Artur Yakimovich

Cell-Free Transmission of Human Adenovirus by Passive Mass Transfer in Cell Culture Simulated in a Computer Model

ABSTRACT Viruses spread between cells, tissues, and organisms by cell-free and cell-cell transmissions. Both mechanisms enhance disease development, but it is difficult to distinguish between them. Here, we analyzed the transmission mode of human adenovirus (HAdV) in monolayers of epithelial cells by wet laboratory experimentation and a computer simulation. Using live-cell fluorescence microscopy and replication-competent HAdV2 expressing green fluorescent protein, we found that the spread of infection invariably occurred after cell lysis. It was affected by convection and blocked by neutralizing antibodies but was independent of second-round infections. If cells were overlaid with agarose, convection was blocked and round plaques developed around lytic infected cells. Infected cells that did not lyse did not give rise to plaques, highlighting the importance of cell-free transmission. Key parameters for cell-free virus transmission were the time from infection to lysis, the dose of free viruses determining infection probability, and the diffusion of single HAdV particles in aqueous medium. With these parameters, we developed an in silico model using multiscale hybrid dynamics, cellular automata, and particle strength exchange. This so-called white box model is based on experimentally determined parameters and reproduces viral infection spreading as a function of the local concentration of free viruses. These analyses imply that the extent of lytic infections can be determined by either direct plaque assays or can be predicted by calculations of virus diffusion constants and modeling.

Simultaneous analysis of large-scale RNAi screens for pathogen entry

BackgroundLarge-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries.ResultsWe show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied.ConclusionsOur results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Plaque2.0-A High-Throughput Analysis Framework to Score Virus-Cell Transmission and Clonal Cell Expansion.

Classical plaque assay measures the propagation of infectious agents across a monolayer of cells. It is dependent on cell lysis, and limited by user-specific settings and low throughput. Here, we developed Plaque2.0, a broadly applicable, fluorescence microscopy-based high-throughput method to mine patho-biological clonal cell features. Plaque2.0 is an open source framework to extract information from chemically fixed cells by immuno-histochemistry or RNA in situ hybridization, or from live cells expressing GFP transgene. Multi-parametric measurements include infection density, intensity, area, shape or location information at single plaque or population levels. Plaque2.0 distinguishes lytic and non-lytic spread of a variety of DNA and RNA viruses, including vaccinia virus, adenovirus and rhinovirus, and can be used to visualize simultaneous plaque formation from co-infecting viruses. Plaque2.0 also analyzes clonal growth of cancer cells, which is relevant for cell migration and metastatic invasion studies. Plaque2.0 is suitable to quantitatively analyze virus infections, vector properties, or cancer cell phenotypes.

Chemical Induction of Unfolded Protein Response Enhances Cancer Cell Killing through Lytic Virus Infection

ABSTRACT Cancer cells are susceptible to oncolytic viruses, albeit variably. Human adenoviruses (HAdVs) are widely used oncolytic agents that have been engineered to produce progeny within the tumor and elicit bystander effects. We searched for host factors enhancing bystander effects and conducted a targeted RNA interference screen against guanine nucleotide exchange factors (GEFs) of small GTPases. We show that the unfolded protein response (UPR), which is readily inducible in aggressive tumor cells, enhances melanoma or epithelial cancer cell killing upon HAdV infection. UPR was triggered by knockdown of Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF-1) or the GBF-1 inhibitor golgicide A (GCA) and stimulated HAdV infection. GBF-1 is a GEF for ADP ribosylation factors (Arfs) regulating endoplasmic reticulum (ER)-to-Golgi apparatus and intra-Golgi apparatus membrane transport. Cells treated with GCA enhanced HAdV-induced cytopathic effects in epithelial and melanoma cancer cells but not normal cells, if the drug was applied several hours prior to HAdV inoculation. This was shown by real-time label-free impedance measurements using the xCELLigence system. GCA-treated cells contained fewer incoming HAdVs than control cells, but GCA treatment boosted HAdV titers and spreading in cancer cells. GCA enhanced viral gene expression or transgene expression from the cytomegalovirus promoter of B- or C-species HAdVs but did not enhance viral early region 1A (E1A) expression in uninfected cell lines or cells transfected with plasmid reporter DNA. The UPR-enhanced cell killing required the nuclease activity of the UPR sensor inositol-requiring enzyme 1 (IRE-1) and X box binding protein 1 (XBP-1), which alleviate ER stress. The collective results show that chemical UPR induction and viruses boost tumor cell killing by enhancing oncolytic viral efficacy. IMPORTANCE Cancer is difficult to combat. A wide range of oncolytic viruses show promise for killing cancer cells, yet the efficacy of oncolytic killing is low. We searched for host factors enhancing adenovirus cancer cell killing and found that the knockdown of Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF-1) or chemical inhibition of GBF-1 enhanced adenovirus infection by triggering the IRE-1/XBP-1 branch of the unfolded protein response (UPR). IRE-1/XBP-1 promote cell survival and enhanced the levels of the adenoviral immediate early gene product E1A, virus spreading, and killing of cancer cells. Aggressive tumor cells depend on a readily inducible UPR and, hence, present prime targets for a combined strategy involving adenoviruses and small chemicals inducing UPR.

The nuclear export factor CRM1 controls juxta-nuclear microtubule-dependent virus transport

ABSTRACT Transport of large cargo through the cytoplasm requires motor proteins and polarized filaments. Viruses that replicate in the nucleus of post-mitotic cells use microtubules and the dynein–dynactin motor to traffic to the nuclear membrane and deliver their genome through nuclear pore complexes (NPCs) into the nucleus. How virus particles (virions) or cellular cargo are transferred from microtubules to the NPC is unknown. Here, we analyzed trafficking of incoming cytoplasmic adenoviruses by single-particle tracking and super-resolution microscopy. We provide evidence for a regulatory role of CRM1 (chromosome-region-maintenance-1; also known as XPO1, exportin-1) in juxta-nuclear microtubule-dependent adenovirus transport. Leptomycin B (LMB) abolishes nuclear targeting of adenovirus. It binds to CRM1, precludes CRM1–cargo binding and blocks signal-dependent nuclear export. LMB-inhibited CRM1 did not compete with adenovirus for binding to the nucleoporin Nup214 at the NPC. Instead, CRM1 inhibition selectively enhanced virion association with microtubules, and boosted virion motions on microtubules less than ∼2 µm from the nuclear membrane. The data show that the nucleus provides positional information for incoming virions to detach from microtubules, engage a slower microtubule-independent motility to the NPC and enhance infection. Summary: The mechanism through which macromolecular complexes reach the nuclear pores is incompletely understood. We show that the cytoplasmic perinuclear ecology is tuned by CRM1 to control virus transport to the nuclear pore complex.

Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells.

Infectio presents a generalized platform to analyze virus infection spread between cells. It allows the simulation of plaque phenotypes from image-based assays. Viral plaques are the result of virus spreading from primary infected cells to neighboring cells. This is a complex process and involves neighborhood effects at cell-cell contact sites or fluid dynamics in the extracellular medium. Infectio differentiates between two major modes of virus transmission between cells, allowing in silico testing of hypotheses about spreading mechanisms of any virus which can be grown in cell cultures, based on experimentally measured parameters, such as infection intensity or cell killing. The results of these tests can be compared with experimental data and allow interpretations with regard to biophysical mechanisms. Infectio also facilitates characterizations of the mode of action of therapeutic agents, such as oncolytic viruses or other infectious or cytotoxic agents. ABSTRACT Viruses spread between cells, tissues, and organisms by cell-free and cell-cell mechanisms, depending on the cell type, the nature of the virus, or the phase of the infection cycle. The mode of viral transmission has a large impact on disease development, the outcome of antiviral therapies or the efficacy of gene therapy protocols. The transmission mode of viruses can be addressed in tissue culture systems using live-cell imaging. Yet even in relatively simple cell cultures, the mechanisms of viral transmission are difficult to distinguish. Here we present a cross-platform software framework called “Infectio,” which is capable of simulating transmission phenotypes in tissue culture of virtually any virus. Infectio can estimate interdependent biological parameters, for example for vaccinia virus infection, and differentiate between cell-cell and cell-free virus spreading. Infectio assists in elucidating virus transmission mechanisms, a feature useful for designing strategies of perturbing or enhancing viral transmission. The complexity of the Infectio software is low compared to that of other software commonly used to quantitate features of cell biological images, which yields stable and relatively error-free output from Infectio. The software is open source (GPLv3 license), and operates on the major platforms (Windows, Mac, and Linux). The complete source code can be downloaded from http://infectio.github.io/index.html . IMPORTANCE Infectio presents a generalized platform to analyze virus infection spread between cells. It allows the simulation of plaque phenotypes from image-based assays. Viral plaques are the result of virus spreading from primary infected cells to neighboring cells. This is a complex process and involves neighborhood effects at cell-cell contact sites or fluid dynamics in the extracellular medium. Infectio differentiates between two major modes of virus transmission between cells, allowing in silico testing of hypotheses about spreading mechanisms of any virus which can be grown in cell cultures, based on experimentally measured parameters, such as infection intensity or cell killing. The results of these tests can be compared with experimental data and allow interpretations with regard to biophysical mechanisms. Infectio also facilitates characterizations of the mode of action of therapeutic agents, such as oncolytic viruses or other infectious or cytotoxic agents.

Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function.

Cell Cycle-Dependent Expression of Adeno-Associated Virus 2 (AAV2) Rep in Coinfections with Herpes Simplex Virus 1 (HSV-1) Gives Rise to a Mosaic of Cells Replicating either AAV2 or HSV-1

ABSTRACT Adeno-associated virus 2 (AAV2) depends on the simultaneous presence of a helper virus such as herpes simplex virus 1 (HSV-1) for productive replication. At the same time, AAV2 efficiently blocks the replication of HSV-1, which would eventually limit its own replication by diminishing the helper virus reservoir. This discrepancy begs the question of how AAV2 and HSV-1 can coexist in a cell population. Here we show that in coinfected cultures, AAV2 DNA replication takes place almost exclusively in S/G2-phase cells, while HSV-1 DNA replication is restricted to G1 phase. Live microscopy revealed that not only wild-type AAV2 (wtAAV2) replication but also reporter gene expression from both single-stranded and double-stranded (self-complementary) recombinant AAV2 vectors preferentially occurs in S/G2-phase cells, suggesting that the preference for S/G2 phase is independent of the nature of the viral genome. Interestingly, however, a substantial proportion of S/G2-phase cells transduced by the double-stranded but not the single-stranded recombinant AAV2 vectors progressed through mitosis in the absence of the helper virus. We conclude that cell cycle-dependent AAV2 rep expression facilitates cell cycle-dependent AAV2 DNA replication and inhibits HSV-1 DNA replication. This may limit competition for cellular and viral helper factors and, hence, creates a biological niche for either virus to replicate. IMPORTANCE Adeno-associated virus 2 (AAV2) differs from most other viruses, as it requires not only a host cell for replication but also a helper virus such as an adenovirus or a herpesvirus. This situation inevitably leads to competition for cellular resources. AAV2 has been shown to efficiently inhibit the replication of helper viruses. Here we present a new facet of the interaction between AAV2 and one of its helper viruses, herpes simplex virus 1 (HSV-1). We observed that AAV2 rep gene expression is cell cycle dependent and gives rise to distinct time-controlled windows for HSV-1 replication. High Rep protein levels in S/G2 phase support AAV2 replication and inhibit HSV-1 replication. Conversely, low Rep protein levels in G1 phase permit HSV-1 replication but are insufficient for AAV2 replication. This allows both viruses to productively replicate in distinct sets of dividing cells.

An Artificial Intelligence Workflow for Defining Host-Pathogen Interactions

For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capability to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella typhimurium we demonstrate HRMAn’s capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses.

Concepts in Light Microscopy of Viruses

Viruses threaten humans, livestock, and plants, and are difficult to combat. Imaging of viruses by light microscopy is key to uncover the nature of known and emerging viruses in the quest for finding new ways to treat viral disease and deepening the understanding of virus–host interactions. Here, we provide an overview of recent technology for imaging cells and viruses by light microscopy, in particular fluorescence microscopy in static and live-cell modes. The review lays out guidelines for how novel fluorescent chemical probes and proteins can be used in light microscopy to illuminate cells, and how they can be used to study virus infections. We discuss advantages and opportunities of confocal and multi-photon microscopy, selective plane illumination microscopy, and super-resolution microscopy. We emphasize the prevalent concepts in image processing and data analyses, and provide an outlook into label-free digital holographic microscopy for virus research.