Biology subjects

Ganusov, V. V.

Publications and source records attributed to Ganusov, V. V..

At least 19 recordsLinked to original sources

bioRxiv2026

Data selection choices influence the inferred movement patterns of Plasmodium sporozoites in skin

Motility of Plasmodium sporozoites (SPZs) in the skin is a key determinant of successful host infection. Earlier studies have described rapid movement of both murine and human SPZs in skin following syringe inoculation. It is typical to classify SPZ trajectories into "motile" and "immotile" and restrict the analysis of movement patterns to motile SPZs. Because criteria to define motile SPZs are dependent on the study and are often qualitative, it remains unclear if sub-selection of motile tracks introduces biases in characterization of SPZ movement in vivo. We processed imaging data (22 movies) from a recent study of movement of P. falciparum (Pf) and P. yoelii (Py) SPZ in skin. We proposed a novel metric - maximal spatial spread (MSS or S) -- that is the maximum Euclidean distance between any two recorded positions in a trajectory. We used MSS to classify SPZ trajectories as immotile (S [≤] Sthreshold) or motile (S > Sthreshold) for a given threshold value Sthreshold. Larger Sthreshold values naturally resulted in a smaller fraction of tracks classified as motile, and subsequently, in an increased overall displacement, instantaneous and mean speeds, decreased mean turning angle, and higher initial slopes of the mean squared displacement (MSD) curves. We found that at intermediate values of Sthreshold Pf SPZs had a lower average speed than Py SPZs suggesting that host environment may impact SPZ movement. Both species exhibited a small but statistically significant decline in average speed with time after inoculation but this was also dependent on the Sthreshold value. Our analysis of MSD curves and turning angle distributions suggests that both Pf and Py SPZs undergo correlated random walks - a type of Brownian walk with short-term superdiffusive displacement. By using a novel methodology of hidden Markov models (moveHMM package in R) we found that SPZ movement is best described by three movement states; however, none of these states corresponded to previously described circling gliding. Taking together, our results suggest that inference of SPZ movement patterns depends on the criteria used to define tracks as motile or immotile. Standardized preprocessing criteria are therefore important when comparing motility across Plasmodium species, experimental time points, or laboratories. Analysis of turning angle distributions and application of hidden Markov models provided additional metrics to quantify distinct modes of SPZ movement in vivo.

microbiology↗

bioRxiv2026

BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs

The BCG vaccine remains the only licensed vaccine against tuberculosis (TB), yet the mechanisms behind BCG-induced protection remain poorly understood. Plumlee et al. (PLOS Pathogens 2023) infected over 1,000 mice, half of which were vaccinated with BCG, with an ultra-low dose (ULD) of Mycobacterium tuberculosis (Mtb); the authors found that BCG vaccination resulted in fewer infected mice, lower CFU lung burden, and more frequent unilateral lung infection. We have developed several mathematical models of Mtb dynamics and dissemination between murine right and left lungs and fit these models to the CFU data from unvaccinated or BCG-vaccinated mice. Alternative mathematical models incorporating either direct (lung-to-lung) or indirect (lung-intermediate tissue-lung) dissemination pathways fit the unvaccinated data equally well, suggesting multiple plausible routes of Mtb spread. Yet, irrespective of the dissemination route, the models predicted rapid Mtb replication during early infection, transient control within 1-2 months after infection, and continued bacterial growth in the chronic phase. Fitting models to the data from BCG-vaccinated animals revealed that BCG reduces the rate of Mtb dissemination between the lungs by 89% while having a more modest effect on the replication rate within the lung, reducing it by 9%. We found that the dominant effect of BCG in curbing lung dissemination arises from its ability to reduce Mtb replication resulting in fewer infected mice, lower lung CFU, and decreased bilateral infection of the lung. We used our parameterized mathematical models to calculate the number of mice needed to detect the efficacy of a hypothetical vaccine on the probability of Mtb clearance or dissemination between murine lungs that extends previously provided estimates. Taken together, our novel mathematical modeling-based framework provides a rigorous way of quantifying vaccine efficacy in ULD-infected mice, paving the way for the pre-clinical evaluation of next-generation TB vaccines.

immunology↗

bioRxiv2025

Mind the gap: Understanding discordance between culture- and a non-culture-based measure of bacterial burden in murine tuberculosis treatment models

The standard pharmacodynamic marker in murine tuberculosis drug studies is colony-forming units (CFU). A faster PCR-based marker of bacterial burden is 16S rRNA. For unclear reasons, treatment reduces CFU more than 16S rRNA. We evaluated this CFU-16S gap and estimated the fraction potentially attributable to slow decay of 16S rRNA from dead Mycobacterium tuberculosis (Mtb) versus transition to a viable but not culturable on solid agar (VBNCSA) population. We quantified the CFU-16S gap during and following treatment in six BALB/c mouse studies and one in vitro study. Applying a two-population ordinary differential equation-based model of Mtb death and 16S rRNA decay, we estimated the fraction of the gap potentially attributable to dead Mtb. Using meta-regression, we estimated the association between CFU or 16S rRNA with relapse. For all regimens, CFU fell more than 16S rRNA, ranging from isoniazid-rifampin-pyrazinamide-ethambutol (CFU decreased 39-times more than 16S rRNA at week 4) to bedaquiline-pretomanid-moxifloxacin-pyrazinamide (CFU decreased >500,000-times more). The two-population model suggested that the fraction of the CFU-16S gap attributable to residual 16S rRNA from dead Mtb is modest and decreases over time. After treatment, 16S rRNA often fell while CFU rose. Four-week CFU change explained most variation in relapse (R{superscript 2}=0.90) while four-week 16S rRNA change did not (R{superscript 2}=0.24). CFU-16S gap is only partially explained by slow decay of residual 16S, suggesting development of a VBNCSA population. However, continued decrease in 16S rRNA after treatment cessation and its limited association with relapse suggests VBNCSA may be a transient rather than persistent state.

microbiology↗

bioRxiv2025

Liver sinusoid constraints make random search of CD8 T cells for Plasmodium parasites efficient

A relatively small number of liver-localized CD8 T cells can provide sterilizing protection against exposure to Plasmodium sporozoites. Previously published mathematical model-based simulations of randomly searching for an infection T cells, assuming that T cells move in open (3D) space or on a regular lattice, suggested that some degree of attraction is needed for cells to find the infection. Yet, in our previous experiments we failed to find evidence of attraction towards the infection in most T cells. Because the movement of liver-localized T cells is confined to sinusoids, the blood vessels of the liver, T cells may in fact be attracted to the infection site via the sinusoids. In new experiments we imaged Plasmodium-specific CD8 T cells, sporozoites, and liver sinusoids simultaneously. We also developed a new method to model imaged sinusoids as graphs and to simulate movement of T cells on graphs, and new tests to detect biased cell movement on graphs. As before, our previously published open space/3D-based metric suggested that few T cells are attracted to the infection site in presence of moderate cluster of T cells. However, with our new graph-based metric we could not detect attraction when constraining T cell movement to sinusoids. Surprisingly, simulations of T cells searching for an infection via liver sinusoids showed that a relatively small number of T cells (1 cell/imaging volume or <10^5 cell/liver), moving without attraction at experimentally observed speeds, is sufficient to find the infection within 24 hours, well below the expected lifespan of the Plasmodium liver stage in mice. Our results suggest that the constrained environment of the tissue structure makes a random search more effective, and that detecting T cell attraction towards specific areas may arise as an artifact of metrics designed for open space/3D. Our results thus call for a re-evaluation of the implicit assumption that attraction is necessary for T cells to find infections in tissues.

immunology↗

bioRxiv2025

Immortal genome assumption significantly underestimates replication and death rates of Mycobacterium tuberculosis in mice and monkeys

Immune correlates of protection against infection with Mycobacterium tuberculosis (Mtb) or against tuberculosis (TB) remain poorly defined. The ratio of colony forming units (CFUs) to chromosomal equivalents (CEQs), Z = CFUs/CEQs, recovered either from the whole lung (mice) or individual lesions (monkeys or rabbits) of Mtb-infected animals has been used as a metric for how effectively Mtb is killed in vivo. However, the contribution of bacterial killing to changes in the CFU/CEQ ratio during an infection has not been rigorously investigated. We developed alternative mathematical models to study the dynamics of CFUs, CEQs, and their ratio during an Mtb infection. We find that the ratio Z alone cannot be used to infer the death rate of bacteria, unless the dynamics of CEQs and CFUs are entirely uncoupled, which is biologically unreasonable and inconsistent with the view that CEQs reflect an accumulated burden of both viable and non-viable bacteria. Importantly, we estimate a decay rate of 3.6%/day (a half life of about 20 days) of Mtb H37Rv CEQs in B6 mice that is similar to 4%/day, previously found for Mtb Erdman in cynomolgus macaques. While the estimated Mtb DNA decay rate seems small, we found that estimated rates of Mtb replication and death/killing are still extremely sensitive even to slow decay of Mtb DNA, in part, because Mtb replication and death rates are also small especially during chronic phases of infection. By applying our models to data on Mtb dynamics during the first 3 weeks of infection in macaques, we provide evidence of substantial killing of Mtb bacteria, prior to arrival of adaptive immunity to the site of infection, challenging the previously established notion of non-dying bacteria in the absence of T cell immunity and granuloma formation. We also propose experiments that will allow more accurately to measure the rate of Mtb DNA loss, helping more rigorously quantify impact of immunity on within-host Mtb dynamics.

microbiology↗

bioRxiv2025

Using Imaris to rigorously track PET-defined sites of lung inflammation in Mycobacterium tuberculosis-exposed non-human primates

Aerosol exposure of non-human primates (NHPs) to Mycobacterium tuberculosis (Mtb) typically results in discrete sites of inflammation of the lung that is detectable by 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG)-based PET/CT scans. Such scans are often analyzed using software such as Invicro VivoQuant or OsiriX as 3D images by manual labeling sites of PET signal using 2D slices and by reporting maximal standardized uptake value (SUVmax) either of the whole lung or of individual lesions. Here we propose a pipeline for analysis of the same PET/CT scans using Imaris, a proprietary software typically used for analysis of fluorescent microscopy data. We show that by using locations of spine vertebra (denoted as "landmarks") we can align serials scans of the same animal, and by using automated (with some manual corrections) image segmentation of PET scans in 3D as "surfaces", we can accurately define location of all sites of inflammation in the lung and lung-associated thoracic lymph nodes (LNs). We show that there is an excellent correlation between individual lesions SUVmax determined by VivoQuant and maximum intensity determined by Imaris suggesting utility of this approach. Imaris also provides wealth of additional information for each of the identified lesions such as volume, location, shape, surface area, and others, and each lesion can be exported in Virtual Reality file format (.wrl) allowing for detailed and rigorous analyses of how features of these PET-defined lesions evolve over time and correlate with the outcome of infection and/or treatment.

immunology↗

bioRxiv2025

Apparent cooperativity between human CMV virions introduces errors in conventional methods of calculating multiplicity of infection

Whether infection of cells by individual virions occurs randomly or if there is some form(s) of competition or cooperativity between individual virions remains largely unknown for most virus-cell associations. Here we studied cooperativity/competition for three different strains of human cytomegalovirus (HCMV) on two different cell types (fibroblasts and epithelial cells). By titrating viral inocula concentrations in small steps over several orders of magnitude, and by using flow cytometry to precisely measure frequency of infected cells, we found that for most virus-cell associations, the frequency of cell infection increases faster than linear with an increasing inoculum concentration, indicating cooperativity between individual infecting virions. Mathematical modeling suggests that this apparent cooperativity cannot be explained by heterogeneity in either the infectivity of the individual virions or the resistance of individual cells to infection, or by simple aggregation/clumping of viral particles. Stochastic simulations of two additional alternative models that allow for i) reduction in cell resistance to infection when exposed to multiple virions, or ii) compensation in infectivity of poorly infectious virions when coinfecting cells with more infectious virions, resulted in apparent viral cooperativity. Analysis of other published datasets suggests presence of apparent viral cooperativity for HIV and vaccinia virus, infecting CRFK or HeLa cells, respectively, but not for tobacco mosaic virus forming plaques on plant leaves. We thus 1) propose a methodology to rigorously evaluate apparent cooperativity of viruses infecting target cells, and 2) demonstrate that knowing the degree of virus cooperativity for any given virus-cell combination is important for an accurate quantification of multiplicity of infection (MOI). Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/650360v2_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@f4de20org.highwire.dtl.DTLVardef@2342dcorg.highwire.dtl.DTLVardef@fab722org.highwire.dtl.DTLVardef@d43bd_HPS_FORMAT_FIGEXP M_FIG C_FIG Infection Unit per cell (IU/Cell) and specific infectivity (Genome/IU) of human cytomegalovirus depend on the infecting dose (Genome/Cell). The data are for HCMV-TB infecting fibroblasts.

microbiology↗

bioRxiv2024

Mathematical modeling suggests heterogeneous replication of Mycobacterium tuberculosis in rabbits

Tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb), remains a major health problem with 10.6 million cases of the disease and 1.6 million deaths in 2021. It is well understood that pulmonary TB is due to Mtb growth in the lung but quantitative estimates of rates of Mtb replication and death in lungs of patients or animals such as monkeys or rabbits remain largely unknown. We performed experiments with rabbits infected with a novel, virulent clinical Mtb isolate of the Beijing lineage, HN878, carrying an unstable plasmid pBP10. In our in vitro experiments we found that pBP10 is more stable in HN878 strain than in a more commonly used laboratory-adapted Mtb strain H37Rv (the segregation coefficient being s = 0.10 in HN878 vs. s = 0.18 in H37Rv). Interestingly, the kinetics of plasmid-bearing bacteria in lungs of Mtb-infected rabbits did not follow an expected monotonic decline; the percent of plasmid-bearing cells increased between 28 and 56 days post-infection and remained stable between 84 and 112 days post-infection despite a large increase in bacterial numbers in the lung at late time points. Mathematical modeling suggested that such a non-monotonic change in the percent of plasmid-bearing cells can be explained if the lung Mtb population consists of several (at least 2) sub-populations with different replication/death kinetics: one major population expanding early and being controlled/eliminated, while another, a smaller population expanding at later times causing a counterintuitive increase in the percent of plasmid-bearing cells. Importantly, a model with one kinetically homogeneous Mtb population could not explain the data including when the model was run stochastically. Given that in rabbits HN878 strain forms well circumscribed granulomas, our results suggest independent bacterial dynamics in subsets of such granulomas. Our model predictions can be tested in future experiments in which HN878-pBP10 dynamics in individual granulomas is followed over time. Taken together, our new data and mathematical modeling-based analyses illustrate differences in Mtb dynamics in mice and rabbits confirming a perhaps somewhat obvious observation that "rabbits are not mice". Author SummaryHow quickly Mycobacterium tuberculosis (Mtb) replicates and dies in lungs of infected individuals is likely to determine the outcome of the infection - either control/clearance of the bacteria by the host immune response or progression to active disease, tuberculosis (TB). And yet, only a few studies, primarily in mice, rigorously estimated the rates of Mtb replication and death during an in vivo infection. We infected rabbits with a novel clinical isolate of Mtb carrying an unstable, "replication clock" plasmid and followed the dynamics of bacteria over time. Interestingly, previous methods developed to estimate Mtb replication and death rates using similar data for Mtb infection of mice failed to describe our novel data on Mtb dynamics in rabbits; we showed that heterogeneous dynamics of Mtb in semi-independent subpopulations in lungs of Mtb-infected rabbits may be one explanation of this failure of the method. Our results highlight potential differences in Mtb dynamics in different mammalian hosts and suggest ways to evaluate heterogeneity of Mtb replication and death rates in vivo.

microbiology↗

bioRxiv2023

Mathematical modeling suggests cytotoxic T lymphocytes control growth of B16 tumor cells in collagin-fibrin gels by cytolytic and non-lytic mechanisms

Cytotoxic T lymphocytes (CTLs) are important in controlling some viral infections, and therapies involving transfer of large numbers of cancer-specific CTLs have been successfully used to treat several types of cancers in humans. While molecular mechanisms of how CTLs kill their targets are relatively well understood we still lack solid quantitative understanding of the kinetics and efficiency at which CTLs kill their targets in different conditions. Collagen-fibrin gel-based assays provide a tissue-like environment for the migration of CTLs, making them an attractive system to study the cytotoxicity in vitro. Budhu et al. [1] systematically varied the number of peptide (SIINFEKL)- pulsed B16 melanoma cells and SIINFEKL-specific CTLs (OT-1) and measured remaining targets at different times after target and CTL co-inoculation into collagen-fibrin gels. The authors proposed that their data were consistent with a simple model in which tumors grow exponentially and are killed by CTLs at a per capita rate proportional to the CTL density in the gel. By fitting several alternative mathematical models to these data we found that this simple "exponential-growth-mass-action-killing" model does not precisely fit the data. However, determining the best fit model proved difficult because the best performing model was dependent on the specific dataset chosen for the analysis. When considering all data that include biologically realistic CTL concentrations (E [≤] 107 cell/ml) the model in which tumors grow exponentially and CTLs suppress tumors growth non-lytically and kill tumors according to the mass-action law (SiGMA model) fitted the data with best quality. Results of power analysis suggested that longer experiments ([~] 3 - 4 days) with 4 measurements of B16 tumor cell concentrations for a range of CTL concentrations would best allow to discriminate between alternative models. Taken together, our results suggest that interactions between tumors and CTLs in collagen-fibrin gels are more complex than a simple exponential-growth- mass-action killing model and provide support for the hypothesis that CTLs impact on tumors may go beyond direct cytotoxicity.

immunology↗

bioRxiv2023

Brain-localized CD4 and CD8 T cells perform correlated random walks and not Levy walks

For survival of the organism T cells must efficiently control pathogens invading different peripheral tissues but whether such control (and lack of thereof) is achieved by utilizing different movement strategies remains poorly understood. Liver-localized CD8 T cells perform correlated random walks -- a type of a Brownian walk - in liver sinusoids but in some condition these T cells may also perform Levy flights - rapid and large displacements by floating with the blood flow. CD8 T cells in lymph nodes or skin also undergo Brownian walks. A recent study suggested that brain-localized CD8 T cells, specific to Toxoplasma gondii, perform generalized Levy walks - a walk type in which T cells alternate pausing and displacing long distances -- which may indicate that brain is a unique organ where T cells exhibit movement strategies different from other tissues. We quantified movement patterns of brain-localized Plasmodium berghei-specific CD4 and CD8 T cells by using well-established statistical and computational methods. Interestingly, we found that T cells change their movement pattern with time since infection and that CD4 T cells move faster and turn less than CD8 T cells. Importantly, both CD4 and CD8 T cells move in the brain by correlated random walks without long displacements challenging previous observations. We have also re-analyzed the movement data of brain-localized CD8 T cells in T. gondii -infected mice and found no evidence of Levy walks. We hypothesize that the previous conclusion of Levy walks of T. gondii-specific CD8 T cells in the brain was reached due to missing time-frames in the data that create an impression of large displacements between assumed-to-be-sequential movements. Taken together, our results suggests that movement strategies of CD8 T cells are largely similar between LNs, liver, and the brain and consistent with correlated random walks and not Levy walks.

immunology↗

bioRxiv2022

Mathematical modeling suggests that a single Plasmodium-specific CD8 T cell can eliminate a malaria liver stage in mice

Vaccination strategies in mice inducing high numbers of memory CD8+ T cells specific to a single epitope are able to provide sterilizing protection against infection with Plasmodium sporozoites. We have recently found that Plasmodium-specific CD8+ T cells cluster around sporozoite-infected hepatocytes but whether such clusters are important in elimination of the parasite remains incompletely understood. Here we used our previously generated data in which we employed intravital microscopy to longitudinally image 32 GFP-expressing Plasmodium yoelii parasites in livers of mice that had received activated Plasmodium-specific CD8+ T cells after sporozoite infection. We found significant heterogeneity in the dynamics of the normalized GFP signal from the parasites (termed "vitality index" or VI) that was weakly correlated with the number of T cells near the parasite. We also found that a simple model assuming mass-action, additive killing by T cells well describes the VI dynamics for most parasites and predicts a highly variable killing efficacy by individual T cells. Given our estimated median per capita kill rate of k = 0.031/h we predict that a single T cell is typically incapable to kill a parasite within the 48 hour lifespan of the liver stage in mice. Stochastic simulations of T cell clustering and killing of the liver stage also suggested that 1) three or more T cells per infected hepatocyte are required to ensure sterilizing protection; 2) both variability in killing efficacy of individual T cells and resistance to killing by individual parasites may contribute to the observed variability in VI decline, and 3) the stable VI of some clustered parasites cannot be explained by measurement noise. Taken together, our analysis for the first time provides estimates of efficiency at which individual CD8+ T cells eliminate intracellular parasitic infection in vivo.

immunology↗

bioRxiv2022

Evaluating impact of experimental design on accuracy of parameter estimation and model selection efficiency: T cell clustering as a case study

Mathematical modeling provides a rigorous way to quantify immunological processes and to discriminate between alternative mechanisms driving specific biological phenomena. It is typical that mathematical models of immunological phenomena are developed by modellers to explain specific sets of experimental data after the data have been collected by experimental collaborators. Whether the available data are sufficient to accurately estimate model parameters or to discriminate between alternative models is not typically investigated. While previously collected data may be sufficient to guide development of alternative models and help estimating model parameters, such data often do not allow to discriminate between alternative models. As a case study we develop a series of power analyses to determine optimal sample sizes that allow for accurate estimation of model parameters and for discrimination between alternative models describing clustering of T cells around Plasmodium liver stages. In our typical experiments, mice are infected intravenously with Plasmodium sporozoites that invade hepatocytes (liver cells), and then activated CD8 T cells are transferred into the infected mice. The number of T cells found in the vicinity of individual infected hepatocytes at different times after T cell transfer is counted using intravital microscopy. We previously developed a series of mathematical models aimed to explain highly variable number of T cells per parasite; one of such model, the density-dependent recruitment (DDR) model, fitted the data from preliminary experiments better than the alternative models, such as the density-independent exit (DIE) model. Here we show that the ability to discriminate between these alternative models depends on the number of parasites imaged in the analysis; analysis of about n = 50 parasites at 2, 4, and 8 hours after T cell transfer will allow for over 95% probability to select the correct model. The type of data collected also has an impact; following T cell clustering around individual parasites over time (called as longitudinal (LT) data) allows for a more precise and less biased estimates of the parameters of the DDR model than that generated from a more traditional way of imaging individual parasites in different liver areas/mice (cross-sectional (CS) data). However, LT imaging comes at a cost of a need to keep the mice alive under the microscope for hours which may be ethically unacceptable. We finally show that the number of time points at which the measurements are taken also impacts the precision of estimation of DDR model parameters; in particular, measuring T cell clustering at one time point does not allow accurately estimating all parameters of the DDR model. Using our case study, we propose a general framework on how mathematical modeling can be used to guide experimental designs and power analyses of complex biological processes.

immunology↗

bioRxiv2021

Mathematical modeling suggests cooperation of plant-infecting viruses

Viruses are major pathogens of agricultural crops. Viral infections often start after the virus enters the outer layer of a tissue or surface and many successful viruses, after local replication in the infected tissue, are able to spread systemically. Quantitative details of virus dynamics in plants, however, have been poorly understood, in part, because of the lack of experimental methods allowing to accurately measure the degree of infection in individual plant tissues. Recently, by using flow cytometry and two different flourescently-labeled strains of the Tobacco etch virus (TEV), Venus and BFP, kinetics of viral infection of individual cells in leaves of Nicotiana tabacum plants was followed over time [1]. A simple mathematical model, assuming that viral spread occurs from lower to upper leaves, was fitted to these data. While the the original model could accurately describe the kinetics of viral spread locally and systemically, we also found that many alternative versions of the model, for example, if viral spread starts at upper leaves and progresses to lower leaves or when virus dissemination is stopped due to an immune response, provided fits of the data with reasonable quality, and yet with different parameter estimates. These results strongly suggest that experimental measurements of the virus infection in individual leaves may not be sufficient to identify the pathways of viral dissemination between different leaves and reasons for viral control; we propose experiments that may allow discrimination between the alternatives. By analyzing the kinetics of coinfection of individual cells by Venus and BFP strains of TEV we found a strong deviation from the random infection model, suggesting cooperation between the two strains when infecting plant cells. Importantly, we showed that many mathematical models on the kinetics of coinfection of cells with two strains could not adequately describe the data, and the best fit model needed to assume i) different susceptibility of uninfected cells to infection by two viruses locally in the leaf vs. systemically from other leaves, and ii) decrease in the infection rate depending on the fraction of uninfected cells which could be due to a systemic immune response. Our results thus demonstrate the difficulty in reaching definite conclusions from extensive and yet limited experimental data and provide evidence of potential cooperation between different viral variants infecting individual cells in plants.

microbiology↗

bioRxiv2021

Enhancing Quantitative and Data Science Education for Graduate Students in Biomedical Science

Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science, but far less attention has been paid to the graduate curriculum. In this setting, we propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities. Due to the diversity of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We developed a novel prioritization approach in which we mined and analyzed quantitative concepts and skills from publications that faculty in relevant units deemed central to the scientific comprehension of their field. The analysis provides a prioritization of quantitative skills and concepts and could represent an effective method to drive curricular focus based upon program-specific faculty input for biological science programs of all types. Our results highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty. One Sentence SummaryWe developed a novel approach to prioritize quantitative concepts and methods for inclusion in a graduate biomedical science curriculum based upon approaches included in faculty-identified key publications.

scientific communication and education↗

bioRxiv2021

Platelets are dispensable for the ability of CD8+ T cells to accumulate, patrol, kill and reside in the liver

Effector and memory CD8+ T cells accumulate in large numbers in the liver where they play key roles in the control of liver pathogens including Plasmodium. It has also been proposed that liver may act as the main place for elimination of effector CD8+ T cells at the resolution of immune responses. Platelets and the integrin LFA-1 have been proposed to be critical for the accumulation of protective CD8+ T cells in the liver; conversely, asialo-glycoprotein (ASGP) expression on the surface of CD8+ T cells has been proposed to assist in elimination of effector T cells in the liver. Here we investigated the contributions of these interactions in the accumulation of CD8+ T cells activated in vitro or in vivo by immunization with Plasmodium parasites. Using Mpl-/- mice with constitutive thrombocytopaenia and antibody-mediated platelet depletion models we found that severe reduction in platelet concentration in circulation did not strongly influence the accumulation and protective function of CD8+ T cells in the liver in these models. Surprisingly, inhibition of ASGP receptors did not inhibit the accumulation of effector cells in the liver, but instead prevented these cells from accumulating in the spleen. We further found that enforced expression of ASGP on effector CD8+ T cells using ST3GalI knockout cells lead to their loss from the spleen. These data suggest that platelets play a marginal role in CD8+ T cell function in the liver. Furthermore, ASGP-expressing effector CD8+ T cells are retained in the liver but are lost from the spleen.

immunology↗

bioRxiv2021

Negative correlation between average speed and average turning angle naturally arises for sparsely sampled cell movement data

Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds. Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo.

immunology↗

bioRxiv2020

A minority of liver-localized CD8 T cells demonstrate difficult-to-detect attraction to Plasmodium-infected hepatocytes

Malaria is a disease caused by Plasmodium parasites, resulting in over 200 million infections and 400,000 deaths every year. A critical step of malaria infection is when sporozoites, injected by mosquitoes, travel to the liver and form liver stages. Malaria vaccine candidates which induce large numbers of malaria-specific CD8 T cells in mice are able to eliminate all liver stages, preventing fulminant malaria. However, how CD8 T cells find all parasites in 48 hours of the liver stage lifespan is not well understood. Using intravital microscopy of murine livers, we generated unique data on T cell search for malaria liver stages within a few hours after infection. To detect attraction of T cells to an infection site, we used the von Mises-Fisher distribution in 3D, similar to the 2D von Mises distribution previously used in ecology. Our results suggest that the vast majority (70-95%) of malaria-specific and non-specific liver-localized CD8 T cells did not display attraction towards the infection site, suggesting that the search for malaria liver stages occurs randomly. However, a small fraction (15-20%) displayed weak but detectable attraction towards parasites which already had been surrounded by several T cells. We found that speeds and turning angles correlated with attraction, suggesting that understanding mechanisms that determine the speed of T cell movement in the liver may improve the efficacy of future T cell-based vaccines. Stochastic simulations suggest that a small movement bias towards the parasite dramatically reduces the number of CD8 T cells needed to eliminate all malaria liver stages, but to detect such attraction by individual cells requires data from long imaging experiments which are not currently feasible. Importantly, as far as we know this is the first demonstration of how activated/memory CD8 T cells might search for the pathogen in nonlymphoid tissues a few hours after infection. We have also established a framework for how attraction of individual T cells towards a location in 3D can be rigorously evaluated.

immunology↗

bioRxiv2020

Environment-imposed constraints make Brownian walkers efficient searchers

Pathogen-specific CD8 T cells face the problem of finding rare cells that present their cognate antigen either in the lymph node or infected tissue. While quantitative details of T cell movement strategies in some tissues such lymph nodes or skin have been relatively well characterized, we still lack quantitative understanding of T cell movement in many other important tissues such as the spleen, lung, liver, and gut. Furthermore, how environmental constraints influence movement patterns of T cells in tissues remains incompletely characterized. Liver is one of the major organs in mice and humans and is the target site for many pathogens such as hepatitis B and C viruses in humans and Plasmodium parasites in multiple mammalian species. We developed a protocol to generate stable numbers of liver-located CD8 T cells, used intravital microscopy to record movement patterns of CD8 T cells in livers of live mice, and analyzed these and previously published data using well-established statistical and computational methods. We show that in most of our experiments Plasmodium-specific liver-localized CD8 T cells perform correlated random walks characterized by transiently superdiffusive displacement with persistence times of 10-15 min that exceed those observed for T cells in lymph nodes. Liver-localized CD8 T cells typically crawl on the lumenal side of liver sinusoids (i.e., are in the blood); simulating T cell movement in digital structures derived from the liver sinusoids illustrates that liver structure alone is sufficient to explain the relatively long superdiffusive displacement of T cells. In experiments when CD8 T cells in the liver poorly attach to the sinusoids (e.g., one week post immunization with radiation-attenuated Plasmodium sporozoites) T cells also undergo Levy flights - large displacements occurring due to cell deattaching from the endothelium, floating with the blood flow, and re-attaching at another location. Our analysis, thus, provides quantitative details of movement patterns of liver-localized CD8 T cells and illustrates how structural and physiological details of the tissue may impact T cell movement patterns.

immunology↗