A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions.

Insertions and deletions (indels) are common molecular evolutionary events. However, probabilistic models for indel evolution are under-developed due to their computational complexity. Here, we introduce several improvements to indel modeling: 1) While previous models for indel evolution assumed that the rates and length distributions of insertions and deletions are equal, here we propose a richer model that explicitly distinguishes between the two; 2) we introduce numerous summary statistics that allow approximate Bayesian computation-based parameter estimation; 3) we develop a method to correct for biases introduced by alignment programs, when inferring indel parameters from empirical data sets; and 4) using a model-selection scheme, we test whether the richer model better fits biological data compared with the simpler model. Our analyses suggest that both our inference scheme and the model-selection procedure achieve high accuracy on simulated data. We further demonstrate that our proposed richer model better fits a large number of empirical data sets and that, for the majority of these data sets, the deletion rate is higher than the insertion rate.

M1CR0B1AL1Z3R-a user-friendly web server for the analysis of large-scale microbial genomics data.

Large-scale mining and analysis of bacterial datasets contribute to the comprehensive characterization of complex microbial dynamics within a microbiome and among different bacterial strains, e.g., during disease outbreaks. The study of large-scale bacterial evolutionary dynamics poses many challenges. These include data-mining steps, such as gene annotation, ortholog detection, sequence alignment and phylogeny reconstruction. These steps require the use of multiple bioinformatics tools and ad-hoc programming scripts, making the entire process cumbersome, tedious and error-prone due to manual handling. This motivated us to develop the M1CR0B1AL1Z3R web server, a 'one-stop shop' for conducting microbial genomics data analyses via a simple graphical user interface. Some of the features implemented in M1CR0B1AL1Z3R are: (i) extracting putative open reading frames and comparative genomics analysis of gene content; (ii) extracting orthologous sets and analyzing their size distribution; (iii) analyzing gene presence-absence patterns; (iv) reconstructing a phylogenetic tree based on the extracted orthologous set; (v) inferring GC-content variation among lineages. M1CR0B1AL1Z3R facilitates the mining and analysis of dozens of bacterial genomes using advanced techniques, with the click of a button. M1CR0B1AL1Z3R is freely available at https://microbializer.tau.ac.il/.

Relationship between antiretroviral prescribing patterns and treatment guidelines in treatment-naive HIV-1-infected US veterans (1992-2004).

OBJECTIVE: To analyze temporal patterns of antiretroviral (ARV) prescribing practices relative to nationally defined guidelines in treatment-naive patients with HIV-1 infection. DESIGN: Retrospective cohort study. METHODS: We evaluated ARV prescribing patterns among ARV treatment-naive veterans who were receiving care within the US Department of Veterans Affairs (VA) from 1992 through 2004 in comparison to evolving adult HIV-1 treatment guidelines. RESULTS: A total of 15,934 patients initiated ARV treatment. Since 1999, >94% of patients initiated at least a 3-ARV medication combination, although the percentage of patients who initiated a guideline "preferred" or "alternative" regimen never rose to greater than 72% and was significantly associated with being black and with region of care. After 1999, 20% of patients started 4 or more active ARV agents in combination, which was significantly associated with lower baseline CD4 cell count, higher viral load, and receiving care in the western United States. The proportion of patients receiving guideline "not recommended" regimens (virologically undesirable or overlapping toxicities) was <1% after 1997. VA prescribing trends generally predated guideline recommendations by 6 to 12 months. CONCLUSIONS: VA prescribing patterns for ARV initiation adhere to treatment guidelines that maximize safety. Guidelines designed to maximize efficacy were not followed as stringently. Evaluating clinical practice patterns against contemporary treatment guidelines can inform guideline development.

Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury.

Neutrophil gelatinase-associated lipocalin (Ngal), also known as siderocalin, forms a complex with iron-binding siderophores (Ngal:siderophore:Fe). This complex converts renal progenitors into epithelial tubules. In this study, we tested the hypothesis that Ngal:siderophore:Fe protects adult kidney epithelial cells or accelerates their recovery from damage. Using a mouse model of severe renal failure, ischemia-reperfusion injury, we show that a single dose of Ngal (10 microg), introduced during the initial phase of the disease, dramatically protects the kidney and mitigates azotemia. Ngal activity depends on delivery of the protein and its siderophore to the proximal tubule. Iron must also be delivered, since blockade of the siderophore with gallium inhibits the rescue from ischemia. The Ngal:siderophore:Fe complex upregulates heme oxygenase-1, a protective enzyme, preserves proximal tubule N-cadherin, and inhibits cell death. Because mouse urine contains an Ngal-dependent siderophore-like activity, endogenous Ngal might also play a protective role. Indeed, Ngal is highly accumulated in the human kidney cortical tubules and in the blood and urine after nephrotoxic and ischemic injury. We reveal what we believe to be a novel pathway of iron traffic that is activated in human and mouse renal diseases, and it provides a unique method for their treatment.