Studi Efisiensi Sistem Prasedimentasi Dan Free Water Surface Wetland Dalam Menurunkan Kadar Nitrat, Fosfat, Kekeruhan, Zat Organik Dan Total Coli

Boezem Wonorejo saat ini telah dikembangkan menjadi tempat wisata yaitu Ekowisata Mangrove. Sampai saat ini pihak pengelola boezem masih kesulitan dalam penyediaan air bersihnya Sungai Jagir yang mengalir di sekitar wilayah Ekowisata tersebut merupakan sumber air permukaan yang berpotensi sebagai pemenuhan kebutuhan tersebut secara kuantitatif. Agar dapat terpenuhi secara kualitatif, maka Perlu dilakukan penelitian awal untuk mengetahui efisiensi penurunan kadar Nitrat, Fosfat, Zat Organik, Kekeruhan maupun Total Coli. Dalam penelitian ini akan digunakan rangkaian suatu sistem pengolahan Prasedimentasi dan Free Water Surface wetland skala laboratoium, Dengan variabel ukuran media pasir (16-32 mesh dan lolos 32 mesh) dan umur mangrove (3 bulan dan 6 bulan) yang akan di analisis di laboratorium Teknik Lingkungan ITS. Dari hasil analisis didapat removal maksimum untuk kekeruhan pada prasedimentasi 46,5%, sedangkan pada wetland yaitu pada media pasir mesh 16-32 dan mangrove 6 bulan yaitu 94,8%. Presentase maksimum removal nitrat pada prasedimentasi yaitu 17,8%, removal maksimum pada wetland dengan mangrove 6 bulan dan media pasir lolos 32 mesh yaitu 53,6%. Pada mangrove sendiri removal makismum terdapat pada umur 6 bulan dengan besar removal 36,5%. Removal maksimum fosfat terbesar pada prasedimentasi yaitu 64,3%, untuk Reaktor Wetland yaitu pada wetland dengan mangrove 6 bulan dan media pasir lolos mesh 32 sebesar 90,5%. Untuk . Mangrovenya sendiri mampu meremoval maksimum pada umur 6 bulan dengan besar 53,8%. Presentase removal maksimum zat organik pada prasedimentasi sebesar 35,7%, pada reaktor wetland sebesar 21,8% dengan ukuran media pasir mesh 16-32 dan umur mangrove 3 bulan

SUMOFLUX: A Generalized Method for Targeted ¹³C Metabolic Flux Ratio Analysis

<div><p>Metabolic fluxes are a cornerstone of cellular physiology that emerge from a complex interplay of enzymes, carriers, and nutrients. The experimental assessment of <i>in vivo</i> intracellular fluxes using stable isotopic tracers is essential if we are to understand metabolic function and regulation. Flux estimation based on ¹³C or ²H labeling relies on complex simulation and iterative fitting; processes that necessitate a level of expertise that ordinarily preclude the non-expert user. To overcome this, we have developed SUMOFLUX, a methodology that is broadly applicable to the targeted analysis of ¹³C-metabolic fluxes. By combining surrogate modeling and machine learning, we trained a predictor to specialize in estimating flux ratios from measurable ¹³C-data. SUMOFLUX targets specific flux features individually, which makes it fast, user-friendly, applicable to experimental design and robust in terms of experimental noise and exchange flux magnitude. Collectively, we predict that SUMOFLUX's properties realistically pave the way to high-throughput flux analyses.</p></div

SUMOFLUX is robust in terms of experimental noise and exchange flux magnitude.

<p>(a) Mean absolute errors on the testing dataset of five flux ratio predictors applied to <i>in silico</i> data with different amount of measurement noise and exchange flux magnitude. The dashed rectangle indicates the normal range of noise (0.01) and exchange flux magnitude (10 times the net flux). (b) Mean absolute errors on the testing datasets with different noise levels of five flux ratio predictors trained on datasets with different amount of measurement noise. The exchange flux magnitude was set to 1 for all datasets. (c) Mean absolute errors on the testing dataset with different exchange flux magnitudes of five flux ratio predictors trained on datasets with different values of exchange flux magnitude. The noise level was set to 0.01 for all datasets. E-D—Entner-Doudoroff pathway, MAE—mean absolute error; PPP—pentose phosphate pathway.</p

Comparison of SUMOFLUX and analytic formula estimates for flux ratios in <i>E</i>. <i>coli</i> central carbon metabolism.

<p>From left to right: a schematic representation of the flux ratio; density plot representing SUMOFLUX estimates versus the true flux ratios for <i>in silico</i> data; comparison of the SUMOFLUX and analytic formula estimates for the experimental data; density plot representing analytic formula estimates versus the true flux ratios for <i>in silico</i> data. Vertical error bars in the third panel represent [10–90%] SUMOFLUX prediction quantiles, horizontal error bars represent standard deviation provided with the analytic formula estimate. (a) Glycolysis versus PPP. (b) Pyruvate fraction from the E-D pathway. (c) PEP fraction from gluconeogenesis. (d) Pyruvate fraction from the malic enzyme flux. (e) Oxaloacetate fraction from anaplerosis from PEP. Ratios (a)-(c) were estimated from [1-¹³C] glucose experiment, ratios (d) and (e) were estimated from 20% [U-¹³C] and 80% naturally labeled glucose experiment. 6PG– 6-phosho-D-gluconate; αKG– α-ketoglutarate; AcCoA—acetyl-CoA; E-D—Entner-Doudoroff pathway; F6P –fructose-6-phosphate; Fum—fumarate; G6P –glucose-6-phosphate; Gox—glyoxylate; ICT—isocitrate; KDPG—2-Keto-3-deoxy-6-phosphogluconate; MAE—mean absolute error; Mal—malate; PCC—Pearson correlation coefficient; PEP—phosphoenolpyruvate; PGA—phosphoglycerate; PPP—pentose phosphate pathway.</p

Quantification and Mass Isotopomer Profiling of α‑Keto Acids in Central Carbon Metabolism

Mass spectrometry has been established as a powerful and versatile technique for studying cellular metabolism. Applications range from profiling of metabolites to accurate quantification and tracing of stable isotopes through the biochemical reaction network. Despite broad coverage of central carbon metabolism, most methods fail to provide accurate assessments of the α-keto acids oxaloacetic acid, pyruvate, and glyoxylate because these compounds are highly reactive and degraded during sample processing and mass spectrometric measurement. We present a derivatization procedure to chemically stabilize these compounds readily during quenching of cellular metabolism. Stable derivatives were analyzed by ultrahigh pressure liquid chromatography coupled tandem mass spectrometry to accurately quantify the abundance of α-keto acids in biological matrices. Eventually, we demonstrated that the developed protocol is suited to measure mass isotopomers of these α-keto acids in tracer studies with stable isotopes. In conclusion, the here described method fills one of the last technical gaps for metabolomics investigations of central carbon metabolism

Extensions of linear constraints to integrate the thermodynamics of transport processes and charge-specific catalysis

<p><b>Copyright information:</b></p><p>Taken from "anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data"</p><p>http://www.biomedcentral.com/1471-2105/9/199</p><p>BMC Bioinformatics 2008;9():199-199.</p><p>Published online 16 Apr 2008</p><p>PMCID:PMC2375130.</p><p></p

Quantification of Cellular Folate Species by LC-MS after Stabilization by Derivatization

Folate cofactors play a key role in one-carbon metabolism. Analysis of individual folate species is hampered by the low chemical stability and high interconvertibility of folates, which can lead to severe experimental bias. Here, we present a complete workflow that employs simultaneous extraction and stabilization of folates by derivatization. We perform reductive methylation employing stable isotope labeled reagents to retain information on the position and redox state of one-carbon units as well as the redox state of the pteridine ring. The derivatives are analyzed by a targeted LC­(HILIC)-MS/MS method without the need for deconjugation, thereby also preserving the glutamation state of folates. The presented method does not only improve analyte coverage and sensitivity as compared to other published methods, it also greatly simplifies sample handling and storage. Finally, we report differences in the response of bacterial and mammalian systems to pharmacological inhibition of dihydrofolate reductase

The graphical user interface permits to submit all parameters and options that are necessary to accomplish a NET analysis

<p><b>Copyright information:</b></p><p>Taken from "anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data"</p><p>http://www.biomedcentral.com/1471-2105/9/199</p><p>BMC Bioinformatics 2008;9():199-199.</p><p>Published online 16 Apr 2008</p><p>PMCID:PMC2375130.</p><p></p

Nontargeted Profiling of Coenzyme A thioesters in biological samples by tandem mass spectrometry

Coenzyme A (CoA) thioesters are ubiquitously present in metabolic networks and play a pivotal role in enzymatic formation and cleavage of carbon–carbon bonds. We present a method allowing nontargeted profiling of CoA-thioesters in biological samples. The reported UHPLC-MS/MS approach employes ion-pairing chromatography to separate CoA-metabolites carrying different chemical functionalities such as hydroxyl or multiple carboxyl groups and to distinguish between isomers. Selective detection of CoA-thioesters is accomplished by precursor ion scanning on a triple quadrupole mass spectrometer and takes advantage of the abundant fragment with <i>m</i>/<i>z</i> = −408 that originates from the CoA-moiety. We used a mixture of 19 commercially available CoA-derivatives to develop and optimize our method. As a proof of concept we demonstrated detection of the major CoA-intermediates of branched chain amino acid degradation in biological samples. We then applied our method to investigate degradation of lipids in the microorganism <i>Mycobacterium smegmatis</i>. Profiling of CoA-thioesters led to the discovery of a novel intermediate of cholesterol degradation. This demonstrates the power of our method for untargeted profiling of CoA-thioesters and adds a missing link in mycobacterial cholesterol catabolism

Identification of novel regulatory events in nucleotide metabolism mediated by MetR.

<p>(a) Change in nucleotide triphosphate (NTP), cyclic nucleotide monophosphates (cNMP), nucleotide monophosphates (NMP) and nucleoside metabolite levels comparing Δ<i>metR</i> knockout and wildtype <i>E</i>. <i>coli</i>. (b) Results of CyaA enzyme assays with 10 mM ATP as substrate in crude extracts of Δ<i>metR</i> knockout, <i>metR</i> overexpression and wildtype <i>E</i>. <i>coli</i>. (c) Known and potentially new interactions involved in the regulation of nucleotide metabolism. Our study suggests that MetR inhibits CyaA. This could be mediated through direct inhibition or indirect feedback for example to CRP, the known regulator of CyaA expression.</p