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While durable antibody responses from long-lived plasma cell (LLPC) populations are important for protection against pathogens, LLPC may be harmful if they produce antibodies against self-proteins or self-nuclear antigens as occurs in autoimmune diseases such as systemic lupus erythematosus (SLE). Thus, the elimination of autoreactive LLPC may improve the treatment of antibody-driven autoimmune diseases. However, LLPC remain a challenging therapeutic target. Here, we compare the matched bone marrow (BM) and peripheral blood (PBL) plasma cell (PC) compartments of SLE and healthy donors (HD). We show a similar distribution of CD138- and CD138+ PC, including putative LLPC (CD19- CD138+ CD38+), between SLE and HD BM. For both SLE and HD, CD138+ PC are at a higher frequency in BM than PBL. Expression of Ki-67 associates with the PBL compartment where it is found on all PC subsets regardless of CD19 or CD138 expression. Transcriptomic analysis identifies an interferon (IFN) gene signature in transitional B cells in the SLE BM, but surprisingly also in the BM PC derived from SLE. BM PC and B cells phosphorylate STAT1 in response to type I IFN stimulation in vitro , but with decreased fold change compared to those from the PBL. While BM PC bind type I IFN receptor-blocking antibody anifrolumab, it is to a lesser degree than circulating B cells. Anti-nuclear autoantibodies (ANA) are found in the BM supernatant and PBL serum of SLE patients. Both SLE and HD BM-derived PC have increased survival compared to their PBL counterparts when treated with verdinexor. In summary, these findings show evidence of IFN activation in BM PC from SLE., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2025 Alzamareh, Meednu, Nandedkar-Kulkarni, Krenitsky, Barnard, Yasaka, Durrett, Thakar, Rangel-Moreno, Anolik and Barnas.)

Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins. The immune response is complex and varies across diseases and patients, and its modelling requires the collective expertise of the clinical, immunology, and computational modelling communities. This review outlines the initial progress on immune digital twins and the various initiatives to facilitate communication between interdisciplinary communities. We also outline the crucial aspects of an immune digital twin design and the prerequisites for its implementation in the clinic. We propose some initial use cases that could serve as "proof of concept" regarding the utility of immune digital technology, focusing on diseases with a very different immune response across spatial and temporal scales (minutes, days, months, years). Lastly, we discuss the use of digital twins in drug discovery and point out emerging challenges that the scientific community needs to collectively overcome to make immune digital twins a reality., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Dietary restriction (DR), the process of decreasing overall food consumption over an extended period of time, has been shown to increase longevity across evolutionarily diverse species and delay the onset of age-associated diseases in humans. In Caenorhabditis elegans, the Myc-family transcription factors (TFs) MXL-2 (Mlx) and MML-1 (MondoA/ChREBP), which function as obligate heterodimers, and PHA-4 (orthologous to FOXA) are both necessary for the full physiological benefits of DR. However, the adaptive transcriptional response to DR and the role of MML-1::MXL-2 and PHA-4 remains elusive. We identified the transcriptional signature of C. elegans DR, using the eat-2 genetic model, and demonstrate broad changes in metabolic gene expression in eat-2 DR animals, which requires both mxl-2 and pha-4. While the requirement for these factors in DR gene expression overlaps, we found many of the DR genes exhibit an opposing change in relative gene expression in eat-2;mxl-2 animals compared to wild-type, which was not observed in eat-2 animals with pha-4 loss. Surprisingly, we discovered more than 2000 genes synthetically dysregulated in eat-2;mxl-2, out of which the promoters of down-regulated genes were substantially enriched for PQM-1 and ELT-1/3 GATA TF binding motifs. We further show functional deficiencies of the mxl-2 loss in DR outside of lifespan, as eat-2;mxl-2 animals exhibit substantially smaller brood sizes and lay a proportion of dead eggs, indicating that MML-1::MXL-2 has a role in maintaining the balance between resource allocation to the soma and to reproduction under conditions of chronic food scarcity. While eat-2 animals do not show a significantly different metabolic rate compared to wild-type, we also find that loss of mxl-2 in DR does not affect the rate of oxygen consumption in young animals. The gene expression signature of eat-2 mutant animals is consistent with optimization of energy utilization and resource allocation, rather than induction of canonical gene expression changes associated with acute metabolic stress, such as induction of autophagy after TORC1 inhibition. Consistently, eat-2 animals are not substantially resistant to stress, providing further support to the idea that chronic DR may benefit healthspan and lifespan through efficient use of limited resources rather than broad upregulation of stress responses, and also indicates that MML-1::MXL-2 and PHA-4 may have distinct roles in promotion of benefits in response to different pro-longevity stimuli., (© 2024. The Author(s), under exclusive licence to American Aging Association.)

Single-cell gene set analysis (scGSA) provides a useful approach for quantifying molecular functions and pathways in high-throughput transcriptomic data, facilitating the biological interpretation of complex human datasets. However, various factors such as gene set size, quality of the gene sets and the dropouts impact the performance of scGSA. To address these limitations, we present a single-cell Pathway Score (scPS) method to measure gene set activity at single-cell resolution. Furthermore, we benchmark our method with six other methods: AUCell, AddModuleScore, JASMINE, UCell, SCSE and ssGSEA. The comparison across all the methods using two different simulation approaches highlights the effect of cell count, gene set size, noise, condition-specific genes and zero imputation on their performance. The results of our study indicate that the scPS is comparable with other single-cell scoring methods and detects fewer false positives. Importantly, this work reveals critical variables in the scGSA., (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function. CD8 + T cells show higher oligoclonality than CD4 + T cells, with the largest synovial clones enriched in GZMK+ cells. CD8 + T cells with possibly virus-reactive TCRs are distributed across transcriptomic clusters. In the B cell compartment, NR4A1+ activated B cells, and plasma cells are enriched in the synovium and demonstrate substantial clonal expansion. We identify synovial plasma cells that share BCRs with synovial ABC, memory, and activated B cells. Receptor-ligand analysis predicted IFNG and TNFRSF members as mediators of synovial Tph-B cell interactions. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate the synovium of patients with RA., (© 2024. The Author(s).)

Introduction: The HVTN 105 vaccine clinical trial tested four combinations of two immunogens - the DNA vaccine DNA-HIV-PT123, and the protein vaccine AIDSVAX B/E. All combinations induced substantial antibody and CD4+ T cell responses in many participants. We have now re-examined the intracellular cytokine staining flow cytometry data using the high-resolution SWIFT clustering algorithm, which is very effective for enumerating rare populations such as antigen-responsive T cells, and also determined correlations between the antibody and T cell responses., Methods: Flow cytometry samples across all the analysis batches were registered using the swiftReg registration tool, which reduces batch variation without compromising biological variation. Registered data were clustered using the SWIFT algorithm, and cluster template competition was used to identify clusters of antigen-responsive T cells and to separate these from constitutive cytokine producing cell clusters., Results: Registration strongly reduced batch variation among batches analyzed across several months. This in-depth clustering analysis identified a greater proportion of responders than the original analysis. A subset of antigen-responsive clusters producing IL-21 was identified. The cytokine patterns in each vaccine group were related to the type of vaccine - protein antigens tended to induce more cells producing IL-2 but not IFN-γ, whereas DNA vaccines tended to induce more IL-2+ IFN-γ+ CD4 T cells. Several significant correlations were identified between specific antibody responses and antigen-responsive T cell clusters. The best correlations were not necessarily observed with the strongest antibody or T cell responses., Conclusion: In the complex HVTN105 dataset, alternative analysis methods increased sensitivity of the detection of antigen-specific T cells; increased the number of identified vaccine responders; identified a small IL-21-producing T cell population; and demonstrated significant correlations between specific T cell populations and serum antibody responses. Multiple analysis strategies may be valuable for extracting the most information from large, complex studies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer RP declared a past co-authorship with the author NR to the handling editor. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Mosmann, Rebhahn, De Rosa, Keefer, McElrath, Rouphael, Pantaleo, Gilbert, Corey, Kobie and Thakar.)

Oxygen (O 2 ) regulated pathways modulate B cell activation, migration and proliferation during infection, vaccination, and other diseases. Modeling these pathways in health and disease is critical to understand B cell states and ways to mediate them. To characterize B cells by their activation of O 2 regulated pathways we develop pathway specific discrete state models using previously published single-cell RNA-sequencing (scRNA-seq) datasets from isolated B cells. Specifically, Single Cell Boolean Omics Network Invariant-Time Analysis (scBONITA) was used to infer logic gates for known pathway topologies. The simplest inferred set of logic gates that maximized the number of "OR" interactions between genes was used to simulate B cell networks involved in oxygen sensing until they reached steady network states (attractors). By focusing on the attractors that best represented sequenced cells, we identified genes critical in determining pathway specific cellular states that corresponded to diseased and healthy B cell phenotypes. Specifically, we investigate the transendothelial migration, regulation of actin cytoskeleton, HIF1A, and Citrate Cycle pathways. Our analysis revealed attractors that resembled the state of B cell exhaustion in HIV+ patients as well as attractors that promoted anerobic metabolism, angiogenesis, and tumorigenesis in breast cancer patients, which were eliminated after neoadjuvant chemotherapy (NACT). Finally, we investigated the attractors to which the Azimuth-annotated B cells mapped and found that attractors resembling B cells from HIV+ patients encompassed a significantly larger number of atypical memory B cells than HIV- attractors. Meanwhile, attractors resembling B cells from breast cancer patients post NACT encompassed a reduced number of atypical memory B cells compared to pre-NACT attractors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Boolean modeling is a mathematical modeling framework used for defining and studying gene-regulatory networks (GRNs). It serves as a means to develop mechanistic models, offering insights into the trajectories and dynamic properties of GRNs. In this review, I delve into seminal papers published in the Journal of Theoretical Biology that have spearheaded this field. Additionally, I explore the application of these modeling methods in the current era of data-intensive science., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The atmosphere may be Earth's largest microbial ecosystem. It is connected to all of Earth's surface ecosystems and plays an important role in microbial dispersal on local to global scales. Despite this grand scale, surprisingly little is understood about the atmosphere itself as a habitat. A key question remains unresolved: does the atmosphere simply transport microorganisms from one location to another, or does it harbour adapted, resident, and active microbial communities that overcome the physiological stressors and selection pressures the atmosphere poses to life? Advances in extreme microbiology and astrobiology continue to push our understanding of the limits of life towards ever greater extremes of temperature, pressure, salinity, irradiance, pH, and water availability. Earth's atmosphere stands as a challenging, but potentially surmountable, extreme environment to harbour living, active, resident microorganisms. Here, we confront the current understanding of the atmosphere as a microbial habitat, highlighting key advances and limitations. We pose major ecological and mechanistic questions about microbial life in the atmosphere that remain unresolved and frame the problems and technical pitfalls that have largely hindered recent developments in this space, providing evidence-based insights to drive future research in this field. New innovations supported by rigorous technical standards are needed to enable progress in understanding atmospheric microorganisms and their influence on global processes of weather, climate, nutrient cycling, biodiversity, and microbial connectivity, especially in the context of rapid global change., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)

Dietary restriction (DR), the process of decreasing overall food consumption over an extended period of time, has been shown to increase longevity across evolutionarily diverse species and delay the onset of age-associated diseases in humans. In Caenorhabditis elegans , the Myc-family transcription factors (TFs) MXL-2 (Mlx) and MML-1 (MondoA/ChREBP), which function as obligate heterodimers, and PHA-4 (orthologous to forkhead box transcription factor A) are both necessary for the full physiological benefits of DR. However, the adaptive transcriptional response to DR and the role of MML-1::MXL-2 and PHA-4 remains elusive. We identified the transcriptional signature of C. elegans DR, using the eat-2 genetic model, and demonstrate broad changes in metabolic gene expression in eat-2 DR animals, which requires both mxl-2 and pha-4 . While the requirement for these factors in DR gene expression overlaps, we found many of the DR genes exhibit an opposing change in relative gene expression in eat-2;mxl-2 animals compared to wild-type, which was not observed in eat-2 animals with pha-4 loss. We further show functional deficiencies of the mxl-2 loss in DR outside of lifespan, as eat-2;mxl-2 animals exhibit substantially smaller brood sizes and lay a proportion of dead eggs, indicating that MML-1::MXL-2 has a role in maintaining the balance between resource allocation to the soma and to reproduction under conditions of chronic food scarcity. While eat-2 animals do not show a significantly different metabolic rate compared to wild-type, we also find that loss of mxl-2 in DR does not affect the rate of oxygen consumption in young animals. The gene expression signature of eat-2 mutant animals is consistent with optimization of energy utilization and resource allocation, rather than induction of canonical gene expression changes associated with acute metabolic stress -such as induction of autophagy after TORC1 inhibition. Consistently, eat-2 animals are not substantially resistant to stress, providing further support to the idea that chronic DR may benefit healthspan and lifespan through efficient use of limited resources rather than broad upregulation of stress responses, and also indicates that MML-1::MXL-2 and PHA-4 may have different roles in promotion of benefits in response to different pro-longevity stimuli.

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from transcriptome sequencing (RNA-seq) data sets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hot spots were identified for DVG recombination, and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single-cell RNA-seq analysis indicated the interferon (IFN) stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the next-generation sequencing (NGS) data set from a published cohort study and observed a significantly higher amount and frequency of DVG in symptomatic patients than those in asymptomatic patients. Finally, we observed exceptionally diverse DVG populations in one immunosuppressive patient up to 140 days after the first positive test of COVID-19, suggesting for the first time an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and into how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. IMPORTANCE Defective viral genomes (DVGs) are generated ubiquitously in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide the potential for them to be used in novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex, and this recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hot spots for nonhomologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide evidence to harness the immunostimulatory potential of DVGs in the development of a vaccine and antivirals for SARS-CoV-2., Competing Interests: The authors declare no conflict of interest.

Aging and the age-associated decline of the proteome is determined in part through neuronal control of evolutionarily conserved transcriptional effectors, which safeguard homeostasis under fluctuating metabolic and stress conditions by regulating an expansive proteostatic network. We have discovered the Caenorhabditis elegans homeodomain-interacting protein kinase (HPK-1) acts as a key transcriptional effector to preserve neuronal integrity, function, and proteostasis during aging. Loss of hpk-1 results in drastic dysregulation in expression of neuronal genes, including genes associated with neuronal aging. During normal aging hpk-1 expression increases throughout the nervous system more broadly than any other kinase. Within the aging nervous system, hpk-1 induction overlaps with key longevity transcription factors , which suggests that hpk-1 expression mitigates natural age-associated physiological decline. Consistently, pan-neuronal overexpression of hpk-1 extends longevity, preserves proteostasis both within and outside of the nervous system, and improves stress resistance. Neuronal HPK-1 improves proteostasis through kinase activity. HPK-1 functions cell non-autonomously within serotonergic and γ-aminobutyric acid (GABA)ergic neurons to improve proteostasis in distal tissues by specifically regulating distinct components of the proteostatic network. Increased serotonergic HPK-1 enhances the heat shock response and survival to acute stress. In contrast, GABAergic HPK-1 induces basal autophagy and extends longevity, which requires mxl-2 (MLX), hlh-30 (TFEB), and daf-16 (FOXO). Our work establishes hpk-1 as a key neuronal transcriptional regulator critical for preservation of neuronal function during aging. Further, these data provide novel insight as to how the nervous system partitions acute and chronic adaptive response pathways to delay aging by maintaining organismal homeostasis., Competing Interests: ML, AC, CD, RD, ZW, NM, JT, AS No competing interests declared, (© 2023, Lazaro-Pena et al.)

Multiomics profiling provides a holistic picture of a condition being examined and captures the complexity of signaling events, beginning from the original cause (environmental or genetic), to downstream functional changes at multiple molecular layers. Pathway enrichment analysis has been used with multiomics data sets to characterize signaling mechanisms. However, technical and biological variability between these layered data limit an integrative computational analyses. We present a Boolean network-based method, multiomics Boolean Omics Network Invariant-Time Analysis (mBONITA), to integrate omics data sets that quantify multiple molecular layers. mBONITA utilizes prior knowledge networks to perform topology-based pathway analysis. In addition, mBONITA identifies genes that are consistently modulated across molecular measurements by combining observed fold-changes and variance, with a measure of node (i.e., gene or protein) influence over signaling, and a measure of the strength of evidence for that gene across data sets. We used mBONITA to integrate multiomics data sets from RAMOS B cells treated with the immunosuppressant drug cyclosporine A under varying O 2 tensions to identify pathways involved in hypoxia-mediated chemotaxis. We compare mBONITA's performance with 6 other pathway analysis methods designed for multiomics data and show that mBONITA identifies a set of pathways with evidence of modulation across all omics layers. mBONITA is freely available at https://github.com/Thakar-Lab/mBONITA.

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS coronavirus 2 (SARS-CoV-2) virus. Direct assessment, detection, and quantitative analysis using high throughput methods like single-cell RNA sequencing (scRNAseq) is imperative to understanding the host response to SARS-CoV-2. One barrier to studying SARS-CoV-2 in the laboratory setting is the requirement to process virus-infected cell cultures, and potentially infectious materials derived therefrom, under Biosafety Level 3 (BSL-3) containment. However, there are only 190 BSL3 laboratory facilities registered with the U.S. Federal Select Agent Program, as of 2020, and only a subset of these are outfitted with the equipment needed to perform high-throughput molecular assays. Here, we describe a method for preparing non-hazardous RNA samples from SARS-CoV-2 infected cells, that enables scRNAseq analyses to be conducted safely in a BSL2 facility-thereby making molecular assays of SARS-CoV-2 cells accessible to a much larger community of researchers. Briefly, we infected African green monkey kidney epithelial cells (Vero-E6) with SARS-CoV-2 for 96 hours, trypsin-dissociated the cells, and inactivated them with methanol-acetone in a single-cell suspension. Fixed cells were tested for the presence of infectious SARS-CoV-2 virions using the Tissue Culture Infectious Dose Assay (TCID50), and also tested for viability using flow cytometry. We then tested the dissociation and methanol-acetone inactivation method on primary human lung epithelial cells that had been differentiated on an air-liquid interface. Finally, we performed scRNAseq quality control analysis on the resulting cell populations to evaluate the effects of our virus inactivation and sample preparation protocol on the quality of the cDNA produced. We found that methanol-acetone inactivated SARS-CoV-2, fixed the lung epithelial cells, and could be used to obtain noninfectious, high-quality cDNA libraries. This methodology makes investigating SARS-CoV-2, and related high-containment RNA viruses at a single-cell level more accessible to an expanded community of researchers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Osborn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The identification of baseline host determinants that associate with robust HIV-1 vaccine-induced immune responses could aid HIV-1 vaccine development. We aimed to assess both the collective and relative performance of baseline characteristics in classifying individual participants in nine different Phase 1-2 HIV-1 vaccine clinical trials (26 vaccine regimens, conducted in Africa and in the Americas) as High HIV-1 vaccine responders., Methods: This was a meta-analysis of individual participant data, with studies chosen based on participant-level (vs. study-level summary) data availability within the HIV-1 Vaccine Trials Network. We assessed the performance of 25 baseline characteristics (demographics, safety haematological measurements, vital signs, assay background measurements) and estimated the relative importance of each characteristic in classifying 831 participants as High (defined as within the top 25th percentile among positive responders or above the assay upper limit of quantification) versus Non-High responders. Immune response outcomes included HIV-1-specific serum IgG binding antibodies and Env-specific CD4+ T-cell responses assessed two weeks post-last dose, all measured at central HVTN laboratories. Three variable importance approaches based on SuperLearner ensemble machine learning were considered., Findings: Overall, 30.1%, 50.5%, 36.2%, and 13.9% of participants were categorized as High responders for gp120 IgG, gp140 IgG, gp41 IgG, and Env-specific CD4+ T-cell vaccine-induced responses, respectively. When including all baseline characteristics, moderate performance was achieved for the classification of High responder status for the binding antibody responses, with cross-validated areas under the ROC curve (CV-AUC) of 0.72 (95% CI: 0.68, 0.76) for gp120 IgG, 0.73 (0.69, 0.76) for gp140 IgG, and 0.67 (95% CI: 0.63, 0.72) for gp41 IgG. In contrast, the collection of all baseline characteristics yielded little improvement over chance for predicting High Env-specific CD4+ T-cell responses [CV-AUC: 0.53 (0.48, 0.58)]. While estimated variable importance patterns differed across the three approaches, female sex assigned at birth, lower height, and higher total white blood cell count emerged as significant predictors of High responder status across multiple immune response outcomes using Approach 1. Of these three baseline variables, total white blood cell count ranked highly across all three approaches for predicting vaccine-induced gp41 and gp140 High responder status., Interpretation: The identified features should be studied further in pursuit of intervention strategies to improve vaccine responses and may be adjusted for in analyses of immune response data to enhance statistical power., Funding: National Institute of Allergy and Infectious Diseases (UM1AI068635 to YH, UM1AI068614 to GDT, UM1AI068618 to MJM, and UM1 AI069511 to MCK), the Duke CFAR P30 AI064518 to GDT, and National Institute of Dental and Craniofacial Research (R01DE027245 to JJK). This work was also supported by the Bill and Melinda Gates Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding sources., Competing Interests: Declaration of interests Y.H. declares contract payments to her institution from the World Health Organization to conduct statistical analysis work (outside the scope of the current work; related to COVID-19 vaccines) and plan to submit the results for publication, within the past 36 months, as well as service to WHV as an SMB (payment directly to her) within the past 36 months. K.E.S. and J.H. declare coverage of travel expenses for attendance at the HVTN Full Group Meeting in 2022 (reimbursement by the HVTN); K.E.S. additionally declares payment of a registration fee for virtual seminar attendance directly to Keystone Symposium by the HVTN. S.D.R. declares contracts awarded to his institution from Battelle and from Janssen, and grants awarded to his institution from the Gates Medical Research Institute and from the Paul G. Allen Family Foundation, within the past 36 months. P.A.G. declares consulting fees received from Johnson and Johnson within the past 36 months, as well as a patent for a COVID-19 monoclonal antibody that is not yet clinically available. K.W.C. declares funding from the Bill and Melinda Gates Foundation in the form of payments to her institution within the last 36 months. B.D.W. declares grant payments made to his institution within the past 36 months from the following entities: Centers for Disease Control and Prevention, Patient-Centered Outcomes Research Institute, National Institute of Mental Health, National Institute of Allergy and Infectious Diseases, National Cancer Institute, and the National Institute of General Medical Studies; an honorarium for delivering an invited webinar to the American Statistical Association: Statistical Learning and Data Science Section; travel support through a grant from the National Institute of Mental Health; and retirement accounts invested in mutual funds operated by Vanguard and by TIAA (he does not choose individual stocks). L.-G.B. declares payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Gilead Sciences, Janssen, and Merck PTY LTD within the past 36 months, as well as participation on a Data Safety Monitoring Board or Advisory Board for the PrEPVAC study within the past 36 months. G.D.T. declares consulting fees received from Axon and from Janssen (not related to this work), serving as an Advisory Board member for the NIH VRC, UNC CFAR, and Johns Hopkins (not related to this work), and serving as a scientific review member for Gilead (not related to this work), all within the past 36 months, as well as travel as part of research funding (more than 3 years prior, with funding paid to her institution). J.T. declares consulting fees from Vaccitech within the past 36 months., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from RNA-seq datasets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hotspots were identified for DVG recombination and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single cell RNA-seq analysis indicated the IFN stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the NGS dataset from a published cohort study and observed significantly higher DVG amount and frequency in symptomatic patients than that in asymptomatic patients. Finally, we observed unusually high DVG frequency in one immunosuppressive patient up to 140 days after admitted to hospital due to COVID-19, first-time suggesting an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection., Importance: Defective viral genomes (DVGs) are ubiquitously generated in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide them the potential for novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex and the recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hotspots for non-homologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide the evidence to harness DVGs’ immunostimulatory potential in the development of vaccine and antivirals for SARS-CoV-2.

Atherosclerosis (AS)-associated cardiovascular disease is an important cause of mortality in an aging population of people living with HIV (PLWH). This elevated risk has been attributed to viral infection, anti-retroviral therapy, chronic inflammation, and lifestyle factors. However, the rates at which PLWH develop AS vary even after controlling for length of infection, treatment duration, and for lifestyle factors. To investigate the molecular signaling underlying this variation, we sequenced 9368 peripheral blood mononuclear cells (PBMCs) from eight PLWH, four of whom have atherosclerosis (AS+). Additionally, a publicly available dataset of PBMCs from persons before and after HIV infection was used to investigate the effect of acute HIV infection. To characterize dysregulation of pathways rather than just measuring enrichment, we developed the single-cell Boolean Omics Network Invariant Time Analysis (scBONITA) algorithm. scBONITA infers executable dynamic pathway models and performs a perturbation analysis to identify high impact genes. These dynamic models are used for pathway analysis and to map sequenced cells to characteristic signaling states (attractor analysis). scBONITA revealed that lipid signaling regulates cell migration into the vascular endothelium in AS+ PLWH. Pathways implicated included AGE-RAGE and PI3K-AKT signaling in CD8+ T cells, and glucagon and cAMP signaling pathways in monocytes. Attractor analysis with scBONITA facilitated the pathway-based characterization of cellular states in CD8+ T cells and monocytes. In this manner, we identify critical cell-type specific molecular mechanisms underlying HIV-associated atherosclerosis using a novel computational method., (© 2022. The Author(s).)

Coordinated migration of B cells within and between secondary lymphoid tissues is required for robust antibody responses to infection or vaccination. Secondary lymphoid tissues normally expose B cells to a low O2 (hypoxic) environment. Recently, we have shown that human B cell migration is modulated by an O2-dependent molecular switch, centrally controlled by the hypoxia-induced (transcription) factor-1α (HIF1A), which can be disrupted by the immunosuppressive calcineurin inhibitor, cyclosporine A (CyA). However, the mechanisms by which low O2 environments attenuate B cell migration remain poorly defined. Proteomics analysis has linked CXCR4 chemokine receptor signaling to cytoskeletal rearrangement. We now hypothesize that the pathways linking the O2 sensing molecular switch to chemokine receptor signaling and cytoskeletal rearrangement would likely contain phosphorylation events, which are typically missed in traditional transcriptomic and/or proteomic analyses. Hence, we have performed a comprehensive phosphoproteomics analysis of human B cells treated with CyA after engagement of the chemokine receptor CXCR4 with CXCL12. Statistical analysis of the separate and synergistic effects of CyA and CXCL12 revealed 116 proteins whose abundance is driven by a synergistic interaction between CyA and CXCL12. Further, we used our previously described algorithm BONITA to reveal a critical role for Lymphocyte Specific Protein 1 (LSP1) in cytoskeletal rearrangement. LSP1 is known to modulate neutrophil migration. Validating these modeling results, we show experimentally that LSP1 levels in B cells increase with low O2 exposure, and CyA treatment results in decreased LSP1 protein levels. This correlates with the increased chemotactic activity observed after CyA treatment. Lastly, we directly link LSP1 levels to chemotactic capacity, as shRNA knock-down of LSP1 results in significantly increased B cell chemotaxis at low O2 levels. These results directly link CyA to LSP1-dependent cytoskeletal regulation, demonstrating a previously unrecognized mechanism by which CyA modulates human B cell migration. Data are available via ProteomeXchange with identifier PXD036167.

Traditional farming lifestyle has been shown to be protective against asthma and allergic diseases. The individual factors that appear to be associated with this "farm-life effect" include consumption of unpasteurized farm milk and exposure to farm animals and stables. However, the biomarkers of the protective immunity and those associated with early development of allergic diseases in infancy remain unclear. The "Zooming in to Old Order Mennonites (ZOOM)" study was designed to assess the differences in the lifestyle and the development of the microbiome, systemic and mucosal immunity between infants born to traditional farming lifestyle at low risk for allergic diseases and those born to urban/suburban atopic families with a high risk for allergic diseases in order to identify biomarkers of development of allergic diseases in infancy. 190 mothers and their infants born to Old Order Mennonite population protected from or in Rochester families at high risk for allergic diseases were recruited before birth from the Finger Lakes Region of New York State. Questionnaires and samples are collected from mothers during pregnancy and after delivery and from infants at birth and at 1-2 weeks, 6 weeks, 6, 12, 18, and 24 months, with 3-, 4-, and 5-year follow-up ongoing. Samples collected include maternal blood, stool, saliva, nasal and skin swabs and urine during pregnancy; breast milk postnatally; infant blood, stool, saliva, nasal and skin swabs. Signs and symptoms of allergic diseases are assessed at every visit and serum specific IgE is measured at 1 and 2 years of age. Allergic diseases are diagnosed by clinical history, exam, and sensitization by skin prick test and/or serum specific IgE. By the end of the first year of life, the prevalence of food allergy and atopic dermatitis were higher in ROC infants compared to the rates observed in OOM infants as was the number of infants sensitized to foods. These studies of immune system development in a population protected from and in those at risk for allergic diseases will provide critical new knowledge about the development of the mucosal and systemic immunity and lay the groundwork for future studies of prevention of allergic diseases., Competing Interests: KJ has received research funding from Janssen Research & Development, Food Allergy Research and Education and Aimmune. She is a consultant for DBV Technologies and Janssen and received royalties from Up-To-Date and declares no other conflicts of interest. Other authors declare no conflicts of interest., (Copyright © 2022 Järvinen, Davis, Bevec, Jackson, Pizzarello, Catlin, Klein, Sunkara, Diaz, Miller, Martina, Thakar, Seppo, Looney and the Collaborative Working Group.)

The advent of feeding based RNAi in Caenorhabditis elegans led to an era of gene discovery in aging research. Hundreds of gerogenes were discovered, and many are evolutionarily conserved, raising the exciting possibility that the underlying genetic basis for healthy aging in higher vertebrates could be quickly deciphered. Yet, the majority of putative gerogenes have still only been cursorily characterized, highlighting the need for high-throughput, quantitative assessments of changes in aging. A widely used surrogate measure of aging is lifespan. The traditional way to measure mortality in C. elegans tracks the deaths of individual animals over time within a relatively small population. This traditional method provides straightforward, direct measurements of median and maximum lifespan for the sampled population. However, this method is time consuming, often underpowered, and involves repeated handling of a set of animals over time, which in turn can introduce contamination or possibly damage increasingly fragile, aged animals. We have previously developed an alternative "Replica Set" methodology, which minimizes handling and increases throughput by at least an order of magnitude. The Replica Set method allows changes in lifespan to be measured for over one hundred feeding-based RNAi clones by one investigator in a single experiment- facilitating the generation of large quantitative phenotypic datasets, a prerequisite for development of biological models at a systems level. Here, we demonstrate through analysis of lifespan experiments simulated in silico that the Replica Set method is at least as precise and accurate as the traditional method in evaluating and estimating lifespan, and requires many fewer total animal observations across the course of an experiment. Furthermore, we show that the traditional approach to lifespan experiments is more vulnerable than the Replica Set method to experimental and measurement error. We find no compromise in statistical power for Replica Set experiments, even for moderate effect sizes, or when simulated experimental errors are introduced. We compare and contrast the statistical analysis of data generated by the two approaches, and highlight pitfalls common with the traditional methodology. Collectively, our analysis provides a standard of measure for each method across comparable parameters, which will be invaluable in both experimental design and evaluation of published data for lifespan studies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cornwell, Llop, Salzman, Rasmussen, Thakar and Samuelson.)

Summary: WikiPathways is a database of 2979 biological pathways across 31 species created using the drawing software PathVisio. Many of these pathways are not directly usable for network-based topological analyses due to differences in curation styles and drawings. We developed the WikiNetworks package to standardize and construct directed networks by combining geometric information and manual annotations from WikiPathways. WikiNetworks performs significantly better than existing tools. This enables the use of high-quality WikiPathways resource for network-based topological analysis of high-throughput data., Availability and Implementation: WikiNetworks is written in Python3 and is available on github.com/Thakar-Lab/wikinetworks and on PyPI., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Respiratory syncytial virus (RSV) infection results in millions of hospitalizations and thousands of deaths each year. Variations in the adaptive and innate immune response appear to be associated with RSV severity. To investigate the host response to RSV infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. We implemented a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation, which enabled us to identify cellular pathways associated with RSV severity. In both airway and immune cells, we found an association between RSV severity and activation of pathways controlling Th17 and acute phase response signaling, as well as inhibition of B cell receptor signaling. Dysregulation of both the humoral and mucosal response to RSV may play a critical role in determining illness severity., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: ARF is currently receiving funding from Merck Sharpe and Dohme, Pfizer, Janssen, Astra Zeneca and BioFire and personal fees for DSMB from Novavax. The others authors do not have any competing interests to report.

Computational models of biological systems can exploit a broad range of rapidly developing approaches, including novel experimental approaches, bioinformatics data analysis, emerging modelling paradigms, data standards and algorithms. A discussion about the most recent advances among experts from various domains is crucial to foster data-driven computational modelling and its growing use in assessing and predicting the behaviour of biological systems. Intending to encourage the development of tools, approaches and predictive models, and to deepen our understanding of biological systems, the Community of Special Interest (COSI) was launched in Computational Modelling of Biological Systems (SysMod) in 2016. SysMod's main activity is an annual meeting at the Intelligent Systems for Molecular Biology (ISMB) conference, which brings together computer scientists, biologists, mathematicians, engineers, computational and systems biologists. In the five years since its inception, SysMod has evolved into a dynamic and expanding community, as the increasing number of contributions and participants illustrate. SysMod maintains several online resources to facilitate interaction among the community members, including an online forum, a calendar of relevant meetings and a YouTube channel with talks and lectures of interest for the modelling community. For more than half a decade, the growing interest in computational systems modelling and multi-scale data integration has inspired and supported the SysMod community. Its members get progressively more involved and actively contribute to the annual COSI meeting and several related community workshops and meetings, focusing on specific topics, including particular techniques for computational modelling or standardisation efforts., (© The Author(s) 2021. Published by Oxford University Press.)

Background: Growing up on traditional, single-family farms is associated with protection against asthma in school age, but the mechanisms against early manifestations of atopic disease are largely unknown. We sought determine the gut microbiome and metabolome composition in rural Old Order Mennonite (OOM) infants at low risk and Rochester, NY urban/suburban infants at high risk for atopic diseases., Methods: In a cohort of 65 OOM and 39 Rochester mother-infant pairs, 101 infant stool and 61 human milk samples were assessed by 16S rRNA gene sequencing for microbiome composition and qPCR to quantify Bifidobacterium spp. and B. longum ssp. infantis (B. infantis), a consumer of human milk oligosaccharides (HMOs). Fatty acids (FAs) were analyzed in 34 stool and human 24 milk samples. Diagnoses and symptoms of atopic diseases by 3 years of age were assessed by telephone., Results: At a median age of 2 months, stool was enriched with Bifidobacteriaceae, Clostridiaceae, and Aerococcaceae in the OOM compared with Rochester infants. B. infantis was more abundant (p < .001) and prevalent, detected in 70% of OOM compared with 21% of Rochester infants (p < .001). Stool colonized with B. infantis had higher levels of lactate and several medium- to long/odd-chain FAs. In contrast, paired human milk was enriched with a distinct set of FAs including butyrate. Atopic diseases were reported in 6.5% of OOM and 35% of Rochester children (p < .001)., Conclusion: A high rate of B. infantis colonization, similar to that seen in developing countries, is found in the OOM at low risk for atopic diseases., (© 2021 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.)

Background: In addition to farming exposures in childhood, maternal farming exposures provide strong protection against allergic disease in their children; however, the effect of farming lifestyle on human milk (HM) composition is unknown., Objective: This study aims to characterize the maternal immune effects of Old Order Mennonite (OOM) traditional farming lifestyle when compared with Rochester (ROC) families at higher risk for asthma and allergic diseases using HM as a proxy., Methods: HM samples collected at median 2 months of lactation from 52 OOM and 29 ROC mothers were assayed for IgA 1 and IgA 2 antibodies, cytokines, endotoxin, HM oligosaccharides (HMOs), and targeted fatty acid (FA) metabolites. Development of early childhood atopic diseases in children by 3 years of age was assessed. In addition to group comparisons, systems level network analysis was performed to identify communities of multiple HM factors in ROC and OOM lifestyle., Results: HM contains IgA 1 and IgA 2 antibodies broadly recognizing food, inhalant, and bacterial antigens. OOM HM has significantly higher levels of IgA to peanut, ovalbumin, dust mites, and Streptococcus equii as well TGF-β2, and IFN-λ3. A strong correlation occurred between maternal antibiotic use and levels of several HMOs. Path-based analysis of HMOs shows lower activity in the path involving lactoneohexaose (LNH) in the OOM as well as higher levels of lacto- N -neotetraose (LNnT) and two long-chain FAs C-18OH (stearic acid) and C-23OH (tricosanoic acid) compared with Rochester HM. OOM and Rochester milk formed five different clusters, e.g., butyrate production was associated with Prevotellaceae , Veillonellaceae , and Micrococcaceae cluster. Development of atopic disease in early childhood was more common in Rochester and associated with lower levels of total IgA, IgA 2 to dust mite, as well as of TSLP., Conclusion: Traditional, agrarian lifestyle, and antibiotic use are strong regulators of maternally derived immune and metabolic factors, which may have downstream implications for postnatal developmental programming of infant's gut microbiome and immune system., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Seppo, Choudhury, Pizzarello, Palli, Fridy, Rajani, Stern, Martina, Yonemitsu, Bode, Bu, Tamburini, Piras, Wallach, Allen, Looney, Clemente, Thakar and Järvinen.)

People living with HIV are at higher risk of atherosclerosis (AS). The pathogenesis of this risk is not fully understood. To assess the regulatory networks involved in AS we sequenced mRNA of the peripheral blood mononuclear cells (PBMCs) and measured cytokine and chemokine levels in the plasma of 13 persons living with HIV and 12 matched HIV-negative persons with and without AS. microRNAs (miRNAs) are known to play a role in HIV infection and may modulate gene regulation to drive AS. Hence, we further assessed miRNA expression in PBMCs of a subset of 12 HIV+ people with and without atherosclerosis. We identified 12 miRNAs differentially expressed between HIV+ AS+ and HIV+ , and validated 5 of those by RT-qPCR. While a few of these miRNAs have been implicated in HIV and atherosclerosis, others are novel. Integrating miRNA measurements with mRNA, we identified 27 target genes including SLC4A7, a critical sodium and bicarbonate transporter, that are potentially dysregulated during atherosclerosis. Additionally, we uncovered that levels of plasma cytokines were associated with transcription factor activity and miRNA expression in PBMCs. For example, BACH2 activity was associated with IL-1β, IL-15, and MIP-1α. IP10 and TNFα levels were associated with miR-124-3p. Finally, integration of all data types into a single network revealed increased importance of miRNAs in network regulation of the HIV+ group in contrast with increased importance of cytokines in the HIV+ AS+ group.