Host-microbe multiomic profiling reveals age-dependent immune dysregulation associated with COVID-19 immunopathology

Age is a major risk factor for severe coronavirus disease 2019 (COVID-19), yet the mechanisms behind this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host immune response in the blood and the upper airway, as well as the nasal microbiome in a prospective, multicenter cohort of 1031 vaccine-naïve patients hospitalized for COVID-19 between 18 and 96 years old. We performed mass cytometry, serum protein profiling, anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody assays, and blood and nasal transcriptomics. We found that older age correlated with increased SARS-CoV-2 viral abundance upon hospital admission, delayed viral clearance, and increased type I interferon gene expression in both the blood and upper airway. We also observed age-dependent up-regulation of innate immune signaling pathways and down-regulation of adaptive immune signaling pathways. Older adults had lower naïve T and B cell populations and higher monocyte populations. Over time, older adults demonstrated a sustained induction of pro-inflammatory genes and serum chemokines compared with younger individuals, suggesting an age-dependent impairment in inflammation resolution. Transcriptional and protein biomarkers of disease severity differed with age, with the oldest adults exhibiting greater expression of pro-inflammatory genes and proteins in severe disease. Together, our study finds that aging is associated with impaired viral clearance, dysregulated immune signaling, and persistent and potentially pathologic activation of pro-inflammatory genes and proteins.

Computational prediction of protein interactions in single cells by proximity sequencing

Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model of Prox-seq and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.

Host-Microbe Multiomic Profiling Reveals Age-Dependent COVID-19 Immunopathology

Age is a major risk factor for severe coronavirus disease-2019 (COVID-19), yet the mechanisms responsible for this relationship have remained incompletely understood. To address this, we evaluated the impact of aging on host and viral dynamics in a prospective, multicenter cohort of 1,031 patients hospitalized for COVID-19, ranging from 18 to 96 years of age. We performed blood transcriptomics and nasal metatranscriptomics, and measured peripheral blood immune cell populations, inflammatory protein expression, anti-SARS-CoV-2 antibodies, and anti-interferon (IFN) autoantibodies. We found that older age correlated with an increased SARS-CoV-2 viral load at the time of admission, and with delayed viral clearance over 28 days. This contributed to an age-dependent increase in type I IFN gene expression in both the respiratory tract and blood. We also observed age-dependent transcriptional increases in peripheral blood IFN-γ, neutrophil degranulation, and Toll like receptor (TLR) signaling pathways, and decreases in T cell receptor (TCR) and B cell receptor signaling pathways. Over time, older adults exhibited a remarkably sustained induction of proinflammatory genes (e.g., CXCL6) and serum chemokines (e.g., CXCL9) compared to younger individuals, highlighting a striking age-dependent impairment in inflammation resolution. Augmented inflammatory signaling also involved the upper airway, where aging was associated with upregulation of TLR, IL17, type I IFN and IL1 pathways, and downregulation TCR and PD-1 signaling pathways. Metatranscriptomics revealed that the oldest adults exhibited disproportionate reactivation of herpes simplex virus and cytomegalovirus in the upper airway following hospitalization. Mass cytometry demonstrated that aging correlated with reduced naïve T and B cell populations, and increased monocytes and exhausted natural killer cells. Transcriptional and protein biomarkers of disease severity markedly differed with age, with the oldest adults exhibiting greater expression of TLR and inflammasome signaling genes, as well as proinflammatory proteins (e.g., IL6, CXCL8), in severe COVID-19 compared to mild/moderate disease. Anti-IFN autoantibody prevalence correlated with both age and disease severity. Taken together, this work profiles both host and microbe in the blood and airway to provide fresh insights into aging-related immune changes in a large cohort of vaccine-naïve COVID-19 patients. We observed age-dependent immune dysregulation at the transcriptional, protein and cellular levels, manifesting in an imbalance of inflammatory responses over the course of hospitalization, and suggesting potential new therapeutic targets.

Shared sequence characteristics identified in non-canonical rearrangements of HSV-1 genomes

IMPORTANCE

Mutations and genetic rearrangements are the primary driving forces of evolution. Viruses provide valuable model systems for investigating these mechanisms due to their rapid evolutionary rates and vast genetic variability. To investigate genetic rearrangements in the double-stranded DNA genome of herpes simplex virus type 1, the viral population was serially passaged in various cell types. The serial passaging led to formation of defective genomes, resulted from cell-specific non-canonical rearrangements (NCRs). Interestingly, we discovered shared sequence characteristics underlying the formation of these NCRs across all cell types. Moreover, most NCRs identified in clinical samples shared these characteristics. Based on our findings, we propose a model elucidating the formation of NCRs during viral replication within the nucleus of eukaryotic cells.

Computational prediction of protein interactions on single cells by proximity sequencing

Proximity sequencing (Prox-seq) measures gene expression, protein expression, and protein complexes at the single cell level, using information from dual-antibody binding events and a single cell sequencing readout. Prox-seq provides multi-dimensional phenotyping of single cells and was recently used to track the formation of receptor complexes during inflammatory signaling in macrophages and to discover a new interaction between CD9/CD8 proteins on naïve T cells. The distribution of protein abundance affects identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model for protein dimer formation on single cells and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq single-cell data, which resulted in more accurate and robust quantification of protein complexes. Finally, our model offers a simple way to investigate the behavior of Prox-seq under various biological conditions and guide users toward selecting the best analysis method for their data.

Quantification of extracellular proteins, protein complexes and mRNAs in single cells by proximity sequencing

We present proximity sequencing (Prox-seq) for simultaneous measurement of proteins, protein complexes and mRNAs in thousands of single cells. Prox-seq combines proximity ligation assay with single-cell sequencing to measure proteins and their complexes from all pairwise combinations of targeted proteins, providing quadratically scaled multiplexing. We validate Prox-seq and analyze a mixture of T cells and B cells to show that it accurately identifies these cell types and detects well-known protein complexes. Next, by studying human peripheral blood mononuclear cells, we discover that naïve CD8+ T cells display the protein complex CD8-CD9. Finally, we study protein interactions during Toll-like receptor (TLR) signaling in human macrophages. We observe the formation of signal-specific protein complexes, find CD36 co-receptor activity and additive signal integration under lipopolysaccharide (TLR4) and Pam2CSK4 (TLR2) stimulation, and show that quantification of protein complexes identifies signaling inputs received by macrophages. Prox-seq provides access to an untapped measurement modality for single-cell phenotyping and can discover uncharacterized protein interactions in different cell types.

High-throughput RNA sequencing of paraformaldehyde-fixed single cells

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited. This is because current high-throughput single-cell RNA sequencing methods are either incompatible with or necessitate laborious sample preprocessing for paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq (Fixed Droplet RNA sequencing), a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, permeabilized and sorted single cells. We show that FD-seq preserves the RNA integrity and relative gene expression levels after fixation and permeabilization. Furthermore, FD-seq can detect a higher number of genes and transcripts than methanol fixation. We first apply FD-seq to analyze a rare subpopulation of cells supporting lytic reactivation of the human tumor virus KSHV, and identify TMEM119 as a potential host factor that mediates viral reactivation. Second, we find that infection with the human betacoronavirus OC43 leads to upregulation of pro-inflammatory pathways in cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell subpopulations, and preserving and inactivating pathogenic samples.

High-throughput RNA sequencing of paraformaldehyde-fixed single cells

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited. This is because current high-throughput single-cell RNA sequencing methods are either incompatible with or necessitate laborious sample preprocessing for paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq (Fixed Droplet RNA sequencing), a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, permeabilized and sorted single cells. We show that FD-seq preserves the RNA integrity and relative gene expression levels after fixation and permeabilization. Furthermore, FD-seq can detect a higher number of genes and transcripts than methanol fixation. We first apply FD-seq to analyze a rare subpopulation of cells supporting lytic reactivation of the human tumor virus KSHV, and identify TMEM119 as a potential host factor that mediates viral reactivation. Second, we find that infection with the human betacoronavirus OC43 leads to upregulation of pro-inflammatory pathways in cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell subpopulations, and preserving and inactivating pathogenic samples.

Current high-throughput single-cell transcriptomic methods are incompatible with paraformaldehyde, a common cell fixation technique. Here the authors present FD-seq, a method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single cells.

Fixed single-cell RNA sequencing for understanding virus infection and host response

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited because current high-throughput RNA sequencing methods are incompatible with paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We show that FD-seq preserves the mRNA integrity and relative abundances during fixation and subsequent cell retrieval. Furthermore, FD-seq detects a higher number of genes and transcripts than methanol fixation. We applied FD-seq to investigate two important questions in Virology. First, by analyzing a rare population of cells supporting lytic reactivation of the human tumor virus KSHV, we identified TMEM119 as a host factor that mediates viral reactivation. Second, we found that upon infection with the betacoronavirus OC43, which causes the common cold and is a close relative of SARS-CoV-2, pro-inflammatory pathways are primarily upregulated in lowly-infected cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell populations, and preserving and inactivating pathogenic samples that cannot be handled under regular biosafety measures.

Ultrasensitive digital quantification of cytokines and bacteria predicts septic shock outcomes

Quantification of pathogen and host biomarkers is essential for the diagnosis, monitoring, and treatment of infectious diseases. Here, we demonstrate sensitive and rapid quantification of bacterial load and cytokines from human biological samples to generate actionable hypotheses. Our digital assay measures IL-6 and TNF-α proteins, gram-negative (GN) and gram-positive (GP) bacterial DNA, and the antibiotic-resistance gene bla_TEM with femtomolar sensitivity. We use our method to characterize bronchoalveolar lavage fluid from patients with asthma, and find elevated GN bacteria and IL-6 levels compared to healthy subjects. We then analyze plasma from patients with septic shock and find that increasing levels of IL-6 and bla_TEM are associated with mortality, while decreasing IL-6 levels are associated with recovery. Surprisingly, lower GN bacteria levels are associated with higher probability of death. Applying decision-tree analysis to our measurements, we are able to predict mortality and rate of recovery from septic shock with over 90% accuracy.

Ultrasensitive methods for detection of biomarkers for infectious disease are needed for diagnosing, monitoring and targeting treatment. Here the authors develop a digital assay for inflammatory markers, bacterial DNA and antibotic-resistance genes and apply it to characterise asthma patients and predict mortality from septic shock.

Ultra-sensitive digital quantification of proteins and mRNA in single cells

Simultaneous measurement of proteins and mRNA in single cells enables quantitative understanding and modeling of cellular functions. Here, we present an automated microfluidic system for multi-parameter and ultra-sensitive protein/mRNA measurements in single cells. Our technology improves the sensitivity of digital proximity ligation assay by up to 55-fold, with a detection limit of 2277 proteins per cell and with detection efficiency of as few as 29 protein molecules. Our measurements using this system reveal higher mRNA/protein correlation in single mammalian cells than previous estimates. Furthermore, time-lapse imaging of herpes simplex virus 1 infected epithelial cells enabled by our device shows that expression of ICP4 -a major transcription factor regulating hundreds of viral genes- is only partially correlated with viral protein counts, suggesting that many cells go through abortive infection. These results highlight the importance of high-sensitivity protein/mRNA quantification for understanding fundamental molecular mechanisms in individual cells.

Digital proximity ligation assay (dPLA) can measure proteins and mRNAs in single cells, but is not compatible with cell imaging and cannot quantify rare proteins due to a high dilution factor. Here the authors present an automated microfluidic device that combines live-cell imaging, chemical stimulation, and dPLA in a smaller reaction volume.

Acoustically enhanced microfluidic mixer to synthesize highly uniform nanodrugs without the addition of stabilizers

Background

This article presents an acoustically enhanced microfluidic mixer to generate highly uniform and ultra-fine nanoparticles, offering significant advantages over conventional liquid antisolvent techniques.

Methods

The method employed a 3D microfluidic geometry whereby two different phases – solvent and antisolvent – were introduced at either side of a 1 μm thick resonating membrane, which contained a through-hole. The vibration of the membrane rapidly and efficiently mixed the two phases, at the location of the hole, leading to the formation of nanoparticles.

Results

The versatility of the device was demonstrated by synthesizing budesonide (a common asthma drug) with a mean diameter of 135.7 nm and a polydispersity index of 0.044.

Conclusion

The method offers a 40-fold reduction in the size of synthesized particles combined with a substantial improvement in uniformity, achieved without the need of stabilizers.

Droplet Manipulation Using Acoustic Streaming Induced by a Vibrating Membrane

We present a simple method for on-demand manipulation of aqueous droplets in oil. With numerical simulations and experiments, we show that a vibrating membrane can produce acoustic streaming. By making use of this vortical flow, we manage to repulse the droplets away from the membrane edges. Then, by simply aligning the membrane at 45° to the flow, the droplets can be forced to follow the membrane's boundaries, thus steering them across streamlines and even between different oil types. We also characterize the repulsion and steering effect with various excitation voltages at different water and oil flow rates. The maximum steering frequency we have achieved is 165 Hz. The system is extremely robust and reliable: the same membrane can be reused after many days and with different oils and/or surfactants at the same operating frequency.

On-chip droplet production regimes using surface acoustic waves

Aqueous droplets suspended in an immiscible carrier fluid are a key tool in microfluidic chemical analysis platforms. The approaches for producing droplets in microfluidic devices can be divided into three general categories: batch emulsification, continuous production and tailored on-demand production. The major distinctions between each category are the rate of production and the degree of control over the droplet formation process in terms of the size and quantity. On-demand methods are highly desirable when, for example, small numbers or even single droplets of one sample type are required at a time. Here, we present a method for the on-demand production of femtolitre droplets, utilising a pressure source generated by high frequency surface acoustic waves (SAW). An increase in the continuous phase flow rate is enabled by a quasi-3D feature at the droplet production nozzle. A wide range of accessible flow rates permits the identification of different physical regimes in which droplets of different dimensions are produced. In the system investigated droplets measuring as little as 200 fl have been produced, ∼1/60th of the minimum volume previously reported. The experimental findings are supported by a numerical model which demonstrates the link between the number of droplets formed and the pulse length used.

Vibrating membrane with discontinuities for rapid and efficient microfluidic mixing

This study presents a novel acoustic mixer comprising of a microfabricated silicon nitride membrane with a hole etched through it. We show that the introduction of the through hole leads to extremely fast and homogeneous mixing. When the membrane is immersed in fluid and subjected to acoustic excitation, a strong streaming field in the form of vortices is generated. The vortices are always observed to centre at the hole, pointing to the critical role it has on the streaming field. We hypothesise that the hole introduces a discontinuity to the boundary conditions of the membrane, leading to strong streaming vortices. With numerical simulations, we show that the hole's presence can increase the volume force responsible for driving the streaming field by 2 orders of magnitude, thus supporting our hypothesis. We investigate the mixing performance at different Peclet numbers by varying the flow rates for various devices containing circular, square and rectangular shaped holes of different dimensions. We demonstrate rapid mixing within 3 ms mixing time (90% mixing efficiency at 60 μl min(-1) total flow rate, Peclet number equals 8333 ± 3.5%) is possible with the current designs. Finally, we examine the membrane with two circular holes which are covered by air bubbles and compare it to when the membrane is fully immersed. We find that coupling between the holes' vortices occurs only when membrane is immersed; while with the bubble membrane, the upstream hole's vortices can act as a blockage to fluid flow passing it.