Targeted mutagenesis of the Mycobacterium smegmatis mca gene, encoding a mycothiol-dependent detoxification protein

Mycothiol (MSH), a functional analogue of glutathione (GSH) that is found exclusively in actinomycetes, reacts with electrophiles and toxins to form MSH-toxin conjugates. Mycothiol S-conjugate amidase (Mca) then catalyzes the hydrolysis of an amide bond in the S conjugates, producing a mercapturic acid of the toxin, which is excreted from the bacterium, and glucosaminyl inositol, which is recycled back to MSH. In this study, we have generated and characterized an allelic exchange mutant of the mca gene of Mycobacterium smegmatis. The mca mutant accumulates the S conjugates of the thiol-specific alkylating agent monobromobimane and the antibiotic rifamycin S. Introduction of M. tuberculosis mca epichromosomally or introduction of M. smegmatis mca integratively resulted in complementation of Mca activity and reduced levels of S conjugates. The mutation in mca renders the mutant strain more susceptible to electrophilic toxins, such as N-ethylmalemide, iodoacetamide, and chlorodinitrobenzene, and to several oxidants, such as menadione and plumbagin. Additionally we have shown that the mca mutant is also more susceptible to the antituberculous antibiotic streptomycin. Mutants disrupted in genes belonging to MSH biosynthesis are also more susceptible to streptomycin, providing further evidence that Mca detoxifies streptomycin in the mycobacterial cell in an MSH-dependent manner.     

The glycosyltransferase gene encoding the enzyme catalyzing the first step of mycothiol biosynthesis (mshA)

Mycothiol is the major thiol present in most actinomycetes and is produced from the pseudodisaccharide 1D-myo-inosityl 2-acetamido-2-deoxy-alpha-D-glucopyranoside (GlcNAc-Ins). A transposon mutant of Mycobacterium smegmatis shown to be GlcNAc-Ins and mycothiol deficient was sequenced to identify a putative glycosyltransferase gene designated mshA. The ortholog in Mycobacterium tuberculosis, Rv0486, was used to complement the mutant phenotype.     

A ClpP protein model as tuberculosis target for screening marine compounds

ATP-dependent Clp protease (ClpP) is a core unit of a major bacterial protease complex employing as a new attractive drug target for that isolates, which are resistant to antibiotics. Mycobacterium tuberculosis, a gram-positive bacterium, is one of the major causes of hospital acquired infections. ClpP in Mycobacterium tuberculosis is usually tightly regulated and strictly requires a member of the family of Clp-ATPase and often further accessory proteins for proteolytic activation. Inhibition of ClpP eliminates these safeguards and start proteolytic degradation. Such uncontrolled proteolysis leads to inhibition of bacterial cell division and eventually cell death. In order to inhibit Clp protease, at first three dimensional structure model of ClpP in Mycobacterium tuberculosis was determined by comparative homology modeling program MODELLER based on crystal structure of the proteolytic component of the caseinolytic Clp protease (ClpP) from E. coli as a template protein and has 55%sequence identity with ClpP protein. The computed model's energy was minimized and validated using PROCHECK to obtain a stable model structure and is submitted in Protein Model Database (PMDB-ID: PM0075741). Stable model was further used for virtual screening against marine derived bioactive compound database through molecular docking studies using AutoDock 3.05. The docked complexes were validated and enumerated based on the AutoDock Scoring function to pick out the best marine inhibitors based on docked Energy. Thus from the entire 186 Marine compounds which were Docked, we got best 5 of them with optimal docked Energy (Ara-A: -14.31 kcal/mol, Dysinosin C: - 14.90kcal/mol, Nagelamide A: -20.49 kcal/mol, Strobilin: -8.02 kcal/mol, Manoalide: -8.81 kcal/mol). Further the five best-docked complexes were analyzed through Python Molecular Viewer software for their interaction studies. Thus from the Complex scoring and binding ability its deciphered that these Marine compounds could be promising inhibitors for ClpP as Drug target yet pharmacological studies have to confirm it.     

Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning

Background

Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually.

Aim

To develop an algorithm to identify relevant free texts automatically based on labelled examples.

Methods

We developed a novel machine learning algorithm, the ‘Semi-supervised Set Covering Machine’ (S3CM), and tested its ability to detect the presence of coronary angiogram results and ovarian cancer diagnoses in free text in the General Practice Research Database. For training the algorithm, we used texts classified as positive and negative according to their associated Read diagnostic codes, rather than by manual annotation. We evaluated the precision (positive predictive value) and recall (sensitivity) of S3CM in classifying unlabelled texts against the gold standard of manual review. We compared the performance of S3CM with the Transductive Vector Support Machine (TVSM), the original fully-supervised Set Covering Machine (SCM) and our ‘Freetext Matching Algorithm’ natural language processor.

Results

Only 60% of texts with Read codes for angiogram actually contained angiogram results. However, the S3CM algorithm achieved 87% recall with 64% precision on detecting coronary angiogram results, outperforming the fully-supervised SCM (recall 78%, precision 60%) and TSVM (recall 2%, precision 3%). For ovarian cancer diagnoses, S3CM had higher recall than the other algorithms tested (86%). The Freetext Matching Algorithm had better precision than S3CM (85% versus 74%) but lower recall (62%).

Conclusions

Our novel S3CM machine learning algorithm effectively detected free texts in primary care records associated with angiogram results and ovarian cancer diagnoses, after training on pre-classified test sets. It should be easy to adapt to other disease areas as it does not rely on linguistic rules, but needs further testing in other electronic health record datasets.     

Design,Synthesis, and Docking Study of Quinine-9-Triazolyl Conjugates

To develop a better chemotherapeutically potential candidate for lung cancer treatment and cure with repurposed motifs, quinine has been linked with biocompatible CuAAC-inspired regioselective 1,2,3-triazole linker and a series of ten novel 1,2,3-triazolyl-9-quinine conjugates have been developed by utilizing click conjugation of glycosyl ether alkynes with 9-epi-9-azido-9-deoxy-quinine under standard click conditions. In parallel, the docking study indicated that the resulting conjugates have an overall appreciable interaction with ALK-5 macromolecules. Moreover, the mannose-triazolyl conjugate exhibited the highest binding interactions of −7.6 kcal/mol with H-bond interaction with the targeted macromolecular system and indicate the hope for future trials for anti-lung cancer candidates.     

High level expression of the light chain of botulinum neurotoxin serotype C1 and an efficient HPLC assay to monitor its proteolytic activity

Botulinum neurotoxins (serotypes BoNT/A–BoNT/G) induce botulism, a disease leading to flaccid paralysis. These serotypes are highly specific in their proteolytic cleavage of SNAP-25 (synaptosomal-associated protein of 25 kDa), VAMP (vesicle associated membrane protein) or syntaxin. The catalytic domain (light chain, LC) of the neurotoxin has a Zn²⁺ dependent endopeptidase activity. In order to design drugs and inhibitors against these toxins, high level overexpression and characterization of LC of BoNTs along with the development of assays to monitor their proteolytic activity becomes important. Using the auto-induction method, we attained a high level expression of BoNT/C1(1–430) yielding more than 30 mg protein per 500 ml culture. We also developed an efficient assay to measure the activity of serotype C1 based on a HPLC method. SNAP-25 with varying peptide length has been reported in literature as substrates for BoNT/C1 proteolysis signifying the importance of remote exosites in BoNT/C1 required for activity. Here, we show that a 17-mer peptide corresponding to residues 187–203 of SNAP-25, which has earlier been shown to be a substrate for BoNT/A, can be used as a substrate for quantifying the activity of BoNT/C1(1–430). There was no pH dependence for the proteolysis, however the presence of dithiothreitol is essential for the reaction. Although the 17-mer substrate bound 110-fold less tightly to BoNT/C1(1–430) than SNAP-25, the optimal assay conditions facilitated an increase in the catalytic efficiency of the enzyme by about 5-fold.     

Comparative Chemical Composition and Acetylcholinesterase (AChE) Inhibitory Potential of Cinnamomum camphora and Cinnamomum tamala

Cinnamomum species have applications in the pharmaceutical and fragrance industry for wide biological and pharmaceutical activities. The present study investigates the chemical composition of the essential oils extracted from two species of Cinnamomum namely C. tamala and C. camphora. Chemical analysis showed E-cinnamyl acetate (56.14 %), E-cinnamaldehyde (20.15 %), and linalool (11.77 %) contributed as the major compounds of the 95.22 % of C. tamala leaves essential oil found rich in phenylpropanoids (76.96 %). C. camphora essential oil accounting for 93.57 % of the total oil composition was rich in 1,8-cineole (55.84 %), sabinene (14.37 %), and α-terpineol (10.49 %) making the oil abundant in oxygenated monoterpenes (70.63 %). Furthermore, the acetylcholinesterase inhibitory activity for both the essential oils was carried out using Ellman's colorimetric method. The acetylcholinesterase inhibitory potential at highest studied concentration of 1 mg/mL was observed to be 46.12±1.52 % for C. tamala and 53.61±2.66 % for C. camphora compared to the standard drug physostigmine (97.53±0.63 %) at 100 ng/ml. These multiple natural aromatic and fragrant characteristics with distinct chemical compositions offered by Cinnamon species provide varied benefits in the development of formulations that could be advantageous for the flavor and fragrance industry.     

Effective and specific in planta RNAi in cyst nematodes: expression interference of four parasitism genes reduces parasitic success

Cyst nematodes are highly evolved sedentary plant endoparasitesthat use parasitism proteins injected through the stylet intohost tissues to successfully parasitize plants. These secretoryproteins likely are essential for parasitism as they are involvedin a variety of parasitic events leading to the establishmentof specialized feeding cells required by the nematode to obtainnourishment. With the advent of RNA interference (RNAi) technologyand the demonstration of host-induced gene silencing in parasites,a new strategy to control pests and pathogens has become available,particularly in root-knot nematodes. Plant host-induced silencingof cyst nematode genes so far has had only limited success butsimilarly should disrupt the parasitic cycle and render thehost plant resistant. Additional in planta RNAi data for cystnematodes are being provided by targeting four parasitism genesthrough host-induced RNAi gene silencing in transgenic Arabidopsisthaliana, which is a host for the sugar beet cyst nematode Heteroderaschachtii. Here it is reported that mRNA abundances of targetednematode genes were specifically reduced in nematodes feedingon plants expressing corresponding RNAi constructs. Furthermore,this host-induced RNAi of all four nematode parasitism genesled to a reduction in the number of mature nematode females.Although no complete resistance was observed, the reductionof developing females ranged from 23% to 64% in different RNAilines. These observations demonstrate the relevance of the targetedparasitism genes during the nematode life cycle and, potentiallymore importantly, suggest that a viable level of resistancein crop plants may be accomplished in the future using thistechnology against cyst nematodes. Key words: beet cyst nematode (BCN), soybean cyst nematode (SCN), host induced, in planta RNAi, resistance, RNAi, transgenic Received 19 August 2008; Revised 25 October 2008 Accepted 27 October 2008