Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

HIV-1 cell entry commonly uses, in addition to CD4, one of the chemokine receptors CCR5 or CXCR4 as coreceptor. Knowledge of coreceptor usage is critical for monitoring disease progression as well as for supporting therapy with the novel drug class of coreceptor antagonists. Predictive methods for inferring coreceptor usage based on the third hypervariable (V3) loop region of the viral gene coding for the envelope protein gp120 can provide us with these monitoring facilities while avoiding expensive phenotypic tests. All simple heuristics (such as the 11/25 rule) as well as statistical learning methods proposed to date predict coreceptor usage based on sequence features of the V3 loop exclusively. Here, we show, based on a recently resolved structure of gp120 with an untruncated V3 loop, that using structural information on the V3 loop in combination with sequence features of V3 variants improves prediction of coreceptor usage. In particular, we propose a distance-based descriptor of the spatial arrangement of physicochemical properties that increases discriminative performance. For a fixed specificity of 0.95, a sensitivity of 0.77 was achieved, improving further to 0.80 when combined with a sequence-based representation using amino acid indicators. This compares favorably with the sensitivities of 0.62 for the traditional 11/25 rule and 0.73 for a prediction based on sequence information as input to a support vector machine and constitutes a statistically significant improvement. A detailed analysis and interpretation of structural features important for classification shows the relevance of several specific hydrogen-bond donor sites and aliphatic side chains to coreceptor specificity towards CCR5 or CXCR4. Furthermore, an analysis of side chain orientation of the specificity-determining residues suggests a major role of one side of the V3 loop in the selection of the coreceptor. The proposed method constitutes the first approach to an improved prediction of coreceptor usage based on an original integration of structural bioinformatics methods with statistical learning

Docking Analysis and Resistance Evaluation of Clinically Relevant Mutations Associated with the HIV-1 Non-nucleoside Reverse Transcriptase Inhibitors Nevirapine, Efavirenz and Etravirine

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There is inadequate evidence to support the division of the genus Borrelia

There are surely scientific, genetic or ecological 60 arguments which show that differences exist between the relapsing fever (RF) spirochaetes and the Lyme borreliosis (LB) group of spirochaetes, both of which belong to the genus Borrelia. In a recent publication, Adeolu and Gupta (Adeolu & 63 Gupta, 2014) proposed dividing the genus Borrelia into two genera on the basis of genetic differences revealed by comparative genomics. The new genus name for the LB group of spirochaetes, Borreliella, has subsequently been entered in GenBank for some species of the group and in a validation list (List of new names and new combinations previously effectively, but not validly, published) (Oren & Garrity, 2015). However, rapidly expanding scientific knowledge and considerable conflicting evidence combined with the adverse consequences of splitting the genus Borrelia make such a drastic step somewhat premature. In our opinion, the basis of this division rests on preliminary evidence and should be rescinded

Cyanobacterial lipopolysaccharides and human health – a review

Cyanobacterial lipopolysaccharide/s (LPS) are frequently cited in the cyanobacteria literature as toxins responsible for a variety of heath effects in humans, from skin rashes to gastrointestinal, respiratory and allergic reactions. The attribution of toxic properties to cyanobacterial LPS dates from the 1970s, when it was thought that lipid A, the toxic moiety of LPS, was structurally and functionally conserved across all Gram-negative bacteria. However, more recent research has shown that this is not the case, and lipid A structures are now known to be very different, expressing properties ranging from LPS agonists, through weak endotoxicity to LPS antagonists. Although cyanobacterial LPS is widely cited as a putative toxin, most of the small number of formal research reports describe cyanobacterial LPS as weakly toxic compared to LPS from the Enterobacteriaceae. We systematically reviewed the literature on cyanobacterial LPS, and also examined the much lager body of literature relating to heterotrophic bacterial LPS and the atypical lipid A structures of some photosynthetic bacteria. While the literature on the biological activity of heterotrophic bacterial LPS is overwhelmingly large and therefore difficult to review for the purposes of exclusion, we were unable to find a convincing body of evidence to suggest that heterotrophic bacterial LPS, in the absence of other virulence factors, is responsible for acute gastrointestinal, dermatological or allergic reactions via natural exposure routes in humans. There is a danger that initial speculation about cyanobacterial LPS may evolve into orthodoxy without basis in research findings. No cyanobacterial lipid A structures have been described and published to date, so a recommendation is made that cyanobacteriologists should not continue to attribute such a diverse range of clinical symptoms to cyanobacterial LPS without research confirmation

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Model-based Anti-HIV Therapy

Modern combination drug therapy has substantially improved the clinical management of HIV-1 infection. Still, the emergence of drug-resistant variants eventually leads to therapy failure in most patients. The selection of an optimal follow-up regimen is complicated by an ever-increasing range of possible drug combinations. In this thesis, we present foundations for rational, model-based treatment strategies. Firstly, we study viral evolution. In a simulation study, we establish a general link between the shape of a fitness landscape and population dynamics, using an idealized population undergoing mutation, recombination and selection at three biallelic loci as an example. Using techniques from survival analysis, a model of mutation dynamics in the absence of drug is proposed. Differently from mutation accumulation, mutations are found to disappear independently from each other, but with individual survival probabilities. A Fisher kernel for mixtures of mutagenetic trees is derived, quantifying the similarity of evolutionary escape from drug pressure between two viral sequence samples. Kernel-based prediction of drug resistance leads to significant improvements over an evolution-agnostic approach

Vaccination strategies to enhance immunity in neonates

Neonates are particularly susceptible to infection. This vulnerability occurs despite their responsiveness to most vaccines. However, current vaccines do not target the pathogens responsible for most of the severe neonatal infections, and the time it takes to induce protective pathogen-specific immunity after vaccination limits protection in the first days to weeks of life. Alternative strategies include using vaccines to broadly stimulate neonatal immunity in a pathogen-agnostic fashion or vaccinating women during pregnancy to induce protective antibodies that are vertically transferred to offspring within their window of vulnerability. Protection may be further improved by integrating these approaches, namely vaccinating the neonate under the cover of vertically transferred maternal immunity. The rationale for and knowledge gaps related to each of these alternatives are discussed.SCOPUS: re.jinfo:eu-repo/semantics/publishe

Abstract

Starting with the work of Jaakkola and Haussler, a variety of approaches have been proposed for coupling domain-specific generative models with statistical learning methods. The link is established by a kernel function which provides a similarity measure based inherently on the underlying model. In computational biology, the full promise of this framework has rarely ever been exploited, as most kernels are derived from very generic models, such as sequence profiles or hidden Markov models. Here, we introduce the MTreeMix kernel, which is based on a generative model tailored to the underlying biological mechanism. Specifically, the kernel quantifies the similarity of evolutionary escape from antiviral drug pressure between two viral sequence samples. We compare this novel kernel to a standard, evolution-agnostic amino acid encoding in the prediction of HIV drug resistance from genotype, using support vector regression. The results show significant improvements in predictive performance across 17 anti-HIV drugs. Thus, in our study, the generative-discriminative paradigm is key to bridging the gap between population genetic modeling and clinical decision making.