No abstract

Microbial fatty acid derivatives are emerging as promising alternatives to fossil fuel derived transportation fuels. Among bacterial fatty acid synthases (FAS), the Escherichia coli FAS is perhaps the most well studied, but little is known about its steady-state kinetic behavior. Here we describe the reconstitution of E. coli FAS using purified protein components and report detailed kinetic analysis of this reconstituted system. When all ketosynthases are present at 1 μM, the maximum rate of free fatty acid synthesis of the FAS exceeded 100 μM∕ min. The steady-state turnover frequency was not significantly inhibited at high concentrations of any substrate or cofactor. FAS activity was saturated with respect to most individual protein components when their concentrations exceeded 1 μM. The exceptions were FabI and FabZ, which increased FAS activity up to concentrations of 10 μM; FabH and FabF, which decreased FAS activity at concentrations higher than 1 μM; and holo-ACP and TesA, which gave maximum FAS activity at 30 μM concentrations. Analysis of the S36T mutant of the ACP revealed that the unusual dependence of FAS activity on holo-ACP concentration was due, at least in part, to the acyl-phosphopantetheine moiety. MALDI-TOF mass spectrometry analysis of the reaction mixture further revealed medium and long chain fatty acyl-ACP intermediates as predominant ACP species. We speculate that one or more of such intermediates are key allosteric regulators of FAS turnover. Our findings provide a new basis for assessing the scope and limitations of using E. coli as a biocatalyst for the production of diesel-like fuels.D ue to their high energy density and low water solubility, fatty acids are arguably the most appropriate biofuel precursors. Therefore, fatty acid synthases (FASs) have emerged as attractive engineering targets in society's recent quest for transportation fuels from renewable sources. Among different FASs, the Escherichia coli synthase is perhaps most well understood (1). However, notwithstanding extensive analysis of fatty acid biosynthesis and its regulation in E. coli (2-5), little is known about its steady-state kinetic properties. We therefore sought to undertake systematic kinetic analysis of the fully reconstituted E. coli FAS. It was anticipated that such analysis would provide a fundamentally new basis for assessing the scope and limitations of producing fatty acids using E. coli as a biocatalyst.Fatty acid biosynthesis in E. coli is catalyzed by an enzyme system consisting of nine distinct proteins-FabA, FabB, FabD, FabF, FabG, FabH, FabI, FabZ, and ACP (Fig. 1). Together, they convert one equivalent of acetyl-CoA and 6-8 equivalents of malonyl-CoA into C 14 -C 18 acyl-ACP species. One or two reducing equivalents of NAD(P)H are utilized in each round of chain elongation. Whereas most of the resulting fatty acyl chains are directly harnessed for phospholipid biosynthesis, the cytoplasmic mutant of the periplasmic thioesterase, TesA, is capable of releasing free fatty acids via hydrolysis of acyl-...

The ongoing global novel coronavirus pneumonia COVID‐19 outbreak has engendered numerous cases of infection and death. COVID‐19 diagnosis relies upon nucleic acid detection; however, currently recommended methods exhibit high false‐negative rates and are unable to identify other respiratory virus infections, thereby resulting in patient misdiagnosis and impeding epidemic containment. Combining the advantages of targeted amplification and long‐read, real‐time nanopore sequencing, herein, nanopore targeted sequencing (NTS) is developed to detect SARS‐CoV‐2 and other respiratory viruses simultaneously within 6–10 h, with a limit of detection of ten standard plasmid copies per reaction. Compared with its specificity for five common respiratory viruses, the specificity of NTS for SARS‐CoV‐2 reaches 100%. Parallel testing with approved real‐time reverse transcription‐polymerase chain reaction kits for SARS‐CoV‐2 and NTS using 61 nucleic acid samples from suspected COVID‐19 cases show that NTS identifies more infected patients (22/61) as positive, while also effectively monitoring for mutated nucleic acid sequences, categorizing types of SARS‐CoV‐2, and detecting other respiratory viruses in the test sample. NTS is thus suitable for COVID‐19 diagnosis; moreover, this platform can be further extended for diagnosing other viruses and pathogens.

Background: 2019-Novel coronavirus (2019-nCoV) outbreaks create challenges for hospital laboratories because thousands of samples must be evaluated each day. Sample types, interpretation methods, and corresponding laboratory standards must be established. The possibility of other infections should be assessed to provide a basis for clinical classification, isolation, and treatment. Accordingly, in the present study, we evaluated the testing methods for 2019-nCoV and co-infections. Methods: We used a fluorescence-based quantitative PCR kit urgently distributed by the Chinese CDC to detect 8274 close contacts in the Wuhan region against two loci on the 2019-nCoV genome. We also analyzed 613 patients with fever who underwent multiple tests for 13 respiratory pathogens; 316 subjects were also tested for 2019-nCoV. Findings: Among the 8274 subjects, 2745 (33.2%) had 2019-nCoV infection; 5277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test (non-019-nCoV); and 252 cases (3.0%) because only one target was positive, the diagnosis was not definitive. Sixteen patients who originally had only one positive target were re-examined a few days later; 14 patients (87.5%) were finally defined as 2019-nCoV-positive, and 2 (12.5%) were finally defined as negative. The positive rates of nCoV-NP and nCovORF1ab were 34.7% and 34.7%, respectively. nCoV-NP-positive only and nCovORF1ab-positive cases accounted for 1.5% and 1.5%, respectively. In the 316 patients with multiple respiratory pathogens, 104 were positive for 2019-nCov and 6/104 had co-infection with coronavirus (3/104), influenza A virus (2/104), rhinovirus (2/104), and influenza A H3N2 (1/104); the remaining 212 patients had influenza A virus (11/202), influenza A H3N2 (11/202), rhinovirus (10/202), respiratory syncytial virus (7/202), influenza B virus (6/202), metapneumovirus (4/202), and coronavirus (2/202). Interpretation: Clinical testing methods for 2019-nCoV require improvement. Importantly, 5.8% of 2019-nCoV infected and 18.4% of non-2019-nCoV-infected patients had other pathogen infections. It is important to treat combined infections and perform rapid screening to avoid cross-contamination of patients. A test that quickly and simultaneously screens as many pathogens as possible is needed.