Yates JA et al. (1985) Am J Trop Med Hyg "Brugia malayi: vaccination of jirds with 60cobalt-attenuated infective stage larvae protects against homologous challenge."

Yates JA, Higashi GI

[Am J Trop Med Hyg, 1985]

Vaccination of inbred jirds (Meriones unguiculatus) with 60cobalt radiation-attenuated Brugia malayi infective stage larvae (L3) protected against homologous challenge given either subcutaneously (sc) or by the intraperitoneal (ip) route. Groups of jirds vaccinated once sc with 75, 15 Krad L3 showed from 69% to 91% reduction in recovered worms after ip challenge infection compared to infection in non-vaccinated control jirds, while 75% reduction in mean worm burden was seen in jirds receiving sc challenge infection. A single sc vaccination with 75, 10 or 20 Krad L3 produced no protection (10 Krad) and 64% reduction in recovered worms (20 Krad). Therefore the 15 Krad dose appeared to be best. A marked increase in anti-B. malayi antibody in vaccinated jirds was seen (by ELISA) immediately after challenge infection and an immunofluorescence assay showed that L3 incubated in serum from vaccinated jirds were completely and uniformly covered with specific antibody. Eosinophil-rich granulomas containing dead and moribund L3 were recovered from vaccinated jirds. This model of protective immunity in a Brugia-susceptible small rodent may provide a useful system for identification of molecularly defined filarial-protective immunogens.

Alanis-Lobato G et al. (2013) Genomics "Exploitation of genetic interaction network topology for the prediction of epistatic behavior."

Alanis-Lobato G, Cannistraci CV, Ravasi T

[Genomics, 2013]

Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks. We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks. Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab.

Boucher B et al. (2013) Front Genet "Genetic interaction networks: better understand to better predict."

Boucher B, Jenna S

[Front Genet, 2013]

A genetic interaction (GI) between two genes generally indicates that the phenotype of a double mutant differs from what is expected from each individual mutant. In the last decade, genome scale studies of quantitative GIs were completed using mainly synthetic genetic array technology and RNA interference in yeast and Caenorhabditis elegans. These studies raised questions regarding the functional interpretation of GIs, the relationship of genetic and molecular interaction networks, the usefulness of GI networks to infer gene function and co-functionality, the evolutionary conservation of GI, etc. While GIs have been used for decades to dissect signaling pathways in genetic models, their functional interpretations are still not trivial. The existence of a GI between two genes does not necessarily imply that these two genes code for interacting proteins or that the two genes are even expressed in the same cell. In fact, a GI only implies that the two genes share a functional relationship. These two genes may be involved in the same biological process or pathway; or they may also be involved in compensatory pathways with unrelated apparent function. Considering the powerful opportunity to better understand gene function, genetic relationship, robustness and evolution, provided by a genome-wide mapping of GIs, several in silico approaches have been employed to predict GIs in unicellular and multicellular organisms. Most of these methods used weighted data integration. In this article, we will review the later knowledge acquired on GI networks in metazoans by looking more closely into their relationship with pathways, biological processes and molecular complexes but also into their modularity and organization. We will also review the different in silico methods developed to predict GIs and will discuss how the knowledge acquired on GI networks can be used to design predictive tools with higher performances.

Boucher B et al. (2016) PLoS Comput Biol "Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways."

Hallett M, Boucher B, Lee AY, Jenna S

[PLoS Comput Biol, 2016]

A genetic interaction (GI) is defined when the mutation of one gene modifies the phenotypic expression associated with the mutation of a second gene. Genome-wide efforts to map GIs in yeast revealed structural and functional properties of a GI network. This provided insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While a significant conservation of GIs and GI network structure has been reported between distant yeast species, such a conservation is not clear between unicellular and multicellular organisms. Structural and functional characterization of a GI network in these latter organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identify and characterize six distinct classes of GIs by examining a wide-range of structural and functional properties of genes and network, including co-expression, phenotypical manifestations, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functions, gene essentiality and pleiotropy. Our study shows that GI classes link genes within pathways and display distinctive properties, specifically towards PDS. It suggests a model in which pathways are composed of PDS-centric and PDS-independent GIs coordinating molecular machines through two specific classes of GIs involving pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a GI network within pathways of a multicellular organism. It also suggests a model to understand better how GIs control system robustness and evolution.

Zheng X et al. (2015) Nanoscale "Silica-coated bismuth sulfide nanorods as multimodal contrast agents for a non-invasive visualization of the gastrointestinal tract."

Shi J, Yan L, Zhang X, Yang Z, Gao B, Hu Z, Yin W, Bu Y, Tian G, Liu X, Zhao Y, Gu Z, Zheng X

[Nanoscale, 2015]

Non-invasive and real-time imaging of the gastrointestinal (GI) tract is particularly desirable for research and clinical studies of patients with symptoms arising from gastrointestinal diseases. Here, we designed and fabricated silica-coated bismuth sulfide nanorods (Bi2S3@SiO2 NRs) for a non-invasive spatial-temporally imaging of the GI tract. The Bi2S3 NRs were synthesized by a facile solvothermal method and then coated with a SiO2 layer to improve their biocompatibility and stability in the harsh environments of the GI tract, such as the stomach and the small intestine. Due to their strong X-ray- and near infrared-absorption abilities, we demonstrate that, following oral administration in mice, the Bi2S3@SiO2 NRs can be used as a dual-modal contrast agent for the real-time and non-invasive visualization of NRs distribution and the GI tract via both X-ray computed tomography (CT) and photoacoustic tomography (PAT) techniques. Importantly, integration of PAT with CT provides complementary information on anatomical details with high spatial resolution. In addition, we use Caenorhabditis Elegans (C. Elegans) as a simple model organism to investigate the biological response of Bi2S3@SiO2 NRs by oral administration. The results indicate that these NRs can pass through the GI tract of C. Elegans without inducing notable toxicological effects. The above results suggest that Bi2S3@SiO2 NRs pave an alternative way for the fabrication of multi-modal contrast agents which integrate CT and PAT modalities for a direct and non-invasive visualization of the GI tract with low toxicity.

Boucher, Benjamin et al. (2015) International Worm Meeting "From genetic interaction modules to robustness and evolution of a multicellular organism."

Boucher, Benjamin, Hallett, Michael, Lee, Anna, Jenna, Sarah

[International Worm Meeting, 2015]

A genetic interaction (GI) between two genes is defined when the genetic alteration of one gene modifies the phenotypic expression associated with the alteration of a second gene. Genome-wide efforts to map GIs in yeast revealed structural properties of a GI network, providing insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While GIs appear to be highly conserved between distant yeast species, conservation of GIs and GI network structures between unicellular and multicellular organisms is less evident. Characterization of the structure of the GI network in these later organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identified and characterized six distinct classes of GIs by examining a wide range of properties of the underlying genes and network structure including co-expression, phenotypical profiles, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functionalities, gene essentiality and pleiotropy. Our study highlights significant differences between GI relationships with PDS and pathways. We also established that specific classes of GIs define two types of functional modules: PDS-centric and PDS-independent modules with low and high pleiotropic indices, respectively, as well as pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a genetic interaction network in a multicellular organism. It also suggests how the modular structure of this network contributes to system robustness and evolution.

Cipriani, Patricia G. et al. (2013) International Worm Meeting "A genome-wide network of genetic interactions in embryonic development."

Erickson, Katherine, Cipriani, Patricia G., White, Amelia, Piano, Fabio, Gunsalus, Kristin, Kao, Huey-Ling, Reboul, Jerome, Munarriz, Eliana, Lucas, Jessica, Chatterjee, Indrani

[International Worm Meeting, 2013]

The phenotypes manifested by genetic alleles are influenced by the genetic background in which they reside. Yet, we still have a very limited understanding of how genetic interactions (GIs) influence animal development. The goal of our project is to use genome-wide screens to identify all enhancing and suppressing GIs for a set of strains harboring temperature sensitive (ts) mutations in 24 essential embryonic genes. We have completed over three million primary GI assays and secondary screening of putative suppressors, and we have archived in a database all experimental metadata and images, along with quantitative scoring results from an automated phenotypic scoring algorithm we developed (DevStaR). DevStaR combines computer vision and machine learning methods to count different developmental stages in mixed populations of animals. Using these results we have developed a quantitative phenotypic "GI score" based on the multiplicative model of independence: if the effects of perturbing two genes are independent, then their combined effects should not deviate from the product of their individual effects. GI scores for individual experimental replicates correlate positively with semi-quantitative manual estimates of interaction strength. Using manual inspection as a reference, we devised criteria to combine GI scores across replicates that reliably detect suppressing interactions. We then generated final interaction scores that reflect both strength and reproducibility, which we used to define ~800 high-confidence and ~750 intermediate-confidence suppressing interactions. Based on comparisons with manual scoring, we estimate the false discovery rates in these two sets as 2% and 10%, respectively. The resulting GI network provides the first genome-wide map of suppressing genetic interactions for the embryo based on quantitative phenotypic analysis of viability.

Yates JA et al. (1985) Acta Trop "Activation of the alternative complement pathway in normal human serum by Loa loa and Brugia malayi infective stage larvae."

Lowrie RC, Lowichik A, Yates JA, Higashi GI, Eberhard ML, Orihel TC

[Acta Trop, 1985]

Infective stage larvae (L3) of Loa loa and Brugia malayi upon in vitro incubation with normal human serum activated the alternative complement pathway. C3 conversion products were detected on larval cuticles by eosinophil adherence and by immunofluorescence with C3c antiserum. No evidence for cuticle binding of IgG, IgA, IgM, Clq, or C4 was found by immunofluorescence. L3-induced C3 activation was inhibited by 10 mM EDTA but unaffected by 10 mM Mg++-EGTA. Human sera deficient in C2, C4, or C6 incubated with L3 resulted in C3 activation. However, sera treated with zymosan or heated for 1 h, 56 degrees C were unreactive with L3. Immunoelectrophoresis of fresh serum exposed to L3 for 1 h at 37 degrees C showed C3 cleavage products. The results indicate that these nematode L3 activate the alternative complement cascade via cuticular surface components. Larval viability was unaffected by complement activation or by adherence of eosinophils.

Chen D et al. (2019) Cell Rep "Revealing Functional Crosstalk between Distinct Bioprocesses through Reciprocal Functional Tests of Genetically Interacting Genes."

Shi A, Cheng W, Gao J, Fu X, Xia T, Ye Y, Wang S, Wei J, Yang Z, Dong Y, Ma K, Xu W, Chen D, Zhou J, Zhang H, Chen J, Wang H, Grant BD, Wang Y, Yu M, Myers CL

[Cell Rep, 2019]

To systematically explore the genes mediating functional crosstalk between metazoan biological processes, we apply comparative genetic interaction (GI) mapping in Saccharomyces cerevisiae and Caenorhabditis elegans to generate an inter-bioprocess network consisting of 178 C.elegans GIs. The GI network spans six annotated biological processes including aging, intracellular transport, microtubule-based processes, cytokinesis, lipid metabolic processes, and anatomical structure development. By proposing a strategy called "reciprocal functional test" for interacting gene pairs, we discover a group of genes that mediate crosstalk between distinct biological processes. In particular, we identify the ribosomal S6 Kinase/RSKS-1, previously characterized as an mTOR (mechanistic target of rapamycin) effector, as a regulator of DAF-2 endosomal recycling transport, which traces a functional correlation between endocytic recycling and aging processes. Together, our results provide an alternative and effective strategy for identifying genes and pathways that mediate crosstalk between bioprocesses with little prior knowledge.

Keloth T et al. (2019) Diagn Cytopathol "Microfilaria and Strongyloides larva diagnosed in cerebrospinal fluid and ascitic fluid, respectively: Approach to their morphology on cytology."

Toi PC, Gudivada V, Keloth T, Gochhait D, Rajkumari N, Siddaraju N

[Diagn Cytopathol, 2019]

Filariasis and Strongyloidiasis are two endemic parasitic infections seen in any tropical country. Filariasis, commonly caused by Wuchereria bancrofti, Brugia malayi, and Brugia timori is seen often in peripheral blood and lymphoid tissue. But it can be isolated from wide variety of soft tissue sites in the body like soft tissue lumps, breast, thyroid, body fluids. Strongyloides stercoralis, a helminthic infection, usually affects the respiratory and gastrointestinal (GI) tract, and frequently picked up in GI biopsies. However, in cases of hyper infection and patients with altered immunity, it can be isolated from other rare sites like body fluid samples. Accurate morphological Identification and confirmation are important for specific management. We report a case of microfilaria isolated from cerebrospinal fluid and a case of Strongyloides larva isolated from ascitic fluid in clinically unsuspected cases of these two parasitic infestations. We have also added a brief discussion on morphological differences between the two larval forms.