bluuebunny/crossref_metadata_2025 huggingface dataset:
Cisplatin Induces BDNF Downregulation in Middle-Aged Female Rat Model while BDNF Enhancement Attenuates Cisplatin Neurotoxicity
Authors: Lomeli Naomi , Pearre Diana C. , Cruz Maureen , Di Kaijun , Bota Daniela A.
Published: May 2023

Cancer-related cognitive impairments (CRCI) are debilitating consequences of cancer treatment with platinum agents (e.g., cisplatin) that greatly alter cancer survivors’ health-related quality of life. Brain-derived neurotrophic factor (BDNF) plays an essential role in neurogenesis, learning, and memory, and the reduction of BDNF is associated with the development of cognitive impairment in various neurological disorders, including CRCI. Our previous CRCI rodent studies have shown that cisplatin reduces hippocampal neurogenesis and BDNF expression and increases hippocampal apoptosis, which is associated with cognitive impairments. Few studies have reported on the effects of chemotherapy and medical stress on serum BDNF levels and cognition in middle-aged female rat models. The present study aimed to compare the effects of medical stress and cisplatin on serum BDNF levels and cognitive performance in 9-month-old female Sprague Dawley rats to age-matched controls. Serum BDNF levels were collected longitudinally during cisplatin treatment, and cognitive function was assessed by novel object recognition (NOR) 14 weeks post-cisplatin initiation. Terminal BDNF levels were collected ten weeks after cisplatin completion. We also screened three BDNF-augmenting compounds, riluzole, ampakine CX546, and CX1739, for their neuroprotective effects on hippocampal neurons,in vitro. We assessed dendritic arborization by Sholl analysis and dendritic spine density by quantifying postsynaptic density-95 (PSD95) puncta. Cisplatin and exposure to medical stress reduced serum BDNF levels and impaired object discrimination in NOR compared to age-matched controls. Pharmacological BDNF augmentation protected neurons against cisplatin-induced reductions in dendritic branching and PSD95. Ampakines (CX546 and CX1739) but not riluzole altered the antitumor efficacy of cisplatin in two human ovarian cancer cell lines, OVCAR8 and SKOV3.ip1,in vitro.In conclusion, we established the first middle-aged rat model of cisplatin-induced CRCI, assessing the contribution of medical stress and longitudinal changes in BDNF levels with cognitive function. We conducted anin vitroscreening of BDNF-enhancing agents to evaluate their potential neuroprotective effects against cisplatin-induced neurotoxicity and their effect on ovarian cancer cell viability.
The cellular basis of feeding-dependent body size plasticity in sea anemones
Authors: Garschall Kathrin , Pascal-Carreras Eudald , Garcia-Pascual Belén , Filimonova Daria , Guse Annika , Johnston Iain G. , Steinmetz Patrick R.H
Published: May 2023

Animals with indeterminate growth can adapt their growth rate and body size to changing food availability throughout their lifetime. As the cellular basis underlying food-dependent growth plasticity is poorly understood, we quantified how the sea anemonesNematostella vectensisandExaiptasia diaphana(Aiptasia) respond to feeding and starvation on organismal and cellular levels. Using mathematical modelling to analyse growth phases, we found that growth and shrinkage rates inNematostellaare exponential, stereotypic and accompanied by high levels of cell gain or loss, respectively. During starvation and re-feeding, a considerable proportion of juvenile polyp cells (>7%) reversibly shift between S/G2/M and G1/G0cell cycle phases, suggesting a tight nutritional control of quiescence and cell cycle re-entry. In the facultative symbiotic sea anemone Aiptasia, we found that growth and cell proliferation rates are dependent on the symbiotic state and, in comparison toNematostella, respond less strongly to changes in food supply. Altogether, we provide a benchmark and resource to study the nutritional regulation of body plasticity on molecular, cellular and genomic levels using the rich functional toolkit available forNematostella.

Summary statement

Feeding and starvation in sea anemones induce growth and shrinkage, cell size changes and dynamic cell proliferation changes that support a nutritional control of quiescence and cell cycle re-entry.
Indirect Correlative Light and Electron Microscopy (iCLEM): A Novel Pipeline for Multiscale Quantification of Structure from Molecules to Organs
Authors: Struckman Heather L. , Moise Nicolae , Vanslembrouck Bieke , Rothacker Nathan , Chen Zhenhui , van Hengel Jolanda , Weinberg Seth H. , Veeraraghavan Rengasayee
Published: May 2023

Correlative light and electron microscopy (CLEM) methods are powerful methods which combine molecular organization (from light microscopy) with ultrastructure (from electron microscopy). However, CLEM methods pose high cost/difficulty barriers to entry and have very low experimental throughput. Therefore, we have developed anindirectcorrelative light and electron microscopy (iCLEM) pipeline to sidestep the rate limiting steps of CLEM (i.e., preparing and imaging the same samples on multiple microscopes) and correlate multiscale structural data gleaned from separate samples imaged using different modalities by exploiting biological structures identifiable by both light and electron microscopy as intrinsic fiducials.

We demonstrate here an application ofiCLEM, where we utilized gap junctions and mechanical junctions between muscle cells in the heart as intrinsic fiducials to correlate ultrastructural measurements from transmission electron microscopy (TEM), and focused ion beam scanning electron microscopy (FIB-SEM) with molecular organization from confocal microscopy and single molecule localization microscopy (SMLM). We further demonstrate howiCLEMcan be integrated with computational modeling to discover structure-function relationships. Thus, we presentiCLEMas a novel approach that complements existing CLEM methods and provides a generalizable framework that can be applied to any set of imaging modalities, provided suitable intrinsic fiducials can be identified.
Adaptive RAxML-NG: Accelerating Phylogenetic inference under Maximum Likelihood using dataset difficulty
Authors: Togkousidis Anastasis , Kozlov Alexey M. , Haag Julia , Höhler Dimitri , Stamatakis Alexandros
Published: May 2023

Motivation

Phylogenetic inferences under the Maximum-Likelihood (ML) criterion deploy heuristic tree search strategies to explore the vast search space. Depending on the input dataset, searches from different starting trees might all converge to a single tree topology. Often, though, distinct searches infer multiple topologies with large log-likelihood score differences or yield topologically highly distinct, yet almost equally likely, trees. Recently, Haaget al. introduced an approach to quantify, and implemented machine learning methods to predict, the difficulty of an MSA with respect to phylogenetic inference. Easy MSAs exhibit a single likelihood peak on their likelihood surface, associated with a single tree topology to which most, if not all, independent searches rapidly converge. However, as difficulty increases, multiple locally optimal likelihood peaks emerge, yet from highly distinct topologies.

Results

To this end, we introduce and implement an adaptive tree search heuristic in RAxML-NG, which modifies the thoroughness of the tree search strategy as a function of the predicted difficulty. Our adaptive strategy is based upon three observations. First, on easy datasets, searches converge rapidly and can hence be terminated at an earlier stage. Second, over-analyzing difficult datasets is hopeless and, thus, it suffices to quickly infer only one of the numerous almost equally likely topologies, to reduce overall execution time. Third, more extensive searches are justified and required on datasets with intermediate difficulty. While the likelihood surface exhibits multiple locally optimal peaks in this case, a small proportion of them is significantly better. Our experimental results for the adaptive heuristic on 9, 515 empirical and 5, 000 simulated datasets with varying difficulty exhibit substantial speedups, especially on easy and difficult datasets (53% of total MSAs), where we observe average speedups of more than 10x. Further, approximately 94% of the inferred trees using the adaptive strategy are statistically indistinguishable from the trees inferred under the standard strategy (RAxML-NG).

Availability

GNU GPL athttps://github.com/togkousa/raxml-ng/tree/adaptive.

Contact

Anastasis.Togkousidis@h-its.org

Supplementary Material

Available
Extrastriate activity reflects the absence of local retinal input
Authors: Urale Poutasi W. B. , Zhu Lydia , Gough Roberta , Arnold Derek , Schwarzkopf Dietrich Samuel
Published: May 2023

The physiological blind spot corresponds to the optic disc where the retina contains no light-detecting photoreceptor cells. Our perception seemingly fills in this gap in input. Here we suggest that rather than an active process, such perceptual filling-in could instead be a consequence of the integration of visual inputs at higher stages of processing discounting the local absence of retinal input. Using functional brain imaging, we resolved the retinotopic representation of the physiological blind spot in early human visual cortex and measured responses while participants perceived filling-in. Responses in early visual areas simply reflected the absence of visual input. In contrast, higher extrastriate regions responded more to stimuli in the eye containing the blind spot than the fellow eye. However, this signature was independent of filling-in. We argue that these findings agree with philosophical accounts that posit that the concept of filling-in of absent retinal input is unnecessary.
Toward Understanding Genetic Risk of Burnout through Genome-wide Associations of Cynicism and Cynical Distrust
Authors: Chapleau Richard R
Published: May 2023

Cynicism is an attitude that people are motivated primarily by self-interest, and often manifests alongside emotions like contempt, anger, and hostility. Cynicism can impact all aspects of an individual’s life: in the workplace it is a critical component of burnout, while at home it often leads to marital dissatisfaction and increased family conflicts. Using data from 2,317 participants in the CARDIA Cohort study, we performed a genome-wide association study (GWAS) to identify genetic variants related to cynicism and the cynical distrust sub-trait. We performed two GWAS tests for each trait, one without controlling for population stratification and a second where we considered possible ancestry-related stratification using principal component analysis within plink 1.9. We also tested multiple genetic inheritance models. Finally, we performed pathway analysis using the STRINGdb web resource to identify meaningful relationships. From our various approaches, we identified 12 variants associated with high cynicism in an additive model and 258 in a genotypic model. We also identified 24 and 275 variants associated with cynical distrust using the respective models. Our network analysis revealed clear pathways for how cynicism can lead to health outcomes like cardiovascular disease, adrenal disorders, neurological disorders, and even addiction. Specifically, genes involved in 30 distinct KEGG pathways were related to cynicism and clear connections can be made between cynicism and cardiomyopathies, Cushing syndrome, Alzheimer’s disease, and amphetamine addiction. Each of the outcomes are supported by gene association with at least 3 intermediate pathways. Our results provide the first objective evidence supporting the observational literature connections to cardiovascular disease, Alzheimer’s disease, and addiction. To the best of our knowledge, this is the first evidence presenting a relationship between cynicism and Cushing’s syndrome, demonstrating the power of population and statistical genetics.
Causal relationships between risk of venous thromboembolism and 18 cancers: a bidirectional Mendelian randomisation analysis
Authors: Cornish Naomi , Haycock Philip , Brenner Hermann , Figueiredo Jane C. , Galesloot Tessel , Grant Robert C ,   InterLymph consortium,   INVENT-MVP consortium, Johansson Mattias , Mariosa Daniela , McKay James , Pai Rish , Pellatt Andrew J , Samadder N. Jewel , Shi Jianxin , Thibord Florian , Trégouët David-Alexandre , Voegele Catherine , Thirlwell Chrissie , Mumford Andrew , Langdon Ryan
Published: May 2023

Background:People with cancer experience high rates of venous thromboembolism (VTE). Additionally, risk of subsequent cancer is increased in people experiencing their first VTE. The causal mechanisms underlying this association are not completely understood, and it is unknown whether VTE is itself a risk factor for cancer.

Methods:We used data from large genome-wide association study meta-analyses to perform bi-directional Mendelian randomisation analyses to estimate causal associations between genetically-proxied lifetime risk of VTE and risk of 18 different cancers.

Results:We found no conclusive evidence that genetically-proxied lifetime risk of VTE was causally associated with an increased incidence of cancer, or vice-versa. We observed an association between VTE and pancreatic cancer risk (odds ratio for pancreatic cancer 1.23 (95% confidence interval 1.08 - 1.40) per log-odds increase in risk of VTE,P =0.002). However, sensitivity analyses revealed this association was predominantly driven by a variant proxying non-O blood group, with inadequate evidence from Mendelian randomisation to suggest a causal relationship.

Conclusions:These findings do not support the hypothesis that genetically-proxied lifetime risk of VTE is a cause of cancer. Existing observational epidemiological associations between VTE and cancer are therefore more likely to be driven by pathophysiological changes which occur in the setting of active cancer and anti-cancer treatments. Further work is required to explore and synthesise evidence for these mechanisms.

Key messages

1) There is strong observational evidence that active cancer is associated with venous thromboembolism.

2) It is currently unknown whether venous thromboembolism is a risk factor for cancer.

3) We applied a bi-directional Mendelian randomisation framework to appraise the causal relationships between genetically-proxied risk of venous thromboembolism and 18 different cancers.

4) Overall, there was no clear evidence from Mendelian randomisation that lifetime-elevated risk of venous thromboembolism is causally associated with an increased risk of cancer, or visa versa.
The genetic dissection of fetal haemoglobin persistence in sickle cell disease in Nigeria
Authors: Ojewunmi Oyesola O. , Adeyemo Titilope A. , Oyetunji Ajoke I. , Inyang Bassey , Akinrindoye Afolashade , Mkumbe Baraka S. , Gardner Kate , Rooks Helen , Brewin John , Patel Hamel , Lee Sang-Hyuck , Chung Raymond , Rashkin Sara , Kang Guolian , Chianumba Reuben , Sangeda Raphael , Mwita Liberata , Isa Hezekiah , Agumadu Uche-Nnebe , Ekong Rosemary , Faruk Jamilu A. , Jamoh Bello Y. , Adebiyi Niyi M. , Umar Ismail A. , Hassan Abdulaziz , Grace Christopher , Goel Anuj , Inusa Baba P.D. , Falchi Mario , Nkya Siana , Makani Julie , Ahmad Hafsat R. , Nnodu Obiageli , Strouboulis John , Menzel Stephan
Published: May 2023

Background

The clinical severity of sickle cell disease (SCD) is strongly influenced by the level of fetal haemoglobin (HbF) persistent in each patient. Three major HbF loci (BCL11A,HBS1L-MYB, andXmn1-HBG2) have been reported, but a considerable hidden heritability remains.

Aim

Building on the power of a large and genetically diverse patient pool present in Nigeria, we conducted a genome-wide association study for HbF levels in patients from three regions of the country with a diverse ethnic make-up.

Methods

We analysed genome-wide trait association in 1006 Nigerian patients with SCD (HbSS/HbSβ0), followed by a replication and meta-analysis exercise in four independent SCD cohorts (3,582 patients). To dissect association signals at the major loci, we performed stepwise conditional analysis, haplotype association analysis and included public functional annotation data (fGCTA).

Results

Association signals were detected forBCL11A(lead SNP rs6706648, β=- 0.39,P=4.96 x 10-34) andHBS1L-MYB(lead SNP rs61028892, β=0.73,P=1.18 x 10-9), whereas the variant allele forXmn1-HBG2was found to be very rare. Genetically dissecting the two major loci, we defined trait-boosting haplotypes containing suspected or so-far unidentified causal variants. AtBCL11A, one such haplotype (trait increaseP< 0.0001) contains the putative functional variant rs1427407-‘T’ and a second haplotype (P< 0.0001) is tagged by the rs7565301-‘A’ allele, with no obvious candidate causal variant. AtHBS1L- MYB, one haplotype (trait increaseP< 0.0001) contains the likely functional rs66650371 (Δ3-bp), and a second (P< 0.0001) is tagged by the ‘C’ allele of rs6102889. Together, variants atBCL11AandHBS1L-MYBSNPs explained 24.1% of the trait variance.

We detected three novel association signals:SLC28A3on chromosome 9 (rs115555854: β=- 0.73,P=2.52 x 10-8),TICRRon chromosome 15 (rs140496989: β=-0.43,P=3.34 x 10-8), andPIEZO2on chromosome 18 (rs58817161: β= −0.63,P= 8.04 x 10-8). These appeared to be restricted to the Nigerian patient cohort and were not confirmed in the replication cohorts.

Conclusions

Studying a diverse cohort of Nigerian patients with sickle cell disease, we genetically dissected the known fetal-haemoglobin lociBCL11AandHBS1L-MYBand detected putative new trait-associated regions.
A common gene signature of the right ventricle in failing rat and human hearts
Authors: Jurida Liane , Werner Sebastian , Knapp Fabienne , Niemann Bernd , Li Ling , Grün Dimitri , Wirth Stefanie , Weber Axel , Beuerlein Knut , Liebetrau Christoph , Wiedenroth Christoph B. , Guth Stefan , Kojonazarov Baktybek , Jafari Leili , Weissmann Norbert , Günther Stefan , Braun Thomas , Rohrbach Susanne , Kracht Michael
Published: May 2023

The molecular mechanisms of progressive right heart failure are incompletely understood. We systematically compared rat models of pulmonary artery or aortic banding to identify the transcriptomic changes that occur over months in the failing right versus left ventricle. Detailed bioinformatics analyses of 181 RNAseq datasets from cardiomyocytes or whole heart samples from these models, led to the identification of gene signatures, protein, and transcription factor networks specific to ventricles, compensated or decompensated disease states and type of heart failure. RNA-FISH approaches confirmed PAB-mediated regulation of key genes and revealed striking, spatially heterogeneous mRNA expression in the heart. Intersection of rat PAB-specific gene sets with 95 transcriptome data sets from human patients with chronic thromboembolic pulmonary hypertension led to the identification of more than 50 genes whose expression levels strongly correlated with the severity of right heart disease. Together, these data define a conserved, differentially regulated genetic network that coordinates progressive right heart failure in rats and humans.

Highlights

Side-by-side comparisons of RV or LV transcriptomes in the slowly failing rat heart

Identification of RV-specific gene sets in heart hypertrophy versus heart failure

Identification of RV gene sets correlating with severity of human CTEPH

Development of a core gene signature characteristic for RV failure
Effects of ketamine on frontoparietal interactions during working memory in macaque monkeys
Authors: Ma Liya , Katyare Nupur , Johnston Kevin , Everling Stefan
Published: May 2023

Schizophrenia is known as a syndrome of dysconnection among brain regions. As a model for this syndrome, low doses of N-methyl-D-aspartate (NMDA) receptor antagonists, such as ketamine, produce schizophrenia-like symptoms and cognitive deficits in healthy humans and animals. One of such deficits is impaired working memory, a process that engages an extended network of both frontal and parietal areas. While ketamine is known to disrupt working memory by altering both spiking and oscillatory activities in the lateral prefrontal cortex (lPFC), it remains unknown whether NMDA receptor antagonists also produce frontoparietal dysconnection during working memory processes. Here, we simultaneously recorded both single unit activities and local field potentials from lPFC and posterior parietal cortex (PPC) in macaque monkeys during a rule-based working memory task. Like previous work in the lPFC alone, we found that ketamine compromised delay-period rule coding in single neurons and reduced low-frequency oscillations in the PPC. Furthermore, ketamine reduced task-related connectivity in both fronto-parietal and parieto-frontal directions. Consistent with this, ketamine also weakened interareal coherence between spiking and low-frequency oscillatory activities. Our findings demonstrate the utility of acute NMDA receptor antagonist in simulating a syndrome of dysconnection and support this model in its potential for the exploration of novel treatment strategies for schizophrenia.
Simple droplet microfluidics platform for drug screening on cancer spheroids
Authors: Parent Caroline , Raj Melayil Kiran , Zhou Ya , Aubert Vivian , Surdez Didier , Delattre Olivier , Wilhelm Claire , Viovy Jean-Louis
Published: May 2023

3D in vitro biological systems are progressively replacing 2D systems to increase the physiological relevance of cellular studies. Microfluidics-based approaches can be powerful tools towards such biomimetic systems, but often require high-end complicated and expensive processes and equipments for microfabrication. Herein, a drug screening platform is proposed, minimizing technicality and manufacturing steps. It provides an alternate way of spheroid generation in droplets in tubes. Droplets microfluidics then elicit multiple droplets merging events at programmable times, to submit sequentially the spheroids to chemotherapy and to reagents for cytotoxicity screening. After a comprehensive study of tumorigenesis within the droplets, the system is validated for drug screening (IC50) with chemotherapies in cancer cell lines as well as cells from patient-derived-xenografts (PDX). As compared to microtiter plates methods, our sytem reduces the initial amout of cell up to 10 times and opens new avenues towards primary tumors drug screening approaches.
A comparison of behavior paradigms assessing spatial memory in tree shrew
Authors: Li Cheng-Ji , Hui Yi-Qing , Zhang Rong , Zhou Hai-Yang , Cai Xing , Lu Li
Published: May 2023

Spatial cognition enables animals to navigate the environment. Impairments in spatial navigation are often preclinical signs of Alzheimer’s disease (AD) in human. Therefore, evaluating spatial memory deficits is valuable when assessing incipient AD in animal models. The Chinese tree shrew, a close relative of primates, possesses many features that make it suitable for AD research. However, there is a scarcity of reliable behavior paradigms to monitor changes in spatial cognition in this species. To address this, we established reward-based paradigms in the radial-arm maze and the cheeseboard maze for tree shrew, and tested spatial memory of a group of twelve male animals in both tasks, along with a control water maze test, before and after bilateral lesions to the hippocampus, the brain region essential for spatial navigation. Tree shrews memorized target positions during training, and their task performance improved gradually until reaching a plateau in all three mazes. After the lesion, spatial learning was compromised in both newly-developed tasks, whereas memory retrieval was impaired in the water maze. Furthermore, individual task performance in both dry-land paradigms depended heavily on the size of remaining hippocampal tissue. Notably, all lesioned animals displayed spatial memory deficits in the cheeseboard task, but not in the other two paradigms. Our results suggest that the cheeseboard task currently represents the most sensitive paradigm for assessing spatial memory in tree shrew, with the potential to monitor progressive cognitive declines in aged or genetically modified animals developing AD-like symptoms.

Significance Statement

Cognitive tests that monitor impairments in spatial memory play a crucial role in evaluating animal models with early-stage Alzheimer’s disease (AD). The Chinese tree shrew possesses many features suitable for an AD model, yet behavior tests assessing spatial cognition in this species are lacking. Here we developed novel behavior paradigms tailored to measure spatial memory in tree shrews and evaluated their sensitivity to changes in spatial learning by examining a group of hippocampus-lesioned animals. Our results indicate that the cheeseboard task effectively detects impairments in spatial memory and holds potential for monitoring the progressive cognitive decline in aged or genetically modified tree shrews that develop AD-like symptoms. This research may facilitate the use of tree shrew model in AD research.
GWAIS-Web: A Fast and Secure Web Service for Epistasis Detection in Genome-wide Association Interaction Studies
Authors: Wienbrandt Lars , Prieß Christoph , Ellinghaus David
Published: May 2023

Motivation

Genome-wide association interaction studies (GWAIS) are becoming increasingly important as estimates of genetic interactions at the genome-wide level using genome-wide data from hundreds of thousands of individuals from large biobanks showed that non-additive genetic variance plays a role in complex human traits in addition to additive genetic effects identified in genome-wide association studies (GWAS). However, a comprehensive genome-wide search for all combinations of second-order (SNPxSNP) or third-order (SNPxSNPxSNP) associations using millions of SNP markers is a very computationally intensive task, especially when hundreds of thousands or, in the near future, even millions of individuals can be studied with GWAS datasets. The runtime so far exceeds years, even if the search is performed on a multicore CPU server system.

Results

We developedGWAIS-Web, a web service for fast analysis of genome-wide interactions with case-control GWAS datasets. By using a hybrid combination of graphics-processing units (GPUs) and field-programmable gate arrays (FPGAs),GWAIS-Webspeeds up epistasis detection methods for binary traits by a factor of more than 2000, allowing an exhaustive SNP-SNP GWAIS with a GWAS data set of one million SNPs and 500,000 individuals to complete within one day, which would take more than five years on a regular CPU server system. The user can choose between different methods for epistasis detection, such as logistic regression, BOOST, mutual information (MI) and others, with calculations in double precision and including on-the-fly filtering of correlated results based on linkage disequilibrium (LD). Due to the underlying common data structure ofGWAIS-Web, all methods can be combined and processed together on-the-fly without increasing the runtime. The user can choose between 2nd order (pairwise) and 3rd order tests and can also limit the search to selected chromosomal regions.GWAIS-Weboffers a high level of security through optional 2-factor authentication, encrypted connections and the protection of GWAS/user account data in accordance with the European General Data Protection Regulation (GDPR).

Availability

GWAIS-Webis freely available athttps://hybridcomputing.ikmb.uni-kiel.de. The stand-alone softwareHybridGWAIScan be downloaded athttps://github.com/ikmb/hybridgwais.

Supplementary information

Supplementary data are available online.
Sense and Screen-ability: Development of tuneable, biosensor-based screening platforms for abscisic acid
Authors: Otto Maximilian , Dabirian Yasaman , David Florian , Siewers Verena
Published: May 2023

The activities of heterologous enzymes often limit the production titers, rates and yields of cell factories. With the help of biosensors, large random mutagenesis libraries can be screened for improved enzyme variants in a high-throughput manner, even if the enzyme-of-interest is poorly characterised.

We previously constructed aSaccharomyces cerevisiaecell factory for the heterologous production of abscisic acid (ABA), a high-value product with a broad range of applications in medicine, agriculture and nutrition. In the current study, we developed high-throughput screening platform strains for two rate-limiting cytochrome P450 monooxygenases, BcABA1 and BcABA2, in the ABA biosynthetic pathway. The screening platforms are designed to minimize the occurrence of false positives during screening experiments.

We thoroughly characterised two plant protein-based ABA biosensor candidates. Furthermore, we designed a simple genetic switch, based on the thiamine-repressible promoter pTHI4, to regulate the expression level of enzyme variants. We demonstrated that ABA production can be fine-tuned by varying thiamine concentration in the media. In-depth analysis of the platform strains revealed that screening conditions can be optimized by varying thiamine concentration and cultivation time, making it possible to utilize the full dynamic and operational range of the biosensor. In the future, the constructed strains can be used to screen for improved BcABA1 and BcABA2 variants.
Parameter Inference for an Astrocyte Model using Machine Learning Approaches
Authors: Fritschi Lea , Lenk Kerstin
Published: May 2023

Astrocytes are the largest subset of glial cells and perform structural, metabolic, and regulatory functions. They are directly involved in the communication at neuronal synapses and the maintenance of brain homeostasis. Several disorders, such as Alzheimer’s, epilepsy, and schizophrenia, have been associated with astrocyte dysfunction. Computational models on various spatial levels have been proposed to aid in the understanding and research of astrocytes. The difficulty of computational astrocyte models is to fastly and precisely infer parameters. Physics informed neural networks (PINNs) use the underlying physics to infer parameters and, if necessary, dynamics that can not be observed. We have applied PINNs to estimate parameters for a computational model of an astrocytic compartment. The addition of two techniques helped with the gradient pathologies of the PINNS, the dynamic weighting of various loss components and the addition of Transformers. To overcome the issue that the neural network only learned the time dependence but did not know about eventual changes of the input stimulation to the astrocyte model, we followed an adaptation of PINNs from control theory (PINCs). In the end, we were able to infer parameters from artificial, noisy data, with stable results for the computational astrocyte model.
Icarust, a real-time simulator for Oxford Nanopore adaptive sampling
Authors: Munro Rory , Payne Alexander , Loose Matthew
Published: May 2023

1

Oxford Nanopore Technologies (ONT) sequencers enable real-time generation of sequence data, which allows for concurrent analysis during a run. Adaptive sampling leverages this real-time capabilityin extremis, rejecting or accepting reads for sequencing based on assessment of the sequence from the start of each read. This functionality is provided by ONT’s software, MinKNOW (https://community.nanoporetech.com/downloads). Designing and developing software to take advantage of adaptive sampling can be expensive due to the cost of using real sequencing consumables, using precious samples and preparing sequencing libraries. MinKNOW addresses this issue in part by providing the ability to replay previously sequenced runs for testing, using its playback functionality. However, as we have illustrated here, the sequencing output only partially changes in response to adaptive sampling instructions. Here we present Icarust, a tool enabling more accurate approximations of sequencing runs. Icarust recreates all the required endpoints of MinKNOW to perform adaptive sampling and writes output compatible with current base-callers and analysis pipelines. Icarust is capable of serving nanopore signal to simulate a MinION or PromethION flow cell experiment from any reference genome using either R9 or R10 pore signal. We show that simulating sequencing runs with Icarust provides a realistic testing and development environment for software exploiting the real-time nature of Nanopore sequencing.

Availability and Implementation

All code is open source and freely available here -https://github.com/LooseLab/Icarust. Icarust is implemented in Rust, with an easy to install and use docker container available.

Supplementary Information

Supplementary information is available here -https://github.com/Adoni5/Icarust_paper.
Cutin-Derived Oligomers Act as Damage-Associated Molecular Patterns inArabidopsis thaliana
Authors: Moreira Carlos J.S. , Escórcio Rita , Bento Artur , Bjornson Marta , Tomé Ana S. , Martins Celso , Fanuel Mathieu , Martins Isabel , Bakan Benedicte , Zipfel Cyril , Pereira Cristina Silva
Published: May 2023

The cuticle constitutes the outermost defensive barrier of most land plants. It comprises a polymeric matrix – cutin, surrounded by soluble waxes. Moreover, the cuticle constitutes the first line of defense against pathogen invasion, while also protecting the plant from many abiotic stresses. Aliphatic monomers in cutin have been suggested to act as immune elicitors in plants. This study analyses the potential of tomato cutin oligomers to act as damage-associated molecular patterns (DAMPs) able to induce a rapid immune response in the model plantArabidopsis. Cutin oligomeric mixtures led to Ca2+influx and MAPK activation inArabidopsis. Comparable responses were measured for cutin, which was also able to induce a reactive oxygen species (ROS) burst. Furthermore, treatment ofArabidopsiswith cutin oligomers resulted in a unique transcriptional reprogramming profile, having many archetypal features of pattern-triggered immunity (PTI). Targeted spectroscopic and spectrometric analyses of the cutin oligomers suggest that the elicitors compounds consist mostly of two up to three 10,16-dihydroxyhexadecanoic acid monomers linked together through ester bonds. This study demonstrates that cutin breakdown products can act as DAMPs; a novel class of elicitors deserving further characterization.
Comparison of phage-derived recombinases for genetic manipulation ofPseudomonasspecies
Authors: Kalb Madison J. , Grenfell Andrew W. , Jain Abhiney , Fenske-Newbart Jane , Gralnick Jeffrey A.
Published: May 2023

Several strains in thePseudomonasgenus are categorized as plant growth promoting rhizobacteria (PGPR). Although several of these strains are strong candidates for applications as biofertilizers or biopesticides, known genome editing approaches are generally limited and require further development. Editing genomes in PGPR could enable more robust agricultural applications, persistence and biosafety measures. In this study, we investigate the use of five phage-encoded recombinases to develop a recombineering workflow in 3 PGPR strains:P. protegensPf-5,P. protegensCHA0, andP. putidaKT2440. Using point mutations in therpoBgene, we reach maximum recombineering efficiencies of 1.5 x 10-4, 3 x 10-4, and 5 x 10-5, respectively, in these strains using λ-Red Beta recombinase fromE. coli. We further examine recombineering efficiencies across these strains as a function of selected mutation, editing template concentration, and phosphorothiolate bond protection. This work validates the use of these tools across several environmentally and biotechnologically relevant strains to expand the possibilities of genetic manipulation in thePseudomonasgenus.

Importance

ThePseudomonasgenus contains many members currently being investigated for applications in biodegradation, biopesticides, biocontrol and synthetic biology. Though several strains have been identified with beneficial properties, in situ genetic manipulations to further improve these strains for commercial applications have been limited due to lack of efficient genetic tools that have been tested across this genus. Here we test the recombineering efficiencies of 5 phage-derived recombinases across 3 biotechnologically relevantPseudomonasstrains:P. putidaKT2440,P. protegensPf-5, andP. protegensCHA0. These results demonstrate a method to generate targeted mutations quickly and efficiently across these strains, ideally introducing a method that can be implemented across thePseudomonasgenus and a strategy that may be applied to develop analogous systems in other non-model bacteria.
CParty: Hierarchically Constrained Partition Function of RNA Pseudoknots
Authors: Trinity Luke , Gray Mateo , Will Sebastian , Ponty Yann , Stege Ulrike , Jabbari Hosna
Published: May 2023

Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithmsthat minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As most prominent example McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization. While this algorithm became hugely successful for the stochastic analysis of pseudoknot-free RNA structure, as of yet there exists only one pseudoknotted partition function implementation, which covers only simple pseudoknots and comes with a borderline-prohibitive complexity of O(n^5) in the RNA length n. In this article, we develop a partition function algorithm corresponding to the hierarchical pseudoknot prediction of HFold, which performs exact optimization in a realistic pseudoknot energy model. In consequence, our algorithm CParty carries over HFold's advantages over classical pseudoknot prediction to stochastic analysis. In only cubic time, it computes the hierarchically constrained partition function over pseudoknotted density-2 structures G U G', composed of pseudoknot-free parts G and G', where G is given. Thus, it follows the common hypothesis of hierarchical pseudoknot formation, where pseudoknots form as tertiary contacts only after a first pseudoknot-free 'core' G. Like HFold, CParty is very efficient, achieving the low complexity of the pseudoknot-free algorithm. Finally, by computing pseudoknotted ensemble energies, we unveil kinetics features of a therapeutic target in SARS-CoV-2. Availibility: CParty is available at https://github.com/HosnaJabbari/CParty.
Enhancing AlphaFold-Multimer-based Protein Complex Structure Prediction with MULTICOM in CASP15
Authors: Liu Jian , Guo Zhiye , Wu Tianqi , Roy Raj S. , Quadir Farhan , Chen Chen , Cheng Jianlin
Published: May 2023

AlphaFold-Multimer has emerged as the state-of-the-art tool for predicting the quaternary structure of protein complexes (assemblies or multimers) since its release in 2021. To further enhance the AlphaFold-Multimer-based complex structure prediction, we developed a new quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine the outputs generated by AlphaFold2-Multimer. Specifically, MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural models by using both traditionalsequencealignments and new Foldseek-basedstructurealignments, ranks structural models through multiple complementary metrics, and refines the structural models via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. Our server (MULTICOM_qa) ranked 3rdamong 26 CASP15 server predictors and our human predictor (MULTICOM_human) ranked 7thamong 87 CASP15 server and human predictors. The average TM-score of the first models predicted by MULTICOM_qa for CASP15 assembly targets is ∼0.76, 5.3% higher than ∼0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 models predicted by MULTICOM_qa is ∼0.80, about 8% higher than ∼0.74 of the standard AlphaFold-Multimer. Moreover, the novel Foldseek Structure Alignment-based Model Generation (FSAMG) method based on AlphaFold-Multimer outperforms the widely used sequence alignment-based model generation. The source code of MULTICOM is available at:https://github.com/BioinfoMachineLearning/MULTICOM3.
Deep learning and host variable embedding augment microbiome-based simultaneous detection of multiple diseases
Authors: Wu Shunyao , Li Zhiruo , Chen Yuzhu , Zhang Mingqian , Sun Yangyang , Xing Jieqi , Zhao Fengyang , Huang Shi , Knight Rob , Su Xiaoquan
Published: May 2023

Microbiome has emerged as a promising indicator or predictor of human diseases. However, previous studies typically labeled each specimen as either healthy or with a specific disease, ignoring the prevalence of complications or comorbidities in actual cohorts, which may confound the microbial-disease associations. For instance, a patient may suffer from multiple diseases, making it challenging to detect their health status accurately. Furthermore, host phenotypes such as physiological characteristics and lifestyles can alter the microbiome structure, but this information has not yet been fully utilized in data models. To address these issues, we propose a highly explainable deep learning (DL) method called Meta-Spec. Using a deep neural network (DNN) based approach, it encodes and embeds the refined host variables with microbiome features, enabling the detection of multiple diseases and their correlations simultaneously. Our experiments showed that Meta-Spec outperforms regular machine learning (ML) strategies for multi-label disease screening in several cohorts. More importantly, Meta-Spec can successfully detect comorbidities that are often missed by regular ML approaches. In addition, due to its high interpretability, Meta-Spec captures key factors that shape disease patterns from host variables and microbial members. Hence, these efforts improve the feasibility and sensitivity of microbiome-based disease screening in practical scenarios, representing a significant step towards personalized medicine and better health outcomes.
Practice makes imperfect: stronger implicit interference with practice in individuals at high risk of developing Alzheimer’s disease
Authors: Hung Shao-Min , Adams Sara W. , Molloy Cathleen , Wu Daw-An , Shimojo Shinsuke , Arakaki Xianghong
Published: May 2023

Early screening to determine patient risk of developing Alzheimer’s will allow better interventions and planning but necessitates accessible methods such as behavioral biomarkers. Previously, we showed that cognitively healthy older individuals whose cerebrospinal fluid amyloid / tau ratio indicates high risk of cognitive decline experienced implicit interference during a high-effort task, signaling early changes in attention. To further investigate attention’s effect on implicit interference, we analyzed two experiments completed sequentially by the same high- and low-risk individuals. We hypothesized that if attention modulates interference, practice would affect the influence of implicit distractors. Indeed, while both groups experienced a strong practice effect, the association between practice and interference effects diverged between groups: stronger practice effects correlated with more implicit interference in high-risk participants, but less interference in low-risk individuals. Furthermore, low-risk individuals showed a positive correlation between implicit interference and EEG low-range alpha event-related desynchronization when switching from high-to low-load tasks. These results demonstrate how attention impacts implicit interference and highlight early differences in cognition between high- and low-risk individuals.
RNA- and ATAC-sequencing Reveals a UniqueCD83+Microglial Population Focally Depleted in Parkinson’s Disease
Authors: Chatila Z.K. , Yadav A. , Mares J. , Flowers X. , Yun T.D. , Rashid M. , Talcoff R. , Pelly Z. , Zhang Ya , De Jager P.L. , Teich A. , Costa R. , Gomez E. Area , Martins G. , Alcalay R. , Vonsattel J.P. , Menon V. , Bradshaw E.M. , Przedborski S.
Published: May 2023

All brain areas affected in Parkinson’s disease (PD) show an abundance of microglia with an activated morphology together with increased expression of pro-inflammatory cytokines, suggesting that neuroinflammation may contribute to the neurodegenerative process in this common and incurable disorder. We applied a single nucleus RNA- and ATAC-sequencing approach using the 10x Genomics Chromium platform to postmortem PD samples to investigate microglial heterogeneity in PD. We created a multiomic dataset using substantia nigra (SN) tissues from 19 PD donors and 14 non-PD controls (NPCs), as well as three other brain regions from the PD donors which are differentially affected in this disease: the ventral tegmental area (VTA), substantia inominata (SI), and hypothalamus (HypoTs). We identified thirteen microglial subpopulations within these tissues as well as a perivascular macrophage and a monocyte population, of which we characterized the transcriptional and chromatin repertoires. Using this data, we investigated whether these microglial subpopulations have any association with PD and whether they have regional specificity. We uncovered several changes in microglial subpopulations in PD, which appear to parallel the magnitude of neurodegeneration across these four selected brain regions. Specifically, we identified that inflammatory microglia in PD are more prevalent in the SN and differentially express PD-associated markers. Our analysis revealed the depletion of aCD83andHIF1A-expressing microglial subpopulation, specifically in the SN in PD, that has a unique chromatin signature compared to other microglial subpopulations. Interestingly, this microglial subpopulation has regional specificity to the brainstem in non-disease tissues. Furthermore, it is highly enriched for transcripts of proteins involved in antigen presentation and heat-shock proteins, and its depletion in the PD SN may have implications for neuronal vulnerability in disease.
Two neuronal models of TDP-43 proteinopathy display reduced axonal translation, increased oxidative stress, and defective exocytosis
Authors: Pisciottani Alessandra , Croci Laura , Lauria Fabio , Marullo Chiara , Savino Elisa , Ambrosi Alessandro , Podini Paola , Marchioretto Marta , Casoni Filippo , Cremona Ottavio , Taverna Stefano , Quattrini Angelo , Cioni Jean-Michel , Viero Gabriella , Codazzi Franca , Consalez G. Giacomo
Published: May 2023

Amyotrophic lateral sclerosis (ALS) is a progressive, lethal neurodegenerative disease mostly affecting people around 50-60 years of age. TDP-43, a ubiquitously expressed RNA-binding protein involved in pre-mRNA splicing and controlling mRNA stability and translation, forms neuronal cytoplasmic inclusions in an overwhelming majority of ALS patients, of both sporadic and familial origin, a phenomenon referred to as TDP-43 proteinopathy. These cytoplasmic aggregates disrupt the subcellular transport and localization of mRNA. The axon, like dendrites, is a site of mRNA translation, permitting the local synthesis of selected proteins, both constitutively and in response to stimuli reaching the axon and presynaptic terminal. This is especially relevant in upper and lower motor neurons, whose axon spans long distances, likely accentuating their susceptibility to ALS-related noxae. In this work we have generated and characterized two models of TDP-43 proteinopathy, consisting of virtually pure populations of mouse cortical neurons expressing a human TDP-43 fusion protein, wt or mutant, which accumulates as cytoplasmic aggregates. Neurons expressing human TDP-43 exhibit a global impairment in axonal protein synthesis, an increase in oxidative stress, and defects in presynaptic function and electrical activity. These changes correlate with deregulation in the axonal levels of polysome-engaged mRNAs playing relevant roles in those processes. Our data support the emerging notion that deregulation of mRNA metabolism and of axonal mRNA transport may trigger the dying-back neuropathy that initiates motor neuron degeneration in ALS.