Cryo-EM structure of amyloid fibril formed by α-synuclein hereditary A53E mutation reveals a distinct protofilament interface.

Synucleinopathies like Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple systems atrophy (MSA), have the same pathologic feature of misfolded α-synuclein protein (α-syn) accumulation in the brain. PD patients who carry α-syn hereditary mutations tend to have earlier onset and more severe clinical symptoms than sporadic PD patients. Therefore, revealing the effect of hereditary mutations to the α-syn fibril structure can help us understand these synucleinopathies' structural basis. Here, we present a 3.38 Å cryo-electron microscopy structure of α-synuclein fibrils containing the hereditary A53E mutation. The A53E fibril is symmetrically composed of two protofilaments, similar to other fibril structures of WT and mutant α-synuclein. The new structure is distinct from all other synuclein fibrils, not only at the interface between proto-filaments, but also between residues packed within the same proto-filament. A53E has the smallest interface with the least buried surface area among all α-syn fibrils, consisting of only two contacting residues. Within the same protofilament, A53E reveals distinct residue re-arrangement and structural variation at a cavity near its fibril core. Moreover, the A53E fibrils exhibit slower fibril formation and lower stability compared to WT and other mutants like A53T and H50Q, while also demonstrate strong cellular seeding in α-synuclein biosensor cells and primary neurons. In summary, our study aims to highlight structural differences - both within and between the protofilaments of A53E fibrils - and interpret fibril formation and cellular seeding of α-synuclein pathology in disease, which could further our understanding of the structure-activity relationship of α-synuclein mutants.

Engineering the thermal stability of a polyphosphate kinase by ancestral sequence reconstruction to expand the temperature boundary for an industrially applicable ATP regeneration system.

ATP-dependent energy-consuming enzymatic reactions are widely used in cell-free biocatalysis. However, the direct addition of large amounts of expensive ATP can greatly increase cost, and enzymatic production is often difficult to achieve as a result. Although a polyphosphate kinase (PPK)-polyphosphate-based ATP regeneration system has the potential to solve this challenge, the generally poor thermal stability of PPKs limits the widespread use of this method. In this paper, we evaluated the thermal stability of a PPK from Sulfurovum lithotrophicum (SlPPK2). After directed evolution and computation-supported design, we found that SlPPK2 is very recalcitrant and cannot acquire beneficial mutations. Inspired by the usually outstanding stability of ancestral enzymes, we reconstructed the ancestral sequence of the PPK family and used it as a guide to construct three heat-stable variants of SlPPK2, of which the L35F/T144S variant has a half-life of more than 14 h at 60°C. Molecular dynamics simulations were performed on all enzymes to analyze the reasons for the increased thermal stability. The results showed that mutations at these two positions act synergistically from the interior and surface of the protein, leading to a more compact structure. Finally, the robustness of the L35F/T144S variant was verified in the synthesis of nucleotides at high temperature. In practice, the use of this high-temperature ATP regeneration system can effectively avoid byproduct accumulation. Our work extends the temperature boundary of ATP regeneration and has great potential for industrial applications.IMPORTANCEATP regeneration is an important basic applied study in the field of cell-free biocatalysis. Polyphosphate kinase (PPK) is an enzyme tool widely used for energy regeneration during enzymatic reactions. However, the thermal stability of the PPKs reported to date that can efficiently regenerate ATP is usually poor, which greatly limits their application. In this study, the thermal stability of a difficult-to-engineer PPK from Sulfurovum lithotrophicum was improved, guided by an ancestral sequence reconstruction strategy. The optimal variant has a 4.5-fold longer half-life at 60°C than the wild-type enzyme, thus enabling the extension of the temperature boundary for ATP regeneration. The ability of this variant to regenerate ATP was well demonstrated during high-temperature enzymatic production of nucleotides.

The α-synuclein hereditary mutation E46K unlocks a more stable, pathogenic fibril structure.

Aggregation of α-synuclein is a defining molecular feature of Parkinson's disease, Lewy body dementia, and multiple systems atrophy. Hereditary mutations in α-synuclein are linked to both Parkinson's disease and Lewy body dementia; in particular, patients bearing the E46K disease mutation manifest a clinical picture of parkinsonism and Lewy body dementia, and E46K creates more pathogenic fibrils in vitro. Understanding the effect of these hereditary mutations on α-synuclein fibril structure is fundamental to α-synuclein biology. We therefore determined the cryo-electron microscopy (cryo-EM) structure of α-synuclein fibrils containing the hereditary E46K mutation. The 2.5-Å structure reveals a symmetric double protofilament in which the molecules adopt a vastly rearranged, lower energy fold compared to wild-type fibrils. We propose that the E46K misfolding pathway avoids electrostatic repulsion between K46 and K80, a residue pair which form the E46-K80 salt bridge in the wild-type fibril structure. We hypothesize that, under our conditions, the wild-type fold does not reach this deeper energy well of the E46K fold because the E46-K80 salt bridge diverts α-synuclein into a kinetic trap-a shallower, more accessible energy minimum. The E46K mutation apparently unlocks a more stable and pathogenic fibril structure.

A cocktail of protein engineering strategies: Breaking the enzyme bottleneck one by one for high UTP production in vitro.

The pyrimidine metabolic pathway is tightly regulated in microorganisms, allowing limited success in metabolic engineering for the production of pathway-related substances. Here, we constructed a four-enzyme coupled system for the in vitro production of uridine triphosphate (UTP). The enzymes used include nucleoside kinase, uridylate kinase, nucleoside diphosphate kinase, and polyphosphate kinase for energy regeneration. All these enzymes are derived from extremophiles. To increase the total and unit time yield of the product, three enzymes other than polyphosphate kinase were modified separately by multiple protein engineering strategies. A nucleoside kinase variant with increased specific activity from 2.7 to 36.5 U/mg, a uridylate kinase variant (specific activity of 37.1 U/mg) with a 5.2-fold increase in thermostability, and a nucleoside diphosphate kinase variant with a 2-fold increase in a specific activity to over 900 U/mg were obtained, respectively. The reaction conditions of the coupled system were further optimized, and a two-stage method was taken to avoid the problem of enzymatic pH adaptation mismatch. Under optimal conditions, this system can produce more than 65 mM UTP (31.5 g/L) in 3.0 h. The substrate conversion rate exceeded 98% and the maximum UTP productivity reached 40 mM/h.

CT-based radiomics signature analysis for evaluation of response to induction chemotherapy and progression-free survival in locally advanced hypopharyngeal carcinoma.

OBJECTIVES: To establish and validate a CT radiomics model for prediction of induction chemotherapy (IC) response and progression-free survival (PFS) among patients with locally advanced hypopharyngeal carcinoma (LAHC). METHODS: One hundred twelve patients with LAHC (78 in training cohort and 34 in validation cohort) who underwent contrast-enhanced CT (CECT) scans prior to IC were enrolled. Least absolute shrinkage and selection operator (LASSO) was used to select the crucial radiomic features in the training cohort. Radiomics signature and clinical data were used to build a radiomics nomogram to predict individual response to IC. Kaplan-Meier analysis and log-rank test were used to evaluate ability of radiomics signature in progression-free survival risk stratification. RESULTS: The radiomics signature consisted of 6 selected features from the arterial and venous phases of CECT images and demonstrated good performance in predicting the IC response in both two cohorts. The radiomics nomogram showed good discriminative performance, and the C-index of nomogram was 0.899 (95% confidence interval (CI), 0.831-0.967) and 0.775 (95% CI, 0.591-0.959) in the training and validation cohorts, respectively. Survival analysis indicated that low-risk and high-risk groups defined by the value of radiomics signature had significant difference in PFS (3-year PFS 66.4% vs 29.7%, p < 0.001). CONCLUSIONS: Multiparametric CT-based radiomics model could be useful for predicting treatment response and PFS in patients with LAHC who underwent IC. KEY POINTS: • CT radiomics can predict IC response and progression-free survival in hypopharyngeal carcinoma. • We combined significant radiomics signature with clinical predictors to establish a nomogram to predict individual response to IC. • Radiomics signature could divide patients into the high-risk and low-risk groups based on the PFS.

Computed tomography-based radiomics signature as a pretreatment predictor of progression-free survival in locally advanced hypopharyngeal carcinoma with a different response to induction chemotherapy.

PURPOSE: To establish and validate a radiomics signature for stratifying the risk of progression-free survival (PFS) in patients with locally advanced hypopharyngeal carcinoma (LAHC) undergoing induction chemotherapy (IC). METHODS: We extracted radiomics features from baseline contrast-enhanced computed tomography (CECT) images. We enrolled 112 LAHC patients (78 in the training cohort and 34 in the validation cohort). We used cox regression model and random survival forests variable hunting (RSFVH) algorithm for feature selection and radiomics signature building. The radiomics signature was established in the training cohort and tested in the validation cohort. We used the Kaplan-Meier analysis and log-rank test to evaluate the ability of radiomics signature in PFS risk stratification among patients with different IC responses and constructed a radiomics nomogram to predict individual PFS risk. RESULTS: The radiomics signature performed well in stratifying patients into highrisk and low-risk groups of progression in both the training and validation cohorts. The radiomics nomogram showed good discriminative ability for predicting PFS. Survival outcome analysis of subsets indicated that the radiomics signature performed well in stratifying the risk of PFS in patients with LAHC with different IC responses. CONCLUSIONS: The radiomics signature was a pretreatment predictor for PFS in patients with LAHC who exhibited different responses to IC.

Conformational Dynamics, Intramolecular Domain Conformation Signaling, and Activation of Apo-FimD Revealed by Single-Molecule Fluorescence Resonance Energy Transfer Studies.

The chaperone-usher secretion pathway is a conserved bacterial protein secretion system dedicated to the biogenesis of adhesive fibers. Usher, a multidomain-containing outer membrane protein, plays a central role in this process by acting as a molecular machine that recruits different chaperone-subunit complexes, catalyzes subunit polymerization, and forms a channel for secretion of the assembled subunits. While recent crystal structural studies have greatly advanced our understanding of the structure and function of ushers, the overall architecture of the full-length apo-usher, the molecular events that dictate conformational changes in usher during pilus biogenesis, and its activation by the specific chaperone-adhesin complex remain largely elusive. Using single-molecule fluorescence resonance energy transfer studies, we found that the substrate-free usher FimD (apo-FimD) adopts a contracted conformation that is distinct from its substrate-bound states; both the N-terminal domain (NTD) and the C-terminal domain (CTD) of apo-FimD are highly dynamic, and FimD coordinates its domain conformational changes via intramolecular domain conformation signaling. By combining these studies with in vitro photo-cross-linking studies, we further show that only the chaperone-bound adhesin (FimC:FimH) can be transferred to the CTD, dislocates the plug domain, and triggers conformational changes in the remaining FimD domains. Taken together, these studies delineate an overall architecture of the full-length apo-FimD, provide detailed mechanic insight into the activation of apo-FimD, and explain why FimD could adjust its conformational states to perform multiple functions in each cycle of pilus subunit addition and ensure that pilus assembly proceeds progressively in a cellular energy-free environment.

Engineering a Robust UDP-Glucose Pyrophosphorylase for Enhanced Biocatalytic Synthesis via ProteinMPNN and Ancestral Sequence Reconstruction.

UDP-glucose is a key metabolite in carbohydrate metabolism and plays a vital role in glycosyl transfer reactions. Its significance spans across the food and agricultural industries. This study focuses on UDP-glucose synthesis via multienzyme catalysis using dextrin, incorporating UTP production and ATP regeneration modules to reduce costs. To address thermal stability limitations of the key UDP-glucose pyrophosphorylase (UGP), a deep learning-based protein sequence design approach and ancestral sequence reconstruction are employed to engineer a thermally stable UGP variant. The engineered UGP variant is significantly 500-fold more thermally stable at 60 °C and has a half-life of 49.8 h compared to the wild-type enzyme. MD simulations and umbrella sampling calculations provide insights into the mechanism behind the enhanced thermal stability. Experimental validation demonstrates that the engineered UGP variant can produce 52.6 mM UDP-glucose within 6 h in an in vitro cascade reaction. This study offers practical insights for efficient UDP-glucose synthesis methods.

Development of non-ß-Lactam covalent allosteric inhibitors targeting PBP2a in Methicillin-Resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA), a Gram-positive bacterial pathogen, continues to pose a serious threat to the current public health system in our society. The high level of resistance to ß-lactam antibiotics in MRSA is attributed to the expression of penicillin-binding protein 2a (PBP2a), which catalyzes cell wall cross-linking. According to numerous research reports, the activity of the PBP2a protein is known to be regulated by an allosteric site distinct from the active site where cell wall cross-linking occurs. Here, we conducted a screening of 113 compounds containing a 1,3,4-oxadiazole core to design new covalent inhibitors targeting the allosteric site of PBP2a and establish their structural-activity relationship. The stereochemically selective synthesis of sulfonyl oxadiazole compounds identified in the initial screening resulted in a maximum eightfold enhancement in cell inhibition activity. The sulfonyl oxadiazole-based compounds formulated as PEG-based ointments, with low toxicity test results on human cells (CC 50 : >78µM), demonstrated potent antimicrobial effects not only in a mouse skin wound infection model but also against oxacillin-resistant clinical isolate MRSA (IC 50 ≈ 1µM), as evidenced by the results. Furthermore, additional studies utilizing LC-MS/MS and in-silico approaches clearly support the allosteric site covalent binding mechanism through the nucleophilic aromatic substitution (S N Ar) reaction, as well as its association with the closure of the major active site of PBP2a.

A novel strategy to characterize the pattern of ß-lactam antibiotic-induced drug resistance in Acinetobacter baumannii.

Carbapenem-resistant Acinetobacter baumannii (CRAb) is an urgent public health threat, according to the CDC. This pathogen has few treatment options and causes severe nosocomial infections with > 50% fatality rate. Although previous studies have examined the proteome of CRAb, there have been no focused analyses of dynamic changes to ß-lactamase expression that may occur due to drug exposure. Here, we present our initial proteomic study of variation in ß-lactamase expression that occurs in CRAb with different ß-lactam antibiotics. Briefly, drug resistance to Ab (ATCC 19606) was induced by the administration of various classes of ß-lactam antibiotics, and the cell-free supernatant was isolated, concentrated, separated by SDS-PAGE, digested with trypsin, and identified by label-free LC-MS-based quantitative proteomics. Peptides were identified and evaluated using a 1789 sequence database of Ab ß-lactamases from UniProt. Importantly, we observed that different antibiotics, even those of the same class ( e.g. penicillin and amoxicillin), induce non-equivalent responses comprising various Class C and D serine-ß-lactamases, resulting in unique resistomes. These results open the door to a new approach of analyzing and studying the problem of multi-drug resistance in bacteria that rely strongly on ß-lactamase expression.

A novel strategy to characterize the pattern of ß-lactam antibiotic-induced drug resistance in Acinetobacter baumannii.

Carbapenem-resistant Acinetobacter baumannii (CRAb) is an urgent public health threat, according to the CDC. This pathogen has few treatment options and causes severe nosocomial infections with > 50% fatality rate. Although previous studies have examined the proteome of CRAb, there have been no focused analyses of dynamic changes to ß-lactamase expression that may occur due to drug exposure. Here, we present our initial proteomic study of variation in ß-lactamase expression that occurs in CRAb with different ß-lactam antibiotics. Briefly, drug resistance to Ab (ATCC 19606) was induced by the administration of various classes of ß-lactam antibiotics, and the cell-free supernatant was isolated, concentrated, separated by SDS-PAGE, digested with trypsin, and identified by label-free LC-MS-based quantitative proteomics. Thirteen proteins were identified and evaluated using a 1789 sequence database of Ab ß-lactamases from UniProt, the majority of which were Class C ß-lactamases (≥ 80%). Importantly, different antibiotics, even those of the same class (e.g. penicillin and amoxicillin), induced non-equivalent responses comprising various isoforms of Class C and D serine-ß-lactamases, resulting in unique resistomes. These results open the door to a new approach of analyzing and studying the problem of multi-drug resistance in bacteria that rely strongly on ß-lactamase expression.

Broadband Achromatic Metalens in the Visible Light Spectrum Based on Fresnel Zone Spatial Multiplexing.

Metalenses composed of a large number of subwavelength nanostructures provide the possibility for the miniaturization and integration of the optical system. Broadband polarization-insensitive achromatic metalenses in the visible light spectrum have attracted researchers because of their wide applications in optical integrated imaging. This paper proposes a polarization-insensitive achromatic metalens operating over a continuous bandwidth from 470 nm to 700 nm. The silicon nitride nanopillars of 488 nm and 632.8 nm are interleaved by Fresnel zone spatial multiplexing method, and the particle swarm algorithm is used to optimize the phase compensation. The maximum time-bandwidth product in the phase library is 17.63. The designed focal length can be maintained in the visible light range from 470 nm to 700 nm. The average focusing efficiency reaches 31.71%. The metalens can achieve broadband achromatization using only one shape of nanopillar, which is simple in design and easy to fabricate. The proposed metalens is expected to play an important role in microscopic imaging, cameras, and other fields.

Knee Bone and Cartilage Segmentation Based on a 3D Deep Neural Network Using Adversarial Loss for Prior Shape Constraint.

Fast and accurate segmentation of knee bone and cartilage on MRI images is becoming increasingly important in the orthopaedic area, as the segmentation is an essential prerequisite step to a patient-specific diagnosis, optimising implant design and preoperative and intraoperative planning. However, manual segmentation is time-intensive and subjected to inter- and intra-observer variations. Hence, in this study, a three-dimensional (3D) deep neural network using adversarial loss was proposed to automatically segment the knee bone in a resampled image volume in order to enlarge the contextual information and incorporate prior shape constraints. A restoration network was proposed to further improve the bone segmentation accuracy by restoring the bone segmentation back to the original resolution. A conventional U-Net-like network was used to segment the cartilage. The ultimate results were the combination of the bone and cartilage outcomes through post-processing. The quality of the proposed method was thoroughly assessed using various measures for the dataset from the Grand Challenge Segmentation of Knee Images 2010 (SKI10), together with a comparison with a baseline network U-Net. A fine-tuned U-Net-like network can achieve state-of-the-art results without any post-processing operations. This method achieved a total score higher than 76 in terms of the SKI10 validation dataset. This method showed to be robust to extract bone and cartilage masks from the MRI dataset, even for the pathological case.

A Cascaded Multi-Task Generative Framework for Detecting Aortic Dissection on 3-D Non-Contrast-Enhanced Computed Tomography.

Contrast-enhanced computed tomography (CE-CT) is the gold standard for diagnosing aortic dissection (AD). However, contrast agents can cause allergic reactions or renal failure in some patients. Moreover, AD diagnosis by radiologists using non-contrast-enhanced CT (NCE-CT) images has poor sensitivity. To address this issue, we propose a novel cascaded multi-task generative framework for AD detection using NCE-CT volumes. The framework includes a 3D nnU-Net and a 3D multi-task generative architecture (3D MTGA). Specifically, the 3D nnU-Net was employed to segment aortas from NCE-CT volumes. The 3D MTGA was then employed to simultaneously synthesize CE-CT volumes, segment true & false lumen, and classify the patient as AD or non-AD. A theoretical formulation demonstrated that the 3D MTGA could increase the Jensen-Shannon Divergence (JSD) between AD and non-AD for each NCE-CT volume, thus indirectly improving the AD detection performance. Experiments also showed that the proposed framework could achieve an average accuracy of 0.831, a sensitivity of 0.938, and an F1-score of 0.847 in comparison with seven state-of-the-art classification models used by three radiologists with junior, intermediate, and senior experiences, respectively. The experimental results indicate that the proposed framework obtains superior performance to state-of-the-art models in AD detection. Thus, it has great potential to reduce the misdiagnosis of AD using NCE-CT in clinical practice. The source codes and supplementary materials for our framework are available at https://github.com/yXiangXiong/CMTGF.

In vitro biosynthesis of ATP from adenosine and polyphosphate.

Adenosine triphosphate (ATP) acts as a crucial energy currency in vivo, and it is a widely used energy and/or phosphate donor for enzyme-catalyzed reactions in vitro. In this study, we established an in vitro multi-enzyme cascade system for ATP production. Using adenosine and inorganic polyphosphate (polyP) as key substrates, we combined adenosine kinase and two functionally distinct polyphosphate kinases (PPKs) in a one-pot reaction to achieve chain-like ATP regeneration and production. Several sources of PPK were screened and characterized, and two suitable PPKs were selected to achieve high rates of ATP production. Among these, Sulfurovum lithotrophicum PPK (SlPPK) exhibited excellent activity over a wide pH range (pH 4.0-9.0) and synthesized ATP from ADP using short-chain polyP. Furthermore, it had a half-life > 155.6 h at 45 °C. After optimizing the reaction conditions, we finally carried out the coupling-catalyzed reaction with different initial adenosine concentrations of 10, 20, and 30 mM. The highest yields of ATP were 76.0, 70.5, and 61.3%, respectively.

A Cascaded Deep Learning Framework for Detecting Aortic Dissection Using Non-contrast Enhanced Computed Tomography.

Aortic dissection (AD) is a rare but potentially fatal disease with high mortality. The aim of this study is to synthesize contrast enhanced computed tomography (CE-CT) images from non-contrast CT (NCE-CT) images for detecting aortic dissection. In this paper, a cascaded deep learning framework containing a 3D segmentation network and a synthetic network was proposed and evaluated. A 3D segmentation network was firstly used to segment aorta from NCE-CT images and CE-CT images. A conditional generative adversarial network (CGAN) was subsequently employed to map the NCE-CT images to the CE-CT images non-linearly for the region of aorta. The results of the experiment suggest that the cascaded deep learning framework can be used for detecting the AD and outperforms CGAN alone.

Deep Learning for Accurate Segmentation of Venous Thrombus from Black-Blood Magnetic Resonance Images: A Multicenter Study.

OBJECTIVE: Deep vein thrombosis (DVT) is the third-largest cardiovascular disease, and accurate segmentation of venous thrombus from the black-blood magnetic resonance (MR) images can provide additional information for personalized DVT treatment planning. Therefore, a deep learning network is proposed to automatically segment venous thrombus with high accuracy and reliability. METHODS: In order to train, test, and external test the developed network, total images of 110 subjects are obtained from three different centers with two different black-blood MR techniques (i.e., DANTE-SPACE and DANTE-FLASH). Two experienced radiologists manually contoured each venous thrombus, followed by reediting, to create the ground truth. 5-fold cross-validation strategy is applied for training and testing. The segmentation performance is measured on pixel and vessel segment levels. For the pixel level, the dice similarity coefficient (DSC), average Hausdorff distance (AHD), and absolute volume difference (AVD) of segmented thrombus are calculated. For the vessel segment level, the sensitivity (SE), specificity (SP), accuracy (ACC), and positive and negative predictive values (PPV and NPV) are used. RESULTS: The proposed network generates segmentation results in good agreement with the ground truth. Based on the pixel level, the proposed network achieves excellent results on testing and the other two external testing sets, DSC are 0.76, 0.76, and 0.73, AHD (mm) are 4.11, 6.45, and 6.49, and AVD are 0.16, 0.18, and 0.22. On the vessel segment level, SE are 0.95, 0.93, and 0.81, SP are 0.97, 0.92, and 0.97, ACC are 0.96, 0.94, and 0.95, PPV are 0.97, 0.82, and 0.96, and NPV are 0.97, 0.96, and 0.94. CONCLUSIONS: The proposed deep learning network is effective and stable for fully automatic segmentation of venous thrombus on black blood MR images.

Structures of fibrils formed by α-synuclein hereditary disease mutant H50Q reveal new polymorphs.

Deposits of amyloid fibrils of α-synuclein are the histological hallmarks of Parkinson's disease, dementia with Lewy bodies and multiple system atrophy, with hereditary mutations in α-synuclein linked to the first two of these conditions. Seeing the changes to the structures of amyloid fibrils bearing these mutations may help to understand these diseases. To this end, we determined the cryo-EM structures of α-synuclein fibrils containing the H50Q hereditary mutation. We find that the H50Q mutation results in two previously unobserved polymorphs of α-synuclein: narrow and wide fibrils, formed from either one or two protofilaments, respectively. These structures recapitulate conserved features of the wild-type fold but reveal new structural elements, including a previously unobserved hydrogen-bond network and surprising new protofilament arrangements. The structures of the H50Q polymorphs help to rationalize the faster aggregation kinetics, higher seeding capacity in biosensor cells and greater cytotoxicity that we observe for H50Q compared to wild-type α-synuclein.

Different Amyloid-ß Self-Assemblies Have Distinct Effects on Intracellular Tau Aggregation.

Alzheimer's disease (AD) pathology is characterized by the aggregation of beta-amyloid (Aß) and tau in the form of amyloid plaques and neurofibrillary tangles in the brain. It has been found that a synergistic relationship between these two proteins may contribute to their roles in disease progression. However, how Aß and tau interact has not been fully characterized. Here, we analyze how tau seeding or aggregation is influenced by different Aß self-assemblies (fibrils and oligomers). Our cellular assays utilizing tau biosensor cells show that transduction of Aß oligomers into the cells greatly enhances seeded tau aggregation in a concentration-dependent manner. In contrast, transduced Aß fibrils slightly reduce tau seeding while untransduced Aß fibrils promote it. We also observe that the transduction of α-synuclein fibrils, another amyloid protein, has no effect on tau seeding. The enhancement of tau seeding by Aß oligomers was confirmed using tau fibril seeds derived from both recombinant tau and PS19 mouse brain extracts containing human tau. Our findings highlight the importance of considering the specific form and cellular location of Aß self-assembly when studying the relationship between Aß and tau in future AD therapeutic development.

Astrocytes Protect Neurons in the Hippocampal CA3 Against Ischemia by Suppressing the Intracellular Ca2+ Overload.

In the hippocampus, delayed neuronal death is normally seen in neurons of the CA1 region but not in those of the CA3 region. Astrocytes have been reported to play multiple supporting or pathological roles in neuronal functioning. While evidence indicates that astrocytes could exert neuroprotective effects following ischemia, the possible underlying mechanisms remain unclear. We aimed to investigate the roles of astrocytes in the process of delayed neuronal death following transient forebrain ischemia. L-α-aminoadipic acid (L-α-AAA), an astrocyte-selective gliotoxin, was injected into the hippocampal CA3 region of rats through a cranial window to selectively damage astrocytes. Immunofluorescence staining of glial fibrillary acidic protein (GFAP) was used to evaluate the effect of L-α-AAA on astrocyte numbers. Three days after the L-α-AAA injection, transient forebrain ischemia was induced by a modification of the four-vessel occlusion procedure. Seven days after transient forebrain ischemia, hematoxylin-eosin staining was performed to reveal the morphology of hippocampal pyramidal neurons. In rats with ischemia and reperfusion, regional cerebral blood flow (rCBF) and change in intracellular Ca2+ concentration ([Ca2+]i) were separately measured in CA1 and CA3 regions. L-α-AAA injection significantly decreased the number of astrocytes in CA3, but did not affect the pattern of rCBF changes upon ischemia/reperfusion. Seven days after transient forebrain ischemia, in rats receiving L-α-AAA, delayed neuronal death comparable with that in CA1 was observed in the CA3 region. In addition, the pattern of increase in [Ca2+]i due to transient forebrain ischemia was completely changed in the hippocampal CA3. The loss of astrocytes induced a persistent increase in [Ca2+]i in the CA3 region following transient ischemia, similar to what is observed in the CA1 region. Our study indicates that astrocytes in the hippocampal CA3 region exert neuroprotective effects following transient forebrain ischemia and act by suppressing the intracellular Ca2+ overload. Furthermore, our study will most likely provide a new therapeutic strategy for brain ischemic diseases, targeted to astrocytes.