bluuebunny/crossref_metadata_2025 huggingface dataset:
A distributed integral control mechanism for the regulation of cholesterol concentration in the human retina
Authors: Scheepers Ronél , Levi Noa L. , Araujo Robyn P.
Published: March 2024

Tight homeostatic control of cholesterol concentration within the complex tissue microenvironment of the retina is a hallmark of the healthy eye. By contrast, dysregulation of the biochemical mechanisms governing retinal cholesterol homeostasis is thought to be a major contributor to the aetiology and progression of age-related macular degeneration (AMD) in the ageing human eye. Although the signalling mechanisms that contribute to cholesterol homeostasis at the cellular level have been studied extensively, there is currently no systems-level description of the molecular interactions that could explain cholesterol homeostasis at the level of the human retina. Here were provide a comprehensive overview of all currently-known molecular-level interactions involved in the regulation of cholesterol across all major compartments of the human retina, encompassing the retinal pigment epithelium (RPE), the photoreceptor cell layer, the Müller cell layer, and Bruch’s membrane. We develop a detailed chemical reaction network (CRN) of this complex collection of biochemical interactions, comprising seventy-one (71) molecular species, which we show may be partitioned into ten (10) independent subnetworks. These ten subnetworks work together to confer robust homeostasis on thirteen different forms of cholesterol distributed through distinct cellular compartments of the retina. Remarkably, we provide compelling evidence thatthree independentantithetic integral controllers are responsible for the tight regulation of endoplasmic reticulum (ER) cholesterol in retinal cells, and that severaladditional independentmechanisms transfer this homeostatic property to other forms of cholesterol throughout the human retina. Our novel and exquisitely detailed mathematical description of retinal cholesterol regulation provides a framework for considering potential mechanisms of cholesterol dysregulation in the diseased eye, and for the study of potential therapeutic strategies against these pathologies.
Advancing marker-gene-based methods for prokaryote-mediated multifunctional redundancy: exploring random and nonrandom extinctions in a watershed
Authors: Cheng Wan-Hsuan , Miki Takeshi , Ido Motohiro , Yoneya Kinuyo , Matsui Kazuaki , Yokokawa Taichi , Yamanaka Hiroki , Nakano Shin-ichi
Published: March 2024

Multifunctional redundancy, the extent of loss in multiple ecosystem functions with decreasing biodiversity, stands as a crucial index for evaluating ecosystem resilience to environmental changes. We aimed to refine a marker-gene-based methodology for quantifying multifunctional redundancy in prokaryotic communities. Using PICRUSt2, we predicted KEGG orthologs (KOs) for each Amplicon Sequence Variant (ASV), assessed community-wide KO richness, and validated predictions against experimentally quantified phenotypic multifunctionality. Additionally, we introduced a refined regression on ASV richness–KO richness curves, providing a reliable estimate of the power-law exponent within computational time constraints, serving as the multifunctional redundancy index. Incorporating various non-random extinction scenarios alongside a random one allowed us to quantify estimate variations between scenarios, providing conservative estimates of multifunctional redundancy. Applied to Lake Biwa and four of its inlet rivers, the refined methodology unveiled spatio-temporal variations in multifunctional redundancy. Our analysis demonstrated lower redundancy in Lake Biwa compared to rivers, aiding in prioritizing conservation targets and inferring distinct community assembly processes. Future directions include a deeper exploration of KO composition information for detailed multifunctionality quantification and the refinement of extinction scenarios. This study demonstrates the promising integration of bioinformatic functional prediction and modeling biodiversity loss, offering a valuable tool for effective ecosystem management.
A Hybrid Diffusion Model for Stable, Affinity-Driven, Receptor-Aware Peptide Generation
Authors: Vishva Saravanan R , Choudhuri Soham , Ghosh Bhaswar
Published: March 2024

The convergence of biotechnology and artificial intelligence has the potential to transform drug development, especially in the field of therapeutic peptide design. Peptides are short chains of amino acids with diverse therapeutic applications that offer several advantages over small molecular drugs, such as targeted therapy and minimal side effects. However, limited oral bioavailability and enzymatic degradation have limited their effectiveness. With advances in deep learning techniques, innovative approaches to peptide design have become possible. In this work, we demonstrate HYDRA: a hybrid deep learning approach that leverages the distribution modeling capabilities of a diffusion model and combines it with a binding affinity maximization algorithm that can be used forde novodesign of peptide binders given target receptors. As an application, we have used our approach to design therapeutic peptides targeting proteins expressed by Plasmodium falciparum Erythrocyte Membrane Protein 1 (PfEMP1) genes. The ability of our model to generate peptides conditioned on the target receptor’s binding sites makes it a promising approach for developing effective therapies for malaria and other diseases.
LoCS-Net: Localizing Convolutional Spiking Neural Network for Fast Visual Place Recognition
Authors: Akcal M. Ugur , Raikov Ivan Georgiev , Gribkova Ekaterina , Choudhuri Anwesa , Soltesz Ivan , Gillette Rhanor , Chowdhary Girish
Published: March 2024

Visual place recognition (VPR) is the ability to recognize locations in a physical environment based only on visual inputs. It is a challenging task due to perceptual aliasing, viewpoint and appearance variations and complexity of dynamic scenes. Despite promising demonstrations, many state-of-the-art VPR approaches based on artificial neural networks (ANNs) suffer from computational inefficiency. Spiking neural networks (SNNs), on the other hand, implemented on neuromorphic hardware, are reported to have remarkable potential towards more efficient solutions computationally, compared to ANNs. However, the training of the state-of-the-art (SOTA) SNNs for the VPR task is often intractable on large and diverse datasets. To address this, we develop an end-to-end convolutional SNN model for VPR, that leverages back-propagation for tractable training. Rate-based approximations of leaky integrate-and-fire (LIF) neurons are employed during training to enable back-propagation, and the approximation units are replaced with spiking LIF neurons during inference. The proposed method outperforms the SOTA ANNs and SNNs by achieving 78.2% precision at 100% recall on the challenging Nordland dataset, compared with 53% SOTA performance, and exhibits competitive performance on the Oxford RobotCar dataset while being easier to train and faster in both training and inference when compared to other ANN and SNN-based methods.
Decoding strawberry volatile cultivar diversity through comparative transcriptome analysis
Authors: Passa Kondylia , Tsormpatsidis Evangelos , Ganopoulos Ioannis , Bazakos Christos , Papasotiropoulos Vasileios
Published: March 2024

This study presents a comparative transcriptomic analysis of three commercial strawberry cultivars: ‘Rociera’, ‘Calderon’, and ‘Victory’, aimed at uncovering the molecular basis of their distinct flavor and aroma profiles. Through RNA sequencing, we analyzed the transcriptomic landscape of these varieties, uncovering a notable array of differentially expressed genes (DEGs) between them. Specifically, ‘Rociera’ showed a higher count of DEGs compared to ‘Victory’, suggesting significant differences in gene expression related to flavor and aroma between those cultivars. Our further investigations revealed pivotal metabolic pathways— such as those involving furanones, amino acids, fatty acids, and terpenoids—participating in generating volatile organic compounds in strawberries. These pathways exhibited variety-specific expression patterns, underlining the genetic determinants of each variety’s unique sensory characteristics. Gene Ontology (GO) enrichment analysis underscored important pathways like phototropism, sugar-mediated signaling, and terpenoid biosynthesis, highlighting the genetic intricacy that influences strawberry flavor and aroma. Additionally, our study identified 31,677 single nucleotide polymorphisms (SNPs) with a significant impact on genes associated with volatile compound biosynthesis. Notably, SNPs linked to key enzymes such as lipoxygenase 6, omega-6 fatty acid desaturase (FaFAD1), and phenylalanine ammonia-lyase 1 (PAL) were discovered, shedding light on the genetic variations that underlie flavor differences. Therefore, this research advances our comprehension of the genetic elements that impact strawberry fruit flavor and aroma, offering invaluable insights for molecular breeding endeavors focused on enhancing strawberry flavor.
BMP2 binds non-specifically to PEG-passivated biomaterials and induces substantial signaling
Authors: Le Pennec Jean , Guibert Amaury , Vivès Romain R. , Migliorini Elisa
Published: March 2024

Biomaterials are widely employed across diverse biomedical applications and represent an attractive strategy to explore physiologically how extracellular matrix components influence the cellular response. In this study, we aimed to use previously developed biomimetic streptavidin platforms to investigate the role of glycosaminoglycans (GAGs) in bone morphogenetic protein 2 (BMP2) signaling. However, we observed that the interpretation of our findings was skewed due to the GAG-unrelated, non-specific adsorption of BMP2 on components of our biomaterials. Non-specific adsorption of proteins is a recurrent and challenging issue for biomaterial studies. Despite the initial incorporation of anti-fouling poly(ethylene glycol) (PEG) chains within our biomaterials, the residual non-specific BMP2 adsorption still triggered BMP2 signaling within the same range as our conditions of interest. To tackle this issue, we explored various options to prevent BMP2 non-specific adsorption. Specifically, we tested alternative constructions of our biomaterials on gold or glass substrate using distinct PEG-based linkers. We identified the aggregation of BMP2 at neutral pH as a potential cause of non-specific adsorption and thus determined specific buffer conditions to prevent it. We also investigated the induced BMP2 signaling over different culture periods. Nevertheless, none of these options resulted in a viable suitable solution to reduce the non-specific BMP2 signaling.

Next, we studied the effect of various blocking strategies. We identified a blocking condition involving a combination of bovine serum albumin and trehalose that successfully reduced the unspecific attachment of BMP2 and the non-specific signaling. Furthermore, the effect of this blocking step was improved when using gold platforms instead of glass, particularly with Chinese hamster ovary (CHO) cells that seemed less responsive to non-specifically bound BMP2 than C2C12 cells.
Impact of genomic background and developmental state on signaling pathways and response to therapy in glioblastoma patient-derived cells
Authors: Berezovsky Artem , Nuga Oluwademilade , Datta Indrani , Bergman Kimberly , Sabedot Thais , Gurdziel Katherine , Irtenkauf Susan , Hasselbach Laura , Meng Yuling , Mueller Claudius , Petricoin Emanuel F. , Brown Stephen , Purandare Neeraja , Aras Sidhesh , Mikkelsen Tom , Poisson Laila , Noushmehr Houtan , Ruden Douglas , deCarvalho Ana C.
Published: March 2024

Glioblastoma (GBM) tumors represents diverse genomic epigenomic, and transcriptional landscapes, with significant intratumoral heterogeneity that challenges standard of care treatments involving radiation (RT) and the DNA-alkylating agent temozolomide (TMZ). In this study, we employed targeted proteomics to assess the response of a genomically-diverse panel of GBM patient-derived cancer stem cells (CSCs) to astrocytic differentiation, growth factor withdrawal and traditional high fetal bovine serum culture. Our findings revealed a complex crosstalk and co-activation of key oncogenic signaling in CSCs and diverse patterns of response to these external stimuli. Using RNA sequencing and DNA methylation, we observed common adaptations in response to astrocytic differentiation of CSCs across genomically distinct models, including BMP-Smad pathway activation, reduced cholesterol biosynthesis, and upregulation of extracellular matrix components. Notably, we observed that these differentiated CSC progenies retained a subset of stemness genes and the activation of cell survival pathways. We also examined the impact of differentiation state and genomic background on GBM cell sensitivity and transcriptional response to TMZ and RT. Differentiation of CSCs increased resistance to TMZ but not to RT. While transcriptional responses to these treatments were predominantly regulated by p53 in wild-type p53 GBM cells, its transcriptional activity was modulated by the differentiation status and treatment modality. Both mutant and wild-type p53 models exhibited significant activation of a DNA-damage associated interferon response in CSCs and differentiated cells, suggesting this pathway may play a wider role in GBM response to TMZ and RT. Our integrative analysis of the impact of GBM cell developmental states, in the context of genomic and molecular diversity of patient-derived models, provides valuable insights for pre-clinical studies aimed at optimizing treatment strategies.
Septo-hypothalamic regulation of binge-like alcohol consumption by the nociceptin system
Authors: Haun Harold , Hernandez Raul , Yan Luzi , Flanigan Meghan , Hon Olivia , Lee Sophia , Méndez Hernán , Roland Alison , Taxier Lisa , Kash Thomas
Published: March 2024

High intensity alcohol drinking during binge episodes overwhelmingly contributes to the socioeconomic burden created by Alcohol Use Disorders (AUD). Novel interventions are needed to add to the current therapeutic toolkit and nociceptin receptor (NOP) antagonists have shown promise in reducing heavy drinking days in patients with an AUD. However, an endogenous locus of nociceptin peptide and discrete sites of NOP action underlying this effect remains understudied. Here we show that the lateral septum (LS), a region contributing to binge drinking, is enriched in neurons expressing mRNA coding for the nociceptin peptide (Pnoc). Pnoc-expressing neurons of the LS (LSPnoc) are tuned to stimuli associated with negative valence and display increased excitability during withdrawal from binge-like alcohol drinking. LSPnocactivation was found to have aversive qualities and also potentiates binge-like drinking behavior, suggesting a convergence of circuitry that promotes aversion and drives alcohol consumption. Viral mediated tracing and functional assessment of LSPnocprojection fields revealed GABAergic synapses locally within the LS, and downstream within the lateral hypothalamus (LH) and supramammillary nucleus (SuM). Genetic deletion of NOP from the LS attenuated binge-like alcohol intake in male mice while NOP deletion from the LH and SuM decrease alcohol intake in females. Together, these findings are the first to demonstrate an endogenous population of nociceptin-expressing neurons that contributes to alcohol consumption and identifies sex-dependent modulation of alcohol drinking by NOP.
TargetingLeishmania infantumMannosyl-oligosaccharide glucosidase with natural products: pH-dependent inhibition explored through computer-aided drug design
Authors: Goyzueta-Mamani Luis Daniel , Barazorda-Ccahuana Haruna Luz , Candia-Puma Mayron Antonio , Galdino Alexsandro Sobreira , Machado-de-Avila Ricardo Andrez , Giunchetti Rodolfo Cordeiro , Medina-Franco José L. , Florin-Christensen Mónica , Ferraz Coelho Eduardo Antonio , Chávez-Fumagalli Miguel Angel
Published: March 2024

Visceral Leishmaniasis (VL) is a serious public health issue, documented in more than ninety countries, where an estimated 500,000 new cases emerge each year. Regardless of novel methodologies, advancements, and experimental interventions, therapeutic limitations, and drug resistance are still challenging. For this reason, based on previous research, we screened natural products (NP) from Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBEDB), Mexican Compound Database of Natural Products (BIOFACQUIM), and Peruvian Natural Products Database (PeruNPDB) databases, in addition to structural analogs of Miglitol and Acarbose, which have been suggested as treatments for VL and have shown encouraging action against parasite’s N-glycan biosynthesis. Using computer-aided drug design (CADD) approaches, the inhibitory effect of these NP candidates was evaluated by inhibiting the Mannosyl-oligosaccharide Glucosidase Protein (MOGS) fromLeishmania infantum, an enzyme essential for the protein glycosylation process, at various pH to mimic the parasite’s changing environment. Also, computational analysis was used to evaluate the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profile, while molecular dynamic simulations were used to gather information on the interactions between these ligands and the protein target. Our findings indicated that Ocotillone and Subsessiline have potential antileishmanial effects at pH 5 and 7, respectively, due to their high binding affinity to MOGS and interactions in the active center. Furthermore, these compounds were non-toxic and had the potential to be administered orally. This research indicates the promising anti-leishmanial activity of Ocotillone and Subsessiline, suggesting further validation throughin vitroandin vivoexperiments.
CSF proteomic profiling with amyloid/tau positivity identifies distinctive sex-different alteration of multiple proteins involved in Alzheimer’s disease
Authors: Do Anh N. , Ali Muhammad , Timsina Jigyasha , Wang Lihua , Western Daniel , Liu Menghan , Sanford Jessie , Rosende-Roca Matitee , Boada Merce , Puerta Raquel , Wilson Ted , Ruiz Agustin , Pastor Pau ,   the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Wyss-Coray Tony , Cruchaga Carlos , Sung Yun Ju
Published: March 2024

In Alzheimer’s disease (AD), the most common cause of dementia, females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited. Here, we comprehensively examined and validated 7,006 aptamers targeting 6,162 proteins in cerebral spinal fluid (CSF) from 2,077 amyloid/tau positive cases and controls to identify sex-specific proteomic signatures of AD. In discovery (N=1,766), we identified 330 male-specific and 121 female-specific proteomic alternations in CSF (FDR <0.05). These sex-specific proteins strongly predicted amyloid/tau positivity (AUC=0.98 in males; 0.99 in females), significantly higher than those with age, sex, and APOE-ε4 (AUC=0.85). The identified sex-specific proteins were well validated (r≥0.5) in the Stanford study (N=108) and Emory study (N=148).

Biological follow-up of these proteins led to sex differences in cell-type specificity, pathways, interaction networks, and drug targets. Male-specific proteins, enriched in astrocytes and oligodendrocytes, were involved in postsynaptic and axon-genesis. The male network exhibited direct connections among 152 proteins and highlighted PTEN, NOTCH1, FYN, and MAPK8 as hubs. Drug target suggested melatonin (used for sleep-wake cycle regulation), nabumetone (used for pain), daunorubicin, and verteporfin for treating AD males. In contrast, female-specific proteins, enriched in neurons, were involved in phosphoserine residue binding including cytokine activities. The female network exhibits strong connections among 51 proteins and highlighted JUN and 14-3-3 proteins (YWHAG and YWHAZ) as hubs. Drug target suggested biperiden (for muscle control of Parkinson’s disease), nimodipine (for cerebral vasospasm), quinostatin and ethaverine for treating AD females. Together, our findings provide mechanistic understanding of sex differences for AD risk and insights into clinically translatable interventions.
Location of ryanodine receptor type 2 mutation predicts age of onset of sudden death in catecholaminergic polymorphic ventricular tachycardia – A systematic review and meta-analysis of case-based literature
Authors: Beqaj Halil , Sittenfeld Leah , Chang Alexander , Miotto Marco , Dridi Haikel , Willson Gloria , Jorge Carolyn Martinez , Li Jaan Altosaar , Reiken Steven , Liu Yang , Dai Zonglin , Marks Andrew R.
Published: March 2024

Background

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare inherited arrhythmia caused by mutations in the ryanodine receptor type 2 (RyR2). Diagnosis of CPVT often occurs after a major cardiac event, thus posing a severe threat to the patient’s health.

Methods

Publication databases, including PubMed, Scopus, and Embase, were searched for articles on patients with RyR2-CPVT mutations and their associated clinical presentation. Articles were reviewed by two independent reviewers and mutations were analyzed for demographic information, mutation distribution, and therapeutics. The human RyR2 cryo-EM structure was used to model CPVT mutations and predict the diagnosis and outcomes of CPVT patients.

Findings

We present a database of 1008 CPVT patients from 227 papers. Data analyses revealed that patients most often experienced exercise-induced syncope in their early teenage years but the diagnosis of CPVT took a decade. Mutations located near key regulatory sites in the channel were associated with earlier onset of CPVT symptoms including sudden cardiac death.

Interpretation

The present study provides a road map for predicting clinical outcomes based on the location of RyR2 mutations in CPVT patients. The study was partially limited by the inconsistency in the depth of information provided in each article, but nevertheless is an important contribution to the understanding of the clinical and molecular basis of CPVT and suggests the need for early diagnosis and creative approaches to disease management.

Funding

The work was supported by grant NIH R01HL145473, P01 HL164319 R25HL156002, T32 HL120826.
FABEL: Forecasting Animal Behavioral Events with Deep Learning-Based Computer Vision
Authors: Catto Adam , O’Connor Richard , Braunscheidel Kevin M. , Kenny Paul J. , Shen Li
Published: March 2024

Behavioral neuroscience aims to provide a connection between neural phenomena and emergent organism-level behaviors. This requires perturbing the nervous system and observing behavioral outcomes, and comparing observed post-perturbation behavior with predicted counterfactual behavior and therefore accurate behavioral forecasts. In this study we present FABEL, a deep learning method for forecasting future animal behaviors and locomotion trajectories from historical locomotion alone. We train an offline pose estimation network to predict animal body-part locations in behavioral video; then sequences of pose vectors are input to deep learning time-series forecasting models. Specifically, we train an LSTM network that predicts a future food interaction event in a specified time window, and a Temporal Fusion Transformer that predicts future trajectories of animal body-parts, which are then converted into probabilistic label forecasts. Importantly, accurate prediction of food interaction provides a basis for neurobehavioral intervention in the context of compulsive eating. We show promising results on forecasting tasks between 100 milliseconds and 5 seconds timescales. Because the model takes only behavioral video as input, it can be adapted to any behavioral task and does not require specific physiological readouts. Simultaneously, these deep learning models may serve as extensible modules that can accommodate diverse signals, such as in-vivo fluorescence imaging and electrophysiology, which may improve behavior forecasts and elucidate invervention targets for desired behavioral change.
Rat primary cortical cell tri-culture to study effects of amyloid-beta on microglia function
Authors: Kim Hyehyun , Le Bryan , Goshi Noah , Zhu Kan , Grodzki Ana Cristina , Lein Pamela J. , Zhao Min , Seker Erkin
Published: March 2024

Introduction

The etiology and progression of sporadic Alzheimer’s Disease (AD) have been studied for decades. One proposed mechanism is that amyloid-beta (Aβ) proteins induce neuroinflammation, synapse loss, and neuronal cell death. Microglia play an especially important role in Aβ clearance, and alterations in microglial function due to aging or disease may result in Aβ accumulation and deleterious effects on neuronal function. However, studying these complex factorsin vivo, where numerous confounding processes exist, is challenging, and until recently,in vitromodels have not allowed sustained culture of microglia, astrocytes and neurons in the same culture. Here, we employ a tri-culture model of rat primary neurons, astrocytes, and microglia and compare it to co-culture (neurons and astrocytes) and mono-culture enriched for microglia to study microglial function (i.e., motility and Aβ clearance) and proteomic response to exogenous Aβ.

Methods

We established cortical co-culture (neurons and astrocytes), tri-culture (neurons, astrocytes, and microglia), and mono-culture (microglia) from perinatal rat pups. On daysin vitro(DIV) 7 – 14, the cultures were exposed to fluorescently-labeled Aβ (FITC-Aβ) particles for varying durations. Images were analyzed to determine the number of FITC-Aβ particles after specific lengths of exposure. A group of cells were stained for βIII-tubulin, GFAP, and Iba1 for morphological analysis via quantitative fluorescence microscopy. Cytokine profiles from conditioned media were obtained. Live-cell imaging with images acquired every 5 minutes for 4 hours was employed to extract microglia motility parameters (e.g., Euclidean distance, migration speed, directionality ratio).

Results and discussion

FITC-Aβ particles were more effectively cleared in the tri-culture compared to the co-culture. This was attributed to microglia engulfing FITC-Aβ particles, as confirmed via epifluorescence and confocal microscopy. Adding FITC-Aβ significantly increased the size of microglia, but had no significant effect on neuronal surface coverage or astrocyte size. Analysis of the cytokine profile upon FITC-Aβ addition revealed a significant increase in proinflammatory cytokines (TNF-α, IL-1α, IL-1β, IL-6) in tri-culture, but not co-culture. In addition, Aβ addition altered microglia motility marked by swarming-like motion with decreased Euclidean distance yet unaltered speed. These results highlight the importance of cell-cell communication in microglia function (e.g., motility and Aβ clearance) and the utility of the tri-culture model to further investigate microglia dysfunction in AD.
Contradictory behavioral effects of neuronal perturbations on behavioral responses to linearly polarized light in freely walkingDrosophila
Authors: Titova Anna V. , Straw Andrew D.
Published: March 2024

Many insects can use the polarization of the skylight as a navigational cue. As shown previously, freely walkingDrosophilaorient along the e-vector of linearly polarized UV light presented both dorsally and ventrally. We are interested in the neuronal mechanisms leading to this behavior, and specifically how the central complex and its inputs are involved. We investigated the behavior of flies exposed to linearly polarized near-UV light (400 nm) presented dorsally. Flies walked freely in a circular, flat arena surrounded by a heat barrier. Using the GAL4-UAS genetic system, we drove the expression of the potassium inward rectifier KIR2.1 to perturb each of several different neuron types of the polarization vision pathway. Perturbing EPG compass neurons in the central complex slightly weakened average alignment and increased its variability. On the other hand, when two different GAL4 lines driving expression in the ER4m ring neurons, identified by connectomics as the major polarization inputs to the fly central complex, were perturbed, the alignment strength increased. A similar effect was observed when the inputs to ER4m, the TuBuaneurons, were perturbed. We did not predict EPG and ER4m perturbations to cause opposite effects. Further investigation would be required to understand the physiological mechanisms of these contradictory behavioral effects.
Structural basis for allosteric regulation of human phosphofructokinase-1
Authors: Lynch Eric M. , Hansen Heather , Salay Lauren , Cooper Madison , Timr Stepan , Kollman Justin M. , Webb Bradley A.
Published: March 2024

Phosphofructokinase-1 (PFK1) catalyzes the rate-limiting step of glycolysis, committing glucose to conversion into cellular energy. PFK1 is highly regulated to respond to the changing energy needs of the cell. In bacteria, the structural basis of PFK1 regulation is a textbook example of allostery; molecular signals of low and high cellular energy promote transition between an active R-state and inactive T-state conformation, respectively. Little is known, however, about the structural basis for regulation of eukaryotic PFK1. Here, we determine structures of the human liver isoform of PFK1 (PFKL) in the R- and T-state by cryoEM, providing insight into eukaryotic PFK1 allosteric regulatory mechanisms. The T-state structure reveals conformational differences between the bacterial and eukaryotic enzyme, the mechanisms of allosteric inhibition by ATP binding at multiple sites, and an autoinhibitory role of the C-terminus in stabilizing the T-state. We also determine structures of PFKL filaments that define the mechanism of higher-order assembly and demonstrate that these structures are necessary for higher-order assembly of PFKL in cells.
Bottlenecks in the Implementation of Genome Scale Metabolic Model Based Designs for Bioproduction from Aromatic Carbon Sources
Authors: Banerjee Deepanwita , Menasalvas Javier , Chen Yan , Gin Jennifer W. , Baidoo Edward E. K. , Petzold Christopher J. , Eng Thomas , Mukhopadhyay Aindrila
Published: March 2024

Genome scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling, pairing product formation with substrate utilization. While such approaches can improve strain performance beyond levels typically accessible using targeted strain engineering approaches, sustainable feedstocks often pose a challenge for GSMM-based methods due to incomplete underlying metabolic data. Specifically, we address a four-gene deletion design for the lignin-derived non-sugar carbon source,para-coumarate, that proved challenging to implement. We examine the performance of the fully implemented design forp-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product. Through omics, promoter-variation and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarate hydratase activity in the citrate cycle and required careful optimization of the final fumarate hydratase protein (PP_0897) expression to achieve growth and production. A metabolic cross-feeding experiment with the completed design strain also revealed an unanticipated nutrient requirement suggesting additional functions for the fumarate hydratase protein. A double sensitivity analysis confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. While a complete implementation of the design was achieved, this study highlights the challenge of precisely inactivating metabolic reactions encoded by under-characterized proteins especially in the context of multi-gene edits.
Redefining the role of Hypoxia-inducible factors (HIFs) in oxygen homeostasis
Authors: Arias Clemente F. , Acosta Francisco J. , Bertocchini Federica , Fernańdez-Arias Cristina
Published: March 2024

Hypoxia-inducible factors (HIFs) are key regulators of intracellular oxygen homeostasis. The marked increase in HIFs activity in hypoxia as compared to normoxia, together with their transcriptional control of primary metabolic pathways, motivated the widespread view of HIFs as responsible for the cell’s metabolic adaptation to hypoxic stress. In this work, we suggest that this prevailing model of HIFs regulation is misleading. We propose an alternative model focused on understanding the dynamics of HIFs’ activity within its physiological context. Our model suggests that HIFs would not respond to but rather prevent the onset of hypoxic stress by regulating the traffic of electrons between catabolic substrates and oxygen. The explanatory power of our approach is patent in its interpretation of the Warburg effect, the tendency of tumor cells to favor anaerobic metabolism over respiration, even in fully aerobic conditions. This puzzling behavior is currently considered as an anomalous metabolic deviation. Our model predicts the Warburg effect as the expected homeostatic response of tumor cells to the abnormal increase in metabolic demand that characterizes malignant phenotypes. This alternative perspective prompts a redefinition of HIFs’ function and underscores the need to explicitly consider the cell’s metabolic activity in understanding its responses to changes in oxygen availability.
Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells
Authors: Grasset Eloise M. , Desphande Atul , Lee Jae W. , Cho Yeonju , Shin Sarah M. , Coyne Erin M. , Hernandez Alexei , Yuan Xuan , Zhang Zhehao , Cimino-Matthews Ashley , Ewald Andrew J. , Ho Won Jin
Published: March 2024

The development of metastasis, responsible for the majority of cancer-related fatalities, is the most dangerous aspect of breast cancer, the predominant malignancy affecting women. We previously identified specific cancer cell populations responsible for metastatic events which are cytokeratin-14 (CK14) and E-cadherin positive in luminal tumors, and E-cadherin and vimentin positive in triple-negative tumors. Since cancer cells evolve within a complex ecosystem comprised of immune cells and stromal cells, we sought to decipher the spatial interactions of these aggressive cancer cell populations within the tumor microenvironment (TME). We used imaging mass cytometry to detect 36 proteins in tumor microarrays containing paired primary and metastatic lesions from luminal or triple-negative breast cancers (TNBC), resulting in a dataset of 1,477,337 annotated cells. Focusing on metastasis-initiating cell populations, we observed close proximity to specific fibroblast and macrophage subtypes, a relationship maintained between primary and metastatic tumors. Notably, high CK14 in luminal cancer cells and high vimentin in TNBC cells correlated with close proximity to specific macrophage subtypes (CD163intCD206intPDL1intHLA-DR+or PDL1highARG1high). Our in-depth spatial analysis elucidates that metastasis-initiating cancer cells exhibit with distinct cell populations within the TME, implicating the role of these cell-cell interactions in promoting metastasis.
Myocardin-related transcription factor drives epithelial fibrogenesis in polycystic kidney disease
Authors: Lichner Zsuzsanna , Ding Mei , Khare Tarang , Dan Qinghong , Benitez Raquel , Praszner Mercédesz , Song Xuewen , Saleeb Rola , Hinz Boris , Pei York , Szászi Katalin , Kapus András
Published: March 2024

Polycystic kidney disease (PKD) is characterized by extensive cyst formation and progressive fibrosis. However, the molecular mechanisms whereby the loss/loss-of-function of Polycystin 1 or 2 (PC1/2) provokes fibrosis are largely unknown. The small GTPase RhoA has been recently implicated incystogenesis, and we have shown that the RhoA/cytoskeleton/myocardin-related transcription factor (MRTF) pathway is a key mediator of epithelium-induced fibrogenesis. Therefore, we hypothesized that MRTF is activated by PC1/2 loss and plays a critical role in fibrogenic reprogramming of the epithelium. Loss of PC1 or PC2 induced by siRNA in vitro activated RhoA, caused cytoskeletal remodeling and robust nuclear MRTF translocation and overexpression. These phenomena were also manifest in PKD1 (RC/RC) and PKD2 (WS25/-) mice, with MRTF translocation and overexpression occurring predominantly in dilated tubules and in cyst-lining epithelium, respectively. In epithelial cells, a large cohort of PC1/PC2 downregulation-induced genes was MRTF-dependent, including cytoskeletal, integrin-related, and matricellular/fibrogenic proteins. Epithelial MRTF was necessary for paracrine priming of fibroblast-myofibroblast transition. Thus, MRTF is a critical novel mediator of the PC1/2 loss-induced profibrotic epithelial phenotype, and consequently PKD-related fibrosis.
Transposable element methylation state predicts age and disease
Authors: Morandini Francesco , Lu Jinlong Y. , Rechsteiner Cheyenne , Shadyab Aladdin H. , Casanova Ramon , Snively Beverly M. , Seluanov Andrei , Gorbunova Vera
Published: March 2024

Transposable elements (TEs) are DNA sequences that expand selfishly in the genome, possibly causing severe cellular damage. While normally silenced, TEs have been shown to activate during aging. DNA methylation is one of the main mechanisms by which TEs are silenced and has been used to train highly accurate age predictors. Yet, one common criticism of such predictors is that they lack interpretability. In this study, we investigate the changes in TE methylation that occur during human aging. We find that evolutionarily young LINE1s (L1s), the only known TEs capable of autonomous transposition in humans, undergo the fastest loss of methylation, suggesting an active mechanism of de-repression. We then show that accurate age predictors can be trained on both methylation of individual TE copies and average methylation of TE families genome wide. Lastly, we show that while old L1s gradually lose methylation during the entire lifespan, demethylation of young L1s only happens late in life and is associated with cancer.
Curating models from BioModels: Developing a workflow for creating OMEX files
Authors: Xu Jin , Smith Lucian
Published: March 2024

The reproducibility of computational biology models can be greatly facilitated by widely adopted standards and public repositories. We examined 50 models from the BioModels Database and attempted to validate the original curation and correct some of them if necessary. For each model, we reproduced these published results using Tellurium. Once reproduced we manually created a new set of files, with the model information stored by the Systems Biology Markup Language (SBML), and simulation instructions stored by the Simulation Experiment Description Markup Language (SED-ML), and everything included in an Open Modeling EXchange (OMEX) file, which could be used with a variety of simulators to reproduce the same results. On the one hand, the reproducibility procedure of 50 models developed a manual workflow that we would use to build an automatic platform to help users more easily curate and verify models in the future. On the other hand, these exercises allowed us to find the limitations and possible enhancement of the current curation and tooling to verify and curate models.
A feedback-driven brain organoid platform enables automated maintenance and high-resolution neural activity monitoring
Authors: Voitiuk Kateryna , Seiler Spencer T. , Pessoa de Melo Mirella , Geng Jinghui , van der Molen Tjitse , Hernandez Sebastian , Schweiger Hunter E. , Sevetson Jess L. , Parks David F. , Robbins Ash , Torres-Montoya Sebastian , Ehrlich Drew , Elliott Matthew A. T. , Sharf Tal , Haussler David , Mostajo-Radji Mohammed A. , Salama Sofie R. , Teodorescu Mircea
Published: March 2024

The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control ofin vitrobiological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.
Human cortical neurons rapidly generated by direct ES cell programming integrate into stroke-injured rat cortex
Authors: Martinez-Curiel Raquel , Hayj Mazin , Tsupykov Oleg , Jansson Linda , Avaliani Natalia , Martín Berta Coll-San , Monni Emanuela , Skibo Galyna , Lindvall Olle , Palma-Tortosa Sara , Kokaia Zaal
Published: March 2024

Stroke is a major cause of long-term disability in adult humans, the neuronal loss leading to motor, sensory, and cognitive impairments. Replacement of dead neurons by intracerebral transplantation of stem cell-derived neurons for reconstruction of injured neuronal networks has potential to become a novel therapeutic strategy to promote functional recovery after stroke. Here we describe a rapid and efficient protocol for the generation of cortical neurons via direct programming of human embryonic stem (hES) cells. Our results show that 7 days overexpression of the transcription factor neurogenin 2 (NGN2) in vitro was enough to generate hES-induced cells with cortical phenotype, as revealed by immunocytochemistry and RT-qPCR, and electrophysiological properties of neurons in an intermediate stage of maturity. At 3 months after translantation into the stroke-injured rat cortex, the hES-induced neurons (hES-iNs) showed immunocytochemical markers of mature layer-specific cortical neurons and sent widespread axonal projections to several areas in both hemispheres of the host brain. Their axons became myelinated and formed synaptic contacts with host neurons, as shown by immunoelectron microscopy. Our findings demonstrate for the first time that direct transcription factor programming of hES cells can efficiently and rapidly produce cortical neurons with capacity to integrate into the stroke-injured brain.
Random forest machine-learning algorithm classifies white- and brown-rot fungi according to the number of Carbohydrate-Active enZyme genes
Authors: Hasegawa Natsuki , Sugiyama Masashi , Igarashi Kiyohiko
Published: March 2024

Wood-rotting fungi play an important role in the global carbon cycle because they are only known organisms that digest wood, the largest carbon stock in nature. In the present study, we used linear discriminant analysis and random forest (RF) machine learning algorithms to predict white- or brown-rot decay modes from the numbers of genes encoding Carbohydrate-Active enZymes (CAZymes) with over 98% accuracy. Unlike other algorithms, RF identified specific genes involved in cellulose and lignin degradation, including auxiliary activities (AA) family 9 lytic polysaccharide monooxygenases, glycoside hydrolase family 7 cellobiohydrolases, and AA family 2 peroxidases, as critical factors. This study sheds light on the complex interplay between genetic information and decay modes and underscores the potential of RF for comparative genomics studies of wood-rotting fungi.

Importance

Wood-rotting fungi are categorized as either white- or brown-rot modes based on the coloration of decomposed wood. The process of classification can be influenced by human biases. The random forest machine learning algorithm effectively distinguishes between white- and brown-rot fungi based on the presence of Carbohydrate-Active enZyme genes. These findings not only aid in the classification of wood-rotting fungi but also facilitate the identification of the enzymes responsible for degrading woody biomass.
Anti-Immune Complex Antibodies are Elicited During Repeated Immunization with HIV Env Immunogens
Authors: Brown Sharidan , Antanasijevic Aleksandar , Sewall Leigh M. , Garcia Daniel Montiel , Brouwer Philip J. M. , Sanders Rogier W. , Ward Andrew B.
Published: March 2024

Vaccination strategies against HIV-1 aim to elicit broadly neutralizing antibodies (bnAbs) using prime-boost regimens with HIV envelope (Env) immunogens. Early antibody responses to easily accessible epitopes on these antigens are directed to non-neutralizing epitopes instead of bnAb epitopes. Autologous neutralizing antibody responses appear upon boosting once immunodominant epitopes are saturated. Here we report another type of antibody response that arises after repeated immunizations with HIV Env immunogens and present the structures of six anti-immune complexes discovered using polyclonal epitope mapping. The anti-immune complex antibodies target idiotopes composed of framework regions of antibodies bound to Env. This work sheds light on current vaccine development efforts for HIV, as well as for other pathogens, in which repeated exposure to antigen is required.

One Sentence Summary

Polyclonal epitope mapping reveals anti-immune complex antibodies which target idiotopes on antibodies bound to HIV Env.
Neuronal CBP-1 is required for enhanced body muscle proteostasis in response to reduced translation downstream of mTOR
Authors: Snow Santina , Mir Dilawar , Ma Zhengxin , Horrocks Jordan , Cox Matthew , Ruzga Marissa , Sayed Hussein , Rogers Aric N.
Published: March 2024

Background

The ability to maintain muscle function decreases with age and loss of proteostatic function. Diet, drugs, and genetic interventions that restrict nutrients or nutrient signaling help preserve long-term muscle function and slow age-related decline. Previously, it was shown that attenuating protein synthesis downstream of the mechanistic target of rapamycin (mTOR) gradually increases expression of heat shock response (HSR) genes in a manner that correlates with increased resilience to protein unfolding stress. Here, we investigate the role of specific tissues in mediating the cytoprotective effects of low translation.

Methods

This study uses genetic tools (transgenicC. elegans, RNA interference and gene expression analysis) as well as physiological assays (survival and paralysis assays) in order to better understand how specific tissues contribute to adaptive changes involving cellular cross-talk that enhance proteostasis under low translation conditions.

Results

We use theC. eleganssystem to show that lowering translation in neurons or the germline increases heat shock gene expression and survival under conditions of heat stress. In addition, we find that low translation in these tissues protects motility in a body muscle-specific model of proteotoxicity that results in paralysis. Low translation in neurons or germline also results in increased expression of certain muscle regulatory and structural genes, reversing reduced expression normally observed with aging inC. elegans. Enhanced resilience to protein unfolding stress requires neuronal expression ofcbp-1.

Conclusion

Low translation in either neurons or the germline orchestrate protective adaptation in other tissues, including body muscle.