scPathoQuant: a tool for efficient alignment and quantification of pathogen sequence reads from 10× single cell sequencing datasets

MOTIVATION

Currently there is a lack of efficient computational pipelines/tools for conducting simultaneous genome mapping of pathogen-derived and host reads from single cell RNA sequencing (scRNAseq) output from pathogen-infected cells. Contemporary options include processes involving multiple steps and/or running multiple computational tools, increasing user operations time.

RESULTS

To address the need for new tools to directly map and quantify pathogen and host sequence reads from within an infected cell from scRNAseq datasets in a single operation, we have built a python package, called scPathoQuant. scPathoQuant extracts sequences that were not aligned to the primary host genome, maps them to a pathogen genome of interest (here as demonstrated for viral pathogens), quantifies total reads mapping to the entire pathogen, quantifies reads mapping to individual pathogen genes, and finally integrates pathogen sequence counts into matrix files that are used by standard single cell pipelines for downstream analyses with only one command. We demonstrate that scPathoQuant provides a scRNAseq viral and host genome-wide sequence read abundance analysis that can differentiate and define multiple viruses in a single sample scRNAseq output.

AVAILABILITY AND IMPLEMENTATION

The SPQ package is available software accessible at https://github.com/galelab/scPathoQuant (DOI 10.5281/zenodo.10463670) with test codes and datasets available https://github.com/galelab/Whitmore_scPathoQuant_testSets (DOI 10.5281/zenodo.10463677) to serve as a resource for the community.

Disruption of myelin structure and oligodendrocyte maturation in a pigtail macaque model of congenital Zika infection

Zika virus (ZikV) infection during pregnancy can cause congenital Zika syndrome (CZS) and neurodevelopmental delay in non-microcephalic infants, of which the pathogenesis remains poorly understood. We utilized an established pigtail macaque maternal-to-fetal ZikV infection/exposure model to study fetal brain pathophysiology of CZS manifesting from ZikV exposure in utero. We found prenatal ZikV exposure led to profound disruption of fetal myelin, with extensive downregulation in gene expression for key components of oligodendrocyte maturation and myelin production. Immunohistochemical analyses revealed marked decreases in myelin basic protein intensity and myelinated fiber density in ZikV-exposed animals. At the ultrastructural level, the myelin sheath in ZikV-exposed animals showed multi-focal decompaction consistent with perturbation or remodeling of previously formed myelin, occurring concomitant with dysregulation of oligodendrocyte gene expression and maturation. These findings define fetal neuropathological profiles of ZikV-linked brain injury underlying CZS resulting from ZikV exposure in utero. Because myelin is critical for cortical development, ZikV-related perturbations in oligodendrocyte function may have long-term consequences on childhood neurodevelopment, even in the absence of overt microcephaly.

Modulation of type I interferon responses potently inhibits SARS-CoV-2 replication and inflammation in rhesus macaques

Type I interferons (IFN-I) are critical mediators of innate control of viral infections but also drive the recruitment of inflammatory cells to sites of infection, a key feature of severe coronavirus disease 2019. Here, IFN-I signaling was modulated in rhesus macaques (RMs) before and during acute SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection using a mutated IFN-α2 (IFN-modulator; IFNmod), which has previously been shown to reduce the binding and signaling of endogenous IFN-I. IFNmod treatment in uninfected RMs was observed to induce a modest up-regulation of only antiviral IFN-stimulated genes (ISGs); however, in SARS-CoV-2-infected RMs, IFNmod reduced both antiviral and inflammatory ISGs. IFNmod treatment resulted in a potent reduction in SARS-CoV-2 viral loads both in vitro in Calu-3 cells and in vivo in bronchoalveolar lavage (BAL), upper airways, lung, and hilar lymph nodes of RMs. Furthermore, in SARS-CoV-2-infected RMs, IFNmod treatment potently reduced inflammatory cytokines, chemokines, and CD163+ MRC1- inflammatory macrophages in BAL and expression of Siglec-1 on circulating monocytes. In the lung, IFNmod also reduced pathogenesis and attenuated pathways of inflammasome activation and stress response during acute SARS-CoV-2 infection. Using an intervention targeting both IFN-α and IFN-β pathways, this study shows that, whereas early IFN-I restrains SARS-CoV-2 replication, uncontrolled IFN-I signaling critically contributes to SARS-CoV-2 inflammation and pathogenesis in the moderate disease model of RMs.

Expression of Envelope Protein Encoded by Endogenous Retrovirus K102 in Rheumatoid Arthritis Neutrophils

Many patients suffering from autoimmune diseases have autoantibodies against proteins encoded by genomic retroelements, suggesting that normal epigenetic silencing is insufficient to prevent the production of the encoded proteins for which immune tolerance appears to be limited. One such protein is the transmembrane envelope (Env) protein encoded by human endogenous retrovirus K (HERV-K). We reported recently that patients with rheumatoid arthritis (RA) have IgG autoantibodies that recognize Env. Here, we use RNA sequencing of RA neutrophils to analyze HERV-K expression and find that only two loci with an intact open-reading frame for Env, HERV-K102, and K108 are expressed, but only the former is increased in RA. In contrast, other immune cells express more K108 than K102. Patient autoantibodies recognized endogenously expressed Env in breast cancer cells and in RA neutrophils but not healthy controls. A monoclonal anti-Env antibody also detected Env on the surface of RA neutrophils but very little on the surface of other immune cells. We conclude that HERV-K102 is the locus that produces Env detectable on the surface of neutrophils in RA. The low levels of HERV-K108 transcripts may contribute only marginally to cell surface Env on neutrophils or other immune cells in some patients.

Modulation of type I interferon responses potently inhibits SARS-CoV-2 replication and inflammation in rhesus macaques

Type-I interferons (IFN-I) are critical mediators of innate control of viral infections, but also drive recruitment of inflammatory cells to sites of infection, a key feature of severe COVID-19. Here, and for the first time, IFN-I signaling was modulated in rhesus macaques (RMs) prior to and during acute SARS-CoV-2 infection using a mutated IFNα2 (IFN-modulator; IFNmod), which has previously been shown to reduce the binding and signaling of endogenous IFN-I. In SARS-CoV-2-infected RMs, IFNmod reduced both antiviral and inflammatory ISGs. Notably, IFNmod treatment resulted in a potent reduction in (i) SARS-CoV-2 viral load in Bronchoalveolar lavage (BAL), upper airways, lung, and hilar lymph nodes; (ii) inflammatory cytokines, chemokines, and CD163+MRC1-inflammatory macrophages in BAL; and (iii) expression of Siglec-1, which enhances SARS-CoV-2 infection and predicts disease severity, on circulating monocytes. In the lung, IFNmod also reduced pathogenesis and attenuated pathways of inflammasome activation and stress response during acute SARS-CoV-2 infection. This study, using an intervention targeting both IFN-α and IFN-β pathways, shows that excessive inflammation driven by type 1 IFN critically contributes to SARS-CoV-2 pathogenesis in RMs, and demonstrates the potential of IFNmod to limit viral replication, SARS-CoV-2 induced inflammation, and COVID-19 severity.

Innate immune regulation in HIV latency models

BACKGROUND

Innate immunity and type 1 interferon (IFN) defenses are critical for early control of HIV infection within CD4 + T cells. Despite these defenses, some acutely infected cells silence viral transcription to become latently infected and form the HIV reservoir in vivo. Latently infected cells persist through antiretroviral therapy (ART) and are a major barrier to HIV cure. Here, we evaluated innate immunity and IFN responses in multiple T cell models of HIV latency, including established latent cell lines, Jurkat cells latently infected with a reporter virus, and a primary CD4 + T cell model of virologic suppression.

RESULTS

We found that while latently infected T cell lines have functional RNA sensing and IFN signaling pathways, they fail to induce specific interferon-stimulated genes (ISGs) in response to innate immune activation or type 1 IFN treatment. Jurkat cells latently infected with a fluorescent reporter HIV similarly demonstrate attenuated responses to type 1 IFN. Using bulk and single-cell RNA sequencing we applied a functional genomics approach and define ISG expression dynamics in latent HIV infection, including HIV-infected ART-suppressed primary CD4 + T cells.

CONCLUSIONS

Our observations indicate that HIV latency and viral suppression each link with cell-intrinsic defects in specific ISG induction. We identify a set of ISGs for consideration as latency restriction factors whose expression and function could possibly mitigate establishing latent HIV infection.

Subfamily-specific differential contribution of individual monomers and the tether sequence to mouse L1 promoter activity

BACKGROUND

The internal promoter in L1 5'UTR is critical for autonomous L1 transcription and initiating retrotransposition. Unlike the human genome, which features one contemporarily active subfamily, four subfamilies (A_I, Gf_I and Tf_I/II) have been amplifying in the mouse genome in the last one million years. Moreover, mouse L1 5'UTRs are organized into tandem repeats called monomers, which are separated from ORF1 by a tether domain. In this study, we aim to compare promoter activities across young mouse L1 subfamilies and investigate the contribution of individual monomers and the tether sequence.

RESULTS

We observed an inverse relationship between subfamily age and the average number of monomers among evolutionarily young mouse L1 subfamilies. The youngest subgroup (A_I and Tf_I/II) on average carry 3-4 monomers in the 5'UTR. Using a single-vector dual-luciferase reporter assay, we compared promoter activities across six L1 subfamilies (A_I/II, Gf_I and Tf_I/II/III) and established their antisense promoter activities in a mouse embryonic fibroblast cell line and a mouse embryonal carcinoma cell line. Using consensus promoter sequences for three subfamilies (A_I, Gf_I and Tf_I), we dissected the differential roles of individual monomers and the tether domain in L1 promoter activity. We validated that, across multiple subfamilies, the second monomer consistently enhances the overall promoter activity. For individual promoter components, monomer 2 is consistently more active than the corresponding monomer 1 and/or the tether for each subfamily. Importantly, we revealed intricate interactions between monomer 2, monomer 1 and tether domains in a subfamily-specific manner. Furthermore, using three-monomer 5'UTRs, we established a complex nonlinear relationship between the length of the outmost monomer and the overall promoter activity.

CONCLUSIONS

The laboratory mouse is an important mammalian model system for human diseases as well as L1 biology. Our study extends previous findings and represents an important step toward a better understanding of the molecular mechanism controlling mouse L1 transcription as well as L1's impact on development and disease.

SARS-CoV-2 Infects Human Pluripotent Stem Cell-Derived Cardiomyocytes, Impairing Electrical and Mechanical Function

COVID-19 patients often develop severe cardiovascular complications, but it remains unclear if these are caused directly by viral infection or are secondary to a systemic response. Here, we examine the cardiac tropism of SARS-CoV-2 in human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) and smooth muscle cells (hPSC-SMCs). We find that that SARS-CoV-2 selectively infects hPSC-CMs through the viral receptor ACE2, whereas in hPSC-SMCs there is minimal viral entry or replication. After entry into cardiomyocytes, SARS-CoV-2 is assembled in lysosome-like vesicles and egresses via bulk exocytosis. The viral transcripts become a large fraction of cellular mRNA while host gene expression shifts from oxidative to glycolytic metabolism and upregulates chromatin modification and RNA splicing pathways. Most importantly, viral infection of hPSC-CMs progressively impairs both their electrophysiological and contractile function, and causes widespread cell death. These data support the hypothesis that COVID-19-related cardiac symptoms can result from a direct cardiotoxic effect of SARS-CoV-2.

RetSynth: determining all optimal and sub-optimal synthetic pathways that facilitate synthesis of target compounds in chassis organisms

Background

The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions.

Results

Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules.

Conclusions

The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3025-9) contains supplementary material, which is available to authorized users.

Dissecting Germ Cell Metabolism through Network Modeling

Metabolic pathways are increasingly postulated to be vital in programming cell fate, including stemness, differentiation, proliferation, and apoptosis. The commitment to meiosis is a critical fate decision for mammalian germ cells, and requires a metabolic derivative of vitamin A, retinoic acid (RA). Recent evidence showed that a pulse of RA is generated in the testis of male mice thereby triggering meiotic commitment. However, enzymes and reactions that regulate this RA pulse have yet to be identified. We developed a mouse germ cell-specific metabolic network with a curated vitamin A pathway. Using this network, we implemented flux balance analysis throughout the initial wave of spermatogenesis to elucidate important reactions and enzymes for the generation and degradation of RA. Our results indicate that primary RA sources in the germ cell include RA import from the extracellular region, release of RA from binding proteins, and metabolism of retinal to RA. Further, in silico knockouts of genes and reactions in the vitamin A pathway predict that deletion of Lipe, hormone-sensitive lipase, disrupts the RA pulse thereby causing spermatogenic defects. Examination of other metabolic pathways reveals that the citric acid cycle is the most active pathway. In addition, we discover that fatty acid synthesis/oxidation are the primary energy sources in the germ cell. In summary, this study predicts enzymes, reactions, and pathways important for germ cell commitment to meiosis. These findings enhance our understanding of the metabolic control of germ cell differentiation and will help guide future experiments to improve reproductive health.

Computer simulations of the mouse spermatogenic cycle

The spermatogenic cycle describes the periodic development of germ cells in the testicular tissue. The temporal-spatial dynamics of the cycle highlight the unique, complex, and interdependent interaction between germ and somatic cells, and are the key to continual sperm production. Although understanding the spermatogenic cycle has important clinical relevance for male fertility and contraception, there are a number of experimental obstacles. For example, the lengthy process cannot be visualized through dynamic imaging, and the precise action of germ cells that leads to the emergence of testicular morphology remains uncharacterized. Here, we report an agent-based model that simulates the mouse spermatogenic cycle on a cross-section of the seminiferous tubule over a time scale of hours to years, while considering feedback regulation, mitotic and meiotic division, differentiation, apoptosis, and movement. The computer model is able to elaborate the germ cell dynamics in a time-lapse movie format, allowing us to trace individual cells as they change state and location. More importantly, the model provides mechanistic understanding of the fundamentals of male fertility, namely how testicular morphology and sperm production are achieved. By manipulating cellular behaviors either individually or collectively in silico, the model predicts causal events for the altered arrangement of germ cells upon genetic or environmental perturbations. This in silico platform can serve as an interactive tool to perform long-term simulation and to identify optimal approaches for infertility treatment and contraceptive development.