Detection of New Delhi Metallo-β-Lactamase (Encoded by \u3ci\u3ebla\u3c/i\u3e\u3csub\u3eNDM-1\u3c/sub\u3e) in \u3ci\u3eAcinetobacter schindleri\u3c/i\u3e during Routine Surveillance

A carbapenem-resistant Alcaligenes faecalis strain was isolated from a surveillance swab of a service member injured in Afghanistan. The isolate was positive for blaNDM by real-time PCR. Species identification was reevaluated on three identification systems but was inconclusive. Genome sequencing indicated that the closest relative was Acinetobacter schindleri and that blaNDM-1 was carried on a plasmid that shared \u3e99% identity with one identified in an Acinetobacter lwoffii isolate. The isolate also carried a novel chromosomally encoded class D oxacillinase

Cyclopentenone Isoprostanes Inhibit the Inflammatory Response in Macrophages

Although both inflammation and oxidative stress contribute to the pathogenesis of many disease states, the interaction between the two is poorly understood. Cyclopentenone isoprostanes (IsoPs), highly reactive structural isomers of the bioactive cyclopentenone prostaglandins PGA2 and PGJ2, are formed non-enzymatically as products of oxidative stress in vivo. We have, for the first time, examined the effects of synthetic 15-A2- and 15-J2-IsoPs, two groups of endogenous cyclopentenone IsoPs, on the inflammatory response in RAW264.7 and primary murine macrophages. Cyclopentenone IsoPs potently inhibited lipopolysaccharide-stimulated IkappaB alpha degradation and subsequent NF-kappaB nuclear translocation and transcriptional activity. Expression of inducible nitric-oxide synthase and cyclooxygenase-2 were also inhibited by cyclopentenone IsoPs as was nitrite and prostaglandin production (IC50 approximately 360 and 210 nM, respectively). 15-J2-IsoPs potently activated peroxisome proliferator-activated receptor gamma (PPARgamma) nuclear receptors, whereas 15-A2-IsoP did not, although the anti-inflammatory effects of both molecules were PPARgamma-independent. Interestingly 15-A2-IsoPs induced oxidative stress in RAW cells that was blocked by the antioxidant 4-hydroxy-TEMPO (TEMPOL) or the mitochondrial uncoupler carbonyl cyanide p-(trifluoromethoxy)phenylhydrazone. TEMPOL also abrogated the inhibitory effect of 15-A2-IsoPs on lipopolysaccharide-induced NF-kappaB activation, inducible nitricoxide synthase expression, and nitrite production, suggesting that 15-A2-IsoPs inhibit the NF-kappaB pathway at least partially via a redox-dependent mechanism. 15-J2-IsoP, but not 15-A2-IsoP, also potently induced RAW cell apoptosis again via a PPAR gamma-independent mechanism. These findings suggest that cyclopentenone IsoPs may serve as negative feedback regulators of inflammation and have important implications for defining the role of oxidative stress in the inflammatory response

Microsomal prostaglandin E synthase-2 is not essential for in vivo prostaglandin E2 biosynthesis

Prostaglandin E2 (PGE2) plays an important role in the normal physiology of many organ systems. Increased levels of this lipid mediator are associated with many disease states, and it potently regulates inflammatory responses. Three enzymes capable of in vitro synthesis of PGE2 from the cyclooxygenase metabolite PGH2 have been described. Here, we examine the contribution of one of these enzymes to PGE2 production, mPges-2, which encodes microsomal prostaglandin synthase-2 (mPGES-2), by generating mice homozygous for the null allele of this gene. Loss of mPges-2 expression did not result in a measurable decrease in PGE2 levels in any tissue or cell type examined from healthy mice. Taken together, analysis of the mPGES-2 deficient mouse lines does not substantiate the contention that mPGES-2 is a PGE2 synthase

Department of Pathology, Thomas Jefferson University, Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors.

BACKGROUND: Although numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors. RESULTS: Unsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of histologies and expression profiles developed. In many models, similarities to human breast tumors were recognized, including proliferation and human breast tumor subtype signatures. Significantly, tumors of several models displayed characteristics of human basal-like breast tumors, including two models with induced Brca1 deficiencies. Tumors of other murine models shared features and trended towards significance of gene enrichment with human luminal tumors; however, these murine tumors lacked expression of estrogen receptor (ER) and ER-regulated genes. TgMMTV-Neu tumors did not have a significant gene overlap with the human HER2+/ER- subtype and were more similar to human luminal tumors. CONCLUSION: Many of the defining characteristics of human subtypes were conserved among the mouse models. Although no single mouse model recapitulated all the expression features of a given human subtype, these shared expression features provide a common framework for an improved integration of murine mammary tumor models with human breast tumors

Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors

Comparison of mammary tumor gene-expression profiles from thirteen murine models using microarrays and with that of human breast tumors showed that many of the defining characteristics of human subtypes were conserved among mouse models

Imitation of β-lactam binding enables broad-spectrum metallo-β-lactamase inhibitors

Carbapenems are vital antibiotics, but their efficacy is increasingly compromised by metallo-beta-lactamases (MBLs). Here we report the discovery and optimization of potent broad-spectrum MBL inhibitors. A high-throughput screen for NDM-1 inhibitors identified indole-2-carboxylates (InCs) as potential beta-lactamase stable beta-lactam mimics. Subsequent structure-activity relationship studies revealed InCs as a new class of potent MBL inhibitor, active against all MBL classes of major clinical relevance. Crystallographic studies revealed a binding mode of the InCs to MBLs that, in some regards, mimics that predicted for intact carbapenems, including with respect to maintenance of the Zn(II)-bound hydroxyl, and in other regards mimics binding observed in MBL-carbapenem product complexes. InCs restore carbapenem activity against multiple drug-resistant Gram-negative bacteria and have a low frequency of resistance. InCs also have a good in vivo safety profile, and when combined with meropenem show a strong in vivo efficacy in peritonitis and thigh mouse infection models.Peer reviewe

Prediction of lithium response using genomic data

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14; 95% confidence interval [CI]: −0.24 to −0.03; p value = 0.010) and MDD (β = −0.16; 95% CI: −0.27 to −0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34–1.93; p value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD