Recording physiological history of cells with chemical labeling.

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G protein-coupled receptor activation, and increases in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogeneous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1.

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

A general method for the development of multicolor biosensors with large dynamic ranges.

Fluorescent biosensors enable the study of cell physiology with spatiotemporal resolution; yet, most biosensors suffer from relatively low dynamic ranges. Here, we introduce a family of designed Förster resonance energy transfer (FRET) pairs with near-quantitative FRET efficiencies based on the reversible interaction of fluorescent proteins with a fluorescently labeled HaloTag. These FRET pairs enabled the straightforward design of biosensors for calcium, ATP and NAD+ with unprecedented dynamic ranges. The color of each of these biosensors can be readily tuned by changing either the fluorescent protein or the synthetic fluorophore, which enables simultaneous monitoring of free NAD+ in different subcellular compartments following genotoxic stress. Minimal modifications of these biosensors furthermore allow their readout to be switched to fluorescence intensity, fluorescence lifetime or bioluminescence. These FRET pairs thus establish a new concept for the development of highly sensitive and tunable biosensors.

A machine learning approach to support triaging of primary versus secondary headache patients using complete blood count.

Headaches account for up to 4.5% of emergency department visits, where they present a significant diagnostic challenge. While primary headaches are benign, secondary headaches can be life-threatening. It is essential to rapidly differentiate between primary and secondary headaches as the latter require immediate diagnostic work-up. Current assessment relies on subjective measures; time constraints can result in overuse of diagnostic neuroimaging, prolonging diagnosis, and adding to economic burden. There is therefore an unmet need for a time- and cost-efficient, quantitative triaging tool to guide further diagnostic testing. Routine blood tests may provide important diagnostic and prognostic biomarkers indicating underlying headache causes. In this retrospective study (approved by the UK Medicines and Healthcare products Regulatory Agency Independent Scientific Advisory Committee for Clinical Practice Research Datalink (CPRD) research [20_000173]), UK CPRD real-world data from patients (n = 121,241) presenting with headache from 1993-2021 were used to generate a predictive model based on a machine learning (ML) approach for primary versus secondary headaches. A ML-based predictive model was constructed using two different methods (logistic regression and random forest) and the following predictors were evaluated: ten standard measurements of complete blood count (CBC) test, 19 ratios of the ten CBC test parameters, and patient demographic and clinical characteristics. The model's predictive performance was assessed using a set of cross-validated model performance metrics. The final predictive model showed modest predictive accuracy using the random forest method (balanced accuracy: 0.7405). The sensitivity, specificity, false negative rate (incorrect prediction of secondary headache as primary headache), and false positive rate (incorrect prediction of primary headache as secondary headache) were 58%, 90%, 10%, and 42%, respectively. The ML-based prediction model developed could provide a useful time- and cost-effective quantitative clinical tool to facilitate the triaging of patients presenting to the clinic with headache.

Fluorescent and Bioluminescent Calcium Indicators with Tuneable Colors and Affinities.

We introduce a family of bright, rhodamine-based calcium indicators with tuneable affinities and colors. The indicators can be specifically localized to different cellular compartments and are compatible with both fluorescence and bioluminescence readouts through conjugation to HaloTag fusion proteins. Importantly, their increase in fluorescence upon localization enables no-wash live-cell imaging, which greatly facilitates their use in biological assays. Applications as fluorescent indicators in rat hippocampal neurons include the detection of single action potentials and of calcium fluxes in the endoplasmic reticulum. Applications as bioluminescent indicators include the recording of the pharmacological modulation of nuclear calcium in high-throughput compatible assays. The versatility and remarkable ease of use of these indicators make them powerful tools for bioimaging and bioassays.

IFITM3 incorporation sensitizes influenza A virus to antibody-mediated neutralization.

The disease severity of influenza is highly variable in humans, and one genetic determinant behind these differences is the IFITM3 gene. As an effector of the interferon response, IFITM3 potently blocks cytosolic entry of influenza A virus (IAV). Here, we reveal a novel level of inhibition by IFITM3 in vivo: We show that incorporation of IFITM3 into IAV particles competes with incorporation of viral hemagglutinin (HA). Decreased virion HA levels did not reduce infectivity, suggesting that high HA density on IAV virions may be an antagonistic strategy used by the virus to prevent direct inhibition. However, we found that IFITM3-mediated reduction in HA content sensitizes IAV to antibody-mediated neutralization. Mathematical modeling predicted that this effect decreases and delays peak IAV titers, and we show that, indeed, IFITM3-mediated sensitization of IAV to antibody-mediated neutralization impacts infection outcome in an in vivo mouse model. Overall, our data describe a previously unappreciated interplay between the innate effector IFITM3 and the adaptive immune response.

Heterologous arenavirus vector prime-boost overrules self-tolerance for efficient tumor-specific CD8 T cell attack.

Therapeutic vaccination regimens inducing clinically effective tumor-specific CD8+ T lymphocyte (CTL) responses are an unmet medical need. We engineer two distantly related arenaviruses, Pichinde virus and lymphocytic choriomeningitis virus, for therapeutic cancer vaccination. In mice, life-replicating vector formats of these two viruses delivering a self-antigen in a heterologous prime-boost regimen induce tumor-specific CTL responses up to 50% of the circulating CD8 T cell pool. This CTL attack eliminates established solid tumors in a significant proportion of animals, accompanied by protection against tumor rechallenge. The magnitude of CTL responses is alarmin driven and requires combining two genealogically distantly related arenaviruses. Vector-neutralizing antibodies do not inhibit booster immunizations by the same vector or by closely related vectors. Rather, CTL immunodominance hierarchies favor vector backbone-targeted responses at the expense of self-reactive CTLs. These findings establish an arenavirus-based immunotherapy regimen that allows reshuffling of immunodominance hierarchies and breaking self-directed tolerance for efficient tumor control.

Profiling host ANP32A splicing landscapes to predict influenza A virus polymerase adaptation.

Species' differences in cellular factors limit avian influenza A virus (IAV) zoonoses and human pandemics. The IAV polymerase, vPol, harbors evolutionary sites to overcome restriction and determines virulence. Here, we establish host ANP32A as a critical driver of selection, and identify host-specific ANP32A splicing landscapes that predict viral evolution. We find that avian species differentially express three ANP32A isoforms diverging in a vPol-promoting insert. ANP32As with shorter inserts interact poorly with vPol, are compromised in supporting avian-like IAV replication, and drive selection of mammalian-adaptive vPol sequences with distinct kinetics. By integrating selection data with multi-species ANP32A splice variant profiling, we develop a mathematical model to predict avian species potentially driving (swallow, magpie) or maintaining (goose, swan) mammalian-adaptive vPol signatures. Supporting these predictions, surveillance data confirm enrichment of several mammalian-adaptive vPol substitutions in magpie IAVs. Profiling host ANP32A splicing could enhance surveillance and eradication efforts against IAVs with pandemic potential.

The influence of phylodynamic model specifications on parameter estimates of the Zika virus epidemic.

Each new virus introduced into the human population could potentially spread and cause a worldwide epidemic. Thus, early quantification of epidemic spread is crucial. Real-time sequencing followed by Bayesian phylodynamic analysis has proven to be extremely informative in this respect. Bayesian phylodynamic analyses require a model to be chosen and prior distributions on model parameters to be specified. We study here how choices regarding the tree prior influence quantification of epidemic spread in an emerging epidemic by focusing on estimates of the parameters clock rate, tree height, and reproductive number in the currently ongoing Zika virus epidemic in the Americas. While parameter estimates are quite robust to reasonable variations in the model settings when studying the complete data set, it is impossible to obtain unequivocal estimates when reducing the data to local Zika epidemics in Brazil and Florida, USA. Beyond the empirical insights, this study highlights the conceptual differences between the so-called birth-death and coalescent tree priors: while sequence sampling times alone can strongly inform the tree height and reproductive number under a birth-death model, the coalescent tree height prior is typically only slightly influenced by this information. Such conceptual differences together with non-trivial interactions of different priors complicate proper interpretation of empirical results. Overall, our findings indicate that phylodynamic analyses of early viral spread data must be carried out with care as data sets may not necessarily be informative enough yet to provide estimates robust to prior settings. It is necessary to do a robustness check of these data sets by scanning several models and prior distributions. Only if the posterior distributions are robust to reasonable changes of the prior distribution, the parameter estimates can be trusted. Such robustness tests will help making real-time phylodynamic analyses of spreading epidemic more reliable in the future.

Phenotypic deficits in the HIV-1 envelope are associated with the maturation of a V2-directed broadly neutralizing antibody lineage.

Broadly neutralizing antibodies (bnAbs) to HIV-1 can evolve after years of an iterative process of virus escape and antibody adaptation that HIV-1 vaccine design seeks to mimic. To enable this, properties that render HIV-1 envelopes (Env) capable of eliciting bnAb responses need to be defined. Here, we followed the evolution of the V2 apex directed bnAb lineage VRC26 in the HIV-1 subtype C superinfected donor CAP256 to investigate the phenotypic changes of the virus populations circulating before and during the early phases of bnAb induction. Longitudinal viruses that evolved from the VRC26-resistant primary infecting (PI) virus, the VRC26-sensitive superinfecting (SU) virus and ensuing PI-SU recombinants revealed substantial phenotypic changes in Env, with a switch in Env properties coinciding with early resistance to VRC26. Decreased sensitivity of SU-like viruses to VRC26 was linked with reduced infectivity, altered entry kinetics and lower sensitivity to neutralization after CD4 attachment. VRC26 maintained neutralization activity against cell-associated CAP256 virus, indicating that escape through the cell-cell transmission route is not a dominant escape pathway. Reduced fitness of the early escape variants and sustained sensitivity in cell-cell transmission are both features that limit virus replication, thereby impeding rapid escape. This supports a scenario where VRC26 allowed only partial viral escape for a prolonged period, possibly increasing the time window for bnAb maturation. Collectively, our data highlight the phenotypic plasticity of the HIV-1 Env in evading bnAb pressure and the need to consider phenotypic traits when selecting and designing Env immunogens. Combinations of Env variants with differential phenotypic patterns and bnAb sensitivity, as we describe here for CAP256, may maximize the potential for inducing bnAb responses by vaccination.

Taming the BEAST-A Community Teaching Material Resource for BEAST 2.

Phylogenetics and phylodynamics are central topics in modern evolutionary biology. Phylogenetic methods reconstruct the evolutionary relationships among organisms, whereas phylodynamic approaches reveal the underlying diversification processes that lead to the observed relationships. These two fields have many practical applications in disciplines as diverse as epidemiology, developmental biology, palaeontology, ecology, and linguistics. The combination of increasingly large genetic data sets and increases in computing power is facilitating the development of more sophisticated phylogenetic and phylodynamic methods. Big data sets allow us to answer complex questions. However, since the required analyses are highly specific to the particular data set and question, a black-box method is not sufficient anymore. Instead, biologists are required to be actively involved with modeling decisions during data analysis. The modular design of the Bayesian phylogenetic software package BEAST 2 enables, and in fact enforces, this involvement. At the same time, the modular design enables computational biology groups to develop new methods at a rapid rate. A thorough understanding of the models and algorithms used by inference software is a critical prerequisite for successful hypothesis formulation and assessment. In particular, there is a need for more readily available resources aimed at helping interested scientists equip themselves with the skills to confidently use cutting-edge phylogenetic analysis software. These resources will also benefit researchers who do not have access to similar courses or training at their home institutions. Here, we introduce the "Taming the Beast" (https://taming-the-beast.github.io/) resource, which was developed as part of a workshop series bearing the same name, to facilitate the usage of the Bayesian phylogenetic software package BEAST 2.

Predicting HIV-1 transmission and antibody neutralization efficacy in vivo from stoichiometric parameters.

The potential of broadly neutralizing antibodies targeting the HIV-1 envelope trimer to prevent HIV-1 transmission has opened new avenues for therapies and vaccines. However, their implementation remains challenging and would profit from a deepened mechanistic understanding of HIV-antibody interactions and the mucosal transmission process. In this study we experimentally determined stoichiometric parameters of the HIV-1 trimer-antibody interaction, confirming that binding of one antibody is sufficient for trimer neutralization. This defines numerical requirements for HIV-1 virion neutralization and thereby enables mathematical modelling of in vitro and in vivo antibody neutralization efficacy. The model we developed accurately predicts antibody efficacy in animal passive immunization studies and provides estimates for protective mucosal antibody concentrations. Furthermore, we derive estimates of the probability for a single virion to start host infection and the risks of male-to-female HIV-1 transmission per sexual intercourse. Our work thereby delivers comprehensive quantitative insights into both the molecular principles governing HIV-antibody interactions and the initial steps of mucosal HIV-1 transmission. These insights, alongside the underlying, adaptable modelling framework presented here, will be valuable for supporting in silico pre-trial planning and post-hoc evaluation of HIV-1 vaccination or antibody treatment trials.

Delineating CD4 dependency of HIV-1: Adaptation to infect low level CD4 expressing target cells widens cellular tropism but severely impacts on envelope functionality.

A hallmark of HIV-1 infection is the continuously declining number of the virus' predominant target cells, activated CD4+ T cells. With diminishing CD4+ T cell levels, the capacity to utilize alternate cell types and receptors, including cells that express low CD4 receptor levels such as macrophages, thus becomes crucial. To explore evolutionary paths that allow HIV-1 to acquire a wider host cell range by infecting cells with lower CD4 levels, we dissected the evolution of the envelope-CD4 interaction under in vitro culture conditions that mimicked the decline of CD4high target cells, using a prototypic subtype B, R5-tropic strain. Adaptation to CD4low targets proved to severely alter envelope functions including trimer opening as indicated by a higher affinity to CD4 and loss in shielding against neutralizing antibodies. We observed a strikingly decreased infectivity on CD4high target cells, but sustained infectivity on CD4low targets, including macrophages. Intriguingly, the adaptation to CD4low targets altered the kinetic of the entry process, leading to rapid CD4 engagement and an extended transition time between CD4 and CCR5 binding during entry. This phenotype was also observed for certain central nervous system (CNS) derived macrophage-tropic viruses, highlighting that the functional perturbation we defined upon in vitro adaptation to CD4low targets occurs in vivo. Collectively, our findings suggest that CD4low adapted envelopes may exhibit severe deficiencies in entry fitness and shielding early in their evolution. Considering this, adaptation to CD4low targets may preferentially occur in a sheltered and immune-privileged environment such as the CNS to allow fitness restoring compensatory mutations to occur.

Determinants of HIV-1 broadly neutralizing antibody induction.

Broadly neutralizing antibodies (bnAbs) are a focal component of HIV-1 vaccine design, yet basic aspects of their induction remain poorly understood. Here we report on viral, host and disease factors that steer bnAb evolution using the results of a systematic survey in 4,484 HIV-1-infected individuals that identified 239 bnAb inducers. We show that three parameters that reflect the exposure to antigen-viral load, length of untreated infection and viral diversity-independently drive bnAb evolution. Notably, black participants showed significantly (P = 0.0086-0.038) higher rates of bnAb induction than white participants. Neutralization fingerprint analysis, which was used to delineate plasma specificity, identified strong virus subtype dependencies, with higher frequencies of CD4-binding-site bnAbs in infection with subtype B viruses (P = 0.02) and higher frequencies of V2-glycan-specific bnAbs in infection with non-subtype B viruses (P = 1 × 10-5). Thus, key host, disease and viral determinants, including subtype-specific envelope features that determine bnAb specificity, remain to be unraveled and harnessed for bnAb-based vaccine design.

Tracing HIV-1 transmission: envelope traits of HIV-1 transmitter and recipient pairs.

BACKGROUND: Mucosal HIV-1 transmission predominantly results in a single transmitted/founder (T/F) virus establishing infection in the new host despite the generally high genetic diversity of the transmitter virus population. To what extent HIV-1 transmission is a stochastic process or driven by selective forces that allow T/F viruses best to overcome bottlenecks in transmission has not been conclusively resolved. Building on prior investigations that suggest HIV-1 envelope (Env) features to contribute in the selection process during transmission, we compared phenotypic virus characteristics of nine HIV-1 subtype B transmission pairs, six men who have sex with men and three male-to-female transmission pairs. RESULTS: All recipients were identified early in acute infection and harbored based on extensive sequencing analysis a single T/F virus allowing a controlled analysis of virus properties in matched transmission pairs. Recipient and transmitter viruses from the closest time point to transmission showed no signs of selection for specific Env modifications such as variable loop length and glycosylation. Recipient viruses were resistant to circulating plasma antibodies of the transmitter and also showed no altered sensitivity to a large panel of entry inhibitors and neutralizing antibodies. The recipient virus did not consistently differ from the transmitter virus in terms of entry kinetics, cell-cell transmission and replicative capacity in primary cells. Our paired analysis revealed a higher sensitivity of several recipient virus isolates to interferon-α (IFNα) which suggests that resistance to IFNα cannot be a general driving force in T/F establishment. CONCLUSIONS: With the exception of increased IFNα sensitivity, none of the phenotypic virus properties we investigated clearly distinguished T/F viruses from their matched transmitter viruses supporting the notion that at least in subtype B infection HIV-1 transmission is to a considerable extent stochastic.

HIV-1 resistance to neutralizing antibodies: Determination of antibody concentrations leading to escape mutant evolution.

Broadly neutralizing antibodies against human immunodeficiency virus type 1 (HIV-1) are considered vital components of novel therapeutics and blueprints for vaccine research. Yet escape to even the most potent of these antibodies is imminent in natural infection. Measures to define antibody efficacy and prevent mutant selection are thus urgently needed. Here, we derive a mathematical framework to predict the concentration ranges for which antibody escape variants can outcompete their viral ancestors, referred to as mutant selection window (MSW). When determining the MSW, we focus on the differential efficacy of neutralizing antibodies against HIV-1 in two canonical infection routes, free-virus infection and cell-cell transmission. The latter has proven highly effective in vitro suggesting its importance for both in vivo spread as well as for escaping targeted intervention strategies. We observed a range of MSW patterns that highlight the potential of mutants to arise in both transmission pathways and over wide concentration ranges. Most importantly, we found that only when the arising mutant has both, residual sensitivity to the neutralizing antibody and reduced infectivity compared to the parental virus, antibody dosing outside of the MSW to restrict mutant selection is possible. Emergence of mutants that provide complete escape and have no considerable fitness loss cannot be prevented by adjusting antibody doses. The latter may in part explain the ubiquitous resistance to neutralizing antibodies observed in natural infection and antibody treatment. Based on our findings, combinations of antibodies targeting different epitopes should be favored for antibody-based interventions as this may render complete resistance less likely to occur and also increase chances that multiple escapes result in severe fitness loss of the virus making longer-term antibody treatment more feasible.

The HIV-1 Entry Process: A Stoichiometric View.

HIV-1 infection starts with fusion of the viral and the host cell membranes, a process mediated by the HIV-1 envelope glycoprotein trimer. The number of trimers required to complete membrane fusion, referred to as HIV-1 entry stoichiometry, remains under debate. A precise definition of HIV-1 entry stoichiometry is important as it reflects the efficacy of the viral entry process and steers the infectivity of HIV-1 virion populations. Initial estimates suggested a unanimous entry stoichiometry across HIV-1 strains while recent findings showed that HIV-1 strains can differ in entry stoichiometry. Here, we review current analyses of HIV-1 entry stoichiometry and point out future research directions to further define the interplay between entry stoichiometry, virus entry fitness, transmission, and susceptibility to antibody neutralization.

Capacity of Broadly Neutralizing Antibodies to Inhibit HIV-1 Cell-Cell Transmission Is Strain- and Epitope-Dependent.

An increasing number of broadly neutralizing antibodies (bnAbs) are considered leads for HIV-1 vaccine development and novel therapeutics. Here, we systematically explored the capacity of bnAbs to neutralize HIV-1 prior to and post-CD4 engagement and to block HIV-1 cell-cell transmission. Cell-cell spread is known to promote a highly efficient infection with HIV-1 which can inflict dramatic losses in neutralization potency compared to free virus infection. Selection of bnAbs that are capable of suppressing HIV irrespective of the transmission mode therefore needs to be considered to ascertain their in vivo activity in therapeutic use and vaccines. Employing assay systems that allow for unambiguous discrimination between free virus and cell-cell transmission to T cells, we probed a panel of 16 bnAbs for their activity against 11 viruses from subtypes A, B and C during both transmission modes. Over a wide range of bnAb-virus combinations tested, inhibitory activity against HIV-1 cell-cell transmission was strongly decreased compared to free virus transmission. Activity loss varied considerably between virus strains and was inversely associated with neutralization of free virus spread for V1V2- and V3-directed bnAbs. In rare bnAb-virus combinations, inhibition for both transmission modes was comparable but no bnAb potently blocked cell-cell transmission across all probed virus strains. Mathematical analysis indicated an increased probability of bnAb resistance mutations to arise in cell-cell rather than free virus spread, further highlighting the need to block this pathway. Importantly, the capacity to efficiently neutralize prior to CD4 engagement correlated with the inhibition efficacy against free virus but not cell-cell transmitted virus. Pre-CD4 attachment activity proved strongest amongst CD4bs bnAbs and varied substantially for V3 and V1V2 loop bnAbs in a strain-dependent manner. In summary, bnAb activity against divergent viruses varied depending on the transmission mode and differed depending on the window of action during the entry process, underscoring that powerful combinations of bnAbs are needed for in vivo application.

Classic reaction kinetics can explain complex patterns of antibiotic action.

Finding optimal dosing strategies for treating bacterial infections is extremely difficult, and improving therapy requires costly and time-intensive experiments. To date, an incomplete mechanistic understanding of drug effects has limited our ability to make accurate quantitative predictions of drug-mediated bacterial killing and impeded the rational design of antibiotic treatment strategies. Three poorly understood phenomena complicate predictions of antibiotic activity: post-antibiotic growth suppression, density-dependent antibiotic effects, and persister cell formation. We show that chemical binding kinetics alone are sufficient to explain these three phenomena, using single-cell data and time-kill curves of Escherichia coli and Vibrio cholerae exposed to a variety of antibiotics in combination with a theoretical model that links chemical reaction kinetics to bacterial population biology. Our model reproduces existing observations, has a high predictive power across different experimental setups (R(2) = 0.86), and makes several testable predictions, which we verified in new experiments and by analyzing published data from a clinical trial on tuberculosis therapy. Although a variety of biological mechanisms have previously been invoked to explain post-antibiotic growth suppression, density-dependent antibiotic effects, and especially persister cell formation, our findings reveal that a simple model that considers only binding kinetics provides a parsimonious and unifying explanation for these three complex, phenotypically distinct behaviours. Current antibiotic and other chemotherapeutic regimens are often based on trial and error or expert opinion. Our "chemical reaction kinetics"-based approach may inform new strategies, which are based on rational design.