bluuebunny/crossref_metadata_2025 huggingface dataset:
Inferring extrinsic factor-dependent single-cell transcriptome dynamics using a deep generative model
Authors: Kojima Yasuhiro , Arioka Yuko , Hirose Haruka , Hayashi Shuto , Mizuno Yusuke , Nagaharu Keiki , Okumura Hiroki , Ishikawa Masato , Ohishi Kohshi , Suzuki Yutaka , Ozaki Norio , Shimamura Teppei
Published: April 2024

1

RNA velocity estimation helps elucidate temporal changes in the single-cell transcriptome. However, current methodologies for inferring single-cell transcriptome dynamics ignore extrinsic factors, such as experimental conditions and neighboring cell. Here, we propose ExDyn—a deep generative model integrated with splicing kinetics for estimating cell state dynamics dependent on extrinsic factors. ExDyn enables the counterfactual inference of cell state dynamics under different conditions. Among the extrinsic factors, ExDyn can extract key features which have large effects on cell state dynamics. ExDyn correctly estimated the difference in dynamics between two conditions and showed better accuracy over existing RNA velocity methods. ExDyn were utilized for unveiling the effect of PERK-knockout on neurosphere differentiation, hematopoietic stem cell differentiation driven by chromatin activity and the dynamics of squamous cell carcinoma cells dependent on colocalized neighboring cells. These results demonstrated that ExDyn is useful for analyzing key features in the dynamic generation of heterogeneous cell populations.
High-throughput screening of human genetic variants by pooled prime editing
Authors: Herger Michael , Kajba Christina M. , Buckley Megan , Cunha Ana , Strom Molly , Findlay Gregory M.
Published: April 2024

Understanding the effects of rare genetic variants remains challenging, both in coding and non-coding regions. While multiplexed assays of variant effect (MAVEs) have enabled scalable functional assessment of variants, established MAVEs are limited by either exogenous expression of variants or constraints of genome editing. Here, we introduce a pooled prime editing (PE) platform in haploid human cells to scalably assay variants in their endogenous context. We first optimized delivery of variants to HAP1 cells, defining optimal pegRNA designs and establishing a co-selection strategy for improved efficiency. We characterize our platform in the context of negative selection by testing over 7,500 pegRNAs targetingSMARCB1for editing activity and observing depletion of highly active pegRNAs installing loss-of-function variants. We next assess variants inMLH1via 6-thioguanine selection, assaying 65.3% of all possible SNVs in a 200-bp region spanning exon 10 and distinguishing LoF variants with high accuracy. Lastly, we assay 362 non-codingMLH1variants across a 60 kb region in a single experiment, identifying pathogenic variants acting via multiple mechanisms with high specificity. Our analyses detail how filtering for highly active pegRNAs can facilitate both positive and negative selection screens. Accordingly, our platform promises to enable highly scalable functional assessment of human variants.
Themex-3 3’ untranslated region is essential for reproduction during temperature stress
Authors: Brown Hannah E. , Varderesian Haik V. , Keane Sara A. , Ryder Sean P.
Published: April 2024

Organisms must sense temperature and modify their physiology to survive environmental stress. Elevated temperature reduces fertility in most sexually reproducing organisms. Maternally supplied mRNAs are required for embryogenesis. They encode proteins that govern early embryonic patterning. RNA-binding proteins (RBPs) are major effectors of maternal mRNA regulation. MEX-3 is a conserved RBP essential for anterior patterning ofCaenorhabditis elegansembryos. We previously demonstrated that themex-33’ untranslated region (3’UTR) represses MEX-3 abundance in the germline yet is mostly dispensable for fertility. Here, we show that the 3’UTR is essential during thermal stress. Deletion of the 3’UTR causes a highly penetrant temperature sensitive embryonic lethality phenotype distinct from amex-3null. Loss of the 3’UTR decreases MEX-3 abundance specifically in maturing oocytes and early embryos during temperature stress. Dysregulation ofmex-3reprograms the thermal stress response by reducing the expression of hundreds of heat shock genes. We propose that the primary role of themex-33’UTR is to buffer MEX-3 expression during fluctuating temperature, ensuring the robustness of oocyte maturation and embryogenesis.
Multiplex, multimodal mapping of variant effects in secreted proteins
Authors: Popp Nicholas A. , Powell Rachel L. , Wheelock Melinda K. , Holmes Kristen J. , Zapp Brendan D. , Sheldon Kathryn M. , Fletcher Shelley N. , Wu Xiaoping , Fayer Shawn , Rubin Alan F. , Lannert Kerry W. , Chang Alexis T. , Sheehan John P. , Johnsen Jill M. , Fowler Douglas M.
Published: April 2024

Despite widespread advances in DNA sequencing, the functional consequences of most genetic variants remain poorly understood. Multiplexed Assays of Variant Effect (MAVEs) can measure the function of variants at scale, and are beginning to address this problem. However, MAVEs cannot readily be applied to the ∼10% of human genes encoding secreted proteins. We developed a flexible, scalable human cell surface display method, Multiplexed Surface Tethering of Extracellular Proteins (MultiSTEP), to measure secreted protein variant effects. We used MultiSTEP to study the consequences of missense variation in coagulation factor IX (FIX), a serine protease where genetic variation can cause hemophilia B. We combined MultiSTEP with a panel of antibodies to detect FIX secretion and post-translational modification, measuring a total of 44,816 effects for 436 synonymous variants and 8,528 of the 8,759 possible missense variants. 49.6% of possibleF9missense variants impacted secretion, post-translational modification, or both. We also identified functional constraints on secretion within the signal peptide and for nearly all variants that caused gain or loss of cysteine. Secretion scores correlated strongly with FIX levels in hemophilia B and revealed that loss of secretion variants are particularly likely to cause severe disease. Integration of the secretion and post-translational modification scores enabled reclassification of 63.1% ofF9variants of uncertain significance in theMy Life, Our Futurehemophilia genotyping project. Lastly, we showed that MultiSTEP can be applied to a wide variety of secreted proteins. Thus, MultiSTEP is a multiplexed, multimodal, and generalizable method for systematically assessing variant effects in secreted proteins at scale.
High resolution cryo-EM of V-ATPase in native synaptic vesicles
Authors: Coupland Claire E. , Karimi Ryan , Bueler Stephanie A. , Liang Yingke , Courbon Gautier M. , Di Trani Justin M. , Wong Cassandra J. , Saghian Rayan , Youn Ji-Young , Wang Lu-Yang , Rubinstein John L.
Published: April 2024

Neurotransmitter release into the synaptic cleft between neurons enables the intercellular communication central to the function of the brain. In the presynaptic neuron, the proton pumping vesicular- or vacuolar-type ATPase (V-ATPase) powers neurotransmitter loading into synaptic vesicles (SVs), with the V1complex dissociating from the membrane region of the enzyme before exocytosis. We isolated SVs from rat brain using SidK, a V-ATPase-binding bacterial effector protein. Single particle electron cryomicroscopy of the vesicles allowed high-resolution structure determination of V-ATPase within the native SV membrane. In the structure, regularly spaced cholesterol molecules decorate the enzyme’s rotor and the abundant SV protein synaptophysin binds the complex stoichiometrically. Conditions where ATP hydrolysis drives glutamate loading result in loss of V1from the SV membrane, suggesting that SV loading is sufficient to induce V-ATPase dissociation.
msCNVS: medium throughput single cell copy number variation sequencing with barcoded library construction free of preamplification toward clinical implementation
Authors: Lin Guanchuan , Peng Bin , Chen Caiming , Dong Zhanying , Xu Mengchang , Gao Jinyu , Yu Jie , Jia Bei , Luo Chen , Hua Rui , Xiao Changtai , Wang Linlin , Mai Liyao , Zhang Yulong , Lu Yuanfang , He Yuanqiao , Song Yali , Marjani Sadie L , Zhang Weimin , Zhang Junxiao , Zhong Mei , Quan Song , Weissman Sherman M , Zhu Hao , Pan Xinghua
Published: April 2024

Single cell copy number variation sequencing (scCNV-seq) is valuable for genomic analysis of a variety of health and disease systems, yet the available methods either depend on either preamplification of the whole genome of each cell, special devices or untracable, which hinder scCNV-seq practice in clinics. Here we provide scalable multiplex scCNV-seq (msCNVS) that allows direct medium-throughput library construction for single cells, which are barcoded individually with Tn5 transposome in a microplate and immediately pooled for downstream processes, elevating the efficiency by orders of magnitude. An algorithm is developed on the distribution of segmented normalized read count density to identify the major peaks associating with integer copy numbers, further improving the accuracy for objective CNV calling. Here msCNVS faithfully distinguishes the unique CNV patterns of 5 cell lines. The individual msCNVS profiles of 70 individual K562 cells highly correlate with the profile of K562 bulk cells (R=0.90-0.98), and the triplicates of HeLa3 bulk cells correlated nearly perfect (R=0.99). The msCNVS CNV profiles of primary cell cultures of amniotic fluid are confirmed by G-banding karyotype analysis and chromosomal microarray analysis. Additionally, the coverage uniformity of msCNVS is superior to that of MDA and MALBAC and approaches what eMDA and DOP-PCR achieves. Furthermore, msCNVS detects CNV deletions in 2 stunted, abnormal blastocysts, one with CNV mosaicism, and uncovered variants of CNVs in circulated tumor cells, cancerous pleural effusion cells, and patient-derived xenograft nuclei. Thus, msCNVS promises a robust, reliable and highly efficient approach to genomic testing of precious and rare cells like those typically obtained in reproductive and cancer clinics.

One-Sentence Summary

By early pooling of multiple single cells individually barcoded with Tn5 transposome, msCNVS enables efficient CNV profiling of rare clinic samples
An interpretable integration model improving disease-free survival prediction for gastric cancer based on CT images and clinical parameters
Authors: Cen Xiaoping , Hu Can , Yuan Li , Cheng Xiangdong , Dong Wei , Zhou Run , Wang Yuanmei , Zou Jiansheng , Lu Tianyu , Yang Huanming , Tong Yahan
Published: April 2024

Preoperative prediction of disease-free survival of gastric cancer is significantly important in clinical practice. Existing studies showed the potentials of CT images in identifying predicting the disease-free survival of gastric cancer. However, no studies to date have combined deep features with radiomics features and clinical features. In this study, we proposed a model which embedded radiomics features and clinical features into deep learning model for improving the prediction performance. Our models showed a 3%-5% C-index improvement and 10% AUC improvement in predicting DFS and disease event. Interpretation analysis including T-SNE visualization and Grad-CAM visualization revealed that the model extract biologically meaning features, which are potentially useful in predicting disease trajectory and reveal tumor heterogeneity. The embedding of radiomics features and clinical features into deep learning model could guide the deep learning to learn biologically meaningful information and further improve the performance on the DFS prediction of gastric cancer. The proposed model would be extendable to related problems, at least in few-shot medical image learning.

Key Points

An integration model combining deep features, radiomics features and clinical parameters improved disease-free-survival prediction of gastric cancer by 3%-5% C-index.

Embedding radiomics and clinical features into deep learning model through concatenation and loss design improved feature extraction ability of deep network.

The model revealed disease progression trajectory and tumor heterogeneity.
Landscape profiling of PET depolymerases using a natural sequence cluster framework
Authors: Seo Hogyun , Hong Hwaseok , Park Jiyoung , Lee Seul Hoo , Ki Dongwoo , Ryu Aejin , Sagong Hye-Young , Kim Kyung-Jin
Published: April 2024

Since the demonstration that rapid polyethylene terephthalate (PET) decomposition using enzymes is feasible, a number of efficient depolymerases have been reported with the aim of resolving the plastic pollution issues. However, sporadic studies on enzymes with PET hydrolysis activity hinder the understanding of the distribution of potential PETases hidden in nature’s repertoire, and subsequently, the identification of potent enzymes. Here, we present the clustering of 1,894 PETase candidates, which include the majority of known PETases, and describe their profiling. An archipelago landscape of 170 lineages shows distribution of 289 representative sequences with features associated with PET-degrading capabilities. A bird’s-eye view of the landscape identifies three highly promising yet unexplored PETase lineages and two potent PETases, Mipa-P and Kubu-P. The engineered Mipa-PM19and Kubu-PM12variants exhibit both high PET hydrolysis activity and thermal stability. In particular, Kubu-PM12outperformed the engineered benchmarks in terms of PET depolymerization in harsh environments, such as with high substrate load and ethylene glycol as the solvent. Our landscape framework and the identified variants assist in the understanding of how biological processes respond to solid-state and non-natural PET plastics.
TLR2 Supports γδ T cell IL-17A Response to ocular surface commensals by Metabolic Reprogramming
Authors: Zhu Wenjie , Xu Xiaoyan , Nagarajan Vijayaraj , Guo Jing , Peng Zixuan , Zhang Amy , Liu Jie , Mattapallil Mary J. , Jittayasothorn Yingyos , Horai Reiko , St. Leger Anthony J. , Caspi Rachel R.
Published: April 2024

The ocular surface is a mucosal barrier tissue colonized by commensal microbes, which tune local immunity by eliciting IL-17 from conjunctival γδ T cells to prevent pathogenic infection. The commensalCorynebacterium mastitidis(C. mast) elicits protective IL-17 responses from conjunctival Vγ4 T cells through a combination of γδ TCR ligation and IL-1 signaling. Here, we identify Vγ6 T cells as a majorC. mast-responsive subset in the conjunctiva and uncover its unique activation requirements. We demonstrate that Vγ6 cells require not only extrinsic (via dendritic cells) but also intrinsic TLR2 stimulation for optimal IL-17A response. Mechanistically, intrinsic TLR2 signaling was associated with epigenetic changes and enhanced expression of genes responsible for metabolic shift to fatty acid oxidation to supportIl17atranscription. We identify one key transcription factor, IκBζ, which is upregulated by TLR2 stimulation and is essential for this program. Our study highlights the importance of intrinsic TLR2 signaling in driving metabolic reprogramming and production of IL-17A in microbiome-specific mucosal γδ T cells.

The ocular commensalCorynebacterium mastitidis(C. mast) induces the IL-17 responses from γδ T cells by activating TLR2 signaling. γδ T cell-intrinsic TLR2 stimulation promotes fatty acid oxidation and increasesIL-17Atranscription, favoring IL-17A responses.

Highlights

(1) TLR2-deficient mice exhibit reduced γδ T cell responses to ocular commensal bacteria.

(2) γδ T cell-intrinsic TLR2 deficiency causes defects of fatty acid oxidation and IL-17A production in a γδ subset-specific manner.

(3) The transcription factor, IκBζ is upregulated by TLR2 stimulation and supports γδ IL-17A production through fatty acid oxidation.
Enhancing metabarcoding efficiency and ecological insights through integrated taxonomy and DNA reference barcoding: a case study on beach meiofauna
Authors: Macher Jan-Niklas , Martínez Alejandro , Çakir Sude , Cholley Pierre-Etienne , Christoforou Eleni , Galletti Marco Curini , van Galen Lotte , García-Cobo Marta , Jondelius Ulf , de Jong Daphne , Leasi Francesca , Lemke Michael , Lopez Iñigo Rubio , Sánchez Nuria , Sørensen Martin Vinther , Todaro M. Antonio , Renema Willem , Fontaneto Diego
Published: April 2024

Molecular techniques like metabarcoding, while promising for exploring diversity of communities, are often impeded by the lack of reference DNA sequences available for taxonomic annotation. Our study explores the benefits of combining targeted DNA barcoding and morphological taxonomy to improve metabarcoding efficiency, using beach meiofauna as a case study. Beaches are globally important ecosystems and are inhabited by meiofauna, microscopic animals living in the interstitial space between the sand grains, which play a key role in coastal biodiversity and ecosystem dynamics. However, research on meiofauna faces challenges due to limited taxonomic expertise and sparse sampling. We generated 775 new cytochrome c oxidase I DNA barcodes from meiofauna specimens collected along the Netherlands’ west coast and combined them with the NCBI GenBank database. We analysed alpha and beta diversity in 561 metabarcoding samples from 24 North Sea beaches, a region extensively studied for meiofauna, using both the enriched reference database and the NCBI database without the additional reference barcodes. Our results show a 2.5-fold increase in sequence annotation and a doubling of species-level Operational Taxonomic Units (OTUs) identification when annotating the metabarcoding data with the enhanced database. Additionally, our analyses revealed a bell-shaped curve of OTU richness across the intertidal zone, aligning more closely with morphological analysis patterns, and more defined community dissimilarity patterns between supralittoral and intertidal sites. Our research highlights the importance of expanding molecular reference databases and combining morphological taxonomy with molecular techniques for biodiversity assessments, ultimately improving our understanding of coastal ecosystems.
Representation of sex-specific social memory in ventral CA1 neurons
Authors: Watarai Akiyuki , Tao Kentaro , Okuyama Teruhiro
Published: April 2024

Recognizing familiar individuals is crucial for adaptive social interactions among animals. However, the multidimensional nature of social memory encompassing sexual information remains unelucidated. We found that neurons in the ventral CA1 region (vCA1) of the mouse hippocampus encoded the identities and social properties, specifically sex and strain, of familiar conspecifics by using both rate and theta-based temporal coding. Optogenetic reactivation of social memories of females, but not males, induced place preference. Ablation of the upstream hippocampal dorsal CA2 region (dCA2) or the medial amygdala (MeA) disrupted the representation of sex and the sexual dichotomy of social memory valence. Selective reactivation of overlapping neural populations of distinct female social memories representing the female sex was sufficient to induce preference. Thus, vCA1 neurons employ dual coding schemes to represent the identities and social properties of familiar conspecifics as a cohesive memory.
Trait distribution in Geometrid moth assemblages does not vary along a western Himalayan elevational gradient
Authors: Dey Pritha
Published: April 2024

Elevation gradients pose challenges for flying insects due to temperature and air density shifts, impacting their thermoregulation, flight abilities and subsequently species distribution patterns. Geometrid moths are a model group for studying these traits among insects. This study examines how trait-patterns and niche differentiation of Geometrid moth assemblages change with elevation. Investigating 697 specimens of 120 Geometrid moth species, I assessed species diversity, turnover, and various traits related to body size and flight capabilities along a 1500m elevation span in the western Himalayas. Results indicate a decline in species diversity along the elevational gradients, accompanied by consistent turnover from lower to higher elevations. Despite this pattern, elevation did not significantly influence morphological traits related to thermal sensitivity (body size) and flight capability (wing loading and manoeuvrability) at the assemblage level in Geometrid moths. Furthermore, there was no significant niche differentiation among species across elevations. This supports the argument that species with similar ecological roles persist through turnover, maintaining consistency in trait values across assemblages. These findings from the paleotropics align with patterns observed in Geometrid moths across neotropical and temperate regions, highlighting the importance of trait-based approaches in understanding species responses to environmental changes.

Summary Statement

This study examines how Geometrid moth assemblages in the western Himalayas respond to elevational gradients, revealing consistent turnover, stable traits, and no significant niche differentiation, emphasizing trait-based species adaptation
Brain tumor induce immunoregulatory dendritic cells in tumor draining lymph nodes that can be targeted by OX40
Authors: Badillo-Godinez Oscar , Helfridsson Liam , Niemi Jenni , Karimi Shokoufeh , Ramachandran Mohanraj , Hellström Mats
Published: April 2024

Brain tumors and metastases have a poor prognosis due to the unique characteristics of the central nervous system (CNS) and tumor immune microenvironment (TIME). CNS tumors exhibit limited infiltration and activation of dendritic cells (DCs) in tumor tissue and tumor-draining lymph nodes (TdLN), which regulate immune responses influenced by factors in the TIME. The immune response in the brain is significantly different from the rest of the body, and although DC subtypes have been identified in mice and humans with brain tumors or metastases, little is known how they affect the response to immunotherapy. We investigated the immunoregulatory function of cervical DCs (DC-c) compared to peripheral DCs (DC-p) in TdLN. Our analysis revealed that DC-c have unique phenotypes and promoted regulatory T cell expansion and poorly cytotoxic CD8 T cells compared to DC-p. Furthermore, we identified OX40 as a modulator of immunoregulatory DC-c function, andBatf3knockout confirmed the essential role of DC-c in mounting an immune response to brain tumors. Additionally, the expression of markers associated with mature regulatory DCs (mregDC) in TdLN was associated with immune regulation in the CNS and the response to OX40. Our findings highlight that immunotherapy interventions can modulate DC-c’s immunoregulatory function, offering an innovative approach for optimized immunotherapy against CNS malignancies.
Extending tactile space with hand-held tools: A re-analysis and review
Authors: Miller Luke E. , Farnè Alessandro
Published: April 2024

Tools can extend the sense of touch beyond the body, allowing the user to extract sensory information about distal objects in their environment. Though research on this topic has trickled in over the last few decades, little is known about the neurocomputational mechanisms of extended touch. In 2016, along with our late collaborator Vincent Hayward, we began a series of studies that attempted to fill this gap. We specifically focused on the ability to localize touch on the surface of a rod, as if it were part of the body. We have conducted eight behavioral experiments over the last several years, all of which have found that humans are incredibly accurate at tool-extended tactile localization. In the present article, we perform a model-driven reanalysis of these findings with an eye towards estimating the underlying parameters that map sensory input into spatial perception. This reanalysis revealed that users can almost perfectly localize touch on hand-held tools. This raises the question of how humans can be so good at localizing touch on an inert non-corporeal object. The remainder of the paper focuses on three aspects of this process that occupied much of our collaboration with Vincent: the mechanical information used by participants for localization; the speed by which the nervous system can transform this information into a spatial percept; and whether body-based computations are repurposed for tool-extended touch. In all, these studies underscore the special relationship between bodies and tools.
TAU FILAMENTS WITH THE CHRONIC TRAUMATIC ENCEPHALOPATHY FOLD IN A CASE OF VACUOLAR TAUOPATHY WITHVCPMUTATION D395G
Authors: Qi Chao , Kobayashi Ryota , Kawakatsu Shinobu , Kametani Fuyuki , Scheres Sjors H.W. , Goedert Michel , Hasegawa Masato
Published: April 2024

Dominantly inherited mutation D395G in the gene encoding valosin-containing protein causes vacuolar tauopathy, a type of behavioural-variant frontotemporal dementia, with marked vacuolation and abundant filamentous tau inclusions made of all six brain isoforms. Here we report that tau inclusions were concentrated in layers II/III of the frontotemporal cortex in a case of vacuolar tauopathy. By electron cryo-microscopy, tau filaments had the chronic traumatic encephalopathy (CTE) fold. Tau inclusions of vacuolar tauopathy share this cortical location and the tau fold with CTE, subacute sclerosing panencephalitis and amyotrophic lateral sclerosis/parkinsonism-dementia complex, which are believed to be environmentally induced. Vacuolar tauopathy is the first inherited disease with the CTE tau fold.
Redefining the Game: MVAE-DFDPnet’s Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions
Authors: Xia Liang-Yong , Wu Yu , Zhao Longfei , Chen Leying , Zhang Shiyi , Wang Mengdi , Luo Jie
Published: April 2024

Precisely predicting drug-protein interactions (DPIs) is pivotal for drug discovery and advancing precision medicine. A significant challenge in this domain is the high-dimensional and heterogeneous data characterizing drug and protein attributes, along with their intricate interactions. In our study, we introduce a novel deep learning architecture: theMulti-viewVariationalAuto-Encoder embedded within a cascadeDeepForest (MVAE-DFDPnet). This framework adeptly learns ultra-low-dimensional embedding for drugs and proteins. Notably, our t-SNE analysis reveals that two-dimensional embedding can clearly define clusters corresponding to diverse drug classes and protein families. These ultra-low-dimensional embedding likely contribute to the enhanced robustness and generalizability of our MVAE-DFDPnet. Impressively, our model surpasses current leading methods on benchmark datasets, functioning in significantly reduced dimensional spaces. The model’s resilience is further evidenced by its sustained accuracy in predicting interactions involving novel drugs, proteins, and drug classes. Additionally, we have corroborated several newly identified DPIs with experimental evidence from the scientific literature. The code used to generate and analyze these results can be accessed fromhttps://github.com/Macau-LYXia/MVAE-DFDPnet-V2.
Serial fermentation in milk generates functionally diverse community lineages with different degrees of structure stabilization
Authors: Gapp Chloé , Dijamentiuk Alexis , Mangavel Cécile , Callon Cécile , Theil Sébastien , Revol-Junelles Anne-Marie , Chassard Christophe , Borges Frédéric
Published: April 2024

Microbial communities offer considerable potential for tackling environmental challenges by improving the functioning of ecosystems. Top-down community engineering is a promising strategy that could be used to obtain communities of desired function. However, the ecological factors that control the balance between community shaping and propagation are not well understood. Dairy backslopping can be used as a model engineering approach to investigate the dynamics of communities during serial propagations. In this study, 26 raw milk samples were used to generate lineages of 6 communities obtained by serial propagation. Bacterial community structures were analyzed by metabarcoding and acidification was recorded by pH monitoring. The results revealed that different types of community lineages could be obtained in terms of taxonomic composition and dynamics. Five lineages reached a repeatable community structure in a few propagation steps, with little variation between the final generations, giving rise to stable acidification kinetics. Moreover, these stabilized communities presented a high inter-lineage variability of community structures as well as diverse acidification properties. Besides, the other lineages were characterized by different levels of dynamics leading to parallel or divergent trajectories. The functional properties and dynamics of the communities were mainly related to the relative abundance and the taxonomic composition of lactic acid bacteria within the communities. These findings highlight that short-term schemes of serial fermentation can produce communities with a wide range of dynamics and that the balance between community shaping and propagation is intimately linked to community structure.

Importance

Microbiome applications require approaches for shaping and propagating microbial communities. Shaping allows the selection of communities with desired taxonomic and functional properties, while propagation allows the production of the biomass required to inoculate the engineered communities in the target ecosystem. In top-down community engineering, where communities are obtained from a pool of mixed microorganisms by acting on environmental variables, a major challenge is to master the balance between shaping and propagation. However, the ecological factors that favor high dynamics of community structure and, conversely, those that favor stability during propagation are not well understood. In this work, short-term dairy blacksloping was used to investigate the key role of the taxonomic composition and structure of bacterial communities on their dynamics. The results obtained open up interesting prospects for the biotechnological use of microbiomes, particularly in the field of dairy fermentation, to diversify approaches for injecting microbial biodiversity into cheesemaking processes.
lcUMAPtSNE: Use of non-linear dimensionality reduction techniques with genotype likelihoods
Authors: Uzel Kerem , Grossen Christine , Çilingir F. Gözde
Published: April 2024

Understanding population structure is essential for conservation genetics, as it provides insights into population connectivity and supports the development of targeted strategies to preserve genetic diversity and adaptability.

T-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) have proven effective for revealing population genetic structures in human and model organisms using hard-called genotypes, but their application in wild species using genotype likelihoods from low coverage sequencing (as a cost-saving measure) remains underexplored.

Here, we present a Jupyter Notebook-based workflow that facilitates the use of UMAP and t-SNE on genotype likelihood-derived principal components.

This workflow is demonstrated using medium to low-coverage whole-genome sequencing data from scimitar-horned oryx, which has been reintroduced into the wild and faces multiple conservation challenges.

Detailed guidance on hyperparameter tuning and practical implementation is also provided, enhancing the application of these methods in wildlife genetics to potentially support biodiversity conservation.
Deterministic Formulas and Procedures for Stochastic Trait Introgression Prediction
Authors: Ajayi Temitayo , LaCombe Jason , Ince Güven , Yeats Trevor
Published: April 2024

Key message

We derive formulas for the background noise during trait introgression programs and use these formulas to quickly predict noise for up to five future generations without using simulation.

Trait introgression is a common method for introducing valuable traits into breeding populations and inbred cultivars. The process involves recurrent backcrossing of a donor individual (and its descendants) with a desirable, inbred line that lacks the aforementioned traits. The process typically concludes with a final generation of selfing in order to recover lines with the traits of interest fixed in the homozygous state. The particular breeding scheme is usually designed to maximize the genetic similarity of the converted lines to the recurrent parent while minimizing a breeders’ cost and time to recovering the near isogenic lines. Thus, key variables include the number of generations, number of crosses, and how to apply genotyping and selection during the process. In this paper, we derive analytical formulas that characterize the stochastic nature of residual donor geneome (i.e., “background noise”) during trait introgression. We use these formulas to predict the background noise in simulated trait introgression programs for five generations of progeny, as well as to construct a novel mathematical program to optimally allocate progeny to available parents. This provides a framework for the design of optimal breeding schemes for trait introgression involving one or more traits subject to the requirements of specific crops and breeding programs.
A dynamic epigenetic perspective on above and below-ground phenotypic responses to drought: insights from global DNA methylation inErodium cicutarium
Authors: Alonso Conchita , Medrano Mónica , Herrera Carlos M.
Published: April 2024

Premise of the study. Mounting evidence supports the view that the responses of plants to environmental stress are mediated by epigenetic factors, including DNA methylation. Understanding the relationships between DNA methylation, plant development and individual fitness under contrasting environments is key to uncover the potential impact of epigenetic regulation on plant adaptation. Experimental approaches that combine a controlled alteration of epigenetic features with exposure to some relevant stress factor can contribute to this end.

Methods. We combined the experimental application of a demethylating agent (5-azacytidine) with recurrent drought, and recorded their effects on above- and below-ground phenotypic traits related to early development, phenology and fitness inErodium cicutariumfrom two provenances.

Key results. We found that 5-azacytidine significantly reduced DNA methylation in leaf and root tissues. Moreover, it slowed plant development, delayed flowering, and reduced the number of inflorescences produced, and such detrimental effects occurred independently of water regime. Recurrent drought reduced final above- and below-ground biomass and total inflorescence production, and such negative effects were unaffected by artificial changes in DNA methylation. Increased fruit and seed-set were the only adaptive responses to drought observed inE. cicutarium, together with an increased number of flowers per inflorescence recorded in water stressed plants previously treated with 5-azacytidine.

Conclusion. Epigenetic effects can desynchronize plant growth, flowering and senescence among individual plants in both favourable and adverse environments. Future studies should focus on understanding intraspecific variation in the ability to change plant methylome in response to stress.
Mechanical forces pattern endocardial Notch activation via mTORC2-PKC pathway
Authors: Mu Yunfei , Hu Shijia , Liu Xiangyang , Tang Xin , Lin Jiayi , Shi Hongjun
Published: April 2024

Notch signaling has been identified as a key regulatory pathway in patterning the endocardium through activation of endothelial-to-mesenchymal transition (EMT) in the atrioventricular canal (AVC) and proximal outflow tract (OFT) region. However, the precise mechanism underlying Notch activation remains elusive. By transiently blocking the heartbeat of E9.5 mouse embryos, we found that Notch activation in the arterial endothelium was dependent on its ligand Dll4, whereas the reduced expression of Dll4 in the endocardium led to a ligand-depleted field, enabling Notch to be specifically activated in AVC and OFT by regional increased shear stress. The strong shear stress altered the membrane lipid microdomain structure of endocardial cells, which activated mTORC2 and PKC and promoted Notch1 cleavage even in the absence of strong ligand stimulation. These findings highlight the role of mechanical forces as a primary cue for endocardial patterning and provide insights into the mechanisms underlying congenital heart diseases of endocardial origin.
Mechano-regulation of GLP-1 production by Piezo1 in intestinal L cells
Authors: Huang Yanling , Mo Haocong , Yang Jie , Gao Luyang , Tao Tian , Shu Qing , Guo Wenying , Zhao Yawen , Lyu Jingya , Wang Qimeng , Guo Jinghui , Zhai Hening , Zhu Linyan , Chen Hui , Xu Geyang
Published: April 2024

Glucagon-like peptide 1 (GLP-1) is a gut-derived hormone secreted by intestinal L cells and vital for postprandial glycemic control. As open-type enteroendocrine cells, whether L cells can sense mechanical stimuli caused by chyme and thus regulate GLP-1 synthesis and secretion is unexplored. Our study showed expression of Piezo1 in intestinal L cells. Its level varied in different energy status and correlates with blood glucose and GLP-1 levels. Mice with L cell-specific loss of Piezo1 (IntL-Piezo1-/-) exhibited impaired glucose tolerance, increased body weight, reduced GLP-1 production and decreased CaMKKβ/CaMKIV-mTORC1 signaling pathway under normal chow diet or high fed diet. Activation of the intestinal Piezo1 by its agonist Yoda1 or intestinal bead implantation increased the synthesis and secretion of GLP-1, thus alleviated glucose intolerance in diet-induced-diabetic mice. Overexpression of Piezo1, Yoda1 treatment or stretching stimulated GLP-1 production and CaMKKβ/CaMKIV-mTORC1 signaling pathway, which could be abolished by knockdown or blockage of Piezo1 in primary cultured mouse L cells and STC-1 cells. These findings suggest a previously undiscovered mechano-regulation of GLP-1 production in L cells, which may shed new light on the treatments of diabetes.
Predicting The Pathway Involvement Of Metabolites Based on Combined Metabolite and Pathway Features
Authors: Huckvale Erik D. , Moseley Hunter N.B.
Published: April 2024

A major limitation of most metabolomics datasets is the sparsity of pathway annotations of detected metabolites. It is common for less than half of identified metabolites in these datasets to have known metabolic pathway involvement. Trying to address this limitation, machine learning models have been developed to predict the association of a metabolite with a “pathway category”, as defined by one of the metabolic knowledgebases like the Kyoto Encyclopedia of Gene and Genomes. Most of these models are implemented as a single binary classifier specific to a single pathway category, requiring a set of binary classifiers for generating predictions for multiple pathway categories. This single binary classifier per pathway category approach both multiplies the computational resources necessary for training while diluting the positive entries in gold standard datasets needed for training. To address the limitations of training separate classifiers, we propose a generalization of the metabolic pathway prediction problem using a single binary classifier that accepts both features representing a metabolite and features representing a generic pathway category and then predicts whether the given metabolite is involved in the corresponding pathway category. We demonstrate that this metabolite-pathway features-pair approach is not only competitive with the combined performance of training separate binary classifiers, but it outperforms the previous benchmark models.
Cross-correlation increases sampling in diffusion-based super-resolution optical fluctuation imaging
Authors: Antarasen Jeanpun , Wellnitz Benjamin , Kramer Stephanie N. , Chatterjee Surajit , Kisley Lydia
Published: April 2024

Correlation signal processing of optical three-dimensional (x, y, t) data can produce super-resolution images. The second order cross-correlation functionXC2has been documented to produce super-resolution imaging with static and blinking emitters but not for diffusing emitters. Here, we both analytically and numerically demonstrate cross-correlation analysis for diffusing particles. We then expand our fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) analysis to use cross-correlation as a post-processing computational technique to extract both dynamic and structural information of particle diffusion in nanoscale structures simultaneously. We further show how this method increases sampling rates and reduces aliasing for spatial information in both simulated and experimental data. Our work demonstrates how fcsSOFI with cross-correlation can be a powerful signal-processing tool to resolve the nanoscale dynamics and structure in samples relevant to biological and soft materials.

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Intrapartum antibiotic prophylaxis selects for mutators in group B streptococci among persistently colonized patients
Authors: Pell Macy E. , Blankenship Heather M. , Gaddy Jennifer A. , Davies H. Dele , Manning Shannon D.
Published: April 2024

Through vaginal colonization, GBS causes severe pregnancy outcomes including neonatal sepsis and meningitis. Although intrapartum antibiotic prophylaxis (IAP) has reduced early-onset disease rates, persistent GBS colonization has been observed in patients following prophylaxis. To determine whether IAP selects for genomic signatures that enhance GBS survival and persistence in the vaginal tract, whole-genome sequencing was performed on 97 isolates from 58 patients before (prenatal) and after (postpartum) IAP/childbirth. Core-gene mutation analysis identified 7,025 mutations between the paired isolates. Three postpartum isolates accounted for 98% of mutations and were classified as “mutators” because of point mutations within DNA repair systems.In vitroassays revealed stronger biofilms in two mutators. These findings suggest that antibiotics select for mutations that promote survivalin vivo, which increases the likelihood of transmission to neonates. They also demonstrate how mutators can provide a reservoir of beneficial mutations that enhance fitness and genetic diversity in the GBS population.
Cryo-electron tomographic investigation of native hippocampal glutamatergic synapses
Authors: Matsui Aya , Spangler Cathy J. , Elferich Johannes , Shiozaki Momoko , Jean Nikki , Zhao Xiaowei , Qin Maozhen , Zhong Haining , Yu Zhiheng , Gouaux Eric
Published: April 2024

Chemical synapses are the major sites of communication between neurons in the nervous system and mediate either excitatory or inhibitory signaling [1]. At excitatory synapses, glutamate is the primary neurotransmitter and upon release from presynaptic vesicles, is detected by postsynaptic glutamate receptors, which include ionotropic AMPA and NMDA receptors [2, 3]. Here we have developed methods to identify glutamatergic synapses in brain tissue slices, label AMPA receptors with small gold nanoparticles (AuNPs), and prepare lamella for cryo-electron tomography studies. The targeted imaging of glutamatergic synapses in the lamella is facilitated by fluorescent pre- and postsynaptic signatures, and the subsequent tomograms allow for identification of key features of chemical synapses, including synaptic vesicles, the synaptic cleft and AuNP-labeled AMPA receptors. These methods pave the way for imaging brain regions at high resolution, using unstained, unfixed samples preserved under near-native conditions.
RosetteArray®Platform for Quantitative High-Throughput Screening of Human Neurodevelopmental Risk
Authors: Lundin Brady F. , Knight Gavin T. , Fedorchak Nikolai J. , Krucki Kevin , Iyer Nisha , Maher Jack E. , Izban Nicholas R. , Roberts Abilene , Cicero Madeline R. , Robinson Joshua F. , Iskandar Bermans J. , Willett Rebecca , Ashton Randolph S.
Published: April 2024

Neural organoids have revolutionized how human neurodevelopmental disorders (NDDs) are studied. Yet, their utility for screening complex NDD etiologies and in drug discovery is limited by a lack of scalable and quantifiable derivation formats. Here, we describe the RosetteArray®platform’s ability to be used as an off-the-shelf, 96-well plate assay that standardizes incipient forebrain and spinal cord organoid morphogenesis as micropatterned, 3-D, singularly polarized neural rosette tissues (>9000 per plate). RosetteArrays are seeded from cryopreserved human pluripotent stem cells, cultured over 6-8 days, and immunostained images can be quantified using artificial intelligence-based software. We demonstrate the platform’s suitability for screening developmental neurotoxicity and genetic and environmental factors known to cause neural tube defect risk. Given the presence of rosette morphogenesis perturbation in neural organoid models of NDDs and neurodegenerative disorders, the RosetteArray platform could enable quantitative high-throughput screening (qHTS) of human neurodevelopmental risk across regulatory and precision medicine applications.
Multiple methods of diet assessment reveal differences in Atlantic puffin adult and chick diets both between and within years
Authors: Kennerley William L. , Clucas Gemma V. , Lyons Donald E.
Published: April 2024

Atlantic puffin (Fratercula arctica, hereafter “puffin”) reproductive success in the Gulf of Maine (GoM) has decreased following a recent oceanographic regime shift and subsequent rapid warming. Concurrent changes in both the regional forage fish community and puffin chick diet and provisioning rates suggest that inadequate prey resources may be driving this decline. To determine what prey GoM puffins were feeding on during two years of marine heatwave conditions, we assessed puffin diet using two methods: traditional, observational methods that utilize bill-load photography and emerging methods employing fecal DNA metabarcoding. We identified a strong correlation between the composition of chick diet as estimated through traditional and emerging methods, supporting the interpretation of DNA relative read abundance as a quantitative metric of diet composition. Both methods identified the same dominant prey groups, but metabarcoding identified a greater number of species and offered higher taxonomic resolution. Puffin adults and chicks fed on many of the same prey types, although adults consumed a greater variety of taxa and consumed more low quality prey than they provisioned chicks, as predicted by optimal foraging theory. For both age classes, diet varied both between and within years, likely reflecting changes in the local forage fish community in response to environmental variability. During these two years of marine heatwave conditions, puffins exploited unusual abundances of typically-uncommon prey, yet low puffin productivity suggests the observed dietary plasticity was not able to compensate for apparent prey shortages. Continued refinement of molecular tools and the interpretation of the data they provide will enable better assessments of how seabirds of diverse ages and breeding stages are compensating for changing forage fish communities in response to global climate change.