Mechanisms of HIV-1 evasion to the antiviral activity of chemokine CXCL12 indicate potential links with pathogenesis

HIV-1 infects CD4 T lymphocytes (CD4TL) through binding the chemokine receptors CCR5 or CXCR4. CXCR4-using viruses are considered more pathogenic, linked to accelerated depletion of CD4TL and progression to AIDS. However, counterexamples to this paradigm are common, suggesting heterogeneity in the virulence of CXCR4-using viruses. Here, we investigated the role of the CXCR4 chemokine CXCL12 as a driving force behind virus virulence. In vitro, CXCL12 prevents HIV-1 from binding CXCR4 and entering CD4TL, but its role in HIV-1 transmission and propagation remains speculative. Through analysis of thirty envelope glycoproteins (Envs) from patients at different stages of infection, mostly treatment-naïve, we first interrogated whether sensitivity of viruses to inhibition by CXCL12 varies over time in infection. Results show that Envs resistant (RES) to CXCL12 are frequent in patients experiencing low CD4TL levels, most often late in infection, only rarely at the time of primary infection. Sensitivity assays to soluble CD4 or broadly neutralizing antibodies further showed that RES Envs adopt a more closed conformation with distinct antigenicity, compared to CXCL12-sensitive (SENS) Envs. At the level of the host cell, our results suggest that resistance is not due to improved fusion or binding to CD4, but owes to viruses using particular CXCR4 molecules weakly accessible to CXCL12. We finally asked whether the low CD4TL levels in patients are related to increased pathogenicity of RES viruses. Resistance actually provides viruses with an enhanced capacity to enter naive CD4TL when surrounded by CXCL12, which mirrors their situation in lymphoid organs, and to deplete bystander activated effector memory cells. Therefore, RES viruses seem more likely to deregulate CD4TL homeostasis. This work improves our understanding of the pathophysiology and the transmission of HIV-1 and suggests that RES viruses’ receptors could represent new therapeutic targets to help prevent CD4TL depletion in HIV+ patients on cART.     

Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016–0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.     

A method for the harvest,culture, and characterization of human adult atrial myocardial cells: Correlation with age of donor

Summary Myocardial cell culture methods are now well established for animal and fetal human tissue. We present here a method for harvesting and culturing adult human atrial myocardiocytes. Cells are obtained from fresh atrial tissue normally discarded after being removed to cannulate the right atrium during open heart surgery. The atrial tissue is minced and then digested using collagenase. The single cell suspension is initially cultured in serum-containing growth medium, then transferred to defined medium, selective for myocardial cell growth. The cells are characterized by immunoperoxidase stains and transmission electron microscopy. The cultured cells stain positive for myoglobin, whereas control cultured fibroblasts and endothelial cells do not. Electron microscopy shows the presence of numerous myofibrils, Z-bodies, pleomorphic mitochondria, and secretory granules. The chronological age of the donor was an important factor in culturing the adult tissue, the younger tissue correlated with a higher success rate. This method provides a means for in vitro study of human adult myocardial cells and provides guidelines for appropriate atrial tissue to use.     

Leveraging whole genome sequencing data for demographic inference with approximate Bayesian computation

Accounting for historical demographic features, such as the strength and timing of gene flow and divergence times between closely related lineages, is vital for many inferences in evolutionary biology. Approximate Bayesian computation (ABC) is one method commonly used to estimate demographic parameters. However, the DNA sequences used as input for this method, often microsatellites or RADseq loci, usually represent a small fraction of the genome. Whole genome sequencing (WGS) data, on the other hand, have been used less often with ABC, and questions remain about the potential benefit of, and how to best implement, this type of data; we used pseudo‐observed data sets to explore such questions. Specifically, we addressed the potential improvements in parameter estimation accuracy that could be associated with WGS data in multiple contexts; namely, we quantified the effects of (a) more data, (b) haplotype‐based summary statistics, and (c) locus length. Compared with a hypothetical RADseq data set with 2.5 Mbp of data, using a 1 Gbp data set consisting of 100 Kbp sequences led to substantial gains in the accuracy of parameter estimates, which was mostly due to haplotype statistics and increased data. We also quantified the effects of including (a) locus‐specific recombination rates, and (b) background selection information in ABC analyses. Importantly, assuming uniform recombination or ignoring background selection had a negative effect on accuracy in many cases. Software and results from this method validation study should be useful for future demographic history analyses.