bluuebunny/crossref_metadata_2025 huggingface dataset:
Computing hematopoietic stem and progenitor cell plasticity in response to genetic mutations and environmental stimulations
Authors: Wen Yuchen , He Hang , Ma Yunxi , Cai Lorie Chen , Wang Huaquan , Li Yanmei , Zhao Baobing , Cai Zhigang
Published: August 2024

Cell plasticity (CP), describing a dynamic cell state, plays a crucial role in maintaining homeostasis during organ morphogenesis, regeneration and damage-to-repair biological process. Single-cell-omics datasets provide unprecedented resource to empowers analysis on CP. Hematopoiesis offers fertile opportunities to develop quantitative methods for understanding CP with rich supports from experimental ground-truths. In this study we generated high-quality lineage-negative (Lin−) single-cell RNA-sequencing datasets under various conditions and introduced a working pipeline named Snapdragon to interrogate naïve and disturbed plasticity of hematopoietic stem and progenitor cells (HSPCs) with mutational or environmental challenges. Utilizing embedding methods UMAP or FA, a continuum of hematopoietic development is visually observed in wildtype where the pipeline confirms a very low Proportion of hybrid-cells (Phc, with bias range: 0.4-0.6) on a transition trajectory. UponTet2mutation, a driver of leukemia, or treatment of DSS, an inducer of colitis,Phcis increased and plasticity of HSPCs was enhanced. Quantitative analysis indicates thatTet2mutation enhances HSC self-renewal capability while DSS treatment results in an enhanced myeloid-skewing trajectory, suggesting their similar but different consequences. We prioritized several transcription factors (i.e the EGR family) and signaling pathways (i.e. receptors IL1R1 and ADRB, inflammation and sympathy-sensing respectively) which are responsible forPhcalterations. CellOracle-based simulation suggests that knocking-out EGR regulons or pathways of IL1R1 and ADRB partially reversesPhcpromoted byTet2mutation and inflammation. In conclusion, the study provides high-quality datasets with single-cell transcriptomic matrices for diversified hematopoietic simulations and a computational pipeline Snapdragon for quantifying disturbedPhcand CP. (247 words)

Highlights

To guide CP analysis, we introduce a quantizable parameterPhcand a pipeline Snapdragon, which discriminate naive and disturbed hematopoiesis;

The Snapdragon pipeline analysis onTet2+/-Lin−cells demonstrates many novel insights, including enhanced HSC plasticity and increased PHC; similar trends are observed in inflammatory Lin−cells;

Regulon analysis suggests that transcriptional factor EGR1 is significantly activated to elevated the HSC plasticity and change hematopoietic trajectory;

Stress-response-related signaling pathways mediated by receptors IL1R1 or ADRB were obviously activated in the challenged hematopoiesis;

CellOracle-based simulation suggests that knocking-out EGR regulons or pathways of IL1R1 and ADRB partially reversesPhcpromoted byTet2mutation and inflammation.
S2-PepAnalyst: A Web Tool for Predicting Plant Small Signalling Peptides
Authors: Vomo-Donfack Kelly L. , Abaach Mariem , Luna Ana M. , Ginot Grégory , Doblas Verónica G. , Morilla Ian
Published: August 2024

Small signalling peptides (SSPs) play crucial roles in plant growth, development, and stress responses. However, accurately identifying and characterising SSPs remains challenging due to their structural diversity and the limitations of current prediction tools. Here, we introduce S2-PepAnalyst, a novel web tool designed to enhance the prediction of SSPs in plants. By integrating comprehensive plant-specific datasets into a machine learning model, S2-PepAnalyst offers versatility, improved accuracy of 99.5% on average, and reliability with a low rate of false negatives compared to existing tools. S2-PepAnalyst provides essential resources for plant biologists and facilitates new discoveries in plant peptide signalling.
Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis
Authors: Chouaib Abed Alrahman , Chang Hsin-Fang , Khamis Omnia M. , Echeverry Santiago , Demeersseman Lucie , Elizarova Sofia , Daniel James A , Valitutti Salvatore , Barg Sebastian , Pape Constantin , Shaib Ali H. , Becherer Ute
Published: August 2024

Vesicle exocytosis is a fundamental component of intercellular communication, in all organisms. It has been studied for decades, using various imaging tools. Nevertheless, exocytosis research is still limited by the lack of reliable automated analysis procedures. To address this, we developed the Intelligent Vesicle Exocytosis Analysis Platform (IVEA), a nearly universal solution for analyzing exocytosis acquired with live cell imaging. IVEA is applicable to a wide variety of experimental model systems, microscopes and reporter fluorophores. IVEA combines state-of-the-art deep-learning and computer vision regimes to enable fully automated analysis of large data. IVEA runs as a FIJI plugin and does not require prior training or human intervention. IVEA is 60 times faster than manual analysis and is able to detect rare events often missed by the human eye. Overall, IVEA represents a breakthrough in the analysis of cellular secretory mechanisms and has a transformative potential for the exocytosis imaging field.
Identification of robust RT-qPCR reference genes for studying changes in gene expression in response to hypoxia in breast cancer cell lines
Authors: Malcolm Jodie R. , Bridge Katherine S. , Holding Andrew N. , Brackenbury William J.
Published: August 2024

Hypoxia is common in breast tumours and is linked to therapy resistance and advanced disease. To understand hypoxia-driven breast cancer progression, RT-qPCR quantifies transcriptional changes important for malignant development. Reference genes (RGs) are endogenous RT-qPCR controls used to normalise mRNA levels, allowing accurate assessment of transcriptional changes. However, hypoxia reprograms transcription and post-transcriptional processing of RNA such that favoured RGs includingGAPDHorPGK1are unsuitable for this purpose. To address the need for robust RGs to study hypoxic breast cancer cell lines, we identified 10 RG candidates by analysing public RNA-seq data of MCF-7, T-47D, MDA-MB-231 and MDA-MB-468 cells cultured in normoxia or hypoxia. RT-qPCR determined RG candidate levels in normoxic breast cancer cells, removingTBPandEPAS1from downstream analysis due to insufficient transcript abundance. Assessing primer efficiency further removedACTB, CCSER2andGUSBfrom consideration. Following culture in normoxia, or acute or chronic hypoxia, we ascertained robust non-variable RGs using RefFinder. Here we presentRPLP1andRPL27 asoptimal RGs for breast cancer cell lines cultured in normoxia or hypoxia. Our result enables accurate evaluation of gene expression in hypoxic breast cancer cell lines and provides an essential resource for assessing hypoxia’s impact in breast cancer progression.

Graphical Abstract
ImPaqT - A Golden Gate-based Toolkit for Zebrafish Transgenesis
Authors: Hurst Saskia , Dimmler Christiane , Cronan Mark R.
Published: August 2024

Transgenic animals continue to play an essential role in many aspects of zebrafish research, including the development of disease models. The most widely used system for zebrafish transgenesis is the Tol2 transposon system. Here, we have developed ImPaqT (Immunological toolkit forPaqCI-based Golden Gate Assembly of Tol2Transgenes), a new Tol2-based transgenesis system that utilizes Golden Gate assembly to facilitate the production of transgenic zebrafish lines. This system allows for rapid assembly of multiple fragments into a single transgene, facile swapping of individual sequences to generate new transgenes and an easy cloning workflow to incorporate new genetic elements into the existing kit. Within this toolkit framework, we have generated a number of reagents to enable gene expression within immune and non-immune cell types, an array of best-in-class fluorescent proteins to visualize cell populations and transgenes as well as tools to simplify genetic manipulation, purification and ablation of targeted cells. Unlike recombination-based systems, the Golden Gate approach is also expandable, allowing the incorporation of complex designs such as multi-fragment promoters within the established modular framework of ImPaqT. Here, we demonstrate the function of this new system by generating a number of novel transgenic immune reporter lines. While our toolkit is focused on the immune system as an emerging area of study within zebrafish research, the ImPaqT approach can be broadly adapted to the construction of almost any zebrafish transgene, offering new tools for the generation of transgenes within the zebrafish community.
Reduced function of the adaptor SH2B3 promotes T1D via altered gc cytokine-regulated, T cell intrinsic immune tolerance
Authors: Watson Taylor K. , Rosen Aaron B.I. , Drow Travis , Medjo Jacob A. , MacQuivey Matthew A. , Ge Yan , Liggitt H. Denny , Grosvenor Dane A. , Dill-McFarland Kimberly A. , Altman Matthew C. , Concannon Patrick J. , Buckner Jane H. , Rawlings David J. , Allenspach Eric J.
Published: August 2024

Genome-wide association studies have identifiedSH2B3as an important non-MHC gene for islet autoimmunity and type 1 diabetes (T1D). In this study, we found a singleSH2B3haplotype significantly associated with increased risk for human T1D, and this haplotype carries the single nucleotide variant rs3184504*T inSH2B3.To better characterize the role of SH2B3 in T1D, we used mouse modeling and found a T cell-intrinsic role for SH2B3 regulating peripheral tolerance. SH2B3 deficiency had minimal effect on TCR signaling or proliferation across antigen doses, yet enhanced cell survival and cytokine signaling including common gamma chain-dependent and interferon-gamma receptor signaling. SH2B3 deficient CD8+T cells showed augmented STAT5-MYC and effector-related gene expression partially reversed with blocking autocrine IL-2 in culture. Using the RIP-mOVA model, we found CD8+ T cells lacking SH2B3 promoted early islet destruction and diabetes without requiring CD4+ T cell help. SH2B3-deficient cells demonstrated increased survival post-transfer compared to control cells despite a similar proliferation profile in the same host. Next, we created a spontaneous NOD.Sh2b3-/-mouse model and found markedly increased incidence and accelerated T1D across sexes. Collectively, these studies identify SH2B3 as a critical mediator of peripheral T cell tolerance limiting the T cell response to self-antigens.

Article Highlights

The rs3184504 polymorphism, encoding a hypomorphic variant of the negative regulator SH2B3, strongly associates with T1D.

SH2B3 deficiency results in hypersensitivity to cytokines, including IL-2, in murine CD4+ and CD8+ T cells.

SH2B3 deficient CD8+ T cells exhibit a comparable transcriptome to wild-type CD8+ T cells at baseline, but upon antigen stimulation SH2B3 deficient cells upregulate genes characteristic of enhanced JAK/STAT signaling and effector functions.

We found a T-cell intrinsic role of SH2B3 leading to severe islet destruction in an adoptive transfer murine T1D model, while global SH2B3 deficiency accelerated spontaneous NOD diabetes across sexes.
A high lipid diet leads to greater pathology and lower tolerance during infection
Authors: Perrine Weston G. , Sauer Erin L. , Love Ashley C. , Morris Ashley , Novotny Johnathon , DuRant Sarah E.
Published: August 2024

Despite the clear effect of food resources on wildlife disease dynamics, few studies have investigated how shifts in diet, specifically macronutrient content, shape vertebrate host responses to infection. While each individual macronutrient plays a vital role in physiological processes necessary for pathogen defense, it is often difficult to disentangle the role of an individual macronutrient on disease pathology. We explored the effects of dietary macronutrient composition on disease pathology and feeding behavior of canaries (Serinus canaria domestica)infected withMycoplasma gallisepticum(MG). First, we provided canaries with isocaloric diets comprised of identical ingredients that varied in macronutrient content (high-protein or high-lipid) then MG- or sham-inoculated birds. We then offered both diets to canaries before and after MG- and sham-inoculation. In experiment one, high protein diet birds consumed more food than high lipid diet birds and experienced a more pronounced decrease in food intake after infection. High protein diet birds were more tolerant to MG infection, exhibiting reduced pathology when compared to high lipid diet birds, despite the two treatments having similar levels of MG-specific antibodies and MG loads. When birds had access to both diets, they consumed more of the high protein diet and experienced pathology for less time than lipid or protein restricted birds. These results highlight that macronutrient makeup of the diet can shape host tolerance and pathology and thus affect host-pathogen transmission dynamics.

Summary Statement

Macronutrient composition of the diet shapes tolerance in an avian host pathogen system. Birds that had greater access to protein exhibited reduced pathology despite similar pathogen loads when compared with birds with greater access to lipids.
Six drivers of aging identified among genes differentially expressed with age
Authors: Coler-Reilly Ariella , Pincus Zachary , Scheller Erica L. , Civitelli Roberto
Published: August 2024

Many studies have compared gene expression in young and old samples to gain insights on aging, the primary risk factor for most major chronic diseases. However, these studies only describe associations, failing to distinguish drivers of aging from compensatory geroprotective responses and incidental downstream effects. Here, we introduce a workflow to characterize the causal effects of differentially expressed genes on lifespan. First, we performed a meta-analysis of 25 gene expression datasets comprising samples of various tissues from healthy, untreated adult mammals (humans, dogs, and rodents) at two distinct ages. We ranked each gene according to the number of distinct datasets in which the gene was differentially expressed with age in a consistent direction. The top age-upregulated genes were TMEM176A, EFEMP1, CP, and HLA-A; the top age-downregulated genes were CA4, SIAH, SPARC, and UQCR10. Second, the effects of the top ranked genes on lifespan were measured by applying post-developmental RNA interference of the corresponding ortholog in the nematode C. elegans (two trials, with roughly 100 animals per genotype per trial). Out of 10 age-upregulated and 9 age-downregulated genes that were tested, two age-upregulated genes (csp-3/CASP1 andspch-2/RSRC1) and four age-downregulated genes (C42C1.8/DIRC2,ost-1/SPARC,fzy-1/CDC20, andcah-3/CA4) produced significant and reproducible lifespan extension. Notably, the data do not suggest that the direction of differential expression with age is predictive of the effect on lifespan. Our study provides novel insight into the relationship between differential gene expression and aging phenotypes, pilots an unbiased workflow that can be easily repeated and expanded, and pinpoints six genes with evolutionarily conserved, causal roles in the aging process for further study.

Graphical Abstract
scMitoMut for calling mitochondrial lineage–related mutations in single cells
Authors: Sun Wenjie , van Ginneken Daphne , Perié Leïla
Published: August 2024

Tracing cell lineages has become a valuable tool for studying biological processes. Among the available tools for human data, mitochondria DNA (mtDNA) has a high potential due to its ability to be used in conjunction with single-cell chromatin accessibility data, giving access to the cell phenotype. Nonetheless, the existing mutation calling tools are ill-equipped to deal with the polyploid nature of the mtDNA and lack a robust statistical framework. Here we introduce scMitoMut, an innovative R package that leverages statistical methodologies to accurately identify mitochondrial lineage related mutations at the single-cell level. scMitoMut assigns a mutation quality q-value based on beta-binomial distribution to each mutation at each locus within individual cells, ensuring higher sensitivity and precision of lineage related mutation calling in comparison to current methodologies. We tested scMitoMut using single-cell DNA sequencing, scATAC sequencing and 10× Genomics single cell multiome datasets. Using a single-cell DNA sequencing dataset from a mixed population of cell lines, scMitoMut demonstrated superior sensitivity in identifying small proportion of cancer cell lines compared to existing methods. In a human colorectal cancer scATAC dataset, scMitoMut identified more mutations than state-of-the-art methods. Applied to 10× Genomics multiome datasets, scMitoMut effectively measured the lineage distance in cells from blood or brain tissues. Thus, the scMitoMut is a free available (https://www.bioconductor.org/packages/devel/bioc/html/scMitoMut.html.), well-engineered toolkit for mtDNA mutation calling with high memory and CPU efficiency. Consequently, it will significantly advance the application of single-cell sequencing, facilitating the precise delineation of mitochondrial mutations for lineage tracing purposes in development, tumor and stem cell biology.
Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk
Authors: Mummey Hannah M , Elison Weston , Korgaonkar Katha , Elgamal Ruth M , Kudtarkar Parul , Griffin Emily , Benaglio Paola , Miller Michael , Jha Alokkumar , Manning Fox Jocelyn E , McCarthy Mark I , Preissl Sebastian , Gloyn Anna L , MacDonald Patrick E , Gaulton Kyle J
Published: August 2024

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs forcisregulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.
Comparison of Commercially Available Thermostable DNA Polymerases with Reverse-Transcriptase Activity in Coupled Reverse-Transcription Polymerase Chain Reaction Assays
Authors: Smirnova Evgeniya V. , Blagodatskikh Konstantin A. , Barsova Ekaterina V. , Varlamov Dmitriy A. , Kramarov Vladimir M. , Ignatov Konstantin B.
Published: August 2024

Reverse-transcription polymerase chain reaction (RT-PCR) is an important tool for the detection of target RNA molecules and the assay of RNA pathogens. Coupled RT-PCR is performed with an enzyme mixture containing a reverse transcriptase and a thermostable DNA polymerase. To date, several biotechnological companies offer artificial thermostable DNA polymerases with a built-in reverse-transcriptase activity for use in the coupled RT-PCR instead of the enzyme mixtures. Here, we compared the artificial DNA polymerases and conventional enzyme mixtures for the RT-PCR by performing end-point and real-time RT-PCR assays using severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV2) RNA and endogenous mRNA molecules as templates. We found that the artificial enzymes were suitable for different RT-PCR applications, including SARS-CoV2 RNA detection, but not for long-fragment RT-PCR amplification.
Synergistic control of axon regeneration and functional recovery bylet-7miRNA and Insulin signalling (IIs) pathways
Authors: Ravivarma Sruthy , Behera Sibaram , Roy Dipanjan , Ghosh-Roy Anindya
Published: August 2024

The capability of neurons to regenerate after injury becomes poor in adulthood. Previous studies indicated that loss of eitherlet-7miRNA or components of Insulin signalling (IIs) can overcome the age-related decline in axon regeneration inC. elegans. In this study, we wanted to understand the relationship between these two pathways in axon regeneration. We found that the simultaneous removal oflet-7and the gene for insulin receptordaf-2synergistically increased the functional recovery involving posterior touch sensation following axotomy of PLM neuron in adulthood. Conversely, the loss oflet-7could bypass the regeneration block due to the loss of DAF-16, a transcriptional target of DAF-2. Similarly, the loss ofdaf-2could bypass the requirement of LIN-41, a transcriptional co-factor of thelet-7pathway. Our analysis revealed that these two pathways synergistically control targeting of the regenerating axon to the ventral nerve cord, which leads to functional recovery. The computational analysis of the gene expression data revealed a large number of genes, their interacting modules, and hub genes underlet-7andIIspathway are exclusive in nature. Our study highlights a potential to promote neurite regeneration by harnessing the independent gene expression program involving thelet-7and Insulin signalling pathways.
Computational model for synthesizing auditory brainstem responses to assess neuronal alterations in aging and autistic animal models
Authors: Li Ben-Zheng , Poleg Shani , Ridenour Matthew , Tollin Daniel , Lei Tim , Klug Achim
Published: August 2024

The auditory brainstem response (ABR) is a widely used objective electrophysiology measure for non-invasively assessing auditory function and neural activities in the auditory brainstem, but its ability to reflect detailed neuronal processes is limited due to the averaging nature of the electroencephalogram recordings. This study addresses this limitation by developing a computational model of the auditory brainstem which is capable of synthesizing ABR traces based on a large, population scale neural extrapolation of a spiking neuronal network of auditory brainstem neural circuitry. The model was able to recapitulate alterations in ABR waveform morphology that have been shown to be present in two medical conditions: animal models of autism and aging. Moreover, in both of these conditions, these ABR alterations are caused by known distinct changes in auditory brainstem physiology, and the model could recapitulate these changes. In the autism model, the simulation revealed myelin deficits and hyperexcitability, which caused a decreased wave III amplitude and a prolonged wave III-V interval, consistent with experimentally recorded ABRs in Fmr1-KO mice. In the aging model, the model recapitulated ABRs recorded in aged gerbils and indicated a reduction in activity in the medial nucleus of the trapezoid body (MNTB), a finding validated by confocal imaging data. These results demonstrate not only the model’s accuracy but also its capability of linking features of ABR morphologies to underlying neuronal properties and suggesting follow-up physiological experiments.

Significance Statement

This study presents a novel computational model of the auditory brainstem, capable of synthesizing auditory brainstem response (ABR) traces by simulating large-scale neuronal activities. Addressing limitations of traditional ABR measurements, the model links ABR waveform features to underlying neuronal properties. Validated using empirical ABRs from animal models of autism and aging, the model accurately reproduced observed ABR alterations, revealing influences of myelin deficits and hyperexcitability in Fragile X syndrome, and degraded inhibitory activity in aging. These findings, supported by experimental data, demonstrate the model’s potential for predicting changes in auditory brainstem physiology and guiding further physiological investigations, thus advancing our understanding of auditory neural processes.
Transocular detection of premotor Parkinson’s disease via retinal capillary neurovascular coupling through functional OCT angiography
Authors: Liu Kaiyuan , Wang Ruixue , Huang Longqian , Zhang Huiying , Gao Mengqin , Sun Bin , Tan Yizhou , Ye Juan , Ding Zhihua , Gu Ying , Zhang Shaomin , Li Peng
Published: August 2024

Early detection of Parkinson’s disease (PD) is essential for timely initiating neuroprotective interventions before significant loss of dopaminergic (DAergic) neurons, but faces challenges in accurately and noninvasively detecting subtle neuronal changes in the midbrain. Here, we propose a transocular functional imaging method termed fOCTA-rNVC, which detects premotor PD by measuring alterations in retinal neurovascular coupling (rNVC) at the capillary level using specialized functional OCT angiography (fOCTA). Our findings demonstrate that capillary rNVC is significantly attenuated and delayed due to concurrent retinal dopaminergic degeneration in premotor PD mice. Notably, this PD-related rNVC attenuation can be temporarily reversed in acute levodopa challenge. Utilizing the functional characteristics of capillary rNVC in PD, we achieved an impressive accuracy of ∼100% in detecting premotor PD mice even with only ∼14.1% loss of midbrain DAergic neurons, at which stage prompt treatment offered superior outcomes. In contrast, no significant changes were observed in retinal thickness or vasculature in the premotor PD mice. These findings suggest that fOCTA-rNVC is a promising noninvasive solution for accurately detecting premotor PD and guiding early interventions.
Sound preferences in mice are sex-dependent
Authors: Sehrawat Kamini , Nelken Israel
Published: August 2024

We investigated the impact of early exposure to sound and to silence on sound preferences later in life in mice. We exposed young mice during the critical periods to excerpts of music (first movement of Beethoven’s symphony no. 9), non-music sounds, or to silence. We tested the sound preference behavior a few weeks later. Music exposure affected mouse behavior in a sex- dependent manner: male mice largely preferred the environment to which they were exposed, while female mice showed a weak reduction in their seemingly inborn aversion to sound. The neural activity in auditory cortex was suppressed in exposed compared to naive mice, regardless of exposure type. Remarkably, a robust negative correlation was found between neural response and behavior in female, but not in male, mice.
Get to know your neighbors with a SNAQTM: A framework for single cell spatial neighborhood analysis in immunohistochemical images
Authors: Silver Aryeh , Chakraborty Avirup , Pittu Avinash , Feier Diana , Anica Miruna , West Illeana , Sarkisian Matthew R. , Deleyrolle Loic P.
Published: August 2024

Motivation

Analyzing the local microenvironment of tumor cells can provide significant insights into their complex interactions with their cellular surroundings, including immune cells. By quantifying the prevalence and distances of certain immune cells in the vicinity of tumor cells through a neighborhood analysis, patterns may emerge that indicate specific associations between cell populations. Such analyses can reveal important aspects of tumor-immune dynamics, which may inform therapeutic strategies. This method enables an in-depth exploration of spatial interactions among different cell types, which is crucial for research in oncology, immunology, and developmental biology.

Results

We introduce an R Markdown script called SNAQTM(Single-cell SpatialNeighborhoodAnalysis andQuantification), which conducts a neighborhood analysis on immunofluorescent images without the need for extensive coding knowledge. As a demonstration, SNAQTMwas used to analyze images of pancreatic ductal adenocarcinoma. Samples stained for DAPI, PanCK, CD68, and PD-L1 were segmented and classified using QuPath. The resulting CSV files were exported into RStudio for further analysis and visualization using SNAQTM. Visualizations include plots revealing the cellular composition of neighborhoods around multiple cell types within a customizable radius. Additionally, the analysis includes measuring the distances between cells of certain types relative to others across multiple regions of interest.

Availability and implementation

The R Markdown files that comprise the SNAQTMalgorithm and the input data from this paper are freely available on the web athttps://github.com/AryehSilver1/SNAQ.

Visual Abstract

Created with BioRender.com.
Standardising a microbiome pipeline for body fluid identification from complex crime scene stains
Authors: Swayambhu Meghna , Gysi Mario , Haas Cordula , Schuh Larissa , Walser Larissa , Javanmard Fardin , Flury Tamara , Ahannach Sarah , Lebeer Sarah , Hanssen Eirik , Snipen Lars , Bokulich Nicholas , Kümmerli Rolf , Arora Natasha
Published: August 2024

Background

Recent advances in next-generation sequencing have opened up new possibilities for utilizing the human microbiome in various fields, including forensics. Researchers have capitalized on the site-specific microbial communities found in different parts of the body to identify body fluids from biological evidence. Despite promising results, microbiome-based methods have not yet been fully integrated into forensic practice due to the lack of standardized protocols and systematic testing of methods on forensically relevant samples. Our study addresses critical decisions in establishing these protocols, focusing on bioinformatics choices and the use of machine learning to present microbiome results in court for forensically relevant and challenging samples.

Results

We propose using Operational Taxonomic Units (OTUs) for read data processing and creating heterogeneous training datasets for training a random forest classifier. Our classifier incorporates six forensically relevant classes: saliva, semen, hand skin, penile skin, urine, and vaginal/menstrual fluid. Across these classes, our classifier achieved a high weighted average F1 score of 0.89. Systematic testing on mixed-source samples and underwear revealed reliable detection of at least one component of the mixture and the identification of vaginal fluid from underwear substrates. Additionally, when investigating the sexually shared microbiome (sexome) of heterosexual couples, our classifier shows promising results for the inference of sexual activity.

Conclusion

In our study, we recommend the use of a novel random forest classifier trained on a heterogenous dataset for obtaining predictions from samples mimicking forensic evidence. We also highlight the potential of the sexome for assessing the nature of sexual activities in forensic investigations, while delineating areas that warrant further research. Furthermore, we underscore key considerations when presenting machine learning results for classifying mixed-source samples.
A familial, telomere-to-telomere reference for humande novomutation and recombination from a four-generation pedigree
Authors: Porubsky David , Dashnow Harriet , Sasani Thomas A. , Logsdon Glennis A. , Hallast Pille , Noyes Michelle D. , Kronenberg Zev N. , Mokveld Tom , Koundinya Nidhi , Nolan Cillian , Steely Cody J. , Guarracino Andrea , Dolzhenko Egor , Harvey William T. , Rowell William J. , Grigorev Kirill , Nicholas Thomas J. , Oshima Keisuke K. , Lin Jiadong , Ebert Peter , Watkins W. Scott , Leung Tiffany Y. , Hanlon Vincent C.T. , McGee Sean , Pedersen Brent S. , Goldberg Michael E. , Happ Hannah C. , Jeong Hyeonsoo , Munson Katherine M. , Hoekzema Kendra , Chan Daniel D. , Wang Yanni , Knuth Jordan , Garcia Gage H. , Fanslow Cairbre , Lambert Christine , Lee Charles , Smith Joshua D. , Levy Shawn , Mason Christopher E. , Garrison Erik , Lansdorp Peter M. , Neklason Deborah W. , Jorde Lynn B. , Quinlan Aaron R. , Eberle Michael A. , Eichler Evan E.
Published: August 2024

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assessde novomutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5de novosingle-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6de novoindels or structural variants (SVs) originating from tandem repeats, 7.7 centromericde novoSVs and SNVs, and 12.4de novoY chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documentingde novoSVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% ofde novoSNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map (∼3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations andde novoSVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available “truth set” of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.
Discovery of the first-efficacious A2AR negative allosteric modulators for high adenosine cancer immunotherapies
Authors: Boujut Margot , Héritier Margaux , Gouiller Aurélie , Süess Camille , Scapozza Alessandro , Smedt Thibaut De , Guibert Maxime , Tardy Sébastien , Hamed Hesham , Pejoski David , Scapozza Leonardo
Published: August 2024

Inhibition of adenosine 2A receptor (A2AR) is recognized as a promising immunotherapeutic strategy but is challenged by the ubiquity of A2AR function in the immune system. To develop a safe yet efficacious immunotherapy, the discovery of a novel negative allosteric modulator (NAM) was preferred. Leveraging an in-house, sensitive, high-throughput screening cellular assay, novel A2AR NAM scaffolds were identified followed by an extensive structure-activity relationship (SAR) study, leading to the discovery of potent 2-amino-3,5-dicyanopyridine derivatives. Allosteric mode of action of active compounds was confirmed by shift assay, non-linearity of the Schild plot analysis, biophysical measurements, and retained satisfactory potencies in high-adenosine concentrations. Further correlation of A2AR engagement and downstream signaling was done in a human blood translational assay, clearly showcasing the potential of A2AR allosteric modulation as a novel approach for efficient and safer cancer immunotherapies.
Arsenic impairsDrosophilaneural stem cell mitotic progression and sleep behavior in a tauopathy model
Authors: Adebambo Temitope H. , Flores Ma. Fernanda Medina , Zhang Shirley L. , Lerit Dorothy A.
Published: August 2024

Despite established exposure limits, arsenic remains the most significant environmental risk factor detrimental to human health and is associated with carcinogenesis and neurotoxicity. Arsenic compromises neurodevelopment, and it is associated with peripheral neuropathy in adults. Exposure to heavy metals, such as arsenic, may also increase the risk of neurodegenerative disorders. Nevertheless, the molecular mechanisms underlying arsenic- induced neurotoxicity remain poorly understood. Elucidating how arsenic contributes to neurotoxicity may mitigate some of the risks associated with chronic sublethal exposure and inform future interventions. In this study, we examine the effects of arsenic exposure onDrosophilalarval neurodevelopment and adult neurologic function. Consistent with prior work, we identify significant developmental delays and heightened mortality in response to arsenic. Within the developing larval brain, we identify a dose-dependent increase in brain volume. This aberrant brain growth is coupled with impaired mitotic progression of the neural stem cells (NSCs), progenitors of the neurons and glia of the central nervous system. Live imaging of cycling NSCs reveals significant delays in cell cycle progression upon arsenic treatment, leading to genomic instability. In adults, chronic arsenic exposure reduces neurologic function, such as locomotion. Finally, we show arsenic selectively impairs circadian rhythms in a humanized tauopathy model. These findings inform mechanisms of arsenic neurotoxicity and reveal sex- specific and genetic vulnerabilities to sublethal exposure.
CellClear: Enhancing Single-cell RNA Data Quality via Biologically-Informed Ambient RNA Correction
Authors: Huang Wanxiang , Hu LongFei , Qian Zhengzong , Fan Jue
Published: August 2024

Ambient RNA, caused by the pool of mRNA molecules released from lysed or dead cells in samples, poses persistent challenges to single-cell RNA sequencing data analysis, and leads to potential problems such as inaccurate classification of cell types and downstream functional analyses. Here we propose CellClear to estimate and remove the ambient RNA expression programs in single-cell RNA sequencing data. CellClear demonstrates significant increase in the accuracy of ambient gene expression correction comparing with state-of-art methods, without distorting native information of individual cell types.
Neural Processing of Taste-Related Signals in the Mediodorsal Thalamus of Mice
Authors: Odegaard Katherine E. , Bouaichi Cecilia G. , Owanga Greg , Vincis Roberto
Published: August 2024

Our consummatory decisions depend on the taste of food and the reward experienced while eating, which are processed through neural computations in interconnected brain areas. Although many gustatory regions of rodents have been explored, the mediodorsal nucleus of the thalamus (MD) remains understudied. The MD, a multimodal brain area connected with gustatory centers, is often studied for its role in processing associative and cognitive information and has been shown to represent intraorally-delivered chemosensory stimuli after strong retronasal odor-taste associations. Key questions remain about whether MD neurons can process taste quality independently of odor-taste associations and how they represent extraoral signals predicting rewarding and aversive gustatory outcomes. Here, using C57 male and female mice we present electrophysiological evidence demonstrating how MD neurons represent and encode 1) the identity and concentrations of basic taste qualities during active licking, and 2) auditory signals anticipating rewarding and aversive taste outcomes. Our data reveal that MD neurons can reliably and dynamically encode taste identity in a broadly tuned manner and taste concentrations with spiking activity positively and negatively correlated with stimulus intensity. Our data also show that MD can represent information related to predictive cues and their associated outcomes, regardless of whether the cue predicts a rewarding or aversive outcome. In summary, our findings suggest that the mediodorsal thalamus is integral to the taste pathway, as it can encode sensory-discriminative dimensions of tastants and participate in processing associative information essential for ingestive behaviors.
From Maps to Models: A Survey on the Reliability of Small Studies of Task-Based fMRI
Authors: Sadil Patrick , Lindquist Martin A.
Published: August 2024

Task-based functional magnetic resonance imaging is a powerful tool for studying brain function, but neuroimaging research produces ongoing concerns regarding small-sample studies and how to interpret them. Although it is well understood that larger samples are preferable, many situations require researchers to make judgments from small studies, including reviewing the existing literature, analyzing pilot data, or assessing subsamples. Quantitative guidance on how to make these judgments remains scarce. To address this, we leverage the Human Connectome Project's Young Adult dataset to survey various analyses--from regional activation maps to predictive models. We find that, for some classic analyses such as detecting regional activation or cluster peak location, studies with as few as 40 subjects are adequate, although this depends crucially on effect sizes. For predictive modeling, similar sizes can be adequate for detecting whether features are predictable, but at least an order of magnitude more (at least hundreds) may be required for developing consistent predictions. These results offer valuable insights for designing and interpreting fMRI studies, emphasizing the importance of considering effect size, sample size, and analysis approach when assessing the reliability of findings. We hope that this survey serves as a reference for identifying which kinds of research questions can be reliably answered with small-scale studies.
Genome-Wide Association Study and transcriptome analysis reveals a complex gene network that regulates opsin gene expression and cell fate determination inDrosophilaR7 photoreceptor cells
Authors: Aldrich John C. , Vanderlinden Lauren A. , Jacobsen Thomas L. , Wood Cheyret , Saba Laura M. , Britt Steven G.
Published: August 2024

Background

An animal’s ability to discriminate between differing wavelengths of light (i.e., color vision) is mediated, in part, by a subset of photoreceptor cells that express opsins with distinct absorption spectra. InDrosophilaR7 photoreceptors, expression of the rhodopsin molecules, Rh3 or Rh4, is determined by a stochastic process mediated by the transcription factorspineless. The goal of this study was to identify additional factors that regulate R7 cell fate and opsin choice using a Genome Wide Association Study (GWAS) paired with transcriptome analysis via RNA-Seq.

Results

We examined Rh3 and Rh4 expression in a subset of fully-sequenced inbred strains from theDrosophilaGenetic Reference Panel and performed a GWAS to identify 42 naturally-occurring polymorphisms—in proximity to 28 candidate genes—that significantly influence R7 opsin expression. Network analysis revealed multiple potential interactions between the associated candidate genes,spinelessand its partners. GWAS candidates were further validated in a secondary RNAi screen which identified 12 lines that significantly reduce the proportion of Rh3 expressing R7 photoreceptors. Finally, using RNA-Seq, we demonstrated that all but four of the GWAS candidates are expressed in the pupal retina at a critical developmental time point and that five are among the 917 differentially expressed genes insevenlessmutants, which lack R7 cells.

Conclusions

Collectively, these results suggest that the relatively simple, binary cell fate decision underlying R7 opsin expression is modulated by a larger, more complex network of regulatory factors. Of particular interest are a subset of candidate genes with previously characterized neuronal functions including neurogenesis, neurodegeneration, photoreceptor development, axon growth and guidance, synaptogenesis, and synaptic function.
Th1 polarization inBordetella pertussisvaccine responses is maintained through a positive feedback loop
Authors: Willemsen Lisa , Lee Jiyeun , Shinde Pramod , Soldevila Ferran , Aoki Minori , Orfield Shelby , Kojima Mari , da Silva Antunes Ricardo , Sette Alessandro , Peters Bjoern
Published: August 2024

Outbreaks ofBordetella pertussis(BP), the causative agent of whooping cough, continue despite broad vaccination coverage and have been increasing since vaccination switched from whole-BP (wP) to acellular BP (aP) vaccines. wP vaccination has been associated with more durable protective immunity and an induced Th1 polarized memory T cell response. Here, a multi-omics approach was applied to profile the immune response of 30 wP and 31 aP-primed individuals and identify correlates of T cell polarization before and after Tdap booster vaccination. We found that transcriptional changes indicating an interferon response on day 1 post-booster along with elevated plasma concentrations of IFN-γ and interferon-induced chemokines that peaked at day 1-3 post-booster correlated best with the Th1 polarization of the vaccine-induced memory T cell response on day 28. Our studies suggest that wP-primed individuals maintain their Th1 polarization through this early memory interferon response. This suggests that stimulating the interferon pathway during vaccination could be an effective strategy to elicit a predominant Th1 response in aP-primed individuals that protects better against infection.
Mutant EZH2 alters the epigenetic network and increases epigenetic heterogeneity in B cell lymphoma
Authors: Griess Ofir , Furth Noa , Harpaz Nofar , Bernardo Nicoletta Di , Salame Tomer-Meir , Dassa Bareket , Karagiannidis Ioannis , Isshiki Yusuke , Gross Menachem , Melnick Ari M. , Béguelin Wendy , Ron Guy , Shema Efrat
Published: August 2024

Diffuse large B cell lymphomas and follicular lymphomas show recurrent mutations in epigenetic regulators; among these are loss-of-function mutations in KMT2D and gain-of-function mutations in EZH2. To systematically explore the effects of these mutations on the wiring of the epigenetic network, we applied a single-cell approach to probe a wide array of histone modifications. We show that mutant-EZH2 elicits extensive effects on the epigenome of lymphomas, beyond alterations to H3K27 methylations, and is dominant over KMT2D mutations. Utilizing the single-cell data, we present computational methods to measure epigenetic heterogeneity. We identify an unexpected characteristic of mutant-EZH2, but not KMT2D, in increasing heterogeneity, shedding light on a novel oncogenic mechanism mediated by this mutation. Finally, we present tools to reconstruct known interactions within the epigenetic network, as well as reveal potential novel cross talk between various modifications, validated by functional perturbations. Our work highlights novel roles for mutant-EZH2 in lymphomagenesis and establishes new concepts for measuring epigenetic heterogeneity and intra-chromatin connectivity in cancer cells.