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bioRxiv2021

ANDOR and beyond: dynamically switchable logic gates as modules for flexible information processing

Understanding how complex (bio-)chemical pathways and regulatory networks may be capable of processing information in efficient, flexible, and robust ways is a key question with implications touching fields across biology, systems biology, biochemistry, synthetic biology, dynamical systems theory, and network science. Considerable effort has been focused on the identification and characterization of structural motifs in these signaling networks, and companion efforts have instead sought to cast their operation as controlled by dynamical modules that appear out of dynamical correlations during information processing. While both these approaches have been successful in many examples of biological information processing, cases in which the signaling or regulatory network exhibits multi-functionality or context dependence remain problematic. We here propose a small set of higher-order effective modules that simultaneously incorporate both network structure and the attendant dynamical landscape. In so doing, we render effective computational units that can perform different logical operations based purely on the basin of attraction in which the network dynamics resides or is steered to. These dynamically switchable biochemical logic gates require fewer chemical components or gene products overall than their traditional analogs where static, separate gates are used for each desired function. We demonstrate the applicability and limits of these flexible gates by determining a robust range of parameters over which they correctly operate and further characterize the resilience of their function against intrinsic noise of the constituent reactions using the theory of large deviations. We also show the capability of this framework for general computations by designing a binary adder/subtractor circuit composed of only six components.

biophysics↗

bioRxiv2021

Upregulation of C4 characteristics does not consistently improve photosynthetic performance in intraspecific hybrids of a grass

C4 photosynthesis is thought to have evolved via intermediate stages, with changes towards the C4 phenotype gradually enhancing photosynthetic performance. This hypothesis is widely supported by modelling studies, but experimental tests are missing. Mixing of C4 components to generate artificial intermediates can be achieved via crossing, and the grass Alloteropsis semialata represents an outstanding system since it includes C4 and non-C4 populations. Here, we analyse F1 hybrids between C3 and C4, and C3+C4 and C4 genotypes to determine whether the acquisition of C4 characteristics increases photosynthetic performance. The hybrids have leaf anatomical characters and C4 gene expression profiles that are largely intermediate between those of their parents. Carbon isotope ratios are similarly intermediate, which suggests that a partial C4 cycle coexists with C3 carbon fixation in the hybrids. This partial C4 phenotype is associated with C4-like photosynthetic efficiency in C3+C4 x C4, but not in C3 x C4 hybrids, which are overall less efficient than both parents. Our results support the hypothesis that the photosynthetic gains from the upregulation of C4 characteristics depend on coordinated changes in anatomy and biochemistry. The order of acquisition of C4 components is thus constrained, with C3+C4 species providing an essential step for C4 evolution.

plant biology↗

bioRxiv2021

Characterisation of the Ubiquitin-ESCRT pathway in Asgard archaea sheds new light on origins of membrane trafficking in eukaryotes

The ESCRT machinery performs a critical role in membrane remodelling events in all eukaryotic cells, including in membrane trafficking, membrane repair, cytokinetic abscission, in viral egress, and in the generation of extracellular vesicles. While the machinery is complex in modern day eukaryotes, where it comprises dozens of proteins, the system has simpler and more ancient origins. Indeed, homologues of ESCRT-III and the Vps4 ATPase, the proteins that execute the final membrane scission reaction, play analogous roles in cytokinesis and potentially in extracellular vesicle formation in TACK archaea where ESCRT-I and II homologues seem to be absent. Here, we explore the phylogeny, structure, and biochemistry of homologues of the ESCRT machinery and the associated ubiquitylation system found in genome assemblies of the recently discovered Asgard archaea. In these closest living prokaryotic relatives of eukaryotes, we provide evidence for the ESCRT-I and II sub-complexes being involved in the ubiquitin-directed recruitment of ESCRT-III,_as it is in eukaryotes. This analysis suggests a pre-eukaryotic origin for the Ub-coupled ESCRT system and a likely path of ESCRT evolution via a series of gene duplication and diversification events.

cell biology↗

bioRxiv2021

Course-based Undergraduate Research Module for Enzyme Discovery Using Protein Structure Prediction

A major challenge for science educators is teaching foundational concepts while introducing their students to current research. Here we describe an active learning module developed to teach protein structure fundamentals while supporting ongoing research in enzyme discovery. It can be readily implemented in both entry-level and upper-division college biochemistry or biophysics courses. Pre-activity lectures introduced fundamentals of protein secondary structure and provided context for the research projects, while a homework assignment familiarized students with 3D visualization of biomolecules using UCSF Chimera, a free protein structure viewer. The activity is an online survey in which students compare structure elements in papain, a well-characterized cysteine protease from Carica papaya, to novel homologous proteases identified from the genomes of an extremophilic microbe (Halanaerobium praevalens) and two carnivorous plants (Drosera capensis and Cephalotus follicularis). Students were then able to identify, with varying levels of accuracy, a number of structural features in cysteine proteases that could expedite the identification of novel or biochemically interesting cysteine proteases for experimental validation in a university laboratory. Student responses to a post-activity survey were largely positive and constructive, describing points in the activity that could be improved and indicating that the activity helped them learn about protein structure.

scientific communication and education↗

bioRxiv2021

Learning the local landscape of protein structures with convolutional neural networks

The fundamental problem of protein biochemistry is to predict protein structure from amino acid sequence. The inverse problem, predicting either entire sequences or individual mutations that are consistent with a given protein structure, has received much less attention even though it has important applications in both protein engineering and evolutionary biology. Here, we ask whether 3D convolutional neural networks (3D CNNs) can learn the local fitness landscape of protein structure to reliably predict either the wild-type amino acid or the consensus in a multiple sequence alignment from the local structural context surrounding a site of interest. We find that the network can predict wild type with good accuracy, and that network confidence is a reliable measure of whether a given prediction is likely going to be correct or not. Predictions of consensus are less accurate, and are primarily driven by whether or not the consensus matches the wild type. Our work suggests that high-confidence mis-predictions of the wild type may identify sites that are primed for mutation and likely targets for protein engineering.

bioinformatics↗

bioRxiv2021

Redesigning the Eterna100 for the Vienna 2 folding engine

The rational design of RNA is becoming important for rapidly developing technologies in medicine and biochemistry, spurring development of numerous RNA secondary structure design algorithms and benchmarks to evaluate their performance. However, the problem of RNA design is dependent upon the reverse problem of RNA structure prediction through "folding engines" that predict structure from sequence. We hypothesized that differences in RNA folding engines could impact design algorithms, and recruited an online community of RNA design experts to modify the widely-used RNA secondary structure design benchmark, Eterna100, to address unsolvability of some cases when changing the folding engine used (Vienna 1.8 updated to Vienna 2.6). We tested this new Eterna100-V2 benchmark with five RNA design algorithms, and found that while overall rankings remained similar, the performance of RNA design algorithms that depended on folding engines in their training did indeed depend on which underlying parameter set was used in training. This work demonstrates that the design "difficulty" of RNA structures is intrinsically linked to thermodynamic models, and suggests that future RNA design algorithms that are agnostic to thermodynamic models will result in optimal performance and development. Eterna100-V1 and Eterna100-V2 benchmarks and example solutions are freely available at https://github.com/eternagame/eterna100-benchmarking. Author SummaryDesigning RNA molecules that fold to a desired target structure is an algorithmic problem gathering increasing attention due to the emergence of RNA-based therapies and the need for rational design of RNAs. The Eterna100 dataset, a collection of target structures with increasing design difficulty, designed and selected by players of the crowdsourced RNA game Eterna, has been widely used to benchmark RNA design algorithms. However, these puzzles were originally developed using the now-deprecated version 1 of the ViennaRNA folding engine. In this manuscript, we introduce an updated benchmark, called the Eterna100-V2. We found that nineteen puzzles using Vienna 1 were unsolvable in Vienna 2, but that Eterna participants were able to re-design the puzzles with minimal modifications to make them solvable in Vienna 2. We confirmed that the rankings of 5 RNA design algorithms remained consistent between Eterna100-V1 and -V2. However, discrepancies in performance from algorithms that relied on thermodynamic models in their training suggest that algorithms will benefit from being agnostic to thermodynamic models as these models continue to improve.

bioinformatics↗

bioRxiv2021

The polyglutamine amyloid nucleus in living cells is monomeric and has competing dimensions of order

A long-standing goal of the study of amyloids has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of that event has made it inaccessible to classical biochemistry, structural biology, and computational approaches. Here, we addressed that limitation by measuring the dependence of amyloid formation on concentration and conformational templates in living cells, whose volumes are sufficiently small to resolve the outcomes of independent nucleation events. We characterized numerous rationally designed sequence variants of polyglutamine (polyQ), a polypeptide that precipitates Huntingtons and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. This effort uncovered a pattern of approximately twelve Qs, only for polypeptides exceeding the clinical length threshold, that allow for amyloid nucleation to occur spontaneously within single polypeptides. Nucleation was inhibited by intermolecular phase separation. Using atomistic molecular dynamics simulations, we found that the pattern encodes a minimal steric zipper of interdigitated side chains. Lateral growth of the steric zipper competed with axial growth to produce "pre-amyloid" oligomers. By illuminating the structural mechanism of polyQ amyloid formation in cells, our findings reveal a potential molecular etiology for polyQ diseases, and may provide a roadmap for the design of new therapies.

biophysics↗

bioRxiv2021

Transcriptome phylogenies support ancient evolutionary transitions in bioluminescence traits of cypridinid ostracods

Although the the diversity, beauty, and intricacy of sexually selected courtship displays command the attention of evolutionists, the longevity of these traits in deep time is poorly understood. Population-based theory suggests sexual selection could either lower or raise extinction risk, resulting in high or low persistence of lineages with sexually selected traits. Furthermore, empirical studies that directly estimate longevity of sexually selected traits are uncommon. Sexually selected signals - including bioluminescent courtship - originated multiple times during evolution, allowing empirical study of their longevity after careful phylogenetic and divergence time analyses. Here, we estimate the first transcriptome-based molecular phylogeny and divergence times of Cypridinidae. We report extreme longevity of bioluminescent courtship, a trait important in mate choice and probably under sexual selection. Our relaxed-clock estimates of divergence times coupled with stochastic character mapping show luminous courtship evolved only once in Cypridinidae in a Sub-Tribe we name Luxorina at least 151 Million Years Ago (Ma) from cypridinid ancestors that used bioluminescence only in anti-predator displays, defining a Tribe we name Luminini. This time-calibrated molecular phylogeny of cypridinids will serve as a foundation for integrative and comparative studies on the biochemistry, molecular evolution, courtship, diversification, and ecology of cypridinid bioluminescence. The persistence of luminous courtship for hundreds of millions of years indicates that rates of speciation within the group exceeded extinction risk, allowing for the persistence of a diverse clade of signalling species and that sexual selection did not cause rapid loss of associated traits.

evolutionary biology↗

bioRxiv2021

The efficacy of a ketogenic diet in preclinical models of IDH wild-type and IDH mutant glioma

Infiltrative gliomas are the most common neoplasms arising in the brain, and remain largely incurable despite decades of research. A subset of these gliomas contains mutations in isocitrate dehydrogenase 1 (IDH1) or, less commonly, IDH2 (together called "IDHmut"). These mutations alter cellular biochemistry, and IDHmut gliomas are generally less aggressive than IDH wild-type (IDHwt) gliomas. Some preclinical studies and clinical trials have suggested that a ketogenic diet (KD), characterized by low-carbohydrate and high-fat content, may be beneficial in slowing glioma progression. However, not all studies have shown promising results, and to date, no study has addressed whether IDHmut gliomas might be more sensitive to KD. The aim of the current study was to compare the effects of KD in preclinical models of IDHwt versus IDHmut gliomas. In vitro, simulating KD by treatment with the ketone body {beta}-hydroxybutyrate had no effect on the proliferation of patient-derived IDHwt or IDHmut glioma cells. Likewise, a cycling KD, wherein mice alternated between KD and a standard diet (SD), had no effect on the in vivo growth of patient-derived IDHwt or IDHmut gliomas, even though the cycling KD did result in persistently elevated circulating ketones. Furthermore, KD conferred no survival benefit in mice engrafted with Sleeping-Beauty transposase-engineered IDHmut glioma. These data suggest that neither IDHwt nor IDHmut gliomas are particularly responsive to KD.

cancer biology↗

bioRxiv2021

Genomic and physiological characterization of Novosphingobium terrae sp. nov., an alphaproteobacterium isolated from Cerrado soil containing a megasized chromid

A novel bacterial strain, designated GeG2T, was isolated from soils of native Cerrado, a highly biodiverse savanna-like Brazilian biome. 16S rRNA gene sequence analysis of strain GeG2T revealed high sequence identity (100%) to the alphaproteobacterium Novosphingobium rosa, however, comparisons with N. rosa DSM7285T showed several distinctive features, prompting a full characterization of the new strain in terms of growth, morphology, biochemistry and, ultimately, its genome. GeG2T cells were Gram-stain negative bacilli, facultatively anaerobic, motile, positive for catalase and oxidase activities and for starch hydrolysis. Strain GeG2T presented planktonic-sessile dimorphism and cell aggregates surrounded by extracellular matrix and nanometric spherical structures were observed in liquid cultures, suggesting the production of exopolysaccharides (EPS) and outer membrane vesicles (OMVs). Whole genome assembly revealed four circular replicons: a 4.1 Mb chromosome, a 2.7 Mb extrachromosomal megareplicon and two plasmids (212.7 and 68.6 kb). The megareplicon contains few core genes and plasmid-type replication/maintenance systems, consistent with its classification as a chromid. Genome annotation shows a vast repertoire of carbohydrate active enzymes and genes involved in the degradation of aromatic compounds, highlighting the biotechnological potential of the new isolate obtained from Cerrado soils, especially regarding EPS production and biodegradation of recalcitrant compounds. Chemotaxonomic features, including polar lipid and fatty acid profiles, as well as physiological, molecular and whole genome comparisons showed significant differences between strain GeG2T and a N. rosa, clearly indicating that it represents a novel species, for which the name Novosphingobium terrae is proposed. The type strain is GeG2T (=CBMAI 2313T =CBAS 753T). IMPORTANCENovosphingobium is an alphaproteobacterial genus presenting diverse physiological profiles and broad biotechnological applications. However, many aspects regarding the biology of this important bacterial group remain elusive. A novel Novosphingobium strain was isolated from soils of Cerrado, an important Brazilian biome. Despite 100% 16S rRNA gene identity with Novosphingobium rosa, polyphasic characterizations, including physiological, chemotaxonomic, and whole genome- based analyses revealed significant differences between GeG2T and N. rosa DSM7285T, reinforcing resolution limitations in phylogenetic analysis based solely on 16S RNA and highlighting the importance of employing different approaches for the description of bacterial species. Using short and long read sequencing approaches, a high-quality fully resolved genome assembly was generated and one of the largest chromids reported to date was identified. A comprehensive characterization of environmental isolates allows us to better elucidate the diversity and biology of members of this bacterial group with potential biotechnological importance, guiding future bioprospecting efforts and genomic studies.

microbiology↗

bioRxiv2021

The short term High Fat Diet sparks gut microbiota associated metabolic syndrome pathogenesis and the impact of Amoxicillin intervention in mice

BackgroundKnowledge about alteration in gut microbiota on a high-fat diet (HFD) and common antibiotics for a short period is little known. The study was undertaken to evaluate the changes in the microbiota profile in HFD fed mice followed by amoxicillin intervention. ResultsFor two weeks, the mice were fed with HFD followed by amoxicillin for one week. Animals were evaluated for haemato-biochemical, histopathological and 16S rRNA sequencing followed by bioinformatics analysis to know any changes in gut microbiota ecology. Amoxicillin treatment for a short duration had marked the remarkable remodelling of gut microbiota that directly linked to beneficial impact by countering the pathogenesis of the metabolic syndrome besides overgrowth of particular opportunistic pathogens of gut inflammatory diseases. Amoxicillin treatment significantly decreased blood glucose and a slight elevation in cholesterol levels on blood biochemistry analysis. No marked pathological changes were observed in HFD fed mice. ConclusionsOur results suggest that Amoxicillin treatment had a beneficial influence on the obese related metabolic syndrome with the risk of hypercholesterolemia and some gut-resistant intestinal pathobionts.

microbiology↗

bioRxiv2021

Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants

Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor belong to any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for such mutations. In this study, we present an analysis of 144 human enzymes containing 591 pathogenic missense variants, in which allosteric dynamic coupling of mutated positions with known active sites provides insights into a primary biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of {beta}-Glucocerebrosidase (GCase), which contains 94 Gaucher disease-associated missense variants located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling due to the presence of missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease. Author SummaryGenetic diseases occur when mutations to a particular gene cause a gain/loss in function of the related protein. Although several methods based on conservation and protein biochemistry exist to predict which genetic mutations may impact function, many disease causing changes remain unexplained by these metrics. In this study, we propose an explanation for these genetic changes may cause disease. In order to function, important regions of a protein must be able to exhibit collective motion. Through computer simulations, we observed that changing even a single amino acid within a protein can change the protein motion. Notably, disease causing genetic changes tend to alter the motion of regions which are critically important to protein function, even the mutations are far from these critical regions. In addition, we examined the degree that two amino acids within a protein may "couple" to one another, meaning the degree to which motion in one amino acid will affect the other. We found that amino acids which are highly coupled to the active site of a protein are more likely to result in disease if mutated, thereby offering a new tool for predicting genetic disease which incorporates internal protein dynamics.

biophysics↗

bioRxiv2021

Beyond the reach of homology: successive computational filters find yeast pheromone genes

The mating of fungi depends on pheromones that mediate communication between two mating types. Most species use short peptides as pheromones, which are either unmodified (e.g., -factor in Saccharomyces cerevisiae) or C-terminally farnesylated (e.g., a-factor in S. cerevisiae). Peptide pheromones have been found by genetics or biochemistry in small number of fungi, but their short sequences and modest conservation make it impossible to detect homologous sequences in most species. To overcome this problem, we used a four-step computational pipeline to identify candidate a-factor genes in sequenced genomes of the Saccharomycotina, the fungal clade that contains most of the yeasts: we require that candidate genes have a C-terminal prenylation motif, are fewer than 100 amino acids long, contain a proteolytic processing motif upstream of the potential mature pheromone sequence, and that closely related species contain highly conserved homologs of the potential mature pheromone sequence. Additional manual curation exploits the observation that many species carry more than one a-factor gene, encoding identical or nearly identical pheromones. From 332 fungal genomes, we identified strong candidate pheromone genes in 238 genomes, covering 13 clades that are separated from each other by at least 100 million years, the time required for evolution to remove detectable sequence homology. For one small clade, the Yarrowia, we demonstrated that our algorithm found the a-factor genes: deleting all four related genes in the a-mating type of Yarrowia lipolytica prevents mating.

bioinformatics↗

bioRxiv2021

Training data composition affects performance of protein structure analysis algorithms

The three-dimensional structures of proteins are crucial for understanding their molecular mechanisms and interactions. Machine learning algorithms that are able to learn accurate representations of protein structures are therefore poised to play a key role in protein engineering and drug development. The accuracy of such models in deployment is directly influenced by training data quality. The use of different experimental methods for protein structure determination may introduce bias into the training data. In this work, we evaluate the magnitude of this effect across three distinct tasks: estimation of model accuracy, protein sequence design, and catalytic residue prediction. Most protein structures are derived from X-ray crystallography, nuclear magnetic resonance (NMR), or cryo-electron microscopy (cryo-EM); we trained each model on datasets consisting of either all three structure types or of only X-ray data. We find that across these tasks, models consistently perform worse on test sets derived from NMR and cryo-EM than they do on test sets of structures derived from X-ray crystallography, but that the difference can be mitigated when NMR and cryo-EM structures are included in the training set. Importantly, we show that including all three types of structures in the training set does not degrade test performance on X-ray structures, and in some cases even increases it. Finally, we examine the relationship between model performance and the biophysical properties of each method, and recommend that the biochemistry of the task of interest should be considered when composing training sets.

bioinformatics↗

bioRxiv2021

ChemChaste: Simulating spatially inhomogenous biochemical reaction-diffusion systems for modelling cell-environment feedbacks

MotivationSpatial organisation plays an important role in the function of many biological systems, from cell fate specification in animal development to multi-step metabolic conversions in microbial communities. The study of such systems benefits from the use of spatially explicit computational models that combine a discrete description of cells with a continuum description of one or more chemicals diffusing within a surrounding bulk medium. These models allow the in silico testing and refinement of mechanistic hypotheses. However, most existing models of this type do not account for concurrent bulk and intracellular biochemical reactions and their possible coupling. ResultsHere, we describe ChemChaste, an extension for the open-source C++ computational biology library Chaste. ChemChaste enables the spatial simulation of both multicellular and bulk biochemistry by expanding on Chastes existing capabilities. In particular, ChemChaste enables: (i) simulation of an arbitrary number of spatially diffusing chemicals; (ii) spatially heterogeneous chemical diffusion coefficients; and (iii) inclusion of both bulk and intracellular biochemical reactions and their coupling. ChemChaste also introduces a file-based interface that allows users to define the parameters relating to these functional features without the need to interact directly with Chastes core C++ code. We describe ChemChaste and demonstrate its functionality using a selection of chemical and biochemical exemplars, with a focus on demonstrating increased ability in modelling bulk chemical reactions and their coupling with intracellular reactions. Availability and implementationChemChaste is a free, open-source C++ library, available via GitHub at https://github.com/OSS-Lab/ChemChaste under the BSD license. ContactO.Soyer@warwick.ac.uk or a.g.fletcher@sheffield.ac.uk

systems biology↗

bioRxiv2021

Contribution of cytoplasm viscoelastic properties to mitotic spindle positioning

Cells are filled with macromolecules and polymer networks that set scale-dependent viscous and elastic properties to the cytoplasm. Although the role of these parameters in molecular diffusion, reaction kinetics and cellular biochemistry is being increasingly recognized, their contributions to the motion and positioning of larger organelles, such as mitotic spindles for cell division remain unknown. Here, using magnetic tweezers to displace and rotate mitotic spindles in living embryos, we uncovered that the cytoplasm can impart viscoelastic reactive forces that move spindles, or passive objects with similar size, back to their original position. These forces are independent of cytoskeletal force generators, yet reach hundreds of piconewtons and scale with cytoplasm crowding. Spindle motion shears and fluidizes the cytoplasm, dissipating elastic energy and limiting spindle recoils with functional implications for asymmetric and oriented divisions. These findings suggest that bulk cytoplasm material properties may constitute important control elements for the regulation of division positioning and cellular organization. Significance StatementThe regulation of mitotic spindle positioning is a key process for tissue architecture, embryo development and stem cells. To date, most models have assumed that spindles are positioned by forces exerted by polar cytoskeleton networks, like microtubule asters or acto-myosin bundles. Here, using in situ magnetic tweezers to apply calibrated forces and torques to mitotic spindles in live dividing sea urchin cells, we found that the viscoelastic properties of the cytoplasm medium in which spindles are embedded can hold spindles in place, and move them back if their original position is perturbed. These viscoelastic forces are large and may significantly participate in the force balance that position and orient mitotic spindles in many cell types.

cell biology↗

bioRxiv2021

Universal features shaping organelle gene retention

Mitochondria and plastids power complex life, and retain their own organelle DNA (oDNA) genomes, with highly reduced gene contents compared to their endosymbiont ancestors. Why some protein-coding genes are retained in oDNA and some lost remains a debated question. Here we harness over 15k oDNA sequences and over 300 whole genome sequences with tools from structural biology, bioinformatics, machine learning, and Bayesian model selection to reveal the properties of genes, and associated underlying mechanisms, that shape oDNA evolution. Striking symmetry exists between the two organelle types: gene retention patterns in both are predicted by the hydrophobicity of a protein product and its energetic centrality within its protein complex, with additional influences of nucleic acid and amino acid biochemistry. Remarkably, retention principles from one organelle type successfully and quantitatively predict retention in the other, supporting this universality; these principles also distinguish gene profiles in independent endosymbiotic relationships. The identification of these features shaping organelle gene retention both provides quantitative support for several existing evolutionary hypotheses, and suggests new biochemical and biophysical mechanisms influencing organelle genome evolution.

evolutionary biology↗

bioRxiv2021

Saturated Proteostasis and Nuclear Injuries Defeat Homeostatic Potentials of α-Synuclein Filaments

Biogenesis of inclusion bodies (IBs) facilitates protein quality control (PQC). Canonical aggresomes execute degradation of misfolded proteins while non-degradable amyloids quarantine into Insoluble Protein Deposits. Lewy Bodies (LBs) are well-known neurodegenerative IBs of -Synuclein associated diseases like Dementia with Lewy bodies (DLB) and Parkinsons disease. Intriguingly, the PQC benefits and drawbacks associated with LBs remain underexplored. Here, we report that the crosstalk between LBs and aggresome-like IBs of -Synuclein (Syn-aggresomes) buffers amyloidogenic -Synuclein load in primary neurons and mitotic cell models. Using cellular biochemistry, genetic knockdown, and microscopy tools we find that LBs possess unorthodox PQC-capacities of self-quarantining the Syn-amyloids, and being degradable upon receding fresh amyloidogenesis. Syn-aggresomes equilibrate biogenesis of LBs by facilitating spontaneous and opportunistic turnover of soluble -Synuclein and Syn-amyloids, respectively. However, LBs overgrow at the perinucleus once amyloidogenesis sets in and are misidentified by cytosolic BICD2 as cargos for motor-protein dynein. Simultaneously, microtubules surrounding the perinuclear LBs are distorted, misbalancing the dynein motor-force on nucleoskeleton leading to lamina injuries. Like typical Laminopathies, nucleocytoplasmic mixing, DNA-damage, and deregulated transcription of stress chaperones defeat the proteostatic purposes of LBs. We confirmed the lamina disintegrities in brain sections of Parkinsons disease patients. Together, our study provides insights into the intricate complexities of proteostatic possibilities associated with -Synuclein inclusions and offers understanding on the proteostasis-sensitivity of LB-containing aging neurons via lamina-injuries. Significance statementAmyloid inclusions of -Synuclein called Lewy Bodies (LBs) are hallmark of multiple neurodegenerative diseases like Dementia with Lewy Bodies and Parkinsons disease. A significant reason for the degeneration of LB-containing aging neurons in these diseases is their sensitivity to proteostasis stresses. We find two distinct inclusions of -Synuclein in the same neurons/cells. First, the Syn-aggresomes titrate the biogenesis of the other i.e., the LBs, by facilitating degradation of soluble -Synuclein. Syn-amyloids deposited in LBs remain degradable but LBs overgrow at the perinucleus once the kinetics of amyloid-biogenesis exceeds aggresome-assisted degradation of -Synuclein. Perinuclear LBs destabilize local tubulin-meshwork and are misidentified as cargo for cytosolic motor dynein. Aberrant cytoskeleton-nucleoskeleton tension disintegrates lamina, deregulates stress-responsive transcription, and triggers proteostasis-sensitivity in LB-containing neurons.

cell biology↗