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DOE OSTI2019

Deep Reinforcement Learning and Simulation as a Path Toward Precision Medicine

In the past, precision medicine involves classifying patients to identify subpopulations that respond favorably to specific therapeutics. We discuss precision medicine as a dynamic feedback control problem, where treatment administered to a patient is guided by measurements taken during the course of treatment. We consider sepsis, a life-threatening condition in which dysregulation of the immune system causes tissue damage. We leverage an existing simulation of the innate immune response to infection and apply deep reinforcement learning (DRL) to discover an adaptive personalized treatment policy that specifies effective multicytokine therapy to simulated sepsis patients based on systemic measurements. The learned policy achieves a dramatic reduction in mortality rate over a set of 500 simulated patients relative to standalone antibiotic therapy. Advantages of our approach are threefold: (1) the use of simulation allows exploring therapeutic strategies beyond clinical practice and available data, (2) advances in DRL accommodate learning complex therapeutic strategies for complex biological systems, and (3) optimized treatments respond to a patient's individual disease progression over time, therefore, capturing both differences across patients and the inherent randomness of disease progression within a single patient. We believe that this work motivates both considering adaptive personalized multicytokine mediation therapy for sepsis and exploiting simulation with DRL for precision medicine more broadly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A Unified Resource for Tracking Anti-CRISPR Names

In the battle between CRISPR-Cas* prokaryotic immune systems and the elements that they target, a diverse array of “anti-CRISPR” proteins have evolved. These proteins appear to have arisen independently multiple times in evolution and function through diverse mechanisms to inhibit CRISPR-Cas immunity. For comprehensive reviews on anti-CRISPRs, we direct readers to recent publications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Statistical relationships across epigenomes using large-scale hierarchical clustering

Recent advances in genomics and sequencing platforms have revolutionized our ability to create immense data sets, particularly for studying epigenetic regulation of gene expression. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given nonlinear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3000 epigenomes of uninfected individuals and provide a framework to characterize the relationships among epigenetic modifiers, their modifiers, genetic loci, and specific immune cell types across all chromosomes using hierarchical clustering. Hierarchical clustering of epigenomic data revealed consistent epigenetic patterns across chromosomes, demonstrating that variation due to epigenetic modifiers is greater than variation between cell types. Gene Ontology and KEGG pathway analyses indicated significant enrichment of genes involved in chromatin remodeling, mRNA splicing, immune responses, and the regulation of microRNAs and snoRNAs. Epigenetic modifiers frequently formed biologically relevant clusters, including the cohesin complex, RNA Polymerase II transcription factors, and PRC2 complex members. These clustering behaviors remained consistent across all chromosomes, supported by entropy analysis and high Adjusted Rand Index scores, indicating robust cross-chromosomal similarity. Co-occurrence analysis further revealed specific sets of modifiers that consistently appeared together within clusters, reflecting shared biological functions and interactions. Validation using another dataset confirmed the reproducibility of these clustering patterns and modifier co-occurrence relationships, underscoring the reliability and generalizability of the methodology.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

wavess 1.2: presenting an HLA-aware within-host virus sequence simulation framework

Motivation Understanding how virus sequences are shaped by selection can inform vaccine design and transmission inference. Modeling within-host evolution to interrogate these questions requires a detailed mechanistic framework that accurately captures sequence diversification. The CD8 + cytotoxic T-lymphocyte (CTL) response plays an important role in immune-mediated selection and can leave strong signatures in virus sequences; however, existing sequence-based within-host virus modeling frameworks do not explicitly include a human leukocyte antigen (HLA)-aware CTL response. Results We extended our previously published within-host sequence evolution simulator, wavess, to include an explicit CTL response, and share a method for identifying HLA-specific CTL epitopes given a founder virus sequence. We also updated the model to permit a variable recombination rate, which allows for modeling non-adjacent genes, segmented genomes, and recombination hotspots. These extensions to wavess allow for more accurate simulation of viruses and virus genes, particularly in regions of the genome where the immune response is dominated by CTLs (rather than antibodies). It also provides the foundation for investigations of how these newly-added biological mechanisms influence within-host evolution. Availability and implementation The core of wavess is written in Python 3, with helper functions written in R. It is available at https://github.com/MolEvolEpid/wavess.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

ACTINN: automated identification of cell types in single cell RNA sequencing

Abstract Motivation Cell type identification is one of the major goals in single cell RNA sequencing (scRNA-seq). Current methods for assigning cell types typically involve the use of unsupervised clustering, the identification of signature genes in each cluster, followed by a manual lookup of these genes in the literature and databases to assign cell types. However, there are several limitations associated with these approaches, such as unwanted sources of variation that influence clustering and a lack of canonical markers for certain cell types. Here, we present ACTINN (Automated Cell Type Identification using Neural Networks), which employs a neural network with three hidden layers, trains on datasets with predefined cell types and predicts cell types for other datasets based on the trained parameters. Results We trained the neural network on a mouse cell type atlas (Tabula Muris Atlas) and a human immune cell dataset, and used it to predict cell types for mouse leukocytes, human PBMCs and human T cell sub types. The results showed that our neural network is fast and accurate, and should therefore be a useful tool to complement existing scRNA-seq pipelines. Availability and implementation The codes and datasets are available at https://figshare.com/articles/ACTINN/8967116. Tutorial is available at https://github.com/mafeiyang/ACTINN. All codes are implemented in python. Supplementary information Supplementary data are available at Bioinformatics online.

Ma, Feiyang (ORCID:0000000262600787)↗

DOE OSTI2018

FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true ‘machine-actionable interoperability’, which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Deducing the N- and O-glycosylation profile of the spike protein of novel coronavirus SARS-CoV-2

The current emergence of the novel coronavirus pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demands the development of new therapeutic strategies to prevent rapid progress of mortalities. The coronavirus spike (S) protein, which facilitates viral attachment, entry and membrane fusion is heavily glycosylated and plays a critical role in the elicitation of the host immune response. The spike protein is comprised of two protein subunits (S1 and S2), which together possess 22 potential N-glycosylation sites. Herein, we report the glycosylation mapping on spike protein subunits S1 and S2 expressed on human cells through high-resolution mass spectrometry. We have characterized the quantitative N-glycosylation profile on spike protein and interestingly, observed unexpected O-glycosylation modifications on the receptor-binding domain of spike protein subunit S1. Even though O-glycosylation has been predicted on the spike protein of SARS-CoV-2, this is the first report of experimental data for both the site of O-glycosylation and identity of the O-glycans attached on the subunit S1. Our data on the N- and O-glycosylation are strengthened by extensive manual interpretation of each glycopeptide spectra in addition to using bioinformatics tools to confirm the complexity of glycosylation in the spike protein. Here, the elucidation of the glycan repertoire on the spike protein provides insights into the viral binding studies and more importantly, propels research toward the development of a suitable vaccine candidate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A CRISPR-Cas9–integrase complex generates precise DNA fragments for genome integration

CRISPR-Cas9 is an RNA-guided DNA endonuclease involved in bacterial adaptive immunity and widely repurposed for genome editing in human cells, animals and plants. In bacteria, RNA molecules that guide Cas9 s activity derive from foreign DNA fragments that are captured and integrated into the host CRISPR genomic locus by the Cas1-Cas2 CRISPR integrase. How cells generate the specific lengths of DNA required for integrase capture is a central unanswered question of type II-A CRISPR-based adaptive immunity. Here, we show that an integrase supercomplex comprising guide RNA and the proteins Cas1, Cas2, Csn2 and Cas9 generates precisely trimmed 30-base pair DNA molecules required for genome integration. The HNH active site of Cas9 catalyzes exonucleolytic DNA trimming by a mechanism that is independent of the guide RNA sequence. These results show that Cas9 possesses a distinct catalytic capacity for generating immunological memory in prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Evolutionary analysis of the LORELEI gene family in plants reveals regulatory subfunctionalization

Abstract A signaling complex comprising members of the LORELEI (LRE)-LIKE GPI-anchored protein (LLG) and Catharanthus roseus RECEPTOR-LIKE KINASE 1-LIKE (CrRLK1L) families perceive RAPID ALKALINIZATION FACTOR (RALF) peptides and regulate growth, reproduction, immunity, and stress responses in Arabidopsis (Arabidopsis thaliana). Genes encoding these proteins are members of multigene families in most angiosperms and could generate thousands of signaling complex variants. However, the links between expansion of these gene families and the functional diversification of this critical signaling complex as well as the evolutionary factors underlying the maintenance of gene duplicates remain unknown. Here, we investigated LLG gene family evolution by sampling land plant genomes and explored the function and expression of angiosperm LLGs. We found that LLG diversity within major land plant lineages is primarily due to lineage-specific duplication events, and that these duplications occurred both early in the history of these lineages and more recently. Our complementation and expression analyses showed that expression divergence (i.e. regulatory subfunctionalization), rather than functional divergence, explains the retention of LLG paralogs. Interestingly, all but one monocot and all eudicot species examined had an LLG copy with preferential expression in male reproductive tissues, while the other duplicate copies showed highest levels of expression in female or vegetative tissues. The single LLG copy in Amborella trichopoda is expressed vastly higher in male compared to in female reproductive or vegetative tissues. We propose that expression divergence plays an important role in retention of LLG duplicates in angiosperms.

Plant Sciences↗

DOE OSTI2022

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

Abstract TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Aging Exacerbates Neuroinflammatory Outcomes Induced by Acute Ozone Exposure

The role of environmental stressors, particularly exposure to air pollution, in the development of neurodegenerative disease remains underappreciated. We examined the neurological effects of acute ozone (O 3 ) exposure in aged mice, where increased blood brain barrier (BBB) permeability may confer vulnerability to neuroinflammatory outcomes. C 57 BL/6 male mice, aged 8-10 weeks or 12–18 months were exposed to either filtered air (FA) or 1.0 ppm O 3 for 4 hours; animals received a single IP injection of sodium fluorescein (FSCN) 20 hours post-exposure. One-hour post-FSCN injection, animals were transcardially perfused for immunohistochemical analysis of BBB permeability. β-amyloid protein expression was assessed via ELISA. Flow cytometric characterization of infiltrating immune cells, including neutrophils, macrophages, and microglia populations was performed 20 hours post-O 3 exposure. Flow cytometry analysis of brains revealed increased microglia “activation” and presentation of CD11b, F4/80 and MHCII in aged animals relative to younger ones; these age-induced differences were potentiated by acute O 3 exposure. Cortical and limbic regions in aged brains had increased reactive microgliosis and β-amyloid protein expression after O 3 insult. The aged cerebellum was particularly vulnerable to acute O 3 exposure with increased populations of infiltrating neutrophils, peripheral macrophages/monocytes, and Ly6C + inflammatory monocytes after insult, which were not significantly increased in the young cerebellum. O 3 exposure increased the penetration of FSCN beyond the BBB, the infiltration of peripheral immune cells, and reactive gliosis of microglia. Furthermore, the aged BBB is vulnerable to insult and becomes highly penetrable in response to O 3 exposure, leading to greater neuroinflammatory outcomes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

JAZ proteins promote growth and reproduction by restraining transcriptional programs that link primary and specialized metabolism

Plants constantly experience attack from surrounding organisms. Because they cannot escape from the environment, plants have evolved a sophisticated immune system to defend themselves against pests and pathogens. However, mounting a defense response is often accompanied by a decrease in growth. The antagonistic relationship between growth and defense has been interpreted as the plant's “dilemma” of how to distribute limited resources between these two fundamental processes. Jasmonic acid (JA) and its derivatives are a class of lipid‐derived hormones that mediate plant immunity against insect herbivores and necrotrophic pathogens, as well as growth, reproduction, and several other physiological processes. JA is perceived by its receptor CORONATINE INSENSITIVE 1 (COI1), which mediates the degradation of the JASMONATE ZIM DOMAIN (JAZ) transcriptional repressors by the 26S proteasome. JAZ degradation releases JA‐responsive transcription factors such as MYC2 from repression, thereby initiating JA responses. Despite the importance of JA in mediating growth‐defense tradeoffs, the mechanism by which JA effects carbon resource allocation between growth and defense is poorly understood. In this study we demonstrate strong constitutive activation of JA signaling pathway in an Arabidopsis mutant ( jazD ) that lacks ten members of JASMONATE ZIM DOMAIN (JAZ) family proteins. This mutant displayed elevated defense against insect herbivores, stunted growth of vegetative tissues, as well as compromised seed reproduction. Metabolic phenotypes of jazD discerned from global protein and transcript profiling were indicative of elevated carbon allocation to protein‐ and amino acid‐based defense compounds. The strong defense sink in jazD leaves was linked to increased respiration and hallmarks of carbon starvation, whereas area‐based photosynthetic efficiency was unaffected. These findings establish a role for JAZ proteins in promoting growth and reproductive success through restraint of transcriptional programs that link primary metabolism to specialized metabolism. Our data suggest that JAZs adjust growth‐defense balance to match anticipated changes in carbon availability, potentially avoiding detrimental effects of carbon limitation that arise during growth‐to‐defense transitions. Support or Funding Information This research was funded by the Chemical Sciences, Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, US Department of Energy through grant DE–FG02–91ER20021. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Guo, Qiang↗

DOE OSTI2023

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and P l a n c k . II. Cross-correlation measurements and cosmological constraints

Cross-correlations of galaxy positions and galaxy shears with maps of gravitational lensing of the cosmic microwave background (CMB) are sensitive to the distribution of large-scale structure in the Universe. Such cross-correlations are also expected to be immune to some of the systematic effects that complicate correlation measurements internal to galaxy surveys. We present measurements and modeling of the cross-correlations between galaxy positions and galaxy lensing measured in the first three years of data from the Dark Energy Survey with CMB lensing maps derived from a combination of data from the 2500 deg 2 SPT-SZ survey conducted with the South Pole Telescope and full-sky data from the Planck satellite. The CMB lensing maps used in this analysis have been constructed in a way that minimizes biases from the thermal Sunyaev Zel’dovich effect, making them well suited for cross-correlation studies. The total signal-to-noise of the cross-correlation measurements is 23.9 (25.7) when using a choice of angular scales optimized for a linear (nonlinear) galaxy bias model. Here we use the cross-correlation measurements to obtain constraints on cosmological parameters. For our fiducial galaxy sample, which consist of four bins of magnitude-selected galaxies, we find constraints of Ω m =0.272$^{+0.032}_{-0.052}$ and S 8 ≡σ8$\sqrt{Ω_m/0.3}$=0.736$^{+0.032}_{-0.028}$ (Ω m =0.245$^{+0.026}_{-0.044}$ and S 8 =0.734$^{+0.035}_{-0.028}$) when assuming linear (nonlinear) galaxy bias in our modeling. Considering only the cross-correlation of galaxy shear with CMB lensing, we find Ω m =0.270$^{+0.043}_{-0.061}$ and S 8 =0.740$^{+0.034}_{-0.029}$. Our constraints on S8 are consistent with recent cosmic shear measurements, but lower than the values preferred by primary CMB measurements from Planck.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Structure of the Fc fragment of the NIST reference antibody RM8671

As the link between antigen binding and immune activation, the antibody Fc region has received extensive structural study. In this report, the structure of the Fc fragment of the NIST IgG1 mAb (reference material 8671) is described at 2.1 Å resolution in space group P 2 1 2 1 2 1 , with approximate unit-cell parameters a = 50, b = 80, c = 138 Å. Prior Fc structures with a wide variety of modifications are also surveyed, focusing on those in the same crystal form. To facilitate the analysis of conformations, a reference frame and a two-parameter metric are proposed, considering the CH 2 domains as mobile with respect to a fixed dimeric CH 3 core. Over several human Fc structures, a significant variation in Fc elbow conformations is observed, which may serve to facilitate the regulation of Fc effector signaling.

Gallagher, D. Travis↗

DOE OSTI2019

Structure of interferon-stimulated gene product 15 (ISG15) from the bat species Myotis davidii and the impact of interdomain ISG15 interactions on viral protein engagement

Bats have long been observed to be the hosts and the origin of numerous human diseases. Bats, like all mammals, rely on a number of innate immune mechanisms to combat invading pathogens, including the interferon type I, II and III responses. Ubiquitin-like interferon-stimulated gene product 15 (ISG15) is a key modulator of these interferon responses. Within these pathways, ISG15 can serve to stabilize host proteins modulating innate immune responses and act as a cytokine. Post-translational modifications of viral proteins introduced by ISG15 have also been observed to directly affect the function of numerous viral proteins. Unlike ubiquitin, which is virtually identical across all animals, comparison of ISG15s across species reveals that they are relatively divergent, with sequence identity dropping to as low as ~58% among mammals. In addition to serving as an obstacle to the zoonotic transmission of influenza, these ISG15 species–species differences have also long been shown to have an impact on the function of viral deISGylases. Recently, the structure of the first nonhuman ISG15, originating from mouse, suggested that the structures of human ISG15 may not be reflective of other species. Here, the structure of ISG15 from the bat species Myotis davidii solved to 1.37 Å resolution is reported. Comparison of this ISG15 structure with those from human and mouse not only underscores the structural impact of ISG15 species–species differences, but also highlights a conserved hydrophobic motif formed between the two domains of ISG15. Using the papain-like deISGylase from Severe acute respiratory syndrome coronavirus as a probe, the biochemical importance of this motif in ISG15–protein engagements was illuminated.

Langley, Caroline↗

DOE OSTI2021

Hardware Design of Medium Voltage SiC-Based Modular Multilevel Converters for Grid-Tied Applications

This paper presents a design of a 10 kV silicon carbide (SiC) MOSFET based modular multilevel converter (MMC). The MMC functions as the interconnection between a 24 kV dc bus and a 13. SkV distribution grid. This paper focuses on the hardware design of the MMC and its submodules. The gate driver, auxiliary power supply and bus bur in submodules are major components that need to meet high dv/dt immunity and high insulation voltage requirements. The gate driver achieves over 200 kV/us common mode transient immunity (CMTI). Its associated auxiliary power supply is based on an on-board transformer with over 30 kV insulation capability and 1.4 pF barrier capacitance. The busbar achieves less than 11 kV/cm electric field in the air to avoid partial discharges. Validation tests of the MMC submodule were performed by double pulse tests at 5 kV and buck converter tests at3 kV, 52A (peak). Reliable operations were achieved in validation tests.

auxiliary power supply↗

DOE OSTI2020

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗

DOE OSTI2018

Mathematical modeling of within-host Zika virus dynamics

Recent Zika virus outbreaks have been associated with severe outcomes, especially during pregnancy. A great deal of effort has been put toward understanding this virus, particularly the immune mechanisms responsible for rapid viral control in the majority of infections. Identifying and understanding the key mechanisms of immune control will provide the foundation for the development of effective vaccines and antiviral therapy. In this paper, we outline a mathematical modeling approach for analyzing the within-host dynamics of Zika virus, and we describe how these models can be used to understand key aspects of the viral life cycle and to predict antiviral efficacy.

60 APPLIED LIFE SCIENCES↗