Antibody profiling and predictive modeling discriminate between Kaposi sarcoma and asymptomatic KSHV infection

Protein-level immunodominance patterns against Kaposi sarcoma-associated herpesvirus (KSHV), the aetiologic agent of Kaposi sarcoma (KS), have been revealed from serological probing of whole protein arrays, however, the epitopes that underlie these patterns have not been defined. We recently demonstrated the utility of phage display in high-resolution linear epitope mapping of the KSHV latency-associated nuclear antigen (LANA/ORF73). Here, a VirScan phage immunoprecipitation and sequencing approach, employing a library of 1,988 KSHV proteome-derived peptides, was used to quantify the breadth and magnitude of responses of 59 sub-Saharan African KS patients and 22 KSHV-infected asymptomatic individuals (ASY), and ultimately to support an application of machine-learning-based predictive modeling using the peptide-level responses. Comparing anti-KSHV antibody repertoire revealed that magnitude, not breadth, increased in KS. The most targeted epitopes in both KS and ASY were in the immunodominant proteins, notably, K8.129−56 and ORF65140-168, in addition to LANA. Finally, using unbiased machine-learning-based predictive models, reactivity to a subset of 25 discriminative peptides was demonstrated to successfully classify KS patients from asymptomatic individuals. Our study provides the highest resolution mapping of antigenicity across the entire KSHV proteome to date, which is vital to discern mechanisms of viral pathogenesis, to define prognostic biomarkers, and to design effective vaccine and therapeutic strategies. Future studies will investigate the diagnostic, prognostic, and therapeutic potential of the 25 discriminative peptides

Genetic Transformation in Citrus

Citrus is one of the world’s important fruit crops. Recently, citrus molecular genetics and biotechnology work have been accelerated in the world. Genetic transformation, a biotechnological tool, allows the release of improved cultivars with desirable characteristics in a shorter period of time and therefore may be useful in citrus breeding programs. Citrus transformation has now been achieved in a number of laboratories by various methods. Agrobacterium tumefaciens is used mainly in citrus transformation studies. Particle bombardment, electroporation, A. rhizogenes, and a new method called RNA interference are used in citrus transformation studies in addition to A. tumefaciens. In this review, we illustrate how different gene transformation methods can be employed in different citrus species

Longitudinal Variations in Antibody Responses against SARS-CoV-2 Spike Epitopes upon Serial Vaccinations

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) impacted healthcare, the workforce, and worldwide socioeconomics. Multi-dose mono- or bivalent mRNA vaccine regimens have shown high efficacy in protection against SARSCoV- 2 and its emerging variants with varying degrees of efficacy. Amino acid changes, primarily in the receptor-binding domain (RBD), result in selection for viral infectivity, disease severity, and immune evasion. Therefore, many studies have centered around neutralizing antibodies that target the RBD and their generation achieved through infection or vaccination. Here, we conducted a unique longitudinal study, analyzing the effects of a three-dose mRNA vaccine regimen exclusively using the monovalent BNT162b2 (Pfizer/BioNTech) vaccine, systematically administered to nine previously uninfected (naïve) individuals. We compare changes in humoral antibody responses across the entire SARS-CoV-2 spike glycoprotein (S) using a high-throughput phage display technique (VirScan). Our data demonstrate that two doses of vaccination alone can achieve the broadest and highest magnitudes of anti-S response. Moreover, we present evidence of novel highly boosted non-RBD epitopes that strongly correlate with neutralization and recapitulate independent findings. These vaccine-boosted epitopes could facilitate multi-valent vaccine development and drug discovery

Viral Epitope Scanning Reveals Correlation between Seasonal HCoVs and SARS-CoV-2 Antibody Responses among Cancer and Non-Cancer Patients

Seasonal coronaviruses (HCoVs) are known to contribute to cross-reactive antibody (Ab) responses against SARS-CoV-2. While these responses are predictable due to the high homology between SARS-CoV-2 and other CoVs, the impact of these responses on susceptibility to SARS-CoV-2 infection in cancer patients is unclear. To investigate the influence of prior HCoV infection on anti- SARS-CoV-2 Ab responses among COVID-19 asymptomatic individuals with cancer and controls without cancers, we utilized the VirScan technology in which phage immunoprecipitation and sequencing (PhIP-seq) of longitudinal plasma samples was performed to investigate high-resolution (i.e., epitope level) humoral CoV responses. Despite testing positive for anti-SARS-CoV-2 Ab in the plasma, a majority of the participants were asymptomatic for COVID-19 with no prior history of COVID-19 diagnosis. Although the magnitudes of the anti-SARS-CoV-2 Ab responses were lower in individuals with Kaposi sarcoma (KS) compared to non-KS cancer individuals and those without cancer, the HCoV Ab repertoire was similar between individuals with and without cancer independent of age, sex, HIV status, and chemotherapy. The magnitudes of the anti-spike HCoV responses showed a strong positive association with those of the anti-SARS-CoV-2 spike in cancer patients, and only a weak association in non-cancer patients, suggesting that prior infection with HCoVs might play a role in limiting SARS-CoV-2 infection and COVID-19 disease severity

Sequential, Spatial and Functional Disposition of CpG Islands

In this dissertation, we characterize and analyze CpG islands (CGIs) using Bioinformatics tools and techniques that lead to an understanding of their biological functions and role in epigenetics and disease mechanisms. We demonstrate the spatial significance of CGIs within the human genome and comparatively, across multiple mammalian genomes. We discuss the spatial characterization of CGIs and introduce a tool (dbCGI), which annotates CGIs based on their colocalization with regulatory regions of genes for multiple species and CGI detection algorithms. We characterize such CGIs under four classes: promoter (pCGI), intragenic (iCGI), gene-terminal (tCGI), and intergenic CGI. Utilizing dbCGI, we present a comparative analysis of CGIs in the human and mouse genomes. We also perform a comprehensive analysis of the spatial CGI frequency distributions across hundreds of biological pathways and gene categories in five mammalian genomes. We assess the level of evolutionary signature conservation of CGI frequencies among the species and highlight pathways or categories governing the same frequency distribution in the majority of the organisms. In the human genome, we analyze spatial CGI distribution patterns across well-studied gene families and perform an enrichment analysis to reveal important distinguishing patterns. We propose an unbiased predictive model that uses a combination of sequential features to identify a genome-wide methylation signature to assess the methylation propensity of CGIs. A successful application of such a signature results in improved accuracies over previous studies and reveals features that contribute to this susceptibility, increasing our understanding of the mechanisms of CGI hypermethylation. Based on this predictive model, we present a proof of concept, which demonstrates the impact of short genetic variations (SGVs) on the methylation propensity of a CGI. Identifying such variants would explain why certain CGIs show a predisposition to methylation in cancer, and advance personalized preventative therapies

Sequential, Spatial and Functional Disposition of CpG Islands

In this dissertation, we characterize and analyze CpG islands (CGIs) using Bioinformatics tools and techniques that lead to an understanding of their biological functions and role in epigenetics and disease mechanisms. We demonstrate the spatial significance of CGIs within the human genome and comparatively, across multiple mammalian genomes. We discuss the spatial characterization of CGIs and introduce a tool (dbCGI), which annotates CGIs based on their colocalization with regulatory regions of genes for multiple species and CGI detection algorithms. We characterize such CGIs under four classes: promoter (pCGI), intragenic (iCGI), gene-terminal (tCGI), and intergenic CGI. Utilizing dbCGI, we present a comparative analysis of CGIs in the human and mouse genomes. We also perform a comprehensive analysis of the spatial CGI frequency distributions across hundreds of biological pathways and gene categories in five mammalian genomes. We assess the level of evolutionary signature conservation of CGI frequencies among the species and highlight pathways or categories governing the same frequency distribution in the majority of the organisms. In the human genome, we analyze spatial CGI distribution patterns across well-studied gene families and perform an enrichment analysis to reveal important distinguishing patterns. We propose an unbiased predictive model that uses a combination of sequential features to identify a genome-wide methylation signature to assess the methylation propensity of CGIs. A successful application of such a signature results in improved accuracies over previous studies and reveals features that contribute to this susceptibility, increasing our understanding of the mechanisms of CGI hypermethylation. Based on this predictive model, we present a proof of concept, which demonstrates the impact of short genetic variations (SGVs) on the methylation propensity of a CGI. Identifying such variants would explain why certain CGIs show a predisposition to methylation in cancer, and advance personalized preventative therapies

Bioinformatics Approaches to Single-Cell Analysis in Developmental Biology

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single-cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement, and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics, and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations, and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering, and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues, and present future prospects for application of single-cell analyses to developmental biology

Influence of dietary protein and sex on walking ability and bone parameters of broilers

WOS: 000073941200014PubMed ID: 96498801. The study was conducted to investigate the effect of dietary protein on the walking ability and bone parameters of broilers reared under summer temperatures which ranged from 26 degrees to 32 degrees C(+/- 2 degrees C). 2. Three different dietary protein combinations were used. The diets (per kg) were: low protein with 205 g crude protein and 12.94 MJ ME, 184 g crude protein and 12.75 MJ ME; medium protein with 219 g crude protein and 12.99 MJ ME, 201 g crude protein and 12.87 MJ ME; and high protein with 238 g crude protein and 12.99 MJ ME, 216 g crude protein and 12.96 MJ ME from 0 to 4 and 4 to 7 weeks of age, respectively. Body weights of birds were recorded and birds' walking ability (gait scoring) were scored for each bird, according to 3 categories (completely normal to immobile, at 4 and 7 weeks). Tibia parameters and tibia plateau angles were also determined at 7 weeks. 3. Birds fed on the low protein were lighter than those fed on the medium or high protein diets. At 7 weeks, birds with poor walking ability weighed 149 g less than birds with no walking difficulty. 4. Bone parameters were not affected by dietary protein, sex or gait score. There was a significantly positive correlation between bone strength and radiographic density. Bone strength was also significantly correlated with bone weight and length

Ticks and Fleas Infestation on East Hedgehogs (Erinaceus concolor) in Van Province, Eastern Region of Turkey

WOS: 000371142900005PubMed ID: 27047971Background: Ixodid ticks (Acari: Ixodidae) and fleas (Siphonaptera) are the major vectors of pathogens threatening animals and human healths. The aim of our study was to detect the infestation rates of East Hedgehogs (Erinaceus concolor) with ticks and fleas in Van Province, eastern region of Turkey. Methods: We examined fleas and ticks infestation patterns in 21 hedgehogs, collected from three suburbs with the greater of number gardens. In order to estimate flea and tick infestation of hedgehogs, we immobilized the ectoparasites by treatment the body with a insecticide trichlorphon (Neguvon (R)-Bayer). Results: On the hedgehogs, 60 ixodid ticks and 125 fleas were detected. All of the ixodid ticks were Rhipicephalus turanicus and all of the fleas were Archaeopsylla erinacei. Infestation rate for ticks and fleas was detected 66.66 % and 100 %, respectively. Conclusion: We detected ticks (R. turanicus) and fleas (A. erinacei) in hedgehogs at fairly high rates. Since many ticks and fleas species may harbor on hedgehogs and transmit some tick-borne and flea-borne patogens, this results are the important in terms of veterinary and public health