IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform

Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals — a cure and a vaccine – remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes) for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab), determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license), documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

This is a PLOS Computational Biology Software Article

     

BAsE-Seq: a method for obtaining long viral haplotypes from short sequence reads

Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional ‘line lists’ (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.     

Genetic relatedness analysis: modern data and new challenges

Individuals who belong to the same family or the same population are related because of their shared ancestry. Population and quantitative genetics theory is built with parameters that describe relatedness, and the estimation of these parameters from genetic markers enables progress in fields as disparate as plant breeding, human disease gene mapping and forensic science. The large number of multiallelic microsatellite loci and biallelic SNPs that are now available have markedly increased the precision with which relationships can be estimated, although they have also revealed unexpected levels of genomic heterogeneity of relationship measures.     

Cellular mechanisms that determine selective RGS protein regulation of G protein-coupled receptor signaling

Regulators of G protein signaling (RGS proteins) bind directly to activated Galpha subunits to inhibit their signaling. However, recent findings show that RGS proteins selectively regulate signaling by certain G protein-coupled receptors (GPCRs) in cells, irrespective of the coupled G protein. New studies support an emerging model that suggests RGS proteins utilize both direct and indirect mechanisms to form stable functional pairs with preferred GPCRs to selectively modulate the signaling functions of those receptors and linked G proteins. Here, we discuss these findings and their implications for established models of GPCR signaling.     

Silencing of the tobacco pollen pectin methylesterase NtPPME1 results in retarded in vivo pollen tube growth

Sperm delivery in flowering plants requires extensive pollen tube growth through the female sporophytic tissues of the pistil. The apical cell wall emerges as a central player in the control of pollen tube growth, since it provides strength to withstand the internal turgor pressure, while imparting sufficient plasticity to allow cell wall extension through the incorporation of new membrane and wall material. Within this scenario, pectin methylesterases (PMEs; EC 3.1.1.11) emerge as crucial regulators in determining the mechanical properties of pectins, the major component of the apical pollen tube wall. We previously identified NtPPME1, a pollen specific PME from Nicotiana tabacum. Here we show that silencing of NtPPME1 results in a mild but significant decrease of in vivo pollen tube growth while the overall PME activity in pollen is not significantly affected. Although the precise mechanisms responsible for the observed phenotype are not known, it seems likely that the cell must maintain a closely regulated level of PME activity in order to maintain the equilibrium between strength and plasticity in the apical cell wall. A relatively minor disturbance of this equilibrium, as caused by NtPPME1 silencing, compromises pollen tube growth.     

Dynamics of Viral Evolution and Neutralizing Antibody Response after HIV-1 Superinfection

Investigating the incidence and prevalence of HIV-1 superinfection is challenging due to the complex dynamics of two infecting strains. The superinfecting strain can replace the initial strain, be transiently expressed, or persist along with the initial strain in distinct or in recombined forms. Various selective pressures influence these alternative scenarios in different HIV-1 coding regions. We hypothesized that the potency of the neutralizing antibody (NAb) response to autologous viruses would modulate viral dynamics in env following superinfection in a limited set of superinfection cases. HIV-1 env pyrosequencing data were generated from blood plasma collected from 7 individuals with evidence of superinfection. Viral variants within each patient were screened for recombination, and viral dynamics were evaluated using nucleotide diversity. NAb responses to autologous viruses were evaluated before and after superinfection. In 4 individuals, the superinfecting strain replaced the original strain. In 2 individuals, both initial and superinfecting strains continued to cocirculate. In the final individual, the surviving lineage was the product of interstrain recombination. NAb responses to autologous viruses that were detected within the first 2 years of HIV-1 infection were weak or absent for 6 of the 7 recently infected individuals at the time of and shortly following superinfection. These 6 individuals had detectable on-going viral replication of distinct superinfecting virus in the env coding region. In the remaining case, there was an early and strong autologous NAb response, which was associated with extensive recombination in env between initial and superinfecting strains. This extensive recombination made superinfection more difficult to identify and may explain why the detection of superinfection has typically been associated with low autologous NAb titers.     

G protein-coupled receptors and resistance to inhibitors of cholinesterase-8A (Ric-8A) both regulate the regulator of g protein signaling 14 RGS14·Gαi1 complex in live cells

Regulator of G protein Signaling 14 (RGS14) is a multifunctional scaffolding protein that integrates both conventional and unconventional G protein signaling pathways. Like other RGS (regulator of G protein signaling) proteins, RGS14 acts as a GTPase accelerating protein to terminate conventional Gα(i/o) signaling. However, unlike other RGS proteins, RGS14 also contains a G protein regulatory/GoLoco motif that specifically binds Gα(i1/3)-GDP in cells and in vitro. The non-receptor guanine nucleotide exchange factor Ric-8A can bind and act on the RGS14·Gα(i1)-GDP complex to play a role in unconventional G protein signaling independent of G protein-coupled receptors (GPCRs). Here we demonstrate that RGS14 forms a Gα(i/o)-dependent complex with a G(i)-linked GPCR and that this complex is regulated by receptor agonist and Ric-8A (resistance to inhibitors of cholinesterase-8A). Using live cell bioluminescence resonance energy transfer, we show that RGS14 functionally associates with the α(2A)-adrenergic receptor (α(2A)-AR) in a Gα(i/o)-dependent manner. This interaction is markedly disrupted after receptor stimulation by the specific agonist UK14304, suggesting complex dissociation or rearrangement. Agonist-mediated dissociation of the RGS14·α(2A)-AR complex occurs in the presence of Gα(i/o) but not Gα(s) or Gα(q). Unexpectedly, RGS14 does not dissociate from Gα(i1) in the presence of stimulated α(2A)-AR, suggesting preservation of RGS14·Gα(i1) complexes after receptor activation. However, Ric-8A facilitates dissociation of both the RGS14·Gα(i1) complex and the Gα(i1)-dependent RGS14·α(2A)-AR complex after receptor activation. Together, these findings indicate that RGS14 can form complexes with GPCRs in cells that are dependent on Gα(i/o) and that these RGS14·Gα(i1)·GPCR complexes may be substrates for other signaling partners such as Ric-8A.