Correcting the Bias of Empirical Frequency Parameter Estimators in Codon Models

Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a “corrected” empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators

Generalized Rosenfeld scalings for tracer diffusivities in not-so-simple fluids: Mixtures and soft particles

Rosenfeld [Phys. Rev. A 15, 2545 (1977)] noticed that casting transport coefficients of simple monatomic, equilibrium fluids in specific dimensionless forms makes them approximately single-valued functions of excess entropy. This has predictive value because, while the transport coefficients of dense fluids are difficult to estimate from first principles, excess entropy can often be accurately predicted from liquid-state theory. Here, we use molecular simulations to investigate whether Rosenfeld's observation is a special case of a more general scaling law relating mobility of particles in mixtures to excess entropy. Specifically, we study tracer diffusivities, static structure, and thermodynamic properties of a variety of one- and two-component model fluid systems with either additive or non-additive interactions of the hard-sphere or Gaussian-core form. The results of the simulations demonstrate that the effects of mixture concentration and composition, particle-size asymmetry and additivity, and strength of the interparticle interactions in these fluids are consistent with an empirical scaling law relating the excess entropy to a new dimensionless (generalized Rosenfeld) form of tracer diffusivity, which we introduce here. The dimensionless form of the tracer diffusivity follows from knowledge of the intermolecular potential and the transport / thermodynamic behavior of fluids in the dilute limit. The generalized Rosenfeld scaling requires less information, and provides more accurate predictions, than either Enskog theory or scalings based on the pair-correlation contribution to the excess entropy. As we show, however, it also suffers from some limitations, especially for systems that exhibit significant decoupling of individual component tracer diffusivities.Comment: 15 pages, 10 figure

Mechanical Testing of 3D Printed Prosthetics

The Rapid Orthotics for CURE Kenya team as a whole aims to empower the orthopedic technicians in the CURE Kenya hospital by creating, optimizing, and testing 3D printed prosthetics and orthotics. Our team started in 2016 by creating a 3D printing process for below the knee prosthetic sockets. Since then, we had adapted to the hospital\u27s needs over the years, expanding the capabilities of the system itself. Presently, a section of our team has worked specifically with these leg sockets to ensure the safety and functionality for patients. They have done testing to make sure the sockets are strong enough and to make sure the silicone liners are safe for use in developing countries. In addition to safety testing, over the years we have created ankle-foot orthotics and prosthetic hands. The design part of our team works to create new 3D printed devices to help our clients reach more patients. By 2024 we hope to fully integrate our expanded system in the orthopedic workshop in Kijabe, Kenya.https://mosaic.messiah.edu/engr2020/1018/thumbnail.jp

Genetic attributes of cerebrospinal fluid-derived HIV-1 env

HIV-1 often invades the CNS during primary infection, eventually resulting in neurological disorders in up to 50% of untreated patients. The CNS is a distinct viral reservoir, differing from peripheral tissues in immunological surveillance, target cell characteristics and antiretroviral penetration. Neurotropic HIV-1 likely develops distinct genotypic characteristics in response to this unique selective environment. We sought to catalogue the genetic features of CNS-derived HIV-1 by analysing 456 clonal RNA sequences of the C2-V3 env subregion generated from CSF and plasma of 18 chronically infected individuals. Neuropsychological performance of all subjects was evaluated and summarized as a global deficit score. A battery of phylogenetic, statistical and machine learning tools was applied to these data to identify genetic features associated with HIV-1 neurotropism and neurovirulence. Eleven of 18 individuals exhibited significant viral compartmentalization between blood and CSF (P < 0.01, Slatkin-Maddison test). A CSF-specific genetic signature was identified, comprising positions 9, 13 and 19 of the V3 loop. The residue at position 5 of the V3 loop was highly correlated with neurocognitive deficit (P < 0.0025, Fisher's exact test). Antibody-mediated HIV-1 neutralizing activity was significantly reduced in CSF with respect to autologous blood plasma (P < 0.042, Student's t-test). Accordingly, CSF-derived sequences exhibited constrained diversity and contained fewer glycosylated and positively selected sites. Our results suggest that there are several genetic features that distinguish CSF- and plasma-derived HIV-1 populations, probably reflecting altered cellular entry requirements and decreased immune pressure in the CNS. Furthermore, neurological impairment may be influenced by mutations within the viral V3 loop sequenc

Non-Negative Matrix Factorization for Learning Alignment-Specific Models of Protein Evolution

Models of protein evolution currently come in two flavors: generalist and specialist. Generalist models (e.g. PAM, JTT, WAG) adopt a one-size-fits-all approach, where a single model is estimated from a number of different protein alignments. Specialist models (e.g. mtREV, rtREV, HIVbetween) can be estimated when a large quantity of data are available for a single organism or gene, and are intended for use on that organism or gene only. Unsurprisingly, specialist models outperform generalist models, but in most instances there simply are not enough data available to estimate them. We propose a method for estimating alignment-specific models of protein evolution in which the complexity of the model is adapted to suit the richness of the data. Our method uses non-negative matrix factorization (NNMF) to learn a set of basis matrices from a general dataset containing a large number of alignments of different proteins, thus capturing the dimensions of important variation. It then learns a set of weights that are specific to the organism or gene of interest and for which only a smaller dataset is available. Thus the alignment-specific model is obtained as a weighted sum of the basis matrices. Having been constrained to vary along only as many dimensions as the data justify, the model has far fewer parameters than would be required to estimate a specialist model. We show that our NNMF procedure produces models that outperform existing methods on all but one of 50 test alignments. The basis matrices we obtain confirm the expectation that amino acid properties tend to be conserved, and allow us to quantify, on specific alignments, how the strength of conservation varies across different properties. We also apply our new models to phylogeny inference and show that the resulting phylogenies are different from, and have improved likelihood over, those inferred under standard models

Convergent Evolution of Escape from Hepaciviral Antagonism in Primates

Escape from antagonism by hepatitis C and related viruses has repeatedly evolved in antiviral factor MAVS via convergent evolution, revealing an ancient history of previous viral encounters in primates

Daily Sampling of an HIV-1 Patient with Slowly Progressing Disease Displays Persistence of Multiple env Subpopulations Consistent with Neutrality

The molecular evolution of HIV-1 is characterized by frequent substitutions, indels and recombination events. In addition, a HIV-1 population may adapt through frequency changes of its variants. To reveal such population dynamics we analyzed HIV-1 subpopulation frequencies in an untreated patient with stable, low plasma HIV-1 RNA levels and close to normal CD4+ T-cell levels. The patient was intensively sampled during a 32-day period as well as approximately 1.5 years before and after this period (days −664, 1, 2, 3, 11, 18, 25, 32 and 522). 77 sequences of HIV-1 env (approximately 3100 nucleotides) were obtained from plasma by limiting dilution with 7–11 sequences per time point, except day −664. Phylogenetic analysis using maximum likelihood methods showed that the sequences clustered in six distinct subpopulations. We devised a method that took into account the relatively coarse sampling of the population. Data from days 1 through 32 were consistent with constant within-patient subpopulation frequencies. However, over longer time periods, i.e. between days 1…32 and 522, there were significant changes in subpopulation frequencies, which were consistent with evolutionarily neutral fluctuations. We found no clear signal of natural selection within the subpopulations over the study period, but positive selection was evident on the long branches that connected the subpopulations, which corresponds to >3 years as the subpopulations already were established when we started the study. Thus, selective forces may have been involved when the subpopulations were established. Genetic drift within subpopulations caused by de novo substitutions could be resolved after approximately one month. Overall, we conclude that subpopulation frequencies within this patient changed significantly over a time period of 1.5 years, but that this does not imply directional or balancing selection. We show that the short-term evolution we study here is likely representative for many patients of slow and normal disease progression

Riverine sustainment 2012

Student Integrated ProjectIncludes supplementary materialThis technical report analyzed the Navy's proposed Riverine Force (RF) structure and capabilities for 2012. The Riverine Sustainment 2012 Team (RST) examined the cost and performance of systems of systems which increased RF sustainment in logistically barren environments. RF sustainment was decomposed into its functional areas of supply, repair, and force protection. The functional and physical architectures were developed in parallel and were used to construct an operational architecture for the RF. The RST used mathematical, agent-based and queuing models to analyze various supply, repair and force protection system alternatives. Extraction of modeling data revealed several key insights. Waterborne heavy lift connectors such as the LCU-2000 are vital in the re-supply of the RF when it is operating up river in a non-permissive environment. Airborne heavy lift connectors such as the MV-22 were ineffective and dominated by the waterborne variants in the same environment. Increase in manpower and facilities did appreciable add to the operational availability of the RF. Mean supply response time was the biggest factor effecting operational availability and should be kept below 24 hours to maintain operational availability rates above 80%. Current mortar defenses proposed by the RF are insufficient.N

Evolutionary Analysis of Inter-Farm Transmission Dynamics in a Highly Pathogenic Avian Influenza Epidemic

Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8–13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics

Mutation of a Single Residue Renders Human Tetherin Resistant to HIV-1 Vpu-Mediated Depletion

The recently identified restriction factor tetherin/BST-2/CD317 is an interferon-inducible trans-membrane protein that restricts HIV-1 particle release in the absence of the HIV-1 countermeasure viral protein U (Vpu). It is known that Tantalus monkey CV1 cells can be rendered non-permissive to HIV-1 release upon stimulation with type 1 interferon, despite the presence of Vpu, suggesting species-specific sensitivity of tetherin proteins to viral countermeasures such as Vpu. Here we demonstrate that Tantalus monkey tetherin restricts HIV-1 by nearly two orders of magnitude, but in contrast to human tetherin the Tantalus protein is insensitive to HIV-1 Vpu. We have investigated tetherin's sensitivity to Vpu using positive selection analyses, seeking evidence for evolutionary conflict between tetherin and viral countermeasures. We provide evidence that tetherin has undergone positive selection during primate evolution. Mutation of a single amino acid (showing evidence of positive selection) in the trans-membrane cap of human tetherin to that in Tantalus monkey (T45I) substantially impacts on sensitivity to HIV-1 Vpu, but not on antiviral activity. Finally, we provide evidence that cellular steady state levels of tetherin are substantially reduced by Vpu, and that the T45I mutation abrogates this effect. This study provides evidence that tetherin is important in protecting mammals against viral infection, and that the HIV-1 Vpu–mediated countermeasure is specifically adapted to act against human tetherin. It also emphasizes the power of selection analyses to illuminate the molecular details of host–virus interactions. This work suggests that tetherin binding agents might protect it from viral encoded countermeasures and thus make powerful antivirals