levels can correspond with tissue-specific gene expression and provide a snapshot of prenatal health across gestation. Here, we review the physiologic origins of cfRNA and its novel applications and corresponding challenges to monitor fetal and maternal health and predict pregnancy-related complications.

Broadly neutralizing human antibodies against dengue virus identified by single B cell transcriptomics

Eliciting broadly neutralizing antibodies (bNAbs) against the four dengue virus serotypes (DENV1-4) that are spreading into new territories is an important goal of vaccine design. To define bNAb targets, we characterized 28 antibodies belonging to expanded and hypermutated clonal families identified by transcriptomic analysis of single plasmablasts from DENV-infected individuals. Among these, we identified J9 and J8, two somatically related bNAbs that potently neutralized DENV1-4. Mutagenesis studies showed that the major recognition determinants of these bNAbs are in E protein domain I, distinct from the only known class of human bNAbs against DENV with a well-defined epitope. B cell repertoire analysis from acute-phase peripheral blood suggested that J9 and J8 followed divergent somatic hypermutation pathways, and that a limited number of mutations was sufficient for neutralizing activity. Our study suggests multiple B cell evolutionary pathways leading to DENV bNAbs targeting a new epitope that can be exploited for vaccine design.

Continuous and Discrete Neuron Types of the Adult Murine Striatum

The mammalian striatum is involved in many complex behaviors and yet is composed largely of a single neuron class: the spiny projection neuron (SPN). It is unclear to what extent the functional specialization of the striatum is due to the molecular specialization of SPN subtypes. We sought to define the molecular and anatomical diversity of adult SPNs using single-cell RNA sequencing (scRNA-seq) and quantitative RNA in situ hybridization (ISH). We computationally distinguished discrete versus continuous heterogeneity in scRNA-seq data and found that SPNs in the striatum can be classified into four major discrete types with no implied spatial relationship between them. Within these discrete types, we find continuous heterogeneity encoding spatial gradients of gene expression and defining anatomical location in a combinatorial mechanism. Our results suggest that neuronal circuitry has a substructure at far higher resolution than is typically interrogated, which is defined by the precise identity and location of a neuron.

c-Jun overexpression in CAR T cells induces exhaustion resistance

Chimeric antigen receptor (CAR) T cells mediate anti-tumour effects in a small subset of patients with cancer^1-3, but dysfunction due to T cell exhaustion is an important barrier to progress^4-6. To investigate the biology of exhaustion in human T cells expressing CAR receptors, we used a model system with a tonically signaling CAR, which induces hallmark features of exhaustion⁶. Exhaustion was associated with a profound defect in the production of IL-2, along with increased chromatin accessibility of AP-1 transcription factor motifs and overexpression of the bZIP and IRF transcription factors that have been implicated in mediating dysfunction in exhausted T cells^7-10. Here we show that CAR T cells engineered to overexpress the canonical AP-1 factor c-Jun have enhanced expansion potential, increased functional capacity, diminished terminal differentiation and improved anti-tumour potency in five different mouse tumour models in vivo. We conclude that a functional deficiency in c-Jun mediates dysfunction in exhausted human T cells, and that engineering CAR T cells to overexpress c-Jun renders them resistant to exhaustion, thereby addressing a major barrier to progress for this emerging class of therapeutic agents.

Single-cell transcriptomes and whole-brain projections of serotonin neurons in the mouse dorsal and median raphe nuclei

Serotonin neurons of the dorsal and median raphe nuclei (DR, MR) collectively innervate the entire forebrain and midbrain, modulating diverse physiology and behavior. To gain a fundamental understanding of their molecular heterogeneity, we used plate-based single-cell RNA-sequencing to generate a comprehensive dataset comprising eleven transcriptomically distinct serotonin neuron clusters. Systematic in situ hybridization mapped specific clusters to the principal DR, caudal DR, or MR. These transcriptomic clusters differentially express a rich repertoire of neuropeptides, receptors, ion channels, and transcription factors. We generated novel intersectional viral-genetic tools to access specific subpopulations. Whole-brain axonal projection mapping revealed that DR serotonin neurons co-expressing vesicular glutamate transporter-3 preferentially innervate the cortex, whereas those co-expressing thyrotropin-releasing hormone innervate subcortical regions in particular the hypothalamus. Reconstruction of 50 individual DR serotonin neurons revealed diverse and segregated axonal projection patterns at the single-cell level. Together, these results provide a molecular foundation of the heterogenous serotonin neuronal phenotypes.

Self-assembling manifolds in single-cell RNA sequencing data

Single-cell RNA sequencing has spurred the development of computational methods that enable researchers to classify cell types, delineate developmental trajectories, and measure molecular responses to external perturbations. Many of these technologies rely on their ability to detect genes whose cell-to-cell variations arise from the biological processes of interest rather than transcriptional or technical noise. However, for datasets in which the biologically relevant differences between cells are subtle, identifying these genes is challenging. We present the self-assembling manifold (SAM) algorithm, an iterative soft feature selection strategy to quantify gene relevance and improve dimensionality reduction. We demonstrate its advantages over other state-of-the-art methods with experimental validation in identifying novel stem cell populations of Schistosoma mansoni, a prevalent parasite that infects hundreds of millions of people. Extending our analysis to a total of 56 datasets, we show that SAM is generalizable and consistently outperforms other methods in a variety of biological and quantitative benchmarks.

Mini-Metagenomics and Nucleotide Composition Aid the Identification and Host Association of Novel Bacteriophage Sequences

A broad spectrum of metagenomic and single cell sequencing techniques have become popular for dissecting environmental microbial diversity, leading to the characterization of thousands of novel microbial lineages. In addition to recovering bacterial and archaeal genomes, metagenomic assembly can also produce genomes of viruses that infect microbial cells. Because of their diversity, lack of marker genes, and small genome size, identifying novel bacteriophage sequences from metagenomic data is often challenging, especially when the objective is to establish phage-host relationships. The present work describes a computational approach that uses supervised learning to classify metagenomic contigs as phage or non-phage as well as assigning phage taxonomy based on tetranucleotide frequencies. Furthermore, the method assigns phage-host relationships using co-occurrence statistics derived from a recently developed mini-metagenomic experimental technique. This work evaluates method performance at identifying viral contigs and predicting taxonomic classification using publicly available references. Then, using two mini-metagenomic datasets, over 100 novel phage contigs from hot spring samples of Yellowstone National Park are identified and assigned to putative microbial hosts. Results of this work demonstrate the value of combining viral sequence identification with mini-metagenomic experimental methods to understand the microbial ecosystem.

Viral taxonomy derived from evolutionary genome relationships

We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.

Addressing Complex Matrix Interference Improves Multiplex Food Allergen Detection by Targeted LC-MS/MS

The frequent use of precautionary food allergen labeling (PAL) such as "may contain" frustrates allergic individuals who rely on such labeling to determine whether a food is safe to consume. One technique to study whether foods contain allergens is targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing scheduled multiple reaction monitoring (MRM). However, the applicability of a single MRM method to many commercial foods is unknown as complex and heterogeneous interferences derived from the unique composition of each food matrix can hinder quantification of trace amounts of allergen contamination. We developed a freely available, open source software package MAtrix-Dependent Interference Correction (MADIC) to identify interference and applied it with a method targeting 14 allergens. Among 84 unique food products, we found patterns of allergen contamination such as wheat in grains, milk in chocolate-containing products, and soy in breads and corn flours. We also found additional instances of contamination in products with and without PAL as well as highly variable soy content in foods containing only soybean oil and/or soy lecithin. These results demonstrate the feasibility of applying LC-MS/MS to a variety of food products with sensitive detection of multiple allergens in spite of variable matrix interference.

Abstract 1372: Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylated cytosines (5hmC) in circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). 5hmC profiles from PDAC and non-cancer samples were generated using a previously published modified hMe-Seal protocol that utilizes chemical labeling of 5hmC by β-glucosyltransferase and allows detection of cell free 5hmC from small amounts of cfDNA (1). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3’UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3 associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in a comprehensive set of genes with the most variable 5hmC counts and performed with an AUC = 0.94 - 0.96 on training data. We tested the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on three independent pancreatic cancer 5hmC data sets (n = 26, 23 and 7) compared with corresponding independent non-cancer cohorts (n =103, 53 and 10), and found validation performance to be AUC = 0.74 - 0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples. Reference: 1. Song, C. - X. et al. 5 - Hydroxymethylcytosine signatures in cell-free DNA provide information about tumor types and stages. Cell Res 27, 1231 (2017).

Citation Format: Francois Collin, Yuhong Ning, Gulfem D. Guler, Tierney Phillips, Erin McCarthy, Aaron Scott, Chris Ellison, Chin-Jen Ku, Kim Chau, Alan Ashworth, Stephen R. Quake, Samuel Levy. Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1372.

Single Cell Transcriptomes Derived from Human Cervical and Uterine Tissue during Pregnancy

This work presents the workflow for generating single cell transcriptomes derived from primary human uterine and cervical tissue obtained during planned cesarean hysterectomies. In total, a catalogue of 310 single cell transcriptomes are obtained, cell types present in these biopsies are inferred, and specific genes defining each of the cellular types present in the tissue are identified. Further validation of the inferred cell identity is also demonstrated via meta-analysis of independent repositories in literature generated by bulk sequenced data of fluorescence-activated cell sorting sorted cells.

Aged blood impairs hippocampal neural precursor activity and activates microglia via brain endothelial cell VCAM1

An aged circulatory environment can activate microglia, reduce neural precursor cell activity, and impair cognition in mice. We hypothesized that brain endothelial cells (BECs) mediate at least some of these effects. We observe BECs in the aged mouse hippocampus express an inflammatory transcriptional profile with focal upregulation of Vascular Cell Adhesion Molecule 1 (VCAM1), a protein that facilitates vascular-immune cell interactions. Concomitantly, the shed, soluble form of VCAM1 is prominently increased in plasma of aged humans and mice, and their plasma is sufficient to increase VCAM1 expression in cultured BECs and young mouse hippocampi. Systemic anti-VCAM1 antibody or genetic ablation of VCAM1 in BECs counteracts the detrimental effects of aged plasma on young brains and reverses aging aspects including microglial reactivity and cognitive deficits in old mouse brains. Together, these findings establish brain endothelial VCAM1 at the blood-brain barrier (BBB) as a possible target to treat age-related neurodegeneration.

Modeling Spatial Correlation of Transcripts with Application to Developing Pancreas

Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. As an illustration, we analyze the spatial distribution of single mRNA molecules measured by in situ sequencing on human fetal pancreas at three developmental time points–80, 87 and 117 days post-fertilization. We develop a density profile-based method to capture the spatial relationship between gene expression and other morphological features of the tissue sample such as position of nuclei and endocrine cells of the pancreas. In addition, we build a statistical model to characterize correlations in the spatial distribution of the expression level among different genes. This model enables us to infer the inhibitory and clustering effects throughout different time points. Our analysis framework is applicable to a wide variety of spatially-resolved transcriptomic data to derive biological insights.

Understanding health disparities

Based upon our recent insights into the determinants of preterm birth, which is the leading cause of death in children under five years of age worldwide, we describe potential analytic frameworks that provides both a common understanding and, ultimately the basis for effective, ameliorative action. Our research on preterm birth serves as an example that the framing of any human health condition is a result of complex interactions between the genome and the exposome. New discoveries of the basic biology of pregnancy, such as the complex immunological and signaling processes that dictate the health and length of gestation, have revealed a complexity in the interactions (current and ancestral) between genetic and environmental forces. Understanding of these relationships may help reduce disparities in preterm birth and guide productive research endeavors and ultimately, effective clinical and public health interventions.

Donor-derived cell-free DNA predicts allograft failure and mortality after lung transplantation

Background

Allograft failure is common in lung-transplant recipients and leads to poor outcomes including early death. No reliable clinical tools exist to identify patients at high risk for allograft failure. This study tested the use of donor-derived cell-free DNA (%ddcfDNA) as a sensitive marker of early graft injury to predict impending allograft failure.

Methods

This multicenter, prospective cohort study enrolled 106 subjects who underwent lung transplantation and monitored them after transplantation for the development of allograft failure (defined as severe chronic lung allograft dysfunction [CLAD], retransplantation, and/or death from respiratory failure). Plasma samples were collected serially in the first three months following transplantation and assayed for %ddcfDNA by shotgun sequencing. We computed the average levels of ddcfDNA over three months for each patient (avddDNA) and determined its relationship to allograft failure using Cox-regression analysis.

Findings

avddDNA was highly variable among subjects: median values were 3·6%, 1·6% and 0·7% for the upper, middle, and low tertiles, respectively (range 0·1%–9·9%). Compared to subjects in the low and middle tertiles, those with avddDNA in the upper tertile had a 6·6-fold higher risk of developing allograft failure (95% confidence interval 1·6–19·9, p = 0·007), lower peak FEV1 values, and more frequent %ddcfDNA elevations that were not clinically detectable.

Interpretation

Lung transplant patients with early unresolving allograft injury measured via %ddcfDNA are at risk of subsequent allograft injury, which is often clinically silent, and progresses to allograft failure.

Fund

National Institutes of Health.

Signatures of selection in the human antibody repertoire: Selective sweeps, competing subclones, and neutral drift

Antibodies are created and refined by somatic evolution in B cell populations, which endows the human immune system with the ability to recognize and eliminate diverse pathogens. However, the evolutionary processes that sculpt antibody repertoires remain poorly understood. Here, using an unbiased repertoire-scale approach, we show that the population genetic signatures of evolution are evident in human B cell lineages and reveal how antibodies evolve somatically. We measured the dynamics and genetic diversity of B cell responses in five adults longitudinally before and after influenza vaccination using high-throughput antibody repertoire sequencing. We identified vaccine-responsive B cell lineages that carry signatures of selective sweeps driven by positive selection, and discovered that they often display evidence for selective sweeps favoring multiple subclones. We also found persistent B cell lineages that exhibit stable population dynamics and carry signatures of neutral drift. By exploiting the relationship between B cell fitness and antibody binding affinity, we demonstrate the potential for using phylogenetic approaches to identify antibodies with high binding affinity. This quantitative characterization reveals that antibody repertoires are shaped by an unexpectedly broad spectrum of evolutionary processes and shows how signatures of evolutionary history can be harnessed for antibody discovery and engineering.

High-affinity allergen-specific human antibodies cloned from single IgE B cell transcriptomes

Immunoglobulin E (IgE) antibodies protect against helminth infections but can also cause life-threatening allergic reactions. Despite their role in human health, the cells that produce these antibodies are rarely observed and remain enigmatic. We isolated single IgE B cells from individuals with food allergies and used single-cell RNA sequencing to elucidate the gene expression and splicing patterns unique to these cells. We identified a surprising example of convergent evolution in which IgE antibodies underwent identical gene rearrangements in unrelated individuals. Through the acquisition of variable region mutations, these IgE antibodies gained high affinity and unexpected cross-reactivity to the clinically important peanut allergens Ara h 2 and Ara h 3. These findings provide insight into IgE B cell transcriptomics and enable biochemical dissection of this antibody class.

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy

Motivation

Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.

Results

We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.

Availability and implementation

Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.

Supplementary information

Supplementary data are available at Bioinformatics online.