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Recent studies have reported the protective efficacy of both natural1 and vaccine-induced2–7 immunity against challenge with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in rhesus macaques. However, the importance of humoral and cellular immunity for protection against infection with SARS-CoV-2 remains to be determined. Here we show that the adoptive transfer of purified IgG from convalescent rhesus macaques (Macaca mulatta) protects naive recipient macaques against challenge with SARS-CoV-2 in a dose-dependent fashion. Depletion of CD8+ T cells in convalescent macaques partially abrogated the protective efficacy of natural immunity against rechallenge with SARS-CoV-2, which suggests a role for cellular immunity in the context of waning or subprotective antibody titres. These data demonstrate that relatively low antibody titres are sufficient for protection against SARS-CoV-2 in rhesus macaques, and that cellular immune responses may contribute to protection if antibody responses are suboptimal. We also show that higher antibody titres are required for treatment of SARS-CoV-2 infection in macaques. These findings have implications for the development of SARS-CoV-2 vaccines and immune-based therapeutic agents. Adoptive transfer of purified IgG from convalescent macaques protects naive macaques against SARS-CoV-2 infection, and cellular immune responses contribute to protection against rechallenge with SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) in humans is often a clinically mild illness, but some individuals develop severe pneumonia, respiratory failure and death1–4. Studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hamsters5–7 and nonhuman primates8–10 have generally reported mild clinical disease, and preclinical SARS-CoV-2 vaccine studies have demonstrated reduction of viral replication in the upper and lower respiratory tracts in nonhuman primates11–13. Here we show that high-dose intranasal SARS-CoV-2 infection in hamsters results in severe clinical disease, including high levels of virus replication in tissues, extensive pneumonia, weight loss and mortality in a subset of animals. A single immunization with an adenovirus serotype 26 vector-based vaccine expressing a stabilized SARS-CoV-2 spike protein elicited binding and neutralizing antibody responses and protected against SARS-CoV-2-induced weight loss, pneumonia and mortality. These data demonstrate vaccine protection against SARS-CoV-2 clinical disease. This model should prove useful for preclinical studies of SARS-CoV-2 vaccines, therapeutics and pathogenesis., A single immunization with an adenovirus vector-based vaccine expressing a stabilized SARS-CoV-2 spike protein induces protection against SARS-CoV-2-induced weight loss, pneumonia and mortality in hamsters.

Humoral immunity is key to protection for nearly all licensed vaccines. Yet, the design of vaccines has been more difficult for some of our most deadly killers (e.g. HIV, influenza, Dengue virus, etc.), likely due to our incomplete understanding of the precise immunological mechanisms associated with protection. Humoral immunity is governed both by B-cells and their bi-functional secreted antibodies, all of which have a unique capacity to evolve during an immune response. Current OMIC technologies capture individual features of the humoral immune response, providing a glimpse into humoral components (Fab/Fc/B-cell-omic), but fail to provide a wholistic view of the humoral response as a collective functional arm. Here, we dissect current OMIC strategies reviewing experimental and computational approaches, that if integrated could provide a true systems-level view of the humoral immune response.

A safe and effective vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be required to end the coronavirus disease 2019 (COVID-19) pandemic1-8. For global deployment and pandemic control, a vaccine that requires only a single immunization would be optimal. Here we show the immunogenicity and protective efficacy of a single dose of adenovirus serotype 26 (Ad26) vector-based vaccines expressing the SARS-CoV-2 spike (S) protein in non-human primates. Fifty-two rhesus macaques (Macaca mulatta) were immunized with Ad26 vectors that encoded S variants or sham control, and then challenged with SARS-CoV-2 by the intranasal and intratracheal routes9,10. The optimal Ad26 vaccine induced robust neutralizing antibody responses and provided complete or near-complete protection in bronchoalveolar lavage and nasal swabs after SARS-CoV-2 challenge. Titres of vaccine-elicited neutralizing antibodies correlated with protective efficacy, suggesting an immune correlate of protection. These data demonstrate robust single-shot vaccine protection against SARS-CoV-2 in non-human primates. The optimal Ad26 vector-based vaccine for SARS-CoV-2, termed Ad26.COV2.S, is currently being evaluated in clinical trials.

Summary: Chromatin states must be maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications is central in this process. However, the histone modification landscape is challenged by incorporation of new unmodified histones during each cell cycle, and the principles governing heritability remain unclear. We take a quantitative computational modeling approach to describe propagation of histone H3K27 and H3K36 methylation states. We measure combinatorial H3K27 and H3K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones. Using model comparison, we reject active global demethylation and invoke the existence of domains defined by distinct methylation endpoints. We find that H3K27me3 on pre-existing histones stimulates the rate of de novo H3K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed quantitative picture of the mutual antagonism between H3K27 and H3K36 methylation and propose that it stabilizes epigenetic states across cell division. : Alabert et al. introduce a computational model to describe the propagation of histone K27 and K36 methylations on successive generations of histones. This quantitative model invokes the existence of domains with distinct methylation endpoints and reveals that antagonisms between histone methylations enhance the stability of epigenetic states.

Plasma viremia reoccurs in most HIV-infected individuals once antiretroviral therapy is interrupted, and interindividual differences in the kinetics of viral rebound have been associated with virological and immunological factors. Antibody features, including Fc functionality and Fc glycosylation, have been identified as sensitive surrogates for disease activity in multiple diseases., Plasma viremia reoccurs in most HIV-infected individuals once antiretroviral therapy (ART) is interrupted. The kinetics of viral rebound, specifically the time until plasma virus becomes detectable, differ quite substantially between individuals, and associations with virological and immunological factors have been suggested. Standard clinical measures, like CD4 T-cell counts and plasma HIV RNA levels, however, are poor predictive markers. Antibody features, including Fc functionality and Fc glycosylation have been identified as sensitive surrogates for disease activity in multiple diseases. Here, we analyzed HIV-specific antibody quantities and qualitative differences like antibody-mediated functions, Fc gamma receptor (FcγR) binding, and IgG Fc glycosylation as well as cytokine profiles and cellular HIV DNA and RNA levels in 23 ART-suppressed individuals prior to undergoing an analytical ART interruption (ATI). We found that antibodies with distinct functional properties and Fc glycan signatures separated individuals into early and delayed viral rebounders (≤4 weeks versus >4 weeks) and tracked with levels of inflammatory cytokines and transcriptional activity of the viral reservoir. Specifically, individuals with early viral rebound exhibited higher levels of total HIV-specific IgGs carrying inflammatory Fc glycans, while delayed rebounders showed an enrichment of highly functional antibodies. Overall, only four features, including enhanced antibody-mediated NK cell activation in delayed rebounders, were necessary to discriminate the groups. These data suggest that antibody features can be used as sensitive indicators of HIV disease activity and could be included in future ATI studies.

Importance Control of the global COVID-19 pandemic will require the development and deployment of safe and effective vaccines. Objective To evaluate the immunogenicity of the Ad26.COV2.S vaccine (Janssen/Johnson & Johnson) in humans, including the kinetics, magnitude, and phenotype of SARS-CoV-2 spike-specific humoral and cellular immune responses. Design, Setting, and Participants Twenty-five participants were enrolled from July 29, 2020, to August 7, 2020, and the follow-up for this day 71 interim analysis was completed on October 3, 2020; follow-up to assess durability will continue for 2 years. This study was conducted at a single clinical site in Boston, Massachusetts, as part of a randomized, double-blind, placebo-controlled phase 1 clinical trial of Ad26.COV2.S. Interventions Participants were randomized to receive 1 or 2 intramuscular injections with 5 × 1010viral particles or 1 × 1011viral particles of Ad26.COV2.S vaccine or placebo administered on day 1 and day 57 (5 participants in each group). Main Outcomes and Measures Humoral immune responses included binding and neutralizing antibody responses at multiple time points following immunization. Cellular immune responses included immunospot-based and intracellular cytokine staining assays to measure T-cell responses. Results Twenty-five participants were randomized (median age, 42; age range, 22-52; 52% women, 44% male, 4% undifferentiated), and all completed the trial through the day 71 interim end point. Binding and neutralizing antibodies emerged rapidly by day 8 after initial immunization in 90% and 25% of vaccine recipients, respectively. By day 57, binding and neutralizing antibodies were detected in 100% of vaccine recipients after a single immunization. On day 71, the geometric mean titers of spike-specific binding antibodies were 2432 to 5729 and the geometric mean titers of neutralizing antibodies were 242 to 449 in the vaccinated groups. A variety of antibody subclasses, Fc receptor binding properties, and antiviral functions were induced. CD4+ and CD8+ T-cell responses were induced. Conclusion and Relevance In this phase 1 study, a single immunization with Ad26.COV2.S induced rapid binding and neutralization antibody responses as well as cellular immune responses. Two phase 3 clinical trials are currently underway to determine the efficacy of the Ad26.COV2.S vaccine. Trial Registration ClinicalTrials.gov Identifier:NCT04436276

10 pages, 3 figures, 2 tables.-- This is an open access article distributed under the terms of the Creative Commons Attribution License, Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been—so far—no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies, This work was supported by the European Union’s Horizon 2020 research and innovation program (CanPathPro; Grant no. 686282; J.H., D.W., P.L.S., E.D., S.M., A.F.V., J.R.B.), the German Federal Ministry of Education and Research (Grant no. 01ZX1916A; D.W., P.L. & 01ZX1705A; J.H., P.L. & Grant. no. 031L0159C; J.H. & de.NBI ModSim1, 031L0104A; F.T.B. & EA:Sys, 031L0080; J.E, L.R & Grant no. 031L0048; S.K., F.G.W. & 01ZX1310B; E.R.), the German Federal Ministry of Economic Affairs and Energy (Grant no. 16KN074236; D.P.), the German Research Foundation (Grant no. HA7376/1-1; Y.S.; CIBSS-EXC-2189-2100249960-390939984; C.K., J.T.; project ID: 272983813 - TRR 179; M.R. & Clusters of Excellence EXC 2047 and EXC 2151; E.R., J.H.), the Deutsche Krebshilfe (Grant no. 70112355; A.L.H.), the Human Frontier Science Program (Grant no. LT000259/2019-L1; F.F.), the National Institute of Health (Grant no. U54-CA225088; F.F.)

Comorbid medical illnesses, such as obesity and diabetes, are associated with more severe COVID-19, hospitalization, and death. However, the role of the immune system in mediating these clinical outcomes has not been determined. We used multiparameter flow cytometry and systems serology to comprehensively profile the functions of T cells and antibodies targeting spike, nucleocapsid, and envelope proteins in a convalescent cohort of COVID-19 subjects who were either hospitalized (n = 20) or not hospitalized (n = 40). To avoid confounding, subjects were matched by age, sex, ethnicity, and date of symptom onset. Surprisingly, we found that the magnitude and functional breadth of virus-specific CD4+ T cell and antibody responses were consistently higher among hospitalized subjects, particularly those with medical comorbidities. However, an integrated analysis identified more coordination between polyfunctional CD4+ T cells and antibodies targeting the S1 domain of spike among subjects who were not hospitalized. These data reveal a functionally diverse and coordinated response between T cells and antibodies targeting SARS-CoV-2, which is reduced in the presence of comorbid illnesses that are known risk factors for severe COVID-19. CA extern

A critical step to ending the spread of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the ability to detect, diagnose, and understand why some individuals develop mild and others develop severe disease. For example, defining the early evolutionary patterns of humoral immunity to SARS-CoV-2, and whether prevalent coronaviruses or other common infections influence the evolution of immunity, remains poorly understood but could inform diagnostic and vaccine development. Here, we deeply profiled the evolution of SARS-CoV-2 immunity, and how it is influenced by other coinfections. Our data suggest an early and rapid rise in functional humoral immunity in the first 2 weeks of infection across antigen-specific targets, which is negligibly influenced by cross-reactivity to additional common coronaviruses or common respiratory infections. These data suggest that preexisting receptor binding domain-specific immunity does not influence or bias the evolution of immunity to SARS-CoV-2 and should have negligible influence on shaping diagnostic or vaccine-induced immunity., The novel coronavirus, SARS-coronavirus (CoV)-2 (SARS-CoV-2), has caused over 17 million infections in just a few months, with disease manifestations ranging from largely asymptomatic infection to critically severe disease. The remarkable spread and unpredictable disease outcomes continue to challenge management of this infection. Among the hypotheses to explain the heterogeneity of symptoms is the possibility that exposure to other coronaviruses (CoVs), or overall higher capability to develop immunity against respiratory pathogens, may influence the evolution of immunity to SARS-CoV-2. Thus, we profiled the immune response across multiple coronavirus receptor binding domains (RBDs), respiratory viruses, and SARS-CoV-2, to determine whether heterologous immunity to other CoV-RBDs or other infections influenced the evolution of the SARS-CoV-2 humoral immune response. Overall changes in subclass, isotype, and Fc-receptor binding were profiled broadly across a cohort of 43 individuals against different coronaviruses—RBDs of SARS-CoV-2 and the more common HKU1 and NL63 viruses. We found rapid functional evolution of responses to SARS-CoV-2 over time, along with broad but relatively more time-invariant responses to the more common CoVs. Moreover, there was little evidence of correlation between SARS-CoV-2 responses and HKU1, NL63, and respiratory infection (influenza and respiratory syncytial virus) responses. These findings suggest that common viral infections including common CoV immunity, targeting the receptor binding domain involved in viral infection, do not appear to influence the rapid functional evolution of SARS-CoV-2 immunity, and thus should not impact diagnostics or shape vaccine-induced immunity. IMPORTANCE A critical step to ending the spread of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the ability to detect, diagnose, and understand why some individuals develop mild and others develop severe disease. For example, defining the early evolutionary patterns of humoral immunity to SARS-CoV-2, and whether prevalent coronaviruses or other common infections influence the evolution of immunity, remains poorly understood but could inform diagnostic and vaccine development. Here, we deeply profiled the evolution of SARS-CoV-2 immunity, and how it is influenced by other coinfections. Our data suggest an early and rapid rise in functional humoral immunity in the first 2 weeks of infection across antigen-specific targets, which is negligibly influenced by cross-reactivity to additional common coronaviruses or common respiratory infections. These data suggest that preexisting receptor binding domain-specific immunity does not influence or bias the evolution of immunity to SARS-CoV-2 and should have negligible influence on shaping diagnostic or vaccine-induced immunity.

SARS-CoV-2 infection causes more severe disease in pregnant women compared to age-matched non-pregnant women. Whether maternal infection causes changes in the transfer of immunity to infants remains unclear. Maternal infections have previously been associated with compromised placental antibody transfer, but the mechanism underlying this compromised transfer is not established. Here, we used systems serology to characterize the Fc-profile of influenza-, pertussis-, and SARS-CoV-2-specific antibodies transferred across the placenta. Influenza- and pertussis-specific antibodies were actively transferred. However, SARS-CoV-2-specific antibody transfer was significantly reduced compared to influenza- and pertussis-specific antibodies, and cord titers and functional activity were lower than in maternal plasma. This effect was only observed in third trimester infection. SARS-CoV-2-specific transfer was linked to altered SARS-CoV-2-antibody glycosylation profiles and was partially rescued by infection-induced increases in IgG and increased FCGR3A placental expression. These results point to unexpected compensatory mechanisms to boost immunity in neonates, providing insights for maternal vaccine design., Highlights • SARS-CoV-2-specific antibodies have a decreased placental transfer • SARS-CoV-2-spike antibodies have altered glycosylation profiles in pregnant women • Pregnant women with SARS-CoV-2 during the third trimester have elevated IgG levels • SARS-CoV-2-specific antibody transfer is efficient after second trimester infection, Atyeo et al. reveals a deficiency in SARS-CoV-2-antibody placental transfer among women infected during the third trimester. While bulk antibody transfer remains unaltered, SARS-CoV-2-antibodies show perturbed Fc glycosylation profiles and elevated IgG and FCGR3A placental expression that suggest compensation for poor transfer.

Critical to managing the spread of COVID-19 is the ability to diagnose infection and define the acquired immune response across the population. While genomic tests for the novel Several Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) detect the presence of viral RNA for a limited time frame, when the virus is shed in the upper respiratory tract, tests able to define exposure and infection beyond this short window of detectable viral replication are urgently needed. Following infection, antibodies are generated within days, providing a durable read-out and archive of exposure and infection. Several antibody tests have emerged to diagnose SARS-CoV-2. Here we report on a qualified quantitative ELISA assay that displays all the necessary characteristics for high-throughput sample analysis. Collectively, this test offers a quantitative opportunity to define both exposure and levels of immunity to SARS-CoV-2.

Summary As SARS-CoV-2 infections and death counts continue to rise, it remains unclear why some individuals recover from infection whereas others rapidly progress and die. While the immunological mechanisms that underlie different clinical trajectories remain poorly defined, pathogen-specific antibodies often point to immunological mechanisms of protection. Here, we profiled SARS-CoV-2–specific humoral responses on a cohort of 22 hospitalized individuals. Despite inter-individual heterogeneity, distinct antibody signatures resolved individuals with different outcomes. While no differences in SARS-CoV-2-specific IgG levels were observed, spike–specific humoral responses were enriched among convalescent individuals, whereas functional antibody responses to the nucleocapsid were elevated in deceased individuals. Furthermore, this enriched immunodominant S-specific antibody profile in convalescents was confirmed in a larger validation cohort. These results demonstrate that early antigen-specific and qualitative features of SARS-CoV-2-specific antibodies, point to differences in disease trajectory, highlighting the potential importance of functional antigen-specific humoral immunity to guide patient care and vaccine development., Graphical Abstract, Highlights • Limited early differences across groups were observed in titers and neutralization • Five antibody features collectively could differentiate convalescents and deceased • A shift in the balance of spike versus nucleocapsid immunity separated the groups • Spike-specific phagocytic and complement fixing activity was enriched in convalescents, Although most SARS-CoV-2 infected individuals experience mild disease, a significant fraction of individuals become severely infected. Early biomarkers that predict outcome are urgently needed. Atyeo et al demonstrate that distinct acute SARS-CoV-2 humoral immune responses exist across severely ill individuals that ultimately convalesce or pass away.

Summary DNA replication during cell division leads to dilution of histone modifications and can thus affect chromatin-mediated gene regulation, raising the question of how the cell-cycle shapes the histone modification landscape, particularly during embryogenesis. We tackled this problem by manipulating the cell cycle during early Xenopus laevis embryogenesis and analyzing in vivo histone H4K20 methylation kinetics. The global distribution of un-, mono-, di-, and tri-methylated histone H4K20 was measured by mass spectrometry in normal and cell-cycle-arrested embryos over time. Using multi-start maximum likelihood optimization and quantitative model selection, we found that three specific biological methylation rate constants were required to explain the measured H4K20 methylation state kinetics. While demethylation is essential for regulating H4K20 methylation kinetics in non-cycling cells, demethylation is very likely dispensable in rapidly dividing cells of early embryos, suggesting that cell-cycle-mediated dilution of H4K20 methylation is an essential regulatory component for shaping its epigenetic landscape during early development. A record of this paper’s transparent peer review process is included in the Supplemental Information .

SUMMARYChromatin states must be maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications is central in this process. However, the histone modification landscape is challenged by incorporation of new unmodified histones during each cell cycle and the principles governing heritability remain unclear. Here, we take a quantitative computational modeling approach to describes propagation of K27 and K36 methylation states. We measure combinatorial K27 and K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones. Using model comparison, we reject active global demethylation and invoke the existence of domains defined by distinct methylation endpoints. We find that K27me3 on pre-existing histones stimulates the rate of de novo K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed, quantitative picture of the mutual antagonism between K27 and K37 methylation, and propose that it stabilizes epigenetic states across cell division.

Cellular heterogeneity is known to have important effects on signal processing and cellular decision making. To understand these processes, multiple classes of mathematical models have been introduced. The hierarchical population model builds a novel class which allows for the mechanistic description of heterogeneity and explicitly takes into account subpopulation structures. However, this model requires a parametric distribution assumption for the cell population and, so far, only the normal distribution has been employed. Here, we incorporate alternative distribution assumptions into the model, assess their robustness against outliers and evaluate their influence on the performance of model calibration in a simulation study and a real-world application example. We found that alternative distributions provide reliable parameter estimates even in the presence of outliers, and can in fact increase the convergence of model calibration.HighlightsGeneralizes hierarchical population model to various distribution assumptionsProvides framework for efficient calibration of the hierarchical population modelSimulation study and application to experimental data reveal improved robustness and optimization performance

The urgent need for an effective SARS-CoV-2 vaccine has forced development to progress in the absence of well-defined correlates of immunity. While neutralization has been linked to protection against other pathogens, whether neutralization alone will be sufficient to drive protection against SARS-CoV-2 in the broader population remains unclear. Therefore, to fully define protective humoral immunity we dissected the early evolution of the humoral response in 193 hospitalized individuals ranging from moderate-to severe. Although robust IgM and IgA responses evolved in both survivors and non-survivors with severe disease, non-survivors showed attenuated IgG responses, accompanied by compromised Fcɣ-receptor binding and Fc-effector activity, pointing to deficient humoral development rather than disease-enhancing humoral immunity. In contrast, individuals with moderate disease exhibited delayed responses that ultimately matured. These data highlight distinct humoral trajectories associated with resolution of SARS-CoV-2 infection and the need for early functional humoral immunity., Highlights ● IgA and IgM evolve rapidly across all levels of disease severity ● Rapid and potent IgG class switching is linked to survival ● Moderate disease is associated with a delay but ultimate convergence of IgG ● Early S2-cross-reactivity is linked to survival after severe disease, Analyses of the functional humoral trajectories associated with the resolution of SARS-CoV-2 infection find that in spite of equivalent IgM and IgA immunity to the virus across all levels of disease severity, survival and recovery is linked to early class switching to IgG and the ability to leverage Fcγ-receptors targeting the spike protein.

Null models for the effect of combination therapies are widely used to evaluate synergy and antagonism of drugs. Due to the relevance of null models, their suitability is continuously discussed. Here, we contribute to the discussion by investigating the properties of five null models. Our study includes the model proposed by David J. Hand, which we refer to as Hand model. The Hand model has been introduced almost 20 years ago but hardly was used and studied. We show that the Hand model generalizes the principle of dose equivalence compared to the Loewe model and resolves the ambiguity of the Tallarida model. This provides a solution to the persisting conflict about the compatibility of two essential model properties: the sham combination principle and the principle of dose equivalence. By embedding several null models into a common framework, we shed light in their biochemical validity and provide indications that the Hand model is biochemically most plausible. We illustrate the practical implications and differences between null models by examining differences of null models on published data.

Cellular signaling is essential in information processing and decision-making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. Single-cell measurements of signaling molecules demonstrated a substantial cell-to-cell variability, raising questions about its causes and mechanisms and about how cell populations cope with or exploit cellular heterogeneity. To gain insights from single-cell signaling data, analysis and modeling approaches have been introduced. This review discusses these modeling approaches, with a focus on recent advances in the development and calibration of mechanistic models. Additionally, it outlines current and future challenges.

Motivation Dynamic models are used in systems biology to study and understand cellular processes like gene regulation or signal transduction. Frequently, ordinary differential equation (ODE) models are used to model the time and dose dependency of the abundances of molecular compounds as well as interactions and translocations. A multitude of computational approaches, e.g. for parameter estimation or uncertainty analysis have been developed within recent years. However, many of these approaches lack proper testing in application settings because a comprehensive set of benchmark problems is yet missing. Results We present a collection of 20 benchmark problems in order to evaluate new and existing methodologies, where an ODE model with corresponding experimental data is referred to as problem. In addition to the equations of the dynamical system, the benchmark collection provides observation functions as well as assumptions about measurement noise distributions and parameters. The presented benchmark models comprise problems of different size, complexity and numerical demands. Important characteristics of the models and methodological requirements are summarized, estimated parameters are provided, and some example studies were performed for illustrating the capabilities of the presented benchmark collection. Availability and implementation The models are provided in several standardized formats, including an easy-to-use human readable form and machine-readable SBML files. The data is provided as Excel sheets. All files are available at https://github.com/Benchmarking-Initiative/Benchmark-Models, including step-by-step explanations and MATLAB code to process and simulate the models. Supplementary information Supplementary data are available at Bioinformatics online.

Motivation Mathematical models are nowadays important tools for analyzing dynamics of cellular processes. The unknown model parameters are usually estimated from experimental data. These data often only provide information about the relative changes between conditions, hence, the observables contain scaling parameters. The unknown scaling parameters and corresponding noise parameters have to be inferred along with the dynamic parameters. The nuisance parameters often increase the dimensionality of the estimation problem substantially and cause convergence problems. Results In this manuscript, we propose a hierarchical optimization approach for estimating the parameters for ordinary differential equation (ODE) models from relative data. Our approach restructures the optimization problem into an inner and outer subproblem. These subproblems possess lower dimensions than the original optimization problem, and the inner problem can be solved analytically. We evaluated accuracy, robustness and computational efficiency of the hierarchical approach by studying three signaling pathways. The proposed approach achieved better convergence than the standard approach and required a lower computation time. As the hierarchical optimization approach is widely applicable, it provides a powerful alternative to established approaches. Availability and implementation The code is included in the MATLAB toolbox PESTO which is available at http://github.com/ICB-DCM/PESTO Supplementary information Supplementary data are available at Bioinformatics online.

Summary PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB. Availability and implementation PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/. Supplementary information Supplementary data are available at Bioinformatics online.

All biological systems exhibit cell-to-cell variability. Frameworks exist for understanding how stochastic fluctuations and transient differences in cell state contribute to experimentally observable variations in cellular responses. However, current methods do not allow identification of the sources of variability between and within stable subpopulations of cells. We present a data-driven modeling framework for the analysis of populations comprising heterogeneous subpopulations. Our approach combines mixture modeling with frameworks for distribution approximation, facilitating the integration of multiple single-cell datasets and the detection of causal differences between and within subpopulations. The computational efficiency of our framework allows hundreds of competing hypotheses to be compared. We initially validate our method using simulated data with an understood ground truth, then we analyze data collected using quantitative single-cell microscopy of cultured sensory neurons involved in pain initiation. This approach allows us to quantify the relative contribution of neuronal subpopulations, culture conditions, and expression levels of signaling proteins to the observed cell-to-cell variability in NGF/TrkA-initiated Erk1/2 signaling. Loos et al. introduce a data-driven modeling framework for the mechanistic analysis of heterogeneous cell populations consisting of subpopulations. Applying the framework to single-cell microscopy data of primary sensory neurons, they analyze the influence of extracellular scaffolds onto sensitization signaling.