In Vitro HIV-1 Evolution in Response to Triple Reverse Transcriptase Inhibitors & In Silico Phenotypic Analysis

Background

Effectiveness of ART regimens strongly depends upon complex interactions between the selective pressure of drugs and the evolution of mutations that allow or restrict drug resistance.

Methods

Four clinical isolates from NRTI-exposed, NNRTI-naive subjects were passaged in increasing concentrations of NVP in combination with 1 µM 3 TC and 2 µM ADV to assess selective pressures of multi-drug treatment. A novel parameter inference procedure, based on a stochastic viral growth model, was used to estimate phenotypic resistance and fitness from in vitro combination passage experiments.

Results

Newly developed mathematical methods estimated key phenotypic parameters of mutations arising through selective pressure exerted by 3 TC and NVP. Concentrations of 1 µM 3 TC maintained the M184V mutation, which was associated with intrinsic fitness deficits. Increasing NVP concentrations selected major NNRTI resistance mutations. The evolutionary pathway of NVP resistance was highly dependent on the viral genetic background, epistasis as well as stochasticity. Parameter estimation indicated that the previously unrecognized mutation L228Q was associated with NVP resistance in some isolates.

Conclusion

Serial passage of viruses in the presence of multiple drugs may resemble the selection of mutations observed among treated individuals and populations in vivo and indicate evolutionary preferences and restrictions. Phenotypic resistance estimated here “in silico” from in vitro passage experiments agreed well with previous knowledge, suggesting that the unique combination of “wet-” and “dry-lab” experimentation may improve our understanding of HIV-1 resistance evolution in the future.     

A representation of a compressed de Bruijn graph for pan-genome analysis that enables search

Background

Recently, Marcus et al. (Bioinformatics 30:3476–83, 2014) proposed to use a compressed de Bruijn graph to describe the relationship between the genomes of many individuals/strains of the same or closely related species. They devised an \(O(n\log g)\) time algorithm called splitMEM that constructs this graph directly (i.e., without using the uncompressed de Bruijn graph) based on a suffix tree, where n is the total length of the genomes and g is the length of the longest genome. Baier et al. (Bioinformatics 32:497–504, 2016) improved their result.

Results

In this paper, we propose a new space-efficient representation of the compressed de Bruijn graph that adds the possibility to search for a pattern (e.g. an allele—a variant form of a gene) within the pan-genome. The ability to search within the pan-genome graph is of utmost importance and is a design goal of pan-genome data structures.

     

Tracking Resilience to Infections by Mapping Disease Space

Infected hosts differ in their responses to pathogens; some hosts are resilient and recover their original health, whereas others follow a divergent path and die. To quantitate these differences, we propose mapping the routes infected individuals take through “disease space.” We find that when plotting physiological parameters against each other, many pairs have hysteretic relationships that identify the current location of the host and predict the future route of the infection. These maps can readily be constructed from experimental longitudinal data, and we provide two methods to generate the maps from the cross-sectional data that is commonly gathered in field trials. We hypothesize that resilient hosts tend to take small loops through disease space, whereas nonresilient individuals take large loops. We support this hypothesis with experimental data in mice infected with Plasmodium chabaudi, finding that dying mice trace a large arc in red blood cells (RBCs) by reticulocyte space as compared to surviving mice. We find that human malaria patients who are heterozygous for sickle cell hemoglobin occupy a small area of RBCs by reticulocyte space, suggesting this approach can be used to distinguish resilience in human populations. This technique should be broadly useful in describing the in-host dynamics of infections in both model hosts and patients at both population and individual levels.     

Phenotypic plasticity in growth and fecundity induced by strong population fluctuations affects reproductive traits of female fish

Fish are known for their high phenotypic plasticity in life‐history traits in relation to environmental variability, and this is particularly pronounced among salmonids in the Northern Hemisphere. Resource limitation leads to trade‐offs in phenotypic plasticity between life‐history traits related to the reproduction, growth, and survival of individual fish, which have consequences for the age and size distributions of populations, as well as their dynamics and productivity. We studied the effect of plasticity in growth and fecundity of vendace females on their reproductive traits using a series of long‐term incubation experiments. The wild parental fish originated from four separate populations with markedly different densities, and hence naturally induced differences in their growth and fecundity. The energy allocation to somatic tissues and eggs prior to spawning served as a proxy for total resource availability to individual females, and its effects on offspring survival and growth were analyzed. Vendace females allocated a rather constant proportion of available energy to eggs (per body mass) despite different growth patterns depending on the total resources in the different lakes; investment into eggs thus dictated the share remaining for growth. The energy allocation to eggs per mass was higher in young than in old spawners and the egg size and the relative fecundity differed between them: Young females produced more and smaller eggs and larvae than old spawners. In contrast to earlier observations of salmonids, a shortage of maternal food resources did not increase offspring size and survival. Vendace females in sparse populations with ample resources and high growth produced larger eggs and larvae. Vendace accommodate strong population fluctuations by their high plasticity in growth and fecundity, which affect their offspring size and consequently their recruitment and productivity, and account for their persistence and resilience in the face of high fishing mortality.     

Sphingosine-1-Phosphate Lyase Deficient Cells as a Tool to Study Protein Lipid Interactions

Cell membranes contain hundreds to thousands of individual lipid species that are of structural importance but also specifically interact with proteins. Due to their highly controlled synthesis and role in signaling events sphingolipids are an intensely studied class of lipids. In order to investigate their metabolism and to study proteins interacting with sphingolipids, metabolic labeling based on photoactivatable sphingoid bases is the most straightforward approach. In order to monitor protein-lipid-crosslink products, sphingosine derivatives containing a reporter moiety, such as a radiolabel or a clickable group, are used. In normal cells, degradation of sphingoid bases via action of the checkpoint enzyme sphingosine-1-phosphate lyase occurs at position C2-C3 of the sphingoid base and channels the resulting hexadecenal into the glycerolipid biosynthesis pathway. In case the functionalized sphingosine looses the reporter moiety during its degradation, specificity towards sphingolipid labeling is maintained. In case degradation of a sphingosine derivative does not remove either the photoactivatable or reporter group from the resulting hexadecenal, specificity towards sphingolipid labeling can be achieved by blocking sphingosine-1-phosphate lyase activity and thus preventing sphingosine derivatives to be channeled into the sphingolipid-to-glycerolipid metabolic pathway. Here we report an approach using clustered, regularly interspaced, short palindromic repeats (CRISPR)-associated nuclease Cas9 to create a sphingosine-1-phosphate lyase (SGPL1) HeLa knockout cell line to disrupt the sphingolipid-to-glycerolipid metabolic pathway. We found that the lipid and protein compositions as well as sphingolipid metabolism of SGPL1 knock-out HeLa cells only show little adaptations, which validates these cells as model systems to study transient protein-sphingolipid interactions.     

All-Cause and Cause-Specific Mortality among Users of Basal Insulins NPH,Detemir, and Glargine

Background

Insulin therapy in type 2 diabetes may increase mortality and cancer incidence, but the impact of different types of basal insulins on these endpoints is unclear. Compared to the traditional NPH insulin, the newer, longer-acting insulin analogues detemir and glargine have shown benefits in randomized controlled trials. Whether these advantages translate into lower mortality among users in real life is unknown.

Objective

To estimate the differences in all-cause and cause-specific mortality rates between new users of basal insulins in a population-based study in Finland.

Methods

23 751 individuals aged ≥40 with type 2 diabetes, who initiated basal insulin therapy in 2006–2009 were identified from national registers, with comprehensive data for mortality, causes of death, and background variables. Propensity score matching was performed on characteristics. Follow-up time was up to 4 years (median 1.7 years).

Results

2078 deaths incurred. With NPH as reference, the adjusted HRs for all-cause mortality were 0.39 (95% CI, 0.30–0.50) for detemir, and 0.55 (95% CI, 0.44–0.69) for glargine. As compared to glargine, the HR was 0.71 (95% CI, 0.54–0.93) among detemir users. Compared to NPH, the mortality risk for both cardiovascular causes as well as cancer were also significantly lower for glargine, and especially for detemir in adjusted analysis. Furthermore, the results were robust in various sensitivity analyses.

Conclusion

In real clinical practice, mortality was substantially higher among users of NPH insulin as compared to insulins detemir or glargine. Considering the large number of patients who require insulin therapy, this difference in risk may have major clinical and public health implications. Due to limitations of the observational study design, further investigation using an interventional study design is warranted.     

A Novel Glutamyl (Aspartyl)-Specific Aminopeptidase A from Lactobacillus delbrueckii with Promising Properties for Application

Lactic acid bacteria (LAB) are auxotrophic for a number of amino acids. Thus, LAB have one of the strongest proteolytic systems to acquit their amino acid requirements. One of the intracellular exopeptidases present in LAB is the glutamyl (aspartyl) specific aminopeptidase (PepA; EC 3.4.11.7). Most of the PepA enzymes characterized yet, belonged to Lactococcus lactis sp., but no PepA from a Lactobacillus sp. has been characterized so far. In this study, we cloned a putative pepA gene from Lb. delbrueckii ssp. lactis DSM 20072 and characterized it after purification. For comparison, we also cloned, purified and characterized PepA from Lc. lactis ssp. lactis DSM 20481. Due to the low homology between both enzymes (30%), differences between the biochemical characteristics were very likely. This was confirmed, for example, by the more acidic optimum pH value of 6.0 for Lb-PepA compared to pH 8.0 for Lc-PepA. In addition, although the optimum temperature is quite similar for both enzymes (Lb-PepA: 60°C; Lc-PepA: 65°C), the temperature stability after three days, 20°C below the optimum temperature, was higher for Lb-PepA (60% residual activity) than for Lc-PepA (2% residual activity). EDTA inhibited both enzymes and the strongest activation was found for CoCl₂, indicating that both enzymes are metallopeptidases. In contrast to Lc-PepA, disulfide bond-reducing agents such as dithiothreitol did not inhibit Lb-PepA. Finally, Lb-PepA was not product-inhibited by L-Glu, whereas Lc-PepA showed an inhibition.