Kinetic, mutagenic, and structural homology analysis of L-serine dehydratase from Legionella pneumophila

A structural database search has revealed that the same fold found in the allosteric substrate binding (ASB) domain of Mycobacterium tuberculosis D-3-phosphoglycerate dehydrogenase (PGDH) is found in l-serine dehydratase from Legionella pneumophila. The M. tuberculosis PGDH ASB domain functions in the control of catalytic activity. Bacterial l-serine dehydratases are 4Fe-4S proteins that convert l-serine to pyruvate and ammonia. Sequence homology reveals two types depending on whether their α and β domains are on the same (Type 2) or separate (Type 1) polypeptides. The α domains contain the catalytic iron-sulfur center while the β domains do not yet have a described function, but the structural homology with PGDH suggests a regulatory role. Type 1 β domains also contain additional sequence homologous to PGDH ACT domains. A continuous assay for l-serine dehydratase is used to demonstrate homotropic cooperativity, a broad pH range, and essential irreversibility. Product inhibition analysis reveals a Uni-Bi ordered mechanism with ammonia dissociating before pyruvate. l-Threonine is a poor substrate and l-cysteine and d-serine are competitive inhibitors with K(i) values that differ by almost 10-fold from those reported for Escherichia colil-serine dehydratase. Mutagenesis identifies the three cysteine residues at the active site that anchor the iron-sulfur complex.     

Simultaneous quantification of malonyl-CoA and several other short-chain acyl-CoAs in animal tissues by ion-pairing reversed-phase HPLC/MS

Malonyl-CoA is a key intermediate involved in lipid synthesis and lipid oxidation. Here, we report on a novel method for the quantification of malonyl-CoA and seven other short-chain acyl-CoAs in various rat and mouse tissues using ion-pairing reversed-phase HPLC/MS. This method is capable of measuring malonyl-CoA, free coenzyme A (CoASH), acetyl-CoA, beta-hydroxyl-butyryl-CoA (HB-CoA), 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA), propionyl-CoA, succinyl-CoA, and isobutyryl-CoA simultaneously with a dynamic linear range over two orders of magnitude in a 7.0 min HPLC gradient run. The lower limit of quantification (LLOQ) was 0.225 pmol for all acyl-CoAs studied, except for HMG-CoA which had a higher LLOQ of 0.90 pmol. The interference of HB-CoA on the quantification of malonyl-CoA in animal tissues was also explored for the first time.     

Physical and biochemical characterization of a simple intermediate between fluidized and expanded bed contactors

Physical and biochemical comparison has been made of the performance of a simple fluidised bed contactor and a commercial expanded bed contactor, characterised by identical dimensions, and operated at various settled bed heights with two anion exchange adsorbents. The contactors were tested with various feedstocks comprising bovine albumin in the absence and presence of 20 g dry cell weight biomass litre^-1. Earlier classification of the simple contactor as a single-stage, well mixed fluidised bed is reviewed. The relative merits of STREAMLINE DEAE and DEAE Spherodex LS as fluidisable, anion exchange adsorbents are discussed.     

EGFR T790M Mutation as a Possible Target for Immunotherapy; Identification of HLA-A*0201-Restricted T Cell Epitopes Derived from the EGFR T790M Mutation

Treatment with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib and erlotinib, has achieved high clinical response rates in patients with non–small cell lung cancers (NSCLCs). However, over time, most tumors develop acquired resistance to EGFR-TKIs, which is associated with the secondary EGFR T790M resistance mutation in about half the cases. Currently there are no effective treatment options for patients with this resistance mutation. Here we identified two novel HLA-A*0201 (A2)-restricted T cell epitopes containing the mutated methionine residue of the EGFR T790M mutation, T790M-5 (MQLMPFGCLL) and T790M-7 (LIMQLMPFGCL), as potential targets for EGFR-TKI-resistant patients. When peripheral blood cells were repeatedly stimulated in vitro with these two peptides and assessed by antigen-specific IFN-γ secretion, T cell lines responsive to T790M-5 and T790M-7 were established in 5 of 6 (83%) and 3 of 6 (50%) healthy donors, respectively. Additionally, the T790M-5- and T790M-7-specific T cell lines displayed an MHC class I-restricted reactivity against NSCLC cell lines expressing both HLA-A2 and the T790M mutation. Interestingly, the NSCLC patients with antigen-specific T cell responses to these epitopes showed a significantly less frequency of EGFR-T790M mutation than those without them [1 of 7 (14%) vs 9 of 15 (60%); chi-squared test, p  =  0.0449], indicating the negative correlation between the immune responses to the EGFR-T790M-derived epitopes and the presence of EGFR-T790M mutation in NSCLC patients. This finding could possibly be explained by the hypothesis that immune responses to the mutated neo-antigens derived from T790M might prevent the emergence of tumor cell variants with the T790M resistance mutation in NSCLC patients during EGFR-TKI treatment. Together, our results suggest that the identified T cell epitopes might provide a novel immunotherapeutic approach for prevention and/or treatment of EGFR-TKI resistance with the secondary EGFR T790M resistance mutation in NSCLC patients.     

Microplastics in soil-plant system: effects of nano/microplastics on plant photosynthesis,rhizosphere microbes and soil properties in soil with different residues

Plant and Soil - To investigate the effects of polystyrene microplastics (PS-beads) on the soil properties, photosynthesis of Flowering Chinese cabbage, the rhizosphere microbial community and...     

镉对长江华溪蟹心肌细胞超微结构的影响

应用透射电镜方法,研究了镉在24h内对长江华溪触心肌细胞超微结构的影响。结果表明：注射镉后0.5h,心肌细胞超微结构即出现变化,且随着时间的延长,变化渐趋明显,主要表现在细胞核和线粒体。细胞核核膜肿胀、弥散、最后解体。线粒体嵴部分解体、直至全部解体;线粒体内室部分肿胀、明显肿胀、直至高度肿胀。此外,溶酶体的数量和类型随镉处理时间的延长而增多,肌原纤维出现断裂。     

Bone morphogenetic protein 2 signaling in osteoclasts is negatively regulated by the BMP antagonist, twisted gastrulation

Bone morphogenetic proteins (BMPs) have been shown to regulate both osteoblasts and osteoclasts. We previously reported that BMP2 could directly enhance RANKL-mediated osteoclast differentiation by increasing the size and number of osteoclasts. Similarly, genetic deletion of the BMP antagonist Twisted gastrulation (TWSG1) in mice, resulted in an enhancement of osteoclast formation, activity and osteopenia. This was accompanied by increased levels of phosphorylated Smad (pSmad) 1/5/8 in Twsg1(-/-) osteoclasts in vitro. The purpose of this study was to develop an adenoviral vector overexpressing Twsg1 as a means of inhibiting osteoclast activity. We demonstrate that overexpressing TWSG1 in primary osteoclasts decreased the size and number of multinuclear TRAP-positive osteoclasts, expression of osteoclast genes, and resorption ability. Overexpression of TWSG1 did not affect osteoclast proliferation or apoptosis. However, overexpression of TWSG1 decreased the levels of pSmad 1/5/8 in osteoclasts. Addition of exogenous BMP2 to osteoclasts overexpressing TWSG1 rescued the size and levels of pSmad 1/5/8 compared to cultures infected with a control virus. Finally, TWSG1 overexpression in osteoclasts isolated from the Twsg1(-/-) mice rescued size of the osteoclasts while further addition of exogenous BMP2 reversed the effect of TWSG1 overexpression and increased the size of the osteoclasts similar to control virus infected cells. Taken together, we demonstrate that overexpressing TWSG1 in osteoclasts via an adenoviral vector results in inhibition of osteoclastogenesis and may provide a potential therapy for inhibiting osteoclast activity in a localized manner.     

Identification of Targeted Analyte Clusters for Studies of Schizophrenia

The search for biomarkers to diagnose psychiatric disorders such as schizophrenia has been underway for decades. Many molecular profiling studies in this field have focused on identifying individual marker signals that show significant differences in expression between patients and the normal population. However, signals for multiple analyte combinations that exhibit patterned behaviors have been less exploited. Here, we present a novel approach for identifying biomarkers of schizophrenia using expression of serum analytes from first onset, drug-naïve patients and normal controls. The strength of patterned signals was amplified by analyzing data in reproducing kernel spaces. This resulted in the identification of small sets of analytes referred to as targeted clusters that have discriminative power specifically for schizophrenia in both human and rat models. These clusters were associated with specific molecular signaling pathways and less strongly related to other neuropsychiatric disorders such as major depressive disorder and bipolar disorder. These results shed new light concerning how complex neuropsychiatric diseases behave at the pathway level and demonstrate the power of this approach in identification of disease-specific biomarkers and potential novel therapeutic strategies.Schizophrenia is a debilitating neuropsychiatric disorder that affects more than 1% of the world population and costs hundreds of billions of United States dollars in healthcare provision and lost earnings (1). The diagnosis of this disease has not changed substantially over several decades and currently relies on subjective psychopathological ratings such as the Diagnostic and Statistical Manual of Mental Disorders (DSM)1-IV. Thus, diagnosis can be complicated by the presence of overlapping symptoms frequently occurring in other psychiatric illnesses such as bipolar disorder (BD) and major depressive disorder (MDD) and by the presence of confounding factors such as drug abuse and co-morbidities. This often results in diagnosis being delayed for several months to years. A delay in establishing an accurate diagnosis can have serious deleterious implications because a late or imprecise diagnosis can contribute to unsatisfactory outcomes to currently used drug therapies and to higher rates of relapse (2). Most importantly, more than half of schizophrenia subjects develop a progressive course of the disease associated with deficit symptoms (3).In contrast, early therapeutic intervention holds promise in preventing or diminishing such effects (4–6). An empirical assay for early and accurate diagnosis of schizophrenia would deliver improved patient outcomes and reduce the costs of the disease for healthcare services and society (7–9). Such an assay could also provide a means of stratifying patients and monitoring drug responses and may also lead to the development of translational medicine tools that are critical for discovery of novel therapeutic strategies. Molecular profiling methods that afford the simultaneous measurement of multiple analytes in clinical and preclinical samples have considerable promise in this endeavor. These methods have been aimed predominantly at identifying individual molecules that show differences in expression between the disease and control conditions. However, such studies have often been fraught with small fold-changes in analyte levels, a common obstacle when investigating complex neuropsychiatric disorders (10–12). Thus, standard statistical techniques such as t tests will not be able to explore patterned behaviors involving proteins that have subtle expression changes but still contribute to the development of schizophrenia.The main objective of this study was to determine whether unique patterns of biomarkers can be identified for subjects with first onset antipsychotic-naïve schizophrenia. Analyte expression lists were generated using the Multi-Analyte Profiling (MAP®) fluorescent bead-based technology for profiling serum samples from 77 male schizophrenia patients and 66 matched male controls. For comparison with other psychiatric disorders, we also analyzed the serum samples of 13 male BD and 17 male MDD patients. In parallel, serum samples from four relevant animal models were also profiled for comparison with the human disease state. Analysis of the respective expression lists was carried out using non-linear statistical analysis, which identifies small sets of analytes called targeted analyte clusters (TACs) that have the power to discriminate the patients from normal controls. We present here the performance of these clusters for diagnosis of schizophrenia. In addition, we show how this method can also contribute to increasing our understanding of the etiology of the disorder by determining its ability to classify various preclinical models of psychiatric disorders. The biological pathways associated with these clusters are discussed with their relevance to schizophrenia.