scholarly journals Assessment of carbapenems in a mouse model of Mycobacterium tuberculosis infection

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0249841
Author(s):  
Ravindra Jadhav ◽  
Ricardo Gallardo-Macias ◽  
Gaurav Kumar ◽  
Samer S. Daher ◽  
Amit Kaushik ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Mouse Model ◽  
Small Molecules ◽  
Lessons Learned ◽  
Learning Approach ◽  
Mycobacterium Tuberculosis Infection ◽  
Pharmacokinetic Profiles ◽  
Machine Learning Approach ◽  
Selection Of

We present further study of a subset of carbapenems, arising from a previously reported machine learning approach, with regard to their mouse pharmacokinetic profiling and subsequent study in a mouse model of sub-acute Mycobacterium tuberculosis infection. Pharmacokinetic metrics for such small molecules were compared to those for meropenem and biapenem, resulting in the selection of two carbapenems to be assessed for their ability to reduce M. tuberculosis bacterial loads in the lungs of infected mice. The original syntheses of these two carbapenems were optimized to provide multigram quantities of each compound. One of the two experimental carbapenems, JSF-2204, exhibited efficacy equivalent to that of meropenem, while both were inferior to rifampin. The lessons learned in this study point toward the need to further enhance the pharmacokinetic profiles of experimental carbapenems to positively impact in vivo efficacy performance.

scholarly journals The Purinergic P2X7 Receptor Is Not Required for Control of Pulmonary Mycobacterium tuberculosis Infection

2005 ◽  
Vol 73 (5) ◽  
pp. 3192-3195 ◽  
Author(s):  
Amy J. Myers ◽  
Brandon Eilertson ◽  
Scott A. Fulton ◽  
JoAnne L. Flynn ◽  
David H. Canaday
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Mouse Model ◽  
P2x7 Receptor ◽  
Low Dose ◽  
Wild Type ◽  
Mycobacterium Tuberculosis Infection ◽  
P2x7 Receptors ◽  
Purinergic P2x7 Receptor ◽  
Aerosol Infection

ABSTRACT The importance in vivo of P2X7 receptors in control of virulent Mycobacterium tuberculosis was examined in a low-dose aerosol infection mouse model. P2X7−/− mice controlled infection in lungs as well as wild-type mice, suggesting that the P2X7 receptor is not required for control of pulmonary M. tuberculosis infection.

scholarly journals Three-dimensional in situ morphometrics of Mycobacterium tuberculosis infection within lesions by optical mesoscopy and novel acid-fast staining

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Robert J. Francis ◽  
Gillian Robb ◽  
Lee McCann ◽  
Bhagwati Khatri ◽  
James Keeble ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Three Dimensional ◽  
Large Field ◽  
Staining Procedure ◽  
3D Analysis ◽  
Mycobacterium Tuberculosis Infection ◽  
In Vivo Models ◽  
Novel Approach

AbstractTuberculosis (TB) preclinical testing relies on in vivo models including the mouse aerosol challenge model. The only method of determining colony morphometrics of TB infection in a tissue in situ is two-dimensional (2D) histopathology. 2D measurements consider heterogeneity within a single observable section but not above and below, which could contain critical information. Here we describe a novel approach, using optical clearing and a novel staining procedure with confocal microscopy and mesoscopy, for three-dimensional (3D) measurement of TB infection within lesions at sub-cellular resolution over a large field of view. We show TB morphometrics can be determined within lesion pathology, and differences in infection with different strains of Mycobacterium tuberculosis. Mesoscopy combined with the novel CUBIC Acid-Fast (CAF) staining procedure enables a quantitative approach to measure TB infection and allows 3D analysis of infection, providing a framework which could be used in the analysis of TB infection in situ.

scholarly journals Comparing the utility of in vivo transposon mutagenesis approaches in yeast species to infer gene essentiality

2019 ◽  
Author(s):  
Anton Levitan ◽  
Andrew N. Gale ◽  
Emma K. Dallon ◽  
Darby W. Kozan ◽  
Kyle W. Cunningham ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Yeast Species ◽  
Transposon Mutagenesis ◽  
Learning Approach ◽  
Long Distance ◽  
Gene Essentiality ◽  
Genome Wide ◽  
Machine Learning Approach

ABSTRACTIn vivo transposon mutagenesis, coupled with deep sequencing, enables large-scale genome-wide mutant screens for genes essential in different growth conditions. We analyzed six large-scale studies performed on haploid strains of three yeast species (Saccharomyces cerevisiae, Schizosaccaromyces pombe, and Candida albicans), each mutagenized with two of three different heterologous transposons (AcDs, Hermes, and PiggyBac). Using a machine-learning approach, we evaluated the ability of the data to predict gene essentiality. Important data features included sufficient numbers and distribution of independent insertion events. All transposons showed some bias in insertion site preference because of jackpot events, and preferences for specific insertion sequences and short-distance vs long-distance insertions. For PiggyBac, a stringent target sequence limited the ability to predict essentiality in genes with few or no target sequences. The machine learning approach also robustly predicted gene function in less well-studied species by leveraging cross-species orthologs. Finally, comparisons of isogenic diploid versus haploid S. cerevisiae isolates identified several genes that are haplo-insufficient, while most essential genes, as expected, were recessive. We provide recommendations for the choice of transposons and the inference of gene essentiality in genome-wide studies of eukaryotic haploid microbes such as yeasts, including species that have been less amenable to classical genetic studies.

scholarly journals Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252096
Author(s):  
Maria B. Rabaglino ◽  
Alan O’Doherty ◽  
Jan Bojsen-Møller Secher ◽  
Patrick Lonergan ◽  
Poul Hyttel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Integration ◽  
Focal Adhesion ◽  
Learning Approach ◽  
Omics Data ◽  
Machine Learning Approach ◽  
Cluster 2 ◽  
Omics Data Integration

Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in vivo after ovarian superovulation (MOET). This is potentially due to alterations in their trophectoderm (TE), the outermost layer in physical contact with the maternal endometrium. The main objective was to apply a multi-omics data integration approach to identify both temporally differentially expressed and differentially methylated genes (DEG and DMG), between IVP and MOET embryos, that could impact TE function. To start, four and five published transcriptomic and epigenomic datasets, respectively, were processed for data integration. Second, DEG from day 7 to days 13 and 16 and DMG from day 7 to day 17 were determined in the TE from IVP vs. MOET embryos. Third, genes that were both DE and DM were subjected to hierarchical clustering and functional enrichment analysis. Finally, findings were validated through a machine learning approach with two additional datasets from day 15 embryos. There were 1535 DEG and 6360 DMG, with 490 overlapped genes, whose expression profiles at days 13 and 16 resulted in three main clusters. Cluster 1 (188) and Cluster 2 (191) genes were down-regulated at day 13 or day 16, respectively, while Cluster 3 genes (111) were up-regulated at both days, in IVP embryos compared to MOET embryos. The top enriched terms were the KEGG pathway "focal adhesion" in Cluster 1 (FDR = 0.003), and the cellular component: "extracellular exosome" in Cluster 2 (FDR<0.0001), also enriched in Cluster 1 (FDR = 0.04). According to the machine learning approach, genes in Cluster 1 showed a similar expression pattern between IVP and less developed (short) MOET conceptuses; and between MOET and DKK1-treated (advanced) IVP conceptuses. In conclusion, these results suggest that early conceptuses derived from IVP embryos exhibit epigenomic and transcriptomic changes that later affect its elongation and focal adhesion, impairing post-transfer survival.

scholarly journals Distinct Bacterial Pathways Influence the Efficacy of Antibiotics against Mycobacterium tuberculosis

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Michelle M. Bellerose ◽  
Megan K. Proulx ◽  
Clare M. Smith ◽  
Richard E. Baker ◽  
Thomas R. Ioerger ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Treatment Outcome ◽  
Mouse Model ◽  
Genetic Variants ◽  
Drug Efficacy ◽  
Drug Susceptibility ◽  
Clinical Isolates ◽  
Drug Resistant ◽  
Bacterial Clearance

ABSTRACT Effective tuberculosis treatment requires at least 6 months of combination therapy. Alterations in the physiological state of the bacterium during infection are thought to reduce drug efficacy and prolong the necessary treatment period, but the nature of these adaptations remain incompletely defined. To identify specific bacterial functions that limit drug effects during infection, we employed a comprehensive genetic screening approach to identify mutants with altered susceptibility to the first-line antibiotics in the mouse model. We identified many mutations that increase the rate of bacterial clearance, suggesting new strategies for accelerating therapy. In addition, the drug-specific effects of these mutations suggested that different antibiotics are limited by distinct factors. Rifampin efficacy is inferred to be limited by cellular permeability, whereas isoniazid is preferentially affected by replication rate. Many mutations that altered bacterial clearance in the mouse model did not have an obvious effect on drug susceptibility using in vitro assays, indicating that these chemical-genetic interactions tend to be specific to the in vivo environment. This observation suggested that a wide variety of natural genetic variants could influence drug efficacy in vivo without altering behavior in standard drug-susceptibility tests. Indeed, mutations in a number of the genes identified in our study are enriched in drug-resistant clinical isolates, identifying genetic variants that may influence treatment outcome. Together, these observations suggest new avenues for improving therapy, as well as the mechanisms of genetic adaptations that limit it. IMPORTANCE Understanding how Mycobacterium tuberculosis survives during antibiotic treatment is necessary to rationally devise more effective tuberculosis (TB) chemotherapy regimens. Using genome-wide mutant fitness profiling and the mouse model of TB, we identified genes that alter antibiotic efficacy specifically in the infection environment and associated several of these genes with natural genetic variants found in drug-resistant clinical isolates. These data suggest strategies for synergistic therapies that accelerate bacterial clearance, and they identify mechanisms of adaptation to drug exposure that could influence treatment outcome.

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