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Mutations in the protein superoxide dismutase-1 (SOD1) promote its misfolding and aggregation, ultimately causing familial forms of the debilitating neurodegenerative disease amyotrophic lateral sclerosis (ALS). Currently, over 220 (mostly missense) ALS-causing mutations in the SOD1 protein have been identified, indicating that common structural features are responsible for aggregation and toxicity. Using in silico tools, we predicted amyloidogenic regions in the ALS-associated SOD1-G85R mutant, finding seven regions throughout the structure. Introduction of proline residues into β-strands II (I18P) or III (I35P) reduced the aggregation propensity and toxicity of SOD1-G85R in cells, significantly more so than proline mutations in other amyloidogenic regions. The I18P and I35P mutations also reduced the capability of SOD1-G85R to template onto previously formed non-proline mutant SOD1 aggregates as measured by fluorescence recovery after photobleaching. Finally, we found that, while the I18P and I35P mutants are less structurally stable than SOD1-G85R, the proline mutants are less aggregation-prone during proteasome inhibition, and less toxic to cells overall. Our research highlights the importance of a previously underappreciated SOD1 amyloidogenic region in β-strand II (¹⁵QGIINF²⁰) to the aggregation and toxicity of SOD1 in ALS mutants, and suggests that β-strands II and III may be good targets for the development of SOD1-associated ALS therapies.

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5-methylcytosine (5mC) and N6-methyladenine (6mA). These ML-based nanopore callers have typically been trained on data that span all modifications on all possible DNA [Formula: see text]-mer backgrounds-a complete training dataset. However, as nanopore technology is pushed to more and more epigenetic modifications, such complete training data will not be feasible to obtain. Nanopore calling has historically been performed with hidden Markov models (HMMs) that cannot make successful calls for [Formula: see text]-mer contexts not seen during training because of their independent emission distributions. However, deep neural networks (DNNs), which share parameters across contexts, are increasingly being used as callers, often outperforming their HMM cousins. It stands to reason that a DNN approach should be able to better generalize to unseen [Formula: see text]-mer contexts. Indeed, herein we demonstrate that a common DNN approach (DeepSignal) outperforms a common HMM approach (Nanopolish) in the incomplete data setting. Furthermore, we propose a novel hybrid HMM-DNN approach, amortized-HMM, that outperforms both the pure HMM and DNN approaches on 5mC calling when the training data are incomplete. This type of approach is expected to be useful for calling other base modifications such as 5-hydroxymethylcytosine and for the simultaneous calling of different modifications, settings in which complete training data are not likely to be available.

Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions associated with deficits in social interaction and communication, together with repetitive behaviours. The cell adhesion molecule protocadherin10 (PCDH10) is linked to ASD in humans. Pcdh10 is expressed in the nervous system during embryonic and early postnatal development and is important for neural circuit formation. In mice, strong expression of Pcdh10 in the ganglionic eminences and in the basolateral complex (BLC) of the amygdala was observed at mid and late embryonic stages, respectively. Both inhibitory and excitatory neurons expressed Pcdh10 in the BLC at perinatal stages and vocalization-related genes were enriched in Pcdh10-expressing neurons in adult mice. An epitope-tagged Pcdh10-HAV5 mouse line revealed endogenous interactions of PCDH10 with synaptic proteins in the young postnatal telencephalon. Nuanced socio-affective communication changes in call emission rates, acoustic features and call subtype clustering were primarily observed in heterozygous pups of a conditional knockout (cKO) with selective deletion of Pcdh10 in Gsh2-lineage interneurons. These changes were less prominent in heterozygous ubiquitous Pcdh10 KO pups, suggesting that altered anxiety levels associated with Gsh2-lineage interneuron functioning might drive the behavioural effects. Together, loss of Pcdh10 specifically in interneurons contributes to behavioural alterations in socio-affective communication with relevance to ASD.

Neurodegenerative diseases, particularly Alzheimer's disease (AD), pose a significant challenge in ageing populations. Our current understanding indicates that the onset of toxic amyloid and tau protein pathologies initiates disease progression. However, existing treatments targeting these hallmark symptoms offer symptomatic relief without halting disease advancement. This review offers an alternative perspective on AD, centring on impaired adult hippocampal neurogenesis (AHN) as a potential early aetiological factor. By delving into the intricate molecular events during the initial stages of AD (Braak Stages I-III), a novel hypothesis is presented, interweaving the roles of Notch signalling and heparan sulfate proteoglycans (HSPGs) in compromised AHN. While acknowledging the significance of the amyloid and tau hypotheses, it calls for further exploration beyond these paradigms, suggesting the potential of altered HS sulfation patterns in AD initiation. Future directions propose more detailed investigations into early HS aggregation, aberrant sulfation patterns and examination of their temporal relationship with tau hyperphosphorylation. In challenging the conventional 'triggers' of AD and urging their reconsideration as symptoms, this review advocates an alternative approach to understanding this disease, offering new avenues of investigation into the intricacies of AD pathogenesis.

Faithful transmission of genetic material is crucial for the survival of all organisms. In many eukaryotes, a feedback control mechanism called the spindle checkpoint ensures chromosome segregation fidelity by delaying cell cycle progression until all chromosomes achieve proper attachment to the mitotic spindle. Kinetochores are the macromolecular complexes that act as the interface between chromosomes and spindle microtubules. While most eukaryotes have canonical kinetochore proteins that are widely conserved, kinetoplastids such as Trypanosoma brucei have a seemingly unique set of kinetochore proteins including KKT1-25. It remains poorly understood how kinetoplastids regulate cell cycle progression or ensure chromosome segregation fidelity. Here, we report a crystal structure of the C-terminal domain of KKT14 from Apiculatamorpha spiralis and uncover that it is a pseudokinase. Its structure is most similar to the kinase domain of a spindle checkpoint protein Bub1. In addition, KKT14 has a putative ABBA motif that is present in Bub1 and its paralogue BubR1. We also find that the N-terminal part of KKT14 interacts with KKT15, whose WD40 repeat beta-propeller is phylogenetically closely related to a direct interactor of Bub1/BubR1 called Bub3. Our findings indicate that KKT14-KKT15 are divergent orthologues of Bub1/BubR1-Bub3, which promote accurate chromosome segregation in trypanosomes.

We present a novel small molecule antiviral chemotype that was identified by an unconventional cell-free protein synthesis and assembly-based phenotypic screen for modulation of viral capsid assembly. Activity of PAV-431, a representative compound from the series, has been validated against infectious viruses in multiple cell culture models for all six families of viruses causing most respiratory diseases in humans. In animals, this chemotype has been demonstrated efficacious for porcine epidemic diarrhoea virus (a coronavirus) and respiratory syncytial virus (a paramyxovirus). PAV-431 is shown to bind to the protein 14-3-3, a known allosteric modulator. However, it only appears to target the small subset of 14-3-3 which is present in a dynamic multi-protein complex whose components include proteins implicated in viral life cycles and in innate immunity. The composition of this target multi-protein complex appears to be modified upon viral infection and largely restored by PAV-431 treatment. An advanced analog, PAV-104, is shown to be selective for the virally modified target, thereby avoiding host toxicity. Our findings suggest a new paradigm for understanding, and drugging, the host-virus interface, which leads to a new clinical therapeutic strategy for treatment of respiratory viral disease.

Traditional medication and alternative therapies have long been used to treat breast cancer. One of the main problems with current treatments is that there is an increase in drug resistance in the cancer cells owing to genetic differences such as mutational changes, epigenetic changes and miRNA (microRNA) alterations such as miR-1246, miR-298, miR-27b and miR-33a, along with epigenetic modifications, such as Histone3 acetylation and CCCTC-Binding Factor (CTCF) hypermethylation for drug resistance in breast cancer cell lines. Certain forms of conventional drug resistance have been linked to genetic changes in genes such as ABCB1, AKT, S100A8/A9, TAGLN2 and NPM. This review aims to explore the current approaches to counter breast cancer, the action mechanism, along with novel therapeutic methods endowing potential drug resistance. The investigation of novel therapeutic approaches sheds light on the phenomenon of drug resistance including genetic variations that impact distinct forms of oestrogen receptor (ER) cancer, genetic changes, epigenetics-reported resistance and their identification in patients. Long-term effective therapy for breast cancer includes selective oestrogen receptor modulators, selective oestrogen receptor degraders and genetic variations, such as mutations in nuclear genes, epigenetic modifications and miRNA alterations in target proteins. Novel research addressing combinational therapies including maytansine, photodynamic therapy, guajadiol, talazoparib, COX2 inhibitors and miRNA 1246 inhibitors have been developed to improve patient survival rates.

The neuronal cell adhesion molecule contactin-4 (CNTN4) is genetically associated with autism spectrum disorder (ASD) and other psychiatric disorders. Cntn4-deficient mouse models have previously shown that CNTN4 plays important roles in axon guidance and synaptic plasticity in the hippocampus. However, the pathogenesis and functional role of CNTN4 in the cortex has not yet been investigated. Our study found a reduction in cortical thickness in the motor cortex of Cntn4 ^-/- mice, but cortical cell migration and differentiation were unaffected. Significant morphological changes were observed in neurons in the M1 region of the motor cortex, indicating that CNTN4 is also involved in the morphology and spine density of neurons in the motor cortex. Furthermore, mass spectrometry analysis identified an interaction partner for CNTN4, confirming an interaction between CNTN4 and amyloid-precursor protein (APP). Knockout human cells for CNTN4 and/or APP revealed a relationship between CNTN4 and APP. This study demonstrates that CNTN4 contributes to cortical development and that binding and interplay with APP controls neural elongation. This is an important finding for understanding the physiological function of APP, a key protein for Alzheimer's disease. The binding between CNTN4 and APP, which is involved in neurodevelopment, is essential for healthy nerve outgrowth.

Acorn barnacles are efficient colonizers on a wide variety of marine surfaces. As they proliferate on critical infrastructure, their settlement and growth have deleterious effects on performance. To address acorn barnacle biofouling, research has focused on the settlement and adhesion processes with the goal of informing the development of novel coatings. This effort has resulted in the discovery and characterization of several proteins found at the adhesive substrate interface, i.e. cement proteins, and a deepened understanding of the function and composition of the biomaterials within this region. While the adhesive properties at the interface are affected by the interaction between the proteins, substrate and mechanics of the calcified base plate, little attention has been given to the interaction between the proteins and the cuticular material present at the substrate interface. Here, the proteome of the organic matrix isolated from the base plate of the acorn barnacle Amphibalanus amphitrite is compared with the chitinous and proteinaceous matrix embedded within A. amphitrite parietal plates. The objective was to gain an understanding of how the basal organic matrix may be specialized for adhesion via an in-depth comparative proteome analysis. In general, the majority of proteins identified in the parietal matrix were also found in the basal organic matrix, including nearly all those grouped in classes of cement proteins, enzymes and pheromones. However, the parietal organic matrix was enriched with cuticle-associated proteins, of which ca 30% of those identified were unique to the parietal region. In contrast, ca 30-40% of the protease inhibitors, enzymes and pheromones identified in the basal organic matrix were unique to this region. Not unexpectedly, nearly 50% of the cement proteins identified in the basal region were significantly distinct from those found in the parietal region. The wider variety of identified proteins in the basal organic matrix indicates a greater diversity of biological function in the vicinity of the substrate interface where several processes related to adhesion, cuticle formation and expansion of the base synchronize to play a key role in organism survival.

Most successes in computational protein engineering to date have focused on enhancing one biophysical trait, while multi-trait optimization remains a challenge. Different biophysical properties are often conflicting, as mutations that improve one tend to worsen the others. In this study, we explored the potential of an automated computational design strategy, called CamSol Combination, to optimize solubility and stability of enzymes without affecting their activity. Specifically, we focus on Bacillus licheniformis α-amylase (BLA), a hyper-stable enzyme that finds diverse application in industry and biotechnology. We validate the computational predictions by producing 10 BLA variants, including the wild-type (WT) and three designed models harbouring between 6 and 8 mutations each. Our results show that all three models have substantially improved relative solubility over the WT, unaffected catalytic rate and retained hyper-stability, supporting the algorithm's capacity to optimize enzymes. High stability and solubility embody enzymes with superior resilience to chemical and physical stresses, enhance manufacturability and allow for high-concentration formulations characterized by extended shelf lives. This ability to readily optimize solubility and stability of enzymes will enable the rapid and reliable generation of highly robust and versatile reagents, poised to contribute to advancements in diverse scientific and industrial domains.