Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

BACKGROUND: Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons. METHODS: We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI of HIV-1-positive individuals, and a novel incidence estimator which distinguishes between endogenous and exogenous infections by modelling explicitly the probability that a foreign-born person was infected either before or after immigration. The incidence estimator allows for direct calculation of the number of undiagnosed persons. The new methodology is illustrated combining heterogeneous surveillance data from Sweden between 2003 and 2015. RESULTS: A leave-one-out cross-validation study showed that the multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs ≥1.95). We estimate that 816 [95% credible interval (CI) 775-865] PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CI 10.3-11.4%) of all PLHIV. CONCLUSIONS: The proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90-90-90 UNAIDS target

HIV-TRACE (Transmission Cluster Engine):A tool for large scale molecular epidemiology of HIV-1 and other rapidly evolving pathogens

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens

Challenging a ‘Why should I care’ attitude by incorporating societal issues in the classroom

A continuing challenge in life-science education is to foster student engagement with complex, occasionally dry material. One approach to this challenge is to build connections between classroom topics and the “real world.” We outline here an active-learning assignment in which students write to a local representative concerning a current social or environmental problem. In their letters, students present the scientific basis of the problem, evaluate opposing viewpoints, and describe their own science-based recommendation. This assignment empowers students by recognizing their ability to build connections and contribute insight. By fostering student engagement and interdisciplinary understanding, this can be a useful and exciting complement to classroom learning

Application of One Sided t-tests and a Generalized Experiment Wise Error Rate to High-Density Oligonucleotide Microarray Experiments: An Example Using Arabidopsis

Abstract: Motivation: A formidable challenge in the analysis of microarray data is the identification of those genes that exhibit differential expression. The objectives of this research were to examine the utility of simple ANOVA, one sided t tests, natural log transformation, and a generalized experiment wise error rate methodology for analysis of such experiments. As a test case, we analyzed a Affymetrix GeneChip microarray experiment designed to test for the effect of a CHD3 chromatin remodeling factor, PICKLE, and an inhibitor of the plant hormone gibberellin (GA), on the expression of 8256 Arabidopsis thaliana genes. Results: The GFWER(k) is defined as the probability of rejecting k or more true null hypothesis at a given p level. Computing probabilities by GFWER(k) was shown to be simple to apply and, depending on the value of k, can greatly increase power. A k value as small as 2 or 3 was concluded to be adequate for large or small experiments respectively. A one sided ttest along with GFWER(2)=.05 identified 43 genes as exhibiting PICKLEdependent expression. Expression of all 43 genes was re-examined by qRT-PCR, of which 36 (83.7%) were confirmed to exhibit PICKLE-dependent expression

Complete sequences of mitochondria genomes of Aedes aegypti and Culex quinquefasciatus and comparative analysis of mitochondrial DNA fragments inserted in the nuclear genomes

We present complete sequences of the mitochondrial genomes for two important mosquitoes, Aedes aegypti and Culex quinquefasciatus, that are major vectors of dengue virus and lymphatic filariasis, respectively. The A. aegypti mitochondrial genome is 16,655 bp in length and that of Culex quinquefasciatus is 15,587 bp, yet both contain 13 protein coding genes, 22 transfer RNA (tRNA) genes, one 12S ribosomal RNA (rRNA) gene, one 16S rRNA gene and a control region (CR) in the same order. The difference in the genome size is due to the difference in the length of the control region. We also analyzed insertions of nuclear copies of mtDNA-like sequences (NUMTs) in a comparative manner between the two mosquitoes. The NUMT sequences occupy ˜0.008% of the A. aegypti genome and ˜ 0.001% of the C. quinquefasciatus genome. Several NUMTs were found localized in the introns of predicted protein coding genes in both genomes (32 genes in A. aegypti but only four in C. quinquefasciatus). None of these NUMT-containing genes had an ortholog between the two species or had paralogous copies within a genome that was also NUMT-containing. It was further observed that the NUMT-containing genes were relatively longer but had lower GC content compared to the NUMT-less paralogous copies. Moreover, stretches of homologies are present among the genic and non-genic NUMTs that may play important roles in genomic rearrangement of NUMTs in these genomes. Our study provides new insights on understanding the roles of nuclear mtDNA sequences in genome complexities of these mosquitoes