Analysis of genomic differences among Clostridium botulinum type A1 strains

<p>Abstract</p> <p>Background</p> <p>Type A1 <it>Clostridium botulinum </it>strains are a group of Gram-positive, spore-forming anaerobic bacteria that produce a genetically, biochemically, and biophysically indistinguishable 150 kD protein that causes botulism. The genomes of three type A1 <it>C. botulinum </it>strains have been sequenced and show a high degree of synteny. The purpose of this study was to characterize differences among these genomes and compare these differentiating features with two additional unsequenced strains used in previous studies.</p> <p>Results</p> <p>Several strategies were deployed in this report. First, University of Massachusetts Dartmouth laboratory Hall strain (UMASS strain) neurotoxin gene was amplified by PCR and sequenced; its sequence was aligned with the published ATCC 3502 Sanger Institute Hall strain and Allergan Hall strain neurotoxin gene regions. Sequence alignment showed that there was a synonymous single nucleotide polymorphism (SNP) in the region encoding the heavy chain between Allergan strain and ATCC 3502 and UMASS strains. Second, comparative genomic hybridization (CGH) demonstrated that the UMASS strain and a strain expected to be derived from ATCC 3502 in the Centers for Disease Control and Prevention (CDC) laboratory (ATCC 3502*) differed in gene content compared to the ATCC 3502 genome sequence published by the Sanger Institute. Third, alignment of the three sequenced <it>C. botulinum </it>type A1 strain genomes revealed the presence of four comparable blocks. Strains ATCC 3502 and ATCC 19397 share the same genome organization, while the organization of the blocks in strain Hall were switched. Lastly, PCR was designed to identify UMASS and ATCC 3502* strain genome organizations. The PCR results indicated that UMASS strain belonged to Hall type and ATCC 3502* strain was identical to ATCC 3502 (Sanger Institute) type.</p> <p>Conclusions</p> <p>Taken together, <it>C. botulinum </it>type A1 strains including Sanger Institute ATCC 3502, ATCC 3502*, ATCC 19397, Hall, Allergan, and UMASS strains demonstrate differences at the level of the neurotoxin gene sequence, in gene content, and in genome arrangement.</p

Molecular mechanisms of the activation of type A botulinum neurotoxin endopeptidase

Clostridial neurotoxins (BoNTs) are among the most toxic substances presently known. They are a unique group of metalloproteases which catalyze single site cleavage of specific proteins involved in the docking and fusion of synaptic vesicles with plasma membrane for neurotransmitter release. BoNTs are classified into seven distinct serotypes, designated as A to G. Botulinum neurotoxins type A (BoNT/A) is produced by Clostridium botulinum type A as a complex with a group of neurotoxin associated proteins (NAPs). Our results suggest that the bacterial production of NAPs along with BoNT is designed for the NAPs to play an accessory role in the neurotoxin function, in contrast to their previously known limited role in protecting the neurotoxin in the GI tract and in the external environment. We have examined the structure of BoNT/A in aqueous solution, and found the structure in aqueous solution differs dramatically from that resolved by x-ray crystallography, both at secondary and quaternary levels. In terms of secondary structure, BoNT/A in aqueous solution has about 47% β-sheet structure as revealed by infrared spectroscopy, while x-ray crystallography revealed only 17% β-sheet structure. In terms of quaternary structure, BoNT/A exists as a dimer in aqueous solution, which contrasts with the reported monomeric structure of BoNT/A based on the x-ray crystallography. The dimeric form of BoNT/A can self-dissociate into monomeric form at a concentration lower than 50 nM. This concentration-dependent structural change has a significant impact on the endopeptidase activity of BoNT/A: the catalytic efficiency of the monomeric BoNT/A is about 4-fold higher than that of its dimeric form. This difference implies a sterically restricted catalytic site of BoNT/A in the dimeric form of BoNT/A. Reduction of disulfide bond between heavy chain and light chain of BoNTs is required for their enzymatic activity. We are investigating structural differences of BoNT/A under reducing and non-reducing conditions. Reduction of disulfide bond between heavy and light chains of BoNT/A induced a molten globule conformation at physiological temperature (37°C). This molten globule conformation of BoNT/A has been proven to be the enzymatically active structure

Neuroprotective Effects of Blueberries through Inhibition on Cholinesterase, Tyrosinase, Cyclooxygenase-2, and Amyloidogenesis

Blueberries are rich in polyphenolic compounds and have shown improvement in cognitive function in several clinical trials. The molecular basis of the neuronal protection of blueberries, however, is not fully understood. The objective of this research is to understand the biochemistry basis of neuronal protection effects of blueberries through their impacts on several enzymes and pathways involved in Alzheimer&rsquo;s disease (AD) and other neurodegenerative diseases. We examined the inhibition effects of blueberries on the enzymatic activity of cholinesterase (acetylcholinesterase, AChE; and butyrylcholinesterase, BuChE), tyrosinase, and cyclooxygenase-2 (COX-2). The effects of blueberries on the biosynthesis of acetylcholinesterase in a cellular model were also studied. Further, the effect of blueberries on amyloid fibril formation was evaluated. Our results showed that blueberries directly inhibit the enzymatic activity of AChE, BuChE, tyrosinase, and COX-2, with the IC50 at 48 mg/mL, 9 mg/mL, 403 mg/mL, and 12 mg/mL of fresh berry equivalent, respectively. Further, blueberries delay the amyloid fibril formation by 24 h at 39 mg fresh berry/mL. It also reduces the synthesis of acetylcholinesterase synthesis at 19 mg fresh berry/mL in a cellular model. Those results suggested that the neuroprotection effects of blueberries may involve different pathways, including enhancing cholinergic signaling through their effect on cholinesterase, reducing neuroinflammation through inhibition of COX-2, and reducing amyloid formation. Collectively, blueberries may play a vital role in neuronal protection beyond their antioxidant activity and our results provide more molecular mechanisms for their neuroprotective effects, and support blueberries being nutraceutical to improve cognitive function

Clostridial Neurotoxins: Structure, Function and Implications to Other Bacterial Toxins

Gram-positive bacteria are ancient organisms. Many bacteria, including Gram-positive bacteria, produce toxins to manipulate the host, leading to various diseases. While the targets of Gram-positive bacterial toxins are diverse, many of those toxins use a similar mechanism to invade host cells and exert their functions. Clostridial neurotoxins produced by Clostridial tetani and Clostridial botulinum provide a classical example to illustrate the structure–function relationship of bacterial toxins. Here, we critically review the recent progress of the structure–function relationship of clostridial neurotoxins, including the diversity of the clostridial neurotoxins, the mode of actions, and the flexible structures required for the activation of toxins. The mechanism clostridial neurotoxins use for triggering their activity is shared with many other Gram-positive bacterial toxins, especially molten globule-type structures. This review also summarizes the implications of the molten globule-type flexible structures to other Gram-positive bacterial toxins. Understanding these highly dynamic flexible structures in solution and their role in the function of bacterial toxins not only fills in the missing link of the high-resolution structures from X-ray crystallography but also provides vital information for better designing antidotes against those toxins

Multi-Objective Optimization of CNC Turning Process Parameters Considering Transient-Steady State Energy Consumption

Energy-saving and emission reduction are recognized as the primary measure to tackle the problems associated with climate change, which is one of the major challenges for humanity for the forthcoming decades. Energy modeling and process parameters optimization of machining are effective and powerful ways to realize energy saving in the manufacturing industry. In order to realize high quality and low energy consumption machining of computer numerical control (CNC) lathe, a multi-objective optimization of CNC turning process parameters considering transient-steady state energy consumption is proposed. By analyzing the energy consumption characteristics in the process of machining and introducing practical constraints, such as machine tool equipment performance and tool life, a multi-objective optimization model with turning process parameters as optimization variables and high quality and low energy consumption as optimization objectives is established. The model is solved by non-dominated sorting genetic algorithm-II (NSGA-II), and the pareto optimal solution set of the model is obtained. Finally, the machining process of shaft parts is studied by CK6153i CNC lathe. The results show that 38.3% energy consumption is saved, and the surface roughness of workpiece is reduced by 47.0%, which verifies the effectiveness of the optimization method

Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data

With the enactment of privacy-preserving regulations, e.g., GDPR, federated SVD is proposed to enable SVD-based applications over different data sources without revealing the original data. However, many SVD-based applications cannot be well supported by existing federated SVD solutions. The crux is that these solutions, adopting either differential privacy (DP) or homomorphic encryption (HE), suffer from accuracy loss caused by unremovable noise or degraded efficiency due to inflated data. In this paper, we propose FedSVD, a practical lossless federated SVD method over billion-scale data, which can simultaneously achieve lossless accuracy and high efficiency. At the heart of FedSVD is a lossless matrix masking scheme delicately designed for SVD: 1) While adopting the masks to protect private data, FedSVD completely removes them from the final results of SVD to achieve lossless accuracy; and 2) As the masks do not inflate the data, FedSVD avoids extra computation and communication overhead during the factorization to maintain high efficiency. Experiments with real-world datasets show that FedSVD is over 10000 times faster than the HE-based method and has 10 orders of magnitude smaller error than the DP-based solution on SVD tasks. We further build and evaluate FedSVD over three real-world applications: principal components analysis (PCA), linear regression (LR), and latent semantic analysis (LSA), to show its superior performance in practice. On federated LR tasks, compared with two state-of-the-art solutions: FATE and SecureML, FedSVD-LR is 100 times faster than SecureML and 10 times faster than FATE.Comment: 10 page