Protein aggregation and therapeutic strategies in SOD1- and TDP-43- linked ALS

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with severe socio-economic impact. A hallmark of ALS pathology is the presence of aberrant cytoplasmic inclusions composed of misfolded and aggregated proteins, including both wild-type and mutant forms. This review highlights the critical role of misfolded protein species in ALS pathogenesis, particularly focusing on Cu/Zn superoxide dismutase (SOD1) and TAR DNA-binding protein 43 (TDP-43), and emphasizes the urgent need for innovative therapeutic strategies targeting these misfolded proteins directly. Despite significant advancements in understanding ALS mechanisms, the disease remains incurable, with current treatments offering limited clinical benefits. Through a comprehensive analysis, the review focuses on the direct modulation of the misfolded proteins and presents recent discoveries in small molecules and peptides that inhibit SOD1 and TDP-43 aggregation, underscoring their potential as effective treatments to modify disease progression and improve clinical outcomes

Expression of active human sialyltransferase ST6GalNAcI in Escherichia coli

Georgios Skretas, Sean Carroll, and George Georgiou are with the Department of Chemical Engineering, University of Texas at Austin, Austin, TX 78712, USA -- George Georgiou is with the Department of Biomedical Engineering, University of Texas at Austin and the Section of Microbiology and Molecular Genetics, University of Texas at Austin, Austin, TX 78712, USA -- Georgios Skretas and George Georgiou are with the Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA -- Shawn DeFrees, Karl F. Johnson, and Marc F. Schwartz are with Neose Technologies Inc, 102 Rock Road, Horsham, PA, 19044, USABackground: The presence of terminal, surface-exposed sialic acid moieties can greatly enhance the in vivo half-life of glycosylated biopharmaceuticals and improve their therapeutic efficacy. Complete and homogeneous sialylation of glycoproteins can be efficiently performed enzymically in vitro but this process requires large amounts of catalytically active sialyltransferases. Furthermore, standard microbial hosts used for large-scale production of recombinant enzymes can only produce small quantities of glycosyltransferases of animal origin, which lack catalytic activity. Results and conclusion: In this work, we have expressed the human sialyltransferase ST6GalNAc I (ST6), an enzyme that sialylates O-linked glycoproteins, in Escherichia coli cells. We observed that wild-type bacterial cells are able to produce only very small amounts of soluble ST6 enzyme. We have found, however, that engineered bacterial strains which possess certain types of oxidative cytoplasm or which co-express the molecular chaperones/co-chaperones trigger factor, DnaK/DnaJ, GroEL/GroES, and Skp, can produce greatly enhanced amounts of soluble ST6. Furthermore, we have developed a novel high-throughput assay for the detection of sialyltransferase activity and used it to demonstrate that the bacterially expressed ST6 enzyme is active and able to transfer sialic acid onto a desialylated O-glycoprotein, bovine submaxillary mucin. To the best of our knowledge, this is the first example of expression of active human sialyltransferase in bacteria. This system may be used as a starting point for the evolution of sialyltransferases with better expression characteristics or altered donor/acceptor specificities.Chemical EngineeringBiomedical EngineeringInstitute for Cellular and Molecular [email protected]

Multi-copy genes that enhance the yield of mammalian G protein-coupled receptors in Escherichia coli

Low yields of recombinant expression represent a major barrier to the physical characterization of membrane proteins. Here, we have identified genes that globally enhance the production of properly folded G protein-coupled receptors (GPCRs) in Escherichia coli. Libraries of bacterial chromosomal fragments were screened using two separate systems that monitor: (i) elevated fluorescence conferred by enhanced expression of GPCR–GFP fusions and (ii) increased binding of fluorescent ligand in cells producing more active receptor. Three multi-copy hits were isolated by both methods: nagD, encoding the ribonucleotide phosphatase NagD; a fragment of nlpD, encoding a truncation of the predicted lipoprotein NlpD, and the three-gene cluster ptsN–yhbJ–npr, encoding three proteins of the nitrogen phosphotransferase system. Expression of these genes resulted in a 3- to 10-fold increase in the yields of different mammalian GPCRs. Our data is consistent with the hypothesis that the expression of these genes may serve to maintain the integrity of the bacterial periplasm and to provide a favorable environment for proper membrane protein folding, possibly by inducing a fine-tuned stress response and/or via modifying the composition of the bacterial cell envelope

Strain engineering for improved expression of recombinant proteins in bacteria

Tomohiro Makino and George Georgiou are with the Department of Chemical Engineering, The University of Texas at Austin and the Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas 78712, USA -- George Gerorgiou is with the Department of Biomedical Engineering, The University of Texas at Austin and the Section of Molecular Genetics and Microbiology, The University of Texas at Austin, Austin, Texas 78712, USA -- Georgios Skretas is with the Insitute of Biological Research and Biotechnology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635 Athens, Greece -- Tomohiro Makino is with the Asubio Pharma CO., LTD. 6-4-3, Minatojima-Minamimachi Chuo-ku, Kobe 650-0047, JapanProtein expression in Escherichia coli represents the most facile approach for the preparation of non-glycosylated proteins for analytical and preparative purposes. So far, the optimization of recombinant expression has largely remained a matter of trial and error and has relied upon varying parameters, such as expression vector, media composition, growth temperature and chaperone co-expression. Recently several new approaches for the genome-scale engineering of E. coli to enhance recombinant protein expression have been developed. These methodologies now enable the generation of optimized E. coli expression strains in a manner analogous to metabolic engineering for the synthesis of low-molecular-weight compounds. In this review, we provide an overview of strain engineering approaches useful for enhancing the expression of hard-to-produce proteins, including heterologous membrane proteins.Chemical EngineeringInstitute for Cellular and Molecular BiologyBiomedical EngineeringMolecular [email protected]

Distributed Computation and Reconfiguration in Actively Dynamic Networks

We study here systems of distributed entities that can actively modify their communication network. This gives rise to distributed algorithms that apart from communication can also exploit network reconfiguration to carry out a given task. Also, the distributed task itself may now require a global reconfiguration from a given initial network Gs to a target network Gf from a desirable family of networks. To formally capture costs associated with creating and maintaining connections, we define three edge-complexity measures: the total edge activations, the maximum activated edges per round, and the maximum activated degree of a node. We give (poly)log(n) time algorithms for the task of transforming any Gs into a Gf of diameter (poly)log(n), while minimizing the edge-complexity. Our main lower bound shows that Ω(n) total edge activations and Ω(n/logn) activations per round must be paid by any algorithm (even centralized) that achieves an optimum of Θ(logn) rounds. We give three distributed algorithms for our general task. The first runs in O(logn) time, with at most 2n active edges per round, a total of O(nlogn) edge activations, a maximum degree n−1, and a target network of diameter 2. The second achieves bounded degree by paying an additional logarithmic factor in time and in total edge activations. It gives a target network of diameter O(logn) and uses O(n) active edges per round. Our third algorithm shows that if we slightly increase the maximum degree to polylog(n) then we can achieve o(log2n) running time