Structural studies demonstrating a bacteriophage-like replication cycle of the eukaryote-infecting \u3ci\u3eParamecium bursaria\u3c/i\u3e chlorella virus-1

A fundamental stage in viral infection is the internalization of viral genomes in host cells. Although extensively studied, the mechanisms and factors responsible for the genome internalization process remain poorly understood. Here we report our observations, derived from diverse imaging methods on genome internalization of the large dsDNA Paramecium bursaria chlorella virus-1 (PBCV-1). Our studies reveal that early infection stages of this eukaryotic- infecting virus occurs by a bacteriophage-like pathway, whereby PBCV-1 generates a hole in the host cell wall and ejects its dsDNA genome in a linear, base-pair-by-base-pair process, through a membrane tunnel generated by the fusion of the virus internal membrane with the host membrane. Furthermore, our results imply that PBCV-1 DNA condensation that occurs shortly after infection probably plays a role in genome internalization, as hypothesized for the infection of some bacteriophages. The subsequent perforation of the host photosynthetic membranes presumably enables trafficking of viral genomes towards host nuclei. Previous studies established that at late infection stages PBCV-1 generates cytoplasmic organelles, termed viral factories, where viral assembly takes place, a feature characteristic of many large dsDNA viruses that infect eukaryotic organisms. PBCV-1 thus appears to combine a bacteriophage-like mechanism during early infection stages with a eukaryotic-like infection pathway in its late replication cycle. Author summary -- Although extensively studied, the mechanisms responsible for internalization of viral genomes into their host cells remain unclear. A particularly interesting case of genome release and internalization is provided by the large Paramecium bursaria chlorella virus-1 (PBCV-1), which infects unicellular eukaryotic photosynthetic chlorella cells. In order to release its long dsDNA genome and to enable its translocation to the host nucleus, PBCV-1 must overcome multiple hurdles, including a thick host cell wall and multilayered chloroplast membranes that surround the host cytoplasm. Our observations indicate that these obstacles are dealt with perforations of the host wall, the host cellular membrane, and the host photosynthetic membranes by viral-encoded proteins. Furthermore, our results highlight a bacteriophage-like nature of early PBCV-1 infection stages, thus implying that this virus uniquely combines bacteriophage-like and eukaryotic-like pathways to accomplish its replication cycle

Virus–host interactions: insights from the replication cycle of the large \u3ci\u3eParamecium bursaria\u3c/i\u3e chlorella virus

The increasing interest in cytoplasmic factories generated by eukaryotic-infecting viruses stems from the realization that these highly ordered assemblies may contribute fundamental novel insights to the functional significance of order in cellular biology. Here, we report the formation process and structural features of the cytoplasmic factories of the large dsDNA virus Paramecium bursaria chlorella virus 1 (PBCV-1). By combining diverse imaging techniques, including scanning transmission electron microscopy tomography and focused ion beam technologies, we show that the architecture and mode of formation of PBCV-1 factories are significantly different from those generated by their evolutionary relatives Vaccinia and Mimivirus. Specifically, PBCV-1 factories consist of a network of single membrane bilayers acting as capsid templates in the central region, and viral genomes spread throughout the host cytoplasm but excluded from the membranecontaining sites. In sharp contrast, factories generated by Mimivirus have viral genomes in their core, with membrane biogenesis region located at their periphery. Yet, all viral factories appear to share structural features that are essential for their function. In addition, our studies support the notion that PBCV-1 infection, which was recently reported to result in significant pathological outcomes in humans andmice, proceeds througha bacteriophage -like infection pathway

Beyond Hebb: Exclusive-OR and Biological Learning

A learning algorithm for multilayer neural networks based on biologically plausible mechanisms is studied. Motivated by findings in experimental neurobiology, we consider synaptic averaging in the induction of plasticity changes, which happen on a slower time scale than firing dynamics. This mechanism is shown to enable learning of the exclusive-OR (XOR) problem without the aid of error back-propagation, as well as to increase robustness of learning in the presence of noise.Comment: 4 pages RevTeX, 2 figures PostScript, revised versio

Identification of a Chlorovirus PBCV-1 Protein Involved in Degrading the Host Cell Wall during Virus Infection

Chloroviruses are unusual among viruses infecting eukaryotic organisms in that they must, like bacteriophages, penetrate a rigid cell wall to initiate infection. Chlorovirus PBCV-1 infects its host, Chlorella variabilis NC64A by specifically binding to and degrading the cell wall of the host at the point of contact by a virus-packaged enzyme(s). However, PBCV-1 does not use any of the five previously characterized virus-encoded polysaccharide degrading enzymes to digest the Chlorella host cell wall during virus entry because none of the enzymes are packaged in the virion. A search for another PBCV-1-encoded and virion-associated protein identified protein A561L. The fourth domain of A561L is a 242 amino acid C-terminal domain, named A561LD4, with cell wall degrading activity. An A561LD4 homolog was present in all 52 genomically sequenced chloroviruses, infecting four different algal hosts. A561LD4 degraded the cell walls of all four chlorovirus hosts, as well as several non-host Chlorella spp. Thus, A561LD4 was not cell-type specific. Finally, we discovered that exposure of highly purified PBCV-1 virions to A561LD4 increased the specific infectivity of PBCV-1 from about 25–30% of the particles forming plaques to almost 50%. We attribute this increase to removal of residual host receptor that attached to newly replicated viruses in the cell lysates

Metaheuristic design of feedforward neural networks: a review of two decades of research

Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest among the researchers and practitioners of multiple disciplines. The FNN optimization is often viewed from the various perspectives: the optimization of weights, network architecture, activation nodes, learning parameters, learning environment, etc. Researchers adopted such different viewpoints mainly to improve the FNN's generalization ability. The gradient-descent algorithm such as backpropagation has been widely applied to optimize the FNNs. Its success is evident from the FNN's application to numerous real-world problems. However, due to the limitations of the gradient-based optimization methods, the metaheuristic algorithms including the evolutionary algorithms, swarm intelligence, etc., are still being widely explored by the researchers aiming to obtain generalized FNN for a given problem. This article attempts to summarize a broad spectrum of FNN optimization methodologies including conventional and metaheuristic approaches. This article also tries to connect various research directions emerged out of the FNN optimization practices, such as evolving neural network (NN), cooperative coevolution NN, complex-valued NN, deep learning, extreme learning machine, quantum NN, etc. Additionally, it provides interesting research challenges for future research to cope-up with the present information processing era