Immunological evidence that inactive renin is prorenin

Antibody raised to a synthetic dodecapeptide, corresponding to the C-terminal portion of the human renin pro-segment, was tested for its ability to recognize highly purified human inactive or active (mature) renins; immune complexes were detected by precipitation with protein A-Sepharose. Serial antibody dilutions caused identical binding of renal or plasma inactive renins but failed to bind active renin. In contrast, antibody to active renin recognized both active and inactive forms. Reversible acid activation of inactive renin enhanced its binding to the anti-prorenin antibody, whereas irreversible trypsin activation significantly reduced binding. Binding was abolished following prolonged exposure to trypsin or if inactive renin was acidified prior to trypsin treatment. These results indicate that inactive renin shares immunochemical determinants with prorenin; they suggest that acidification alters the conformation of the pro-segment and that trypsin can convert the molecule both to fully mature renin and to intermediate form(s).     

Tyrosine Phosphorylation of Caspase-8 Abrogates Its Apoptotic Activity and Promotes Activation of c-Src

Src family tyrosine kinases (SFKs) phosphorylate caspase-8A at tyrosine (Y) 397 resulting in suppression of apoptosis. In addition, the phosphorylation of caspase-8A at other sites including Y465 has been implicated in the regulation of caspase-8 activity. However, the functional consequences of these modifications on caspase-8 processing/activity have not been elucidated. Moreover, various Src substrates are known to act as potent Src regulators, but no such role has been explored for caspase-8. We asked whether the newly identified caspase-8 phosphorylation sites might regulate caspase-8 activation and conversely, whether caspase-8 phosphorylation might affect Src activity. Here we show that Src phosphorylates caspase-8A at multiple tyrosine sites; of these, we have focused on Y397 within the linker region and Y465 within the p12 subunit of caspase-8A. We show that phosphomimetic mutation of caspase-8A at Y465 prevents its cleavage and the subsequent activation of caspase-3 and suppresses apoptosis. Furthermore, simultaneous phosphomimetic mutation of caspase-8A at Y397 and Y465 promotes the phosphorylation of c-Src at Y416 and increases c-Src activity. Finally, we demonstrate that caspase-8 activity prevents its own tyrosine phosphorylation by Src. Together these data reveal that dual phosphorylation converts caspase-8 from a pro-apoptotic to a pro-survival mediator. Specifically, tyrosine phosphorylation by Src renders caspase-8 uncleavable and thereby inactive, and at the same time converts it to a Src activator. This novel dynamic interplay between Src and caspase-8 likely acts as a potent signal-integrating switch directing the cell towards apoptosis or survival.     

Mineralization of the dibenzothiophene biodegradation products 3-hydroxy-2-formyl benzothiophene and dibenzothiophene sulfone

Dibenzothiophene is degraded to 3-hydroxy-2-formyl benzothiophene by various bacteria, including a strain of Pseudomonas putida that also forms dibenzothiophene sulfone via an alternate pathway. By using these end products as substrates, mixed enrichment cultures that could degrade 3-hydroxy-2-formyl benzothiophene and dibenzothiophene sulfone with the formation of CO2 were established.     

Hydroxylation and biodegradation of 6-methylquinoline by pseudomonads in aqueous and nonaqueous immobilized-cell bioreactors.

Selective culturing of pseudomonads that could degrade quinoline led to enrichment cultures and pure cultures with expanded substrate utilization and transformation capabilities for substituted quinolines in immobilized and batch cultures. Immobilized cells of the pseudomonad cultures rapidly transformed quinolines to hydroxyquinolines in bioreactors and were able to tolerate higher substrate concentrations compared with batch cultures. After prolonged incubation on a mixture of quinoline and 6-methylquinoline, a quinoline-degrading culture of Pseudomonas putida developed the ability to biodegrade 6-methylquinoline, which initially was resistant to microbial attack, as a sole source of carbon and energy. 6-Methylquinoline was also degraded in a nonaqueous solution by this strain of P. putida when a solution of 6-methylquinoline in decane was flowed through an immobilized-cell fixed-bed bioreactor.     

Antimicrobial resistance including Extended Spectrum Beta Lactamases (ESBL) among E. coli isolated from kenyan children at hospital discharge

BackgroundChildren who have been discharged from hospital in sub-Saharan Africa remain at substantial risk of mortality in the post-discharge period. Antimicrobial resistance (AMR) may be an important factor. We sought to determine the prevalence and risk factors associated with AMR in commensal Escherichia coli (E. coli) from Kenyan children at the time of discharge.Methodology/Principle findingsFecal samples were collected from 406 children aged 1–59 months in western Kenya at the time of discharge from hospital and cultured for E. coli. Susceptibility to ampicillin, ceftriaxone, cefotaxime, ceftazidime, cefoxitin, imipenem, ciprofloxacin, gentamicin, combined amoxicillin/clavulanic acid, trimethoprim-sulfamethoxazole, azithromycin, and chloramphenicol was determined by disc diffusion according to guidelines from the Clinical and Laboratory Standards Institute (CLSI). Poisson regression was used to determine associations between participant characteristics and the presence of extended-spectrum beta-lactamases (ESBL) producing E. coli. Non-susceptibility to ampicillin (95%), gentamicin (44%), ceftriaxone (46%), and the presence of ESBL (44%) was high. Receipt of antibiotics during the hospitalization was associated with the presence of ESBL (aPR = 2.23; 95% CI: 1.29–3.83) as was being hospitalized within the prior year (aPR = 1.32 [1.07–1.69]). Open defecation (aPR = 2.02; 95% CI: 1.39–2.94), having a toilet shared with other households (aPR = 1.49; 95% CI: 1.17–1.89), and being female (aPR = 1.42; 95% CI: 1.15–1.76) were associated with carriage of ESBL E. coliConclusions/SignificanceAMR is common among isolates of E. coli from children at hospital discharge in Kenya, including nearly half having detectable ESBL.     

A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems

Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical–subcortical systems developed from prior literature (“multisystem models”); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains.

Is pain represented by a single brain area or network, spanning multiple systems or distributed throughout the brain? fMRI brain decoding in a large multi-study dataset shows that multiple cortical and subcortical systems are needed to decode pain intensity; the approach is novel and can characterize scale of representation across diverse brain processes.     

Model suicide vector for containment of genetically engineered microorganisms

A model suicide vector (pBAP19h), designed for the potential containment of genetically engineered microorganisms, was made by constructing a plasmid with the hok gene, which codes for a lethal polypeptide, under the control of the lac promoter. The vector plasmid also codes for carbenicillin resistance. In the absence of carbenicillin, induction of the hok gene in vitro caused elimination of all detectable cells containing the suicide vector; pBAP19h-free cells of the culture survived and grew exponentially. In the presence of carbenicillin, however, the number of cells containing pBAP19h initially declined after induction of hok but then multiplied exponentially. The surviving cells still had a fully functional hok gene and had apparently developed resistance to the action of the Hok polypeptide. Thus, high selective pressure against the loss of the suicide vector led to a failure of the system. Soil microcosm experiments confirmed the ability of a suicide vector to restrict the growth of a genetically engineered microorganism in the absence of selective pressure against the loss of the plasmid, with 90 to 99% elimination of hok-bearing cells within 24 h of hok induction. However, some pBAP19h-bearing cells survived in the soil microcosms after hok induction. The surviving cells contained an active hok gene but were not capable of normal growth even after elimination of the hok gene; it appears that a mutation that made them Hok resistant also reduced their capacity for membrane functions needed for energy generation and exponential cell growth. Thus, the model suicide vector was shown to be functional in soil as well as in vitro.(ABSTRACT TRUNCATED AT 250 WORDS)     

A Bayesian network classification methodology for gene expression data.

We present new techniques for the application of a Bayesian network learning framework to the problem of classifying gene expression data. The focus on classification permits us to develop techniques that address in several ways the complexities of learning Bayesian nets. Our classification model reduces the Bayesian network learning problem to the problem of learning multiple subnetworks, each consisting of a class label node and its set of parent genes. We argue that this classification model is more appropriate for the gene expression domain than are other structurally similar Bayesian network classification models, such as Naive Bayes and Tree Augmented Naive Bayes (TAN), because our model is consistent with prior domain experience suggesting that a relatively small number of genes, taken in different combinations, is required to predict most clinical classes of interest. Within this framework, we consider two different approaches to identifying parent sets which are supported by the gene expression observations and any other currently available evidence. One approach employs a simple greedy algorithm to search the universe of all genes; the second approach develops and applies a gene selection algorithm whose results are incorporated as a prior to enable an exhaustive search for parent sets over a restricted universe of genes. Two other significant contributions are the construction of classifiers from multiple, competing Bayesian network hypotheses and algorithmic methods for normalizing and binning gene expression data in the absence of prior expert knowledge. Our classifiers are developed under a cross validation regimen and then validated on corresponding out-of-sample test sets. The classifiers attain a classification rate in excess of 90% on out-of-sample test sets for two publicly available datasets. We present an extensive compilation of results reported in the literature for other classification methods run against these same two datasets. Our results are comparable to, or better than, any we have found reported for these two sets, when a train-test protocol as stringent as ours is followed.