bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic mechanistic inference from large families of Boolean models generated by Monte Carlo Tree Search
Authors: Glazer Bryan , Lifferth Jonathan , Lopez Carlos F.
Published: October 2022

1

Motivation

Many important processes in biology, such as signaling and gene regulation, can be described using logic models. These logic models are typically built to behaviorally emulate experimentally observed phenotypes, which are assumed to be steady states of a biological system. Most models are built by hand and therefore researchers are only able to consider one or perhaps a few potential mechanisms. We present a method to automatically synthesize Boolean logic models with a specified set of steady states. Our method, called MC-Boomer, is based on Monte Carlo Tree Search (MCTS), an efficient, parallel search method using reinforcement learning. Our approach enables users to constrain the model search space using prior knowledge or biochemical interaction databases, thus leading to generation of biologically plausible mechanistic hypotheses. Our approach can generate very large numbers of data-consistent models. To help develop mechanistic insight from these models, we developed analytical tools for multi-model inference and model selection. These tools reveal the key sets of interactions that govern the behavior of the models.

Results

We demonstrate that MC-Boomer works well at reconstructing randomly generated models. Then, using single time point measurements and reasonable biological constraints, our method generates hundreds of thousands of candidate models that match experimentally validatedin-vivobehaviors of theDrosophilasegment polarity network. Finally we outline how our multimodel analysis procedures elucidate potentially novel biological mechanisms and provide opportunities for model-driven experimental validation.

Availability

Code is available at:www.github.com/bglazer/mcboomer
Automated Protein Function Description for Novel Class Discovery
Authors: Barot Meet , Gligorijevic Vladimir , Bonneau Richard , Cho Kyunghyun
Published: October 2022

Knowledge of protein function is necessary for understanding biological systems, but the discovery of new sequences from high-throughput sequencing technologies far outpaces their functional characterization. Beyond the problem of assigning newly sequenced proteins to known functions, a more challenging issue is discovering novel protein functions. The space of possible functions becomes unlimited when considering designed proteins. Protein function prediction, as it is framed in the case of Gene Ontology term prediction, is a multilabel classification problem with a hierarchical label space. However, this framing does not provide guiding principles for discovering completely novel functions. Here we propose a neural machine translation model in order to generate descriptions of protein functions in natural language. In this way, instead of making predictions in a limited label space, our model generates descriptions in the language space, and thus is capable of composing novel functions. Given the novelty of our approach, we design metrics to evaluate the performance of our model: correctness, specificity and robustness. We provide results of our model in the zero-shot classification setting, scoring functional descriptions that the model has not seen before for proteins that have limited homology to those in the training set. Finally, we show generated function descriptions compared to ground truth descriptions for qualitative evaluation.
NIS metastable intermediates provide insights into conformational transition between principal thermodynamic states
Authors: Chakrabarti Mayukh , Amzel L. Mario , Lau Albert Y.
Published: October 2022

The Sodium/Iodide Symporter (NIS), a thirteen-helix transmembrane protein found in the thyroid and other tissues, transports iodide, a required constituent of thyroid hormones T3 and T4. Despite extensive experimental information and clinical data, structural details of the intermediate microstates comprising the conformational transition of NIS between its inwardly and outwardly open states remain unresolved. We present data from a combination of enhanced sampling and transition path molecular dynamics (MD) simulations that elucidate the nature of the principal intermediate states comprising the transition between the inwardly and outwardly open metastable states of fully bound and unbound NIS under an enforced ionic gradient. Our findings suggest that in both the absence and presence of bound physiological ions, NIS principally occupies a proximally inward to inwardly open state, whereas when fully bound, it also occupies a rare but thermodynamically favorable ‘inward occluded’ state. The results of this work provide novel insight into the populations of NIS intermediates and the free energy landscape comprising the conformational transition, adding to a mechanistic understanding of NIS ion transport. Moreover, the knowledge gained from this approach can serve as a basis for studies of NIS mutants to target therapeutic interventions.

Abstract Figure

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Rubber needs to be included in deforestation-free commodity legislation
Authors: Warren-Thomas Eleanor , Ahrends Antje , Wang Yunxia , Wang Maria M H , Jones Julia P G
Published: October 2022

Natural rubber production uses increasing amounts of land in the tropics and is linked to deforestation. There is debate as to whether current legislative proposals to reduce the import of deforestation-linked commodities into the EU, US and the UK will include rubber. Globally, sustained growth in demand is chiefly driven by tyre production, linked to rising freight and passenger transport flows. Yields of natural rubber remain static, meaning increased plantation area will be required: 2.7 – 5.3 million ha of additional harvested area could be needed by 2030 to meet demand. In order to prevent further deforestation and associated biodiversity loss, millions of smallholder growers producing the majority of rubber globally need support to increase production from existing plantations and close yield gaps, without undermining long-term sustainability through soil or water degradation. Rubber should also be included in legislative proposals to reduce deforestation in supply chains to avoid undermining the impact of these ambitious initiatives on forest loss globally.
Born with intronless ERF transcriptional factors: C4photosynthesis inherits a legacy dating back 450 million years
Authors: Lyu Ming-Ju Amy , Du Huilong , Yao Hongyan , Zhang Zhiguo , Chen Genyun , Chen Faming , Zhao Yong-Yao , Tang Qiming , Miao Fenfen , Wang Yanjie , Zhao Yuhui , Lu Hongwei , Fang Lu , Gao Qiang , Qi Yiying , Zhang Qing , Zhang Jisen , Yang Tao , Cui Xuean , Liang Chengzhi , Lu Tiegang , Zhu Xin-Guang
Published: October 2022

The genusFlaveria, containing species at different evolutionary stages of the progression from C3to C4photosynthesis, is used as a model system to study the evolution of C4photosynthesis. Here, we report chromosome-scale genome sequences for fiveFlaveriaspecies, including C3, C4, and intermediate species. Our analyses revealed that both acquiring additional gene copies and recruiting ethylene responsive factor (ERF)cis-regulatory elements (CREs) contributed to the emergence of C4photosynthesis. ERF transcriptional factors (TFs), especially intronless ERF TFs, were co-opted in dicotyledonous C4species and monocotyledonous C4species in parallel. These C4species co-opted intronless ERF TFs originated from the Late Ordovician mass extinction that occurred ∼450 million years ago in coping with environmental stress. Therefore, this study demonstrated that intronless ERF TFs were acquired during the early evolution of plants and provided the molecular toolbox facilitating multiple subsequent independent evolutions of C4photosynthesis.
A new framework for detecting copy number variants from single nucleotide polymorphism data: ‘rCNV’, a versatile R package for paralogs and CNVs detection
Authors: Karunarathne Piyal , Zhou Qiujie , Schliep Klaus , Milesi Pascal
Published: October 2022

Studies show that copy number variants (CNVs), due to their ubiquitous presence in eukaryotes, contribute to phenotypic variation, environmental adaptation, and fuel species divergence at a previously unknown rate. However, the detection of CNVs in genomes, especially in non-model organisms is challenging due to the need for costly genomic resources and complex computational infrastructure. Therefore, to provide researchers with a low-cost and easily accessible resource, we developed a robust statistical framework and an R software package to detect CNVs using allelic-read depth from SNPs data.

The core of the framework exploits i) the allelic-read depth ratio distribution in heterozygotes for individual SNPs and testing it against an expected distribution under a binomial sampling, and ii) SNPs showing an apparent excess of heterozygotes under Hardy-Weinberg equilibrium, to detect alleles in putatively multi-copy regions. The use of multiple statistical tests to find the deviation in allelic-read depth ratio distribution makes our method sensitive to sampling and aware of reference biases thereby minimizing false detection of CNVs.

Our framework is well-catered for high throughput short-reads data, hence, most GBS technologies (e.g., RADseq, Exome-capture, WGS). As such, it allows calling CNVs from genomes of varying complexity. The framework is implemented in the R package “rCNV” which effortlessly automates the analysis. We trained our models on simulated data and tested on four datasets obtained from different sequencing technologies (i.e., RADseq: Chinook salmon –Oncorhynchus tshawytscha, American lobster –Homarus americanus, Exome-capture: Norway Spruce –Picea abies, and WGS: Malaria mosquito -Anopheles gambiae).
Hill-type models of skeletal muscle and neuromuscular actuators: a systematic review
Authors: Caillet Arnault H. , Phillips Andrew T.M. , Carty Christopher , Farina Dario , Modenese Luca
Published: October 2022

Backed by a century of research and development, Hill-type models of skeletal muscle, often including a muscle-tendon complex and neuromechanical interface, are widely used for countless applications. Lacking recent comprehensive reviews, the field of Hill-type modelling is, however, dense and hard-to-explore, with detrimental consequences on innovation. Here we present the first systematic review of Hill-type muscle modelling. It aims to clarify the literature by detailing its contents and critically discussing the state-of-the-art by identifying the latest advances, current gaps, and potential future directions in Hill-type modelling. For this purpose, fifty-seven criteria-abiding Hill-type models were assessed according to a completeness evaluation, which identified the modelled muscle properties, and a modelling evaluation, which considered the level of validation and reusability of the models, as well as their modelling strategy and calibration. It is concluded that most models (1) do not significantly advance beyond historical gold standards, (2) neglect the importance of parameter identification, (3) lack robust validation, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary material for navigating the literature, the results of this review highlight the need for global recommendations in Hill-type modelling to optimize inter-study consistency, knowledge transfer, and model reusability.
Robustness vs productivity during evolutionary community assembly: short-term synergies and long-term trade-offs
Authors: Lepori Vasco J. , Loeuille Nicolas , Rohr Rudolf P.
Published: October 2022

The realization that evolutionary feedbacks need to be considered to fully grasp ecological dynamics has sparked interest in the effect of evolution on community properties like coexistence and productivity. However, little is known about the evolution of community robustness and productivity along diversification processes in species-rich systems. We leverage the recent structural approach to coexistence together with adaptive dynamics to study such properties and their relationships in a general trait-based model of competition on a niche axis. We show that the effects of coevolution on coexistence are two-fold and contrasting depending on the timescale considered. In the short term, evolution of niche differentiation strengthens coexistence, while long-term diversification leads to niche packing and decreased robustness. Moreover, we find that co-evolved communities tend to be on average more robust and more productive than non-evolutionary assemblages. We illustrate how our theoretical predictions echo in observed empirical patterns and the implications of our results for empiricists and applied ecologists. We suggest that some of our results such as the improved robustness of Evolutionary Stable Communities could be tested experimentally in suitable model systems.
Versatile and automated workflow for the analysis of oligodendroglial calcium signals in preclinical mouse models of myelin repair
Authors: Maas Dorien A. , Manot-Saillet Blandine , Bun Philippe , Habermacher Chloé , Poilbout Corinne , Rusconi Filippo , Angulo Maria Cecilia
Published: October 2022

Intracellular Ca2+signals of oligodendroglia, the myelin-forming cells of the central nervous system, regulate vital cellular processes including myelination. However, studies on oligodendroglia Ca2+signal dynamics are still scarce, especially during myelin repair, and there are no software solutions to properly analyze the unique Ca2+signal characteristics in these cells. Here, we provide a comprehensive experimental and analytical workflow to acquire and analyze Ca2+imaging data of oligodendroglia at the population and single-cell levels in preclinical mouse models of myelin repair. We report diverseex vivoandin vivoexperimental protocols to obtain reproducible Ca2+imaging data from oligodendroglia in demyelinated lesions. Importantly, we provide an analytical pipeline containing two free, open source and cross-platform software programs, Occam and post-prOccam, that enable the fully automated analysis of one- and two-photon Ca2+imaging datasets from oligodendroglia obtained by eitherex vivoorin vivoCa2+imaging techniques. This versatile and accessible experimental and analytical framework, which revealed significant but uncorrelated spontaneous Ca2+activity in oligodendroglia inside demyelinated lesions, should facilitate the elucidation of Ca2+-mediated mechanisms underlying remyelination and therefore help to accelerate the development of therapeutic strategies for the many myelin-related disorders, such as multiple sclerosis.
SCTC: inference of developmental potential from single-cell transcriptional complexity
Authors: Lin Hai , Hu Huan , Feng Zhen , Xu Fei , Lyu Jie , Shuai Jianwei
Published: October 2022

Inference of single-cell developmental potential from scRNA-Seq data enables us to reconstruct the pseudo-temporal path of cell development, which is an important and challenging task for single-cell analysis. Single-cell transcriptional diversity (SCTD), measured by the number of expressed genes per cell, has been found to be negatively correlated with the development time, and thus can be considered as a hallmark of developmental potential. However, in some cases, the gene expression level of the cells in the early stages of development may be lower than that of the later stages, which may lead to incorrect estimation of differentiation states by gene diversity-based inference. Here we refer to the economic complexity theory and propose single-cell transcriptional complexity (SCTC) metrics as a measure of single-cell developmental potential, given the intrinsic similarities between biological and economic complex systems. We take into account not only the number of genes expressed by cells, but also the more sophisticated structure information of gene expression by treating the scRNA-seq count matrix as a bipartite network. We show that complexity metrics characterize the developmental potential more accurately than the diversity metrics. Especially, in the early stages of development, cells typically have lower gene expression level than that in the later stages, while their complexity in the early stages is significantly higher than that in the later stages. Based on the measurement of SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interaction between cells and genes determines the developmental potential, which may bring new insights into the understanding of biological development from the perspective of the complexity theory.
Alternating selection for dispersal and multicellularity favors regulated life cycles
Authors: Barrere Julien , Nanda Piyush , Murray Andrew W.
Published: October 2022

The evolution of complex multicellularity opened paths to increased morphological diversity and organizational novelty. This transition involved three processes: cells remained attached to one another to form groups, cells within these groups differentiated to perform different tasks, and the groups evolved new reproductive strategies1–5. Recent experiments identified selective pressures and mutations that can drive the emergence of simple multicellularity and cell differentiation6–11but the evolution of life cycles, in particular, how simple multicellular forms reproduce has been understudied. The selective pressure and mechanisms that produced a regular alternation between single cells and multicellular collectives are still unclear12. To probe the factors regulating simple multicellular life cycles, we examined a collection of wild isolates of the budding yeast,S. cerevisiae12,13. We found that all these strains can exist as multicellular clusters, a phenotype that is controlled by the mating type locus and strongly influenced by the nutritional environment. Inspired by this variation, we engineered inducible dispersal in a multicellular laboratory strain and demonstrated that a regulated life cycle has an advantage over constitutively single-celled or constitutively multicellular life cycles when the environment alternates between favoring intercellular cooperation (a low sucrose concentration) and dispersal (a patchy environment generated by emulsion). Our results suggest that the separation of mother and daughter cells is under selection in wild isolates and is regulated by their genetic composition and the environments they encounter and that alternating patterns of resource availability may have played a role in the evolution of life cycles.

Visual abstract
Microrobots Powered by Concentration Polarization Electrophoresis (CPEP)
Authors: Katzmeier Florian , Simmel Friedrich C.
Published: October 2022

Second-order electrokinetic flow around colloidal particles caused by concentration polarization electro-osmosis (CPEO) can result in a phoretic motion of asymmetric particle dimers in a homogeneous AC electrical field, which we refer to as concentration polarization electro-phoresis (CPEP). To demonstrate this actuation mechanism, we created particle dimers from micron-sized silica spheres with sizes 1.0 µm and 2.1 µm by connecting them with DNA linker molecules. The dimers can be steered along arbitrarily chosen paths within a 2D plane by controlling the orientation of the AC electric field in a fluidic chamber with the joystick of a gamepad. Further utilizing induced dipole-dipole interactions, we demonstrate that particle dimers can be used to controllably pick up monomeric particles and release them at any desired position, and also to assemble several particles into groups. Systematic experiments exploring the dependence of the dimer migration speed on the electric field strength, frequency, and buffer composition align with the theoretical framework of CPEO and provide parameter ranges for the operation of our microrobots.
A review of the International Seabed Authority database DeepData: challenges and opportunities in the UN Ocean Decade
Authors: Rabone M. , Horton T. , Jones D. O. B. , Simon-Lledó E. , Glover A. G.
Published: October 2022

1.

There is an urgent need for quality biodiversity data in the context of rapid environmental change. Nowhere is this more urgent than in the deep ocean, with the possibility of seabed mining moving from exploration to exploitation, but where vast knowledge gaps persist. Regions of the seabed beyond national jurisdiction, managed by the International Seabed Authority (ISA) are undergoing intensive mining exploration, including the Clarion-Clipperton Zone. In 2019 the ISA launched its database ‘DeepData’, publishing environmental (including biological) data; and since June 2021, DeepData records have been harvested by OBIS (Ocean Biodiversity Information System) via the ISA node. Here we explore how DeepData could support biological research and environmental policy development in the CCZ (and wider ocean regions); and whether data are Findable, Accessible, Interoperable and Reusable (FAIR). Given the direct connection of DeepData with the regulator of a rapidly developing potential industry, this review is particularly timely. We found evidence of extensive duplication of datasets; an absence of unique record identifiers and significant taxonomic data quality issues, compromising FAIRness of the data. The publication of DeepData records on the OBIS ISA node has led to large-scale improvements in data quality and availability. However, limitations in usage of identifiers and issues with taxonomic information were also evident in datasets published on the node, stemming from mis-mapping of data from the ISA environmental data template to the data standard Darwin Core prior to data harvesting by OBIS. While notable data quality issues remain, these changes signal a rapid evolution for the database and significant movement towards integrating with global systems through usage of data standards and publication on global aggregators. This is exactly what has been needed for biological datasets held by the ISA. We provide recommendations for future development of the database to support this evolution towards FAIR.
Glycolytic reprogramming underlies immune cell activation by polyethylene wear particles
Authors: Maduka Chima V. , Habeeb Oluwatosin M. , Kuhnert Maxwell M. , Hakun Maxwell , Goodman Stuart B. , Contag Christopher H.
Published: October 2022

Primary total joint arthroplasties (TJAs) are widely and successfully applied reconstructive procedures to treat end-stage arthritis. Nearly 50% of TJAs are now performed in young patients, posing a new challenge: performing TJAs which last a lifetime. The urgency is justified because subsequent TJAs are costlier and fraught with higher complication rates, not to mention the toll taken on patients and their families. Polyethylene particles, generated by wear at joint articulations, drive aseptic loosening by inciting insidious inflammation associated with surrounding bone loss. Down modulating polyethylene particle-induced inflammation enhances integration of implants to bone (osseointegration), preventing loosening. A promising immunomodulation strategy could leverage immune cell metabolism, however, the role of immunometabolism in polyethylene particle-induced inflammation is unknown. Our findings reveal that immune cells exposed to sterile or contaminated polyethylene particles show fundamentally altered metabolism, resulting in glycolytic reprogramming. Inhibiting glycolysis controlled inflammation, inducing a pro-regenerative phenotype that could enhance osseointegration.
CD46 targeted212Pb alpha particle radioimmunotherapy for prostate cancer treatment
Authors: Li Jun , Huang Tao , Hua Jun , Wang Qiong , Su Yang , Chen Ping , Bidlingmaier Scott , Li Allan , Xie Zhongqiu , Bidkar Anil , Shen Sui , Shi Weibin , Seo Youngho , Flavell Robert R. , Gioeli Daniel , Dreicer Robert , Li Hui , Liu Bin , He Jiang
Published: October 2022

We recently identified CD46 as a novel prostate cancer cell surface antigen that shows lineage independent expression in both adenocarcinoma and small cell neuroendocrine subtypes of metastatic castration resistant prostate cancer (mCRPC), discovered an internalizing human monoclonal antibody YS5 that binds to a tumor selective CD46 epitope, and developed a microtubule inhibitor-based antibody drug conjugate that is in a multi-center phase I trial for mCRPC (NCT03575819). Here we report the development of a novel CD46-targeted alpha therapy based on YS5. We conjugated212Pb, anin vivogenerator of alpha-emitting212Bi and212Po, to YS5 through the chelator TCMC to create the radioimmunoconjugate,212Pb-TCMC-YS5. We characterized212Pb-TCMC-YS5in vitroand established a safe dosein vivo. We next studied therapeutic efficacy of a single dose of212Pb-TCMC-YS5 using three prostate cancer small animal models: a subcutaneous mCRPC cell line-derived xenograft (CDX) model (subcu-CDX), an orthotopically grafted mCRPC CDX model (ortho-CDX), and a prostate cancer patient-derived xenograft model (PDX). In all three models, a single dose of 20 μCi212Pb-TCMC-YS5 was well tolerated and caused potent and sustained inhibition of established tumors, with significant increases of survival in treated animals. A lower dose (10 μCi212Pb-TCMC-YS5) was also studied on the PDX model, which also showed a significant effect on tumor growth inhibition and prolongation of animal survival. These results demonstrate that212Pb-TCMC-YS5 has an excellent therapeutic window in preclinical models including PDXs, opening a direct path for clinical translation of this novel CD46-targeted alpha radioimmunotherapy for mCRPC treatment.

Significance

This study reports a novel CD46 targeted212Pb alpha particle radioimmunotherapy,212Pb-TCMC-YS5, that is well tolerated and shows potent anti-tumor activity (tumor growth inhibition and increase of animal survival)in vivoin three prostate cancer small animal models, i.e., a subcutaneous and an intraprostate orthotopic mCRPC cell line-derived xenograft models, and a prostate cancer patient-derived xenograft model. Given that YS5 is a clinical stage human antibody, this YS5-based212Pb alpha particle therapy has potential of translation to the clinic for treatment of mCRPC patients.
Diet Induced Obesity and Diabetes Enhance Mortality and Reduces Vaccine Efficacy for SARS-CoV-2
Authors: Johnson Robert M , Ardanuy Jeremy , Hammond Holly , Logue James , Jackson Lian , Baracco Lauren , McGrath Marisa , Dillen Carly , Patel Nita , Smith Gale , Frieman Matthew
Published: October 2022

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of Coronavirus disease 2019 (COVID-19), emerged in Wuhan, China, in December 2019. As of October 2022, there have been over 625 million confirmed cases of COVID-19, including over 6.5 million deaths. Epidemiological studies have indicated that comorbidities of obesity and diabetes mellitus are associated with increased morbidity and mortality following SARS-CoV-2 infection. We determined how the comorbidities of obesity and diabetes affect morbidity and mortality following SARS-CoV-2 infection in unvaccinated and adjuvanted spike nanoparticle (NVX-CoV2373) vaccinated mice. We find that obese/diabetic mice infected with SARS-CoV-2 have increased morbidity and mortality compared to age matched normal mice. Mice fed a high-fat diet (HFD) then vaccinated with NVX-CoV2373 produce equivalent neutralizing antibody titers to those fed a normal diet (ND). However, the HFD mice have reduced viral clearance early in infection. Analysis of the inflammatory immune response in HFD mice demonstrates a recruitment of neutrophils that was correlated with increased mortality and reduced clearance of the virus. Depletion of neutrophils in diabetic/obese vaccinated mice reduced disease severity and protected mice from lethality. This model recapitulates the increased disease severity associated with obesity and diabetes in humans with COVID-19 and is an important comorbidity to study with increasing obesity and diabetes across the world.

Importance

SARS-CoV-2 has caused a wide spectrum of disease in the human population, from asymptomatic infections to death. It is important to study the host differences that may alter the pathogenesis of this virus. One clinical finding in COVID19 patients, is that people with obesity or diabetes are at increased risk of severe illness from SARS-CoV-2 infection. We used a high fat diet model in mice to study the effects of obesity and Type 2 diabetes on SARS-CoV-2 infection as well as how these comorbidities alter the response to vaccination. We find that diabetic/obese mice have increased disease after SARS-CoV-2 infection and they have slower clearance of virus. We find that the lungs of these mice have increased neutrophils and that removing these neutrophils protect diabetic/obese mice from disease. This demonstrates why these diseases have increased risk of severe disease and suggests specific interventions upon infection.
Encoding surprise by retinal ganglion cells
Authors: Despotović Danica , Joffrois Corentin , Marre Olivier , Chalk Matthew
Published: October 2022

The efficient coding hypothesis posits that early sensory neurons transmit maximal information about sensory stimuli, given internal constraints. A central prediction of this theory is that neurons should preferentially encode stimuli that are most surprising. Previous studies suggest this may be the case in early visual areas, where many neurons respond strongly to rare or surprising stimuli. For example, previous research showed that when presented with a rhythmic sequence of full-field flashes, many retinal ganglion cells (RGCs) respond strongly at the instance the flash sequence stops, and when another flash would be expected. This phenomenon is called the ‘omitted stimulus response’. However, it is not known whether the responses of these cells varies in a graded way depending on the level of stimulus surprise. To investigate this, we presented retinal neurons with extended sequences of stochastic flashes. With this stimulus, the surprise associated with a particular flash/silence, could be quantified analytically, and varied in a graded manner depending on the previous sequences of flashes and silences. Interestingly, we found that RGC responses could be well explained by a simple normative model, which described how they optimally combined their prior expectations and recent stimulus history, so as to encode surprise. Further, much of the diversity in RGC responses could be explained by the model, due to the different prior expectations that different neurons had about the stimulus statistics. These results suggest that even as early as the retina many cells encode surprise, relative to their own, internally generated expectations.
Investigating the role of binding free energy, binding affinity and antibody escape in the evolution of SARS-CoV-2 spike protein
Authors: Young Matthew , Lycett Samantha J
Published: October 2022

SARS-CoV-2 is considered a pandemic virus and presents a major strain on public health globally. SARS-CoV-2 infects mammalian cells by binding to its receptor, ACE2 which is mediated by the viral spike glycoprotein, specifically the receptor binding domain (RBD) within the spike protein. Recent development of vaccines against SARS-CoV-2 spike protein are currently the best strategy to reduce morbidity and mortality from infection. Like all viruses, SARS-CoV-2 evolves which may result in mutations which are benign or alter its viral fitness. The evolution of SARS-CoV-2 may increase the virulence, possibly by increasing the infectivity of the virus through strengthening the binding of the RBD to ACE2 or enabling the virus to evade naturally or vaccine induced immune responses. To address the need to characterise the evolution of SARS-CoV-2, this study has compared SARS-CoV2 sequences globally to the Wuhan reference strain at different time points. Additionally, by assigning scores to sequence data, which quantify each sequences binding strength to ACE2 and ability to evade patient derived antibodies, we have demonstrated that over time SARS-CoV-2 has evolved in less than one year to increase its ability to evade antibodies and increase the binding free energy between the RBD and ACE2.
Circadian clock disruption promotes the degeneration of dopaminergic neurons
Authors: Dorcikova Michaëla Majcin , Duret Lou C. , Pottié Emma , Nagoshi Emi
Published: October 2022

Sleep and circadian rhythm disruptions are frequent comorbidities of Parkinson’s disease (PD), a disorder characterized by the progressive loss of dopaminergic (DA) neurons in the substantia nigra. Although sleep/circadian disturbances can be observed years before diagnosing PD, it remains unclear whether circadian clocks have a causal role in the degenerative process. We demonstrated here that circadian clocks regulate the rhythmicity and magnitude of the vulnerability of DA neurons to oxidative stress inDrosophila. Circadian pacemaker neurons are presynaptic to a subset of DA neurons and rhythmically modulate their susceptibility to degeneration. The arrhythmicperiod(per) gene null mutation exacerbates the age-dependent loss of DA neurons and, in combination with brief oxidative stress, causes premature animal death. These findings suggest that circadian clock disruption promotes dopaminergic neurodegeneration.
Ixodes ricinustick bacteriome alterations based on a climatically representative survey in Hungary
Authors: Gréta Tóth Adrienn , Farkas Róbert , Papp Márton , Kilim Oz , Yun Haeun , Makrai László , Maróti Gergely , Gyurkovszky Mónika , Krikó Eszter , Solymosi Norbert
Published: October 2022

Background

The microbial communities of disease vectors may represent a key feature in several biological functions and thus deserve special attention in light of climate change and the consequent need to develop novel control strategies. Nevertheless, vector-borne microbial networks are still poorly understood. Assessing vectors’ microbial interactions and climatic dependencies may contribute to better-estimating pathogen transmission characteristics, public health risks and the urgency for control steps to be taken.

Methods

In a climatically representative country-wide survey,Ixodes ricinusticks were collected from 17 locations in Hungary. Using shotgun metagenomic sequencing, the bacteriome composition was analyzed by investigating the relationship between the abundances of nymphs and females in various climatic environments.

Results

Bacterial composition on the genus level revealed a significant difference between the samples from females and nymphs. Within the core bacteriome, females and nymphs showed significant variation in the following genera:Arsenophonus, Bacillus, Candidatus Midichloria, Rhodococcus, Sphingomonas, Staphylococcus, Wolbachia. Among females, according to temperature strata, the following were found differentiating:Curtobacterium, Pseudomonas, Sphingomonas. There was no genus with a significant difference in precipitation categories for females. In the nymphs,Curtobacteriumshowed significant variation between temperature andBacillusandCurtobacteriumfor various precipitation levels. Based on the full sample set,ArsenophonusandWolbachiacorrelated positively which we assumed to have occurred due to the presence ofI. hookeri.

Conclusions

The composition of vector-borne bacteriome members showed significant alterations at sampling points with different climatic conditions and development stages of the tick hosts. Our findings not only pave the way towards understanding tick-borne bacterial networks and interdependencies but also shed light on the high potential for the presence of a possible biological tick control species, the tick parasitoid,Ixodiphagus hookeribased on related bacteriome patterns. The results of conscious tick microbiome assessment studies may contribute to precision tick control strategies of the future.
HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations
Authors: Schira Mark M. , Isherwood Zoey J , Kassem Mustafa (Steve) , Barth Markus , Shaw Thomas B. , Roberts Michelle M , Paxinos George
Published: October 2022

We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolutionin vivoMR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm3isotropic resolution for T1w, T2w and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages ofin vivoMRI. For example, components of the thalamus, hypothalamus, and hippocampus - difficult or often impossible to identify using standard MRI protocols, can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with existingin vivoNeuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (www.hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high quality individual brain, this serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical and education settings.
Measuring the co-localization and dynamics of mobile proteins in live cells undergoing signaling responses
Authors: Shelby Sarah A. , Shaw Thomas R. , Veatch Sarah L.
Published: October 2022

ii.

Summary/Abstract

Single molecule imaging in live cells enables the study of protein interactions and dynamics as they participate in signaling processes. When combined with fluorophores that stochastically transition between fluorescent and reversible dark states, as in super-resolution localization imaging, labeled molecules can be visualized in single cells over time. This improvement in sampling enables the study of extended cellular responses at the resolution of single molecule localization. This chapter provides optimized experimental and analytical methods used to quantify protein interactions and dynamics within the membranes of adhered live cells. Importantly, the use of pair-correlation functions resolved in both space and time allows researchers to probe interactions between proteins on biologically relevant distance and time-scales, even though fluorescence localization methods typically require long times to assemble well-sampled reconstructed images. We describe an application of this approach to measure protein interactions in B cell receptor signaling and include sample analysis code for post-processing of imaging data. These methods are quantitative, sensitive, and broadly applicable to a range of signaling systems.
Effective Molecular Dynamics from Neural-Network Based Structure Prediction Models
Authors: Jussupow Alexander , Kaila Ville R. I.
Published: October 2022

Recent breakthroughs in neural-network based structure prediction methods, such as AlphaFold2 and RoseTTAFold, have dramatically improved the quality of computational protein structure prediction. These models also provide statistical confidence scores that can estimate uncertainties in the predicted structures, but it remains unclear to what extent these scores are related to the intrinsic conformational dynamics of proteins. Here we compare AlphaFold2 prediction scores with >60 μs of explicit molecular dynamics simulations of 28 one- and two-domain proteins with varying degree of flexibility. We demonstrate a strong correlation between the statistical prediction scores and the explicit motion derived from extensive atomistic molecular dynamics simulations, and further derive an elastic network model based on the statistical scores of AlphFold2 (AF-ENM), which we benchmark in combination with coarse-grained molecular dynamics simulations. We show that our AF-ENM method reproduces the global protein dynamics with improved accuracy, providing a powerful way to derive effective molecular dynamics using neural-network based structure prediction models.
A modular cloning toolbox including CRISPRi for the engineering of the human fungal pathogen and biotechnology hostCandida glabrata
Authors: Billerbeck Sonja , Prins Rianne C , Marquardt Malte
Published: October 2022

The yeastCandida glabratais an emerging, often drug-resistant opportunistic human pathogen, that can cause severe systemic infections in immunocompromised individuals. At the same time, it is a valuable biotechnology host that naturally accumulates high levels of pyruvate – a valuable chemical precursor. Tools for the facile engineering of this yeast could greatly accelerate studies on its pathogenicity and its optimization for biotechnology. While a few tools for plasmid-based expression and CRISPR/Cas-based genome engineering have been developed, there is no well-characterized cloning toolkit available that would allow the assembly of pathways or genetic circuits in a modular fashion. Here, by re-using and characterizing theSaccharomyces cerevisiae-based yeast molecular cloning toolkit (YTK) inC. glabrataand by adding missing components, we build a well-characterized CgTK (Candida glabratatoolkit). We used the CgTK to build a CRISPR interference system forC. glabratathat can be used to generate selectable phenotypes via single-gRNA targeting such as required for genome-wide library screens.
Sex-dimorphic neuroprotective effect of CD163 in an α-synuclein mouse model of Parkinson’s disease
Authors: Ferreira Sara A. , Li Conghui , Klæstrup Ida H. , Vitic Zagorka , Rasmussen Rikke K. , Kirkegaard Asger , Toft Gitte U. , Betzer Cristine , Svendsen Pia , Jensen Poul H. , Luo Yonglun , Etzerodt Anders , Moestrup Søren K. , Romero-Ramos Marina
Published: October 2022

Alpha-synuclein (α-syn) aggregation and immune activation represent hallmark pathological events in Parkinson’s disease (PD). The PD-associated immune response encompasses both brain and peripheral immune cells, although little is known about the immune proteins relevant for such response. We propose that the upregulation of CD163 observed in blood monocytes and in the responsive microglia in the PD patients is a protective mechanism in the disease. To investigate this, we used the PD model based on intrastriatal injections of murine α-syn pre-formed fibrils (PFF) in CD163 knockout (KO) mice and wild-type littermates. CD163KO females revealed an impaired and differential early immune response to α-syn pathology as revealed by immunohistochemical and transcriptomic analysis. After 6 months, CD163KO females showed an exacerbated immune response and α-syn pathology, which ultimately led to dopaminergic neurodegeneration of greater magnitude. These findings support a novel, sex-dimorphic neuroprotective role for CD163 during α-syn-induced neurodegeneration.
Nonionic surfactants can modify the thermal stability of globular and membrane proteins interfering with the thermal proteome profiling principles to identify protein targets
Authors: Berlin Emmanuel , Lizano-Fallas Veronica , Carrasco del Amor Ana , Fresnedo Olatz , Cristobal Susana
Published: October 2022

The membrane proteins are essential targets to understand cellular function. The unbiased identification of membrane protein targets is still the bottleneck for a system-level understanding of cellular response to stimuli or perturbations. It has been suggested to enrich the soluble proteome with membrane proteins by introducing nonionic surfactants in the solubilization solution. This strategy was aiming to simultaneous identify the globular and membrane protein targets by thermal proteome profiling principles. However, the thermal shift assay would surpass the cloud point temperature from the nonionic surfactants frequently utilized for membrane protein solubilization. It is expected that around the cloud point temperature, the surfactant micelles would suffer structural modifications altering protein solubility. Here, we show that the presence of nonionic surfactants can alter protein thermal stability from a mixed, globular and membrane, proteome. In the presence of surfactant micelles, the changes in proteins solubility analyzed after the thermal shift assay were affected by the thermal dependent modification of the micellar size, and its interaction with proteins. We demonstrate that the introduction of nonionic surfactants for the solubilization of membrane proteins is not compatible with the principles of target identification by thermal proteome profiling methodologies. Our results lead to explore thermal-independent strategies for membrane protein solubilization to assure confident membrane protein target identification. The proteome-wide thermal shift methods have already shown their capability to elucidate mechanisms of action from pharma, biomedicine, analytical chemistry, or toxicology and finding strategies, free from surfactants, to identify membrane protein targets would be the next challenge.
Altered cohesin dynamics and histone H3K9 modifications contribute to mitotic defects in thecbf11Δlipid metabolism mutant
Authors: Vishwanatha Akshay , Princová Jarmila , Hohoš Patrik , Zach Róbert , Převorovský Martin
Published: October 2022

Mitotic fidelity is crucial for the faithful distribution of genetic information into the daughter cells. Many fungal species, including the fission yeastSchizosaccharomyces pombe, undergo a closed form of mitosis, during which the nuclear envelope does not break down. InS. pombenumerous processes have been identified that contribute to successful completion of mitosis. Notably, perturbations of lipid metabolism can lead to catastrophic mitosis and the “cut” phenotype. It was suggested that these mitotic defects are caused by insufficient membrane phospholipid supply during the anaphase nuclear expansion. However, it is not clear whether additional factors are involved. In this study we characterized in detail the mitosis in anS. pombemutant lacking the Cbf11 transcription factor, which regulates lipid metabolism genes. We show that incbf11Δcells mitotic defects appear already prior to anaphase, before the nuclear expansion begins. Moreover, we identify altered cohesin dynamics and centromeric chromatin structure as additional factors affecting mitotic fidelity in cells with disrupted lipid homeostasis, providing new insights into this fundamental biological process.