bluuebunny/crossref_metadata_2025 huggingface dataset:
A sexually dimorphic hepatic cycle of periportal VLDL generation and subsequent pericentral VLDLR-mediated lipoprotein re-uptake
Authors: Martini Tomaz , Gobet Cedric , Salati Andrea , Blanc Jérôme , Mookhoek Aart , Reinehr Michael , Knott Graham , Sordet-Dessimoz Jessica , Naef Felix
Published: October 2023

Recent single-cell transcriptomes revealed spatiotemporal programmes of liver function on the sublobular scale. However, how sexual dimorphism affected this space-time logic remained poorly understood. We addressed this by performing scRNA-seq in the mouse liver, which revealed that sex, space and time together markedly influence xenobiotic detoxification and lipoprotein metabolism. The very low density lipoprotein receptor (VLDLR) exhibits a pericentral expression pattern, with significantly higher mRNA and protein levels in female mice. Conversely, VLDL assembly is periportally biased, suggesting a sexually dimorphic hepatic cycle of periportal formation and pericentral uptake of VLDL. In humans,VLDLRexpression is also pericentral, with higher mRNA and protein levels in premenopausal women compared to similarly aged men. Individuals with low hepaticVLDLRexpression show a high prevalence of atherosis in the coronary artery already at an early age and an increased incidence of heart attack.
Benchmarking whole exome sequencing pipeline for predicting pathogenic variants of significance
Authors: Raju Ranjana Mariyam , Singh Ujjwal Prathap , Suravajhala Prashanth
Published: October 2023

Benchmarking whole exome pipelines is crucial for evaluating and comparing their performance in variant calling and clinical significance annotation. It enables researchers and clinicians to assess the accuracy, sensitivity, and specificity of different pipelines and identify the most effective and reliable ones. In this study, we evaluated and compared the performance of our in-house consensus exome pipeline with a widely recognized gold standard Genome Analysis Toolkit (GATK) pipeline. Four datasets were used for evaluation, three 1000 Genome Project (1KGP) datasets and one Prostate cancer (PCa) Sample. The consensus pipeline consistently demonstrated a higher average transition-to-transversion (Ti/Tv) ratio, indicating enhanced precision in identifying single nucleotide variant (SNV) calls. This suggests that the consensus pipeline excels in effectively discerning true genetic variations from sequencing artefacts, particularly in the context of exome sequencing. Additionally, the pipeline exhibited increased sensitivity in detecting pathogenic and likely pathogenic variants in the PCa sample, further highlighting its efficacy in identifying clinically relevant variants. We also conducted a trio exome analysis with the use of two trio pipelines,viz. VarScan Trio and GATK joint calling pipelines on our erstwhile Congenital Pouch Colon (CPC) samples from our rare disease cohort which we published earlier and found that the GATK predicted a significantly higher number of variants compared to VarScan. Our study demonstrates a large potential for trio-variant calling analysis paving the way for precision medicine.
Scaling cross-tissue single-cell annotation models
Authors: Fischer Felix , Fischer David S. , Biederstedt Evan , Villani Alexandra-Chloé , Theis Fabian J.
Published: October 2023

Identifying cellular identities (both novel and well-studied) is one of the key use cases in single-cell transcriptomics. While supervised machine learning has been leveraged to automate cell annotation predictions for some time, there has been relatively little progress both in scaling neural networks to large data sets and in constructing models that generalize well across diverse tissues and biological contexts up to whole organisms. Here, we propose scTab, an automated, feature-attention-based cell type prediction model specific to tabular data, and train it using a novel data augmentation scheme across a large corpus of single-cell RNA-seq observations (22.2 million human cells in total). In addition, scTab leverages deep ensembles for uncertainty quantification. Moreover, we account for ontological relationships between labels in the model evaluation to accommodate for differences in annotation granularity across datasets. On this large-scale corpus, we show that cross-tissue annotation requires nonlinear models and that the performance of scTab scales in terms of training dataset size as well as model size - demonstrating the advantage of scTab over current state-of-the-art linear models in this context. Additionally, we show that the proposed data augmentation schema improves model generalization. In summary, we introduce a de novo cell type prediction model for single-cell RNA-seq data that can be trained across a large-scale collection of curated datasets from a diverse selection of human tissues and demonstrate the benefits of using deep learning methods in this paradigm. Our codebase, training data, and model checkpoints are publicly available athttps://github.com/theislab/scTabto further enable rigorous benchmarks of foundation models for single-cell RNA-seq data.
Molecular mechanisms of liposome interactions with bacterial envelopes
Authors: Scheeder Anna , Brockhoff Marius , Ward Edward N. , Kaminski Schierle Gabriele S. , Mela Ioanna , Kaminski Clemens F.
Published: October 2023

Although fusogenic liposomes offer a promising approach for the delivery of antibiotic payloads across the cell envelope of Gram-negative bacteria, there is still limited understanding of the individual nanocarrier interactions with the bacterial target. Using super-resolution microscopy, we characterize the interaction dynamics of positively charged fusogenic liposomes with Gram-negative (Escherichia coli) and Gram-positive (Bacillus subtilis) bacteria. The liposomes merge with the outer membrane (OM) of Gram-negative bacteria, while attachment or lipid internalization is observed in Gram-positive cells. Employing total internal reflection fluorescence microscopy, we demonstrated liposome fusion with model supported lipid bilayers. For wholeE. colicells, however, we observed heterogeneous membrane integrations, primarily involving liposome attachment and hemifusion events. With increasing lipopolysaccharide length the likelihood of full-fusion events was reduced. The integration of artificial lipids into the OM of Gram-negative cells led to membrane destabilization, resulting in decreased bacterial vitality, membrane detachment, and improved co-delivery of Vancomycin—an effective antibiotic against Gram-positive cells. These findings provide significant insights into the interactions of individual nanocarriers with bacterial envelopes at the single-cell level, uncovering effects that would be missed in bulk measurements. This highlights the importance of conducting single-particle and single-cell investigations to assess the performance of next-generation drug delivery platforms.
Exploring the tumor micro-environment in ovarian cancer histotypes and tumor sites
Authors: Xie Bingqing , Olalekan Susan , Back Rebecca , Ashitey Naa Asheley , Eckart Heather , Basu Anindita
Published: October 2023

Ovarian cancer is a highly heterogeneous disease consisting of at least five different histological subtypes with varying clinical features, cells of origin, molecular composition, risk factors, and treatments. While most single-cell studies have focused on High grade serous ovarian cancer, a comprehensive landscape of the constituent cell types and their interactions within the tumor microenvironment are yet to be established in the different ovarian cancer histotypes. Further characterization of tumor progression, metastasis, and various histotypes are also needed to connect molecular signatures to pathological grading for personalized diagnosis and tailored treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allowed us to deconstruct the histotypes and tumor site-specific expression patterns of cells in the tumor and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving precision disease stratification and optimizing treatment options.
Distribution theories for genetic line of least resistance and evolvability measures
Authors: Watanabe Junya
Published: October 2023

Quantitative genetic theory on multivariate character evolution predicts that a population’s response to directional selection tends to happen around the major axis of the genetic covariance matrixG—the so-called genetic line of least resistance. Inferences on the genetic constraints in this sense have traditionally been made by measuring the angle of deviation of evolutionary trajectories from the major axis, or more recently by calculating the amount of genetic variance—the Hansen–Houle evolvability—available along the trajectories. However, there have not been clear practical guidelines on how these quantities can be interpreted, especially in a high-dimensional space. This study summarizes pertinent distribution theories for relevant quantities, pointing out that they can be written as ratios of quadratic forms in evolutionary trajectory vectors by takingGas a parameter. For example, a beta distribution with appropriate parameters can be used as a null distribution for squared cosine of the angle of deviation from a major axis or subspace. More general cases can be handled with the probability distribution of ratios of quadratic forms in normal variables. Apart from its use in hypothesis-testing, this latter approach could potentially be used as a heuristic tool for looking into various selection scenarios like directional and/or correlated selection as parameterized with mean and covariance of selection gradients.
Effect of altered production and storage of dopamine on development and behavior inC. elegans
Authors: Lee Irene , Knickerbocker Ava C , Depew Charlotte Rose , Martin Elizabeth , Dicent Jocelyn , Miller Gary W , Bucher Meghan L
Published: October 2023

The nematode,Caenorhabditis elegans, is an advantageous model for studying developmental toxicology due to its homology to humans and well-defined developmental stages. Similarly to humans,C. elegansutilize dopamine as a neurotransmitter to regulate motor behavior. We have previously reported behavioral deficits in a genetic model ofC. elegans(OK411) that lack the neurotransmitter transporter necessary for packaging dopamine into synaptic vesicles. Anecdotally, we observed theseC. elegansappeared to have a smaller body size, which is supported by prior studies that observed a larger body size inC. elegansthat lack the enzyme that catalyzes dopamine synthesis, suggesting a complex regulatory system in which dopamine mediates body size inC. elegans. However, the question of whether body size abnormalities apparent inC. eleganswith disruptions to their dopamine system are developmental or purely based on body size remains unanswered. Here, we present data characterizing the effect of gene mutations in dopamine-related proteins on body size, development, and behavior. We analyzedC. elegansthat lack the ability to sequester dopamine (OK411), that overproduce dopamine (UA57), and a novel strain (MBIA) generated through crossing OK411 and UA57, which lacks the ability to sequester dopamine into vesicles and additionally endogenously overproduces dopamine. This novel strain was generated to address the hypothesis that an endogenous increase in production of dopamine can rescue deficits caused by a lack of vesicular dopamine sequestration. Compared to wild type, OK411 have shorter body lengths and behavioral deficits in early life stages. In contrast, the MBIA strain have similar body lengths to wild-type by early adulthood and display similar behavior to wild-type by early adulthood. Our data suggests that endogenously increasing the production of dopamine is able to mitigate deficits inC. eleganslacking the ability to package dopamine into synaptic vesicles. These results provide evidence that the dopamine system impacts development, growth, and reproduction inC. elegans.
Functional genomics reveals an off-target dependency of drug synergy in gastric cancer therapy
Authors: Leylek Ozen , Honeywell Megan E. , Lee Michael J. , Hemann Michael T. , Ozcan Gulnihal
Published: October 2023

The rational combination of anticancer agents is critical to improving patient outcomes in cancer. Nonetheless, most combination regimens in the clinic result from empirical methodologies disregarding insight into the mechanism of action and missing the opportunity to improve therapy outcomes incrementally. Deciphering the genetic dependencies and vulnerabilities responsible for synergistic interactions is crucial for rationally developing effective anticancer drug combinations. Hence, we screened pairwise pharmacological interactions between molecular-targeted agents and conventional chemotherapeutics and examined the genome-scale genetic dependencies in gastric adenocarcinoma cell models. Since this type of cancer is mainly chemoresistant and incurable, clinical situations demand effective combination strategies. Our pairwise combination screen revealed SN38/erlotinib as the drug pair with the most robust synergism. Genome-wide CRISPR screening and a shRNA-based signature assay indicated that the genetic dependency/vulnerability signature of SN38/erlotinib is the same as SN38 alone. Additional investigation revealed that the enhanced cell death with improved death kinetics caused by the SN38/erlotinib combination is surprisingly due to erlotinib’s off-target effect that inhibits ABCG2 but not its on-target effect on EGFR. Our results confirm that a genetic dependency signature different from the single-drug application may not be necessary for the synergistic interaction of molecular-targeted agents with conventional chemotherapeutics in gastric adenocarcinoma. The findings also demonstrated the efficacy of functional genomics approaches in unveiling biologically validated mechanisms of pharmacological interactions.

Significance

Functional genomics approaches efficiently demonstrated an off-target dependency of the synergistic interaction of erlotinib with SN38 in gastric adenocarcinoma cell models.
DIFFERENTIAL SCANNING CALORIMETRY: A SUITABLE METHODOLOGY TO PROBLEM THE BINDING PROPERTIES OF BCL-2 INHIBITORS
Authors: Dinc Bircan , Dogan Berna , Mavromoustakos Thomas , Durdagi Serdar
Published: October 2023

The Differential Scanning Calorimeter (DSC) technique is commonly used for quantitative analysis of protein stability, and it is one of the methods used to quantify protein-ligand interactions. DSC provides denaturation curves that can be a source of data on binding constants. B-cell leukemia/lymphoma-2 (BCL-2) is an antiapoptotic protein, one of the overexpressed proteins in cancer cells. Here, binding constants for BCL-2 of nine BCL-2 inhibitors were evaluated by utilization of DSC measurements. The binding free energies of suggested inhibitors of BCL-2 were measured by melting temperature, Tm,and heat capacity, Cp. Evaluated BCL-2 binding parameters of candidate molecules agreed with our previously reported biological assays and molecular simulations indicating that the DSC method could be applied for the determination of free energies of enzyme inhibitors with high accuracy. Therefore, our results showed that this fast and relatively cheap technique can be conducted in high throughput drug screening analyses to compare the binding affinity of a set of compounds against a specific target protein. BCL-2 and most of its inhibitors have hydrophobic cavities, and a definite percent of dimethyl sulfoxide (DMSO) was advised to increase the solubility. Our work also suggests that the presence of the recommended high concentration of DMSO as the solvent significantly changes the affinity of the inhibitors to BCL-2, revealing similar DSC curves for all inhibitors.
Structural Evolution of Trimeric Gamma-Type Retroviral Envelope Proteins
Authors: Hötzel Isidro
Published: October 2023

The envelope glycoproteins (Env) of retroviruses are highly diverse due to their relatively rapid evolution and the ancient origin of retroviruses. Sequence similarity among the Env of retroviruses is observed in the transmembrane subunit (TM) of Env mediating membrane fusion, whereas this similarity is more limited or absent in the surface subunit (SU) mediating receptor binding. Recent structural modeling of the SU of major retroviral groups identified a structurally conserved β-sheet domain in SU and the SU-equivalent of filoviruses, GP1, that is differentially expanded to generate the structural diversity observed in this protein family. Here, trimeric Env structures from three major exogenous and endogenous gamma-type retroviral Env classes were modeled with AlphaFold2 multimer to address the evolution of trimeric Env in the retroviruses. The models show a close structural relationship between the trimeric Env proteins of gammaretroviruses and alpharetroviruses and the trimeric filoviral spike protein, with an extended hydrophobic structure anchoring SU into TM in retroviral Env occluding the intersubunit disulfide bond. In addition, the murine leukemia virus (MLV) Env trimer model indicates that the type-C gammaretroviral receptor binding domains (RBD) are positioned on the side of the Env trimer pointing towards the viral envelope membrane, unlike those of the gammaretroviral RDR interference group, which are positioned closer to the apical end of the Env trimer. The trimeric MLV Env structural model, including RBD position, is consistent with previous trimeric MLV Env electron-density maps. The structural models provide insights into the structure, function and evolution of trimeric retroviral gamma-type Env.
Multi-omics analysis reveals novel interplays between intratumoral bacteria and glioma
Authors: Li Ting , Zhao Zhanyi , Peng Meichang , Wang Cheng , Luo Feiyang , Zeng Meiqin , Sun Kaijian , Fang Zhencheng , Luo Yunhao , Huang Qiyuan , Xie Yugu , Wang Jiaxuan , Huang Jian-Dong , Zhou Hongwei , Sun Haitao
Published: October 2023

Emerging evidence highlights the potential impact of intratumoral microbiota on cancer. However, the microbial composition and function in glioma remains elusive. Consequently, our study aimed to investigate the microbial community composition in glioma tissues and elucidate its role in glioma development. We parallelly performed microbial profiling, transcriptome sequencing and metabolomics detection on tumor and adjacent normal brain tissues obtained from 50 glioma patients. We employed immunohistochemistry, multicolor immunofluorescence and FISH staining to observe the presence and location of bacteria. Furthermore, an animal model was employed to validate the impact of key bacteria on glioma development. Six genera were found to be significantly enriched in glioma tissues compared to its adjacent normal brain tissues, includingFusobacterium,Longibaculum,Intestinimonas,Pasteurella,LimosilactobacillusandArthrobacter. Both bacterial RNA and LPS were observed in glioma tissues. Multicolor immunofluorescence analysis showed higher bacterial LPS levels in tumor cells than in macrophages and in glioma tissue than in adjacent normal brain tissue. Integrated microbiomics, transcriptomics, and metabolomics revealed that genes associated with intratumoral microbes were enriched in multiple synapse-associated pathways and that metabolites associated with intratumoral microbes were (R)-N-methylsalsolinol, N-acetylaspartylglutamic acid, and N-acetyl-L-aspartic acid. Further mediation analysis suggested that intratumoral microbiome may affect the expression of neuron-related genes through bacteria-associated metabolites. In addition, a glioma mouse model suggested thatFusobacterium nucleatumpromoted glioma growth by increasing the levels of N-acetylneuraminic acid and the expression levels of CCL2, CXCL1, and CXCL2. In conclusion, our findings shed light on the intricate interplays between intratumoral bacteria and glioma.
The fitness cost of spurious phosphorylation
Authors: Bradley David , Hogrebe Alexander , Dandage Rohan , Dubé Alexandre K , Leutert Mario , Dionne Ugo , Chang Alexis , Villén Judit , Landry Christian R
Published: October 2023

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organismS. cerevisiaeto inducibly express tyrosine kinases. Because yeast lacksbona fidetyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ∼30,000 phosphosites mapping to ∼3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species withbona fidetyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.
Climate warming suppresses soil abundant fungal taxa and reduces soil carbon efflux in a semi-arid grassland
Authors: Qiu Yunpeng , Zhang Kangcheng , Zhao Yunfeng , Zhao Yexin , Wang Bianbian , Wang Yi , He Tangqing , Xu Xinyu , Bai Tongshuo , Zhang Yi , Hu Shuijin
Published: October 2023

The abundance, diversity and activity of soil microorganisms critically control the fate of recent plant carbon (C) inputs as well as protecting soil organic C, regulating C-climate feedbacks. However, the effects of climate change drivers such as warming and precipitation change on soil microbial communities and C dynamics remain poorly understood. Utilizing a long-term field warming and precipitation manipulation in a semi-arid grassland on the Loess Plateau and a complementary incubation experiment, here we show that warming and rainfall reduction differentially affect the abundance and composition of bacteria and fungi, and soil C efflux. Warming significantly reduced the abundance of fungi but not bacteria, increasing the relative dominance of bacteria in the soil microbial community. In particular, warming shifted the community composition of abundant fungi in favor of oligotrophicCapnodialesandHypocrealesover potential saprotrophArchaeorhizomycetales. In contrast, precipitation reduction increased soil microbial biomass, but did not significantly affect either the abundance or diversity of bacteria. Furthermore, soil abundant, not rare, fungal community composition was significantly correlated with soil CO2efflux. Our findings suggest that alterations in the fungal community composition, in response to changes in soil C and moisture, dominate the microbial responses to climate change and thus control soil C dynamics in semi-arid grasslands.

Impact statement

Semi-arid grasslands play a critical role in global carbon (C) cycle and potential feedbacks to climate change. Understanding the responses of soil microorganisms to warming and rainfall change is key to evaluating and predicting semi-arid grassland soil C dynamics under future climate change scenarios. Our study showed that warming induced a shift in the abundant fungal community, favoring oligotrophic fungi (i.e.,CapnodialesandHypocreales) over the potential saprotrophicArchaeorhizomycetales,and reduced C efflux. These findings advance our understanding of soil microbial and C responses to climate change drivers and may help predict and possibly manage soil C sequestration in semi-arid grasslands.
Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart
Authors: Pandi Boomathi , Brenman Stella , Black Alexander , Ng Dominic C. M. , Lau Edward , Lam Maggie P. Y.
Published: October 2023

A computational analysis of mass spectrometry data was performed to uncover alternative splicing derived protein variants across chambers of the human heart. Evidence for 216 non-canonical isoforms was apparent in the atrium and the ventricle, including 52 isoforms not documented on SwissProt and recovered using an RNA sequencing derived database. Among non-canonical isoforms, 29 show signs of regulation based on statistically significant preferences in tissue usage, including a ventricular enriched protein isoform of tensin-1 (TNS1) and an atrium-enriched PDZ and LIM Domain 3 (PDLIM3) isoform 2 (PDLIM3-2/ALP-H). Examined variant regions that differ between alternative and canonical isoforms are highly enriched in intrinsically disordered regions, and over two-thirds of such regions are predicted to function in protein binding and/or RNA binding. The analysis here lends further credence to the notion that alternative splicing diversifies the proteome by rewiring intrinsically disordered regions, which are increasingly recognized to play important roles in the generation of biological function from protein sequences.
DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model
Authors: Xie Junjie , Chen Sheng , Lei Jinping , Yang Yuedong
Published: October 2023

In molecular optimization, one popular way is R-groups decoration on molecular scaffolds, and many efforts have been put to generate R-groups based on deep generative models. However, these methods mostly use information of known binding ligands, without fully utilizing target structure information. In this study, we proposed a new method, DiffDec, to involve three-dimensional pocket constraints by a modified diffusion technique for optimizing molecules through molecular scaffold decoration. For an end-to-end generation of R-groups with different sizes, we designed a novel fake atom mechanism. DiffDec was shown able to generate structure-aware R-groups, and simultaneously generate multiple R-groups for one scaffold on different growth anchors. The growth anchors could be provided by users or automatically determined by our model. DiffDec achieved R-group recovery rates of 69.67% and 45.34% in the single and multiple R-group decoration tasks, respectively, and these values were significantly higher than competing methods (37.33% and 26.85%). According to the molecular docking study, our decorated molecules obtained better average binding affinity than baseline methods. The docking pose analysis revealed that DiffDec could decorate scaffolds with R-groups that exhibited improved binding affinities and more favourable interactions with the pocket. These results demonstrated the potential and applicability of DiffDec in real-world scaffold decoration for molecular optimization.
Learning performance and GABAergic pathway link to deformed wing virus in the mushroom bodies of naturally infected honey bees
Authors: Szymański Szymon , Baracchi David , Dingle Lauren , Bowman Alan S. , Manfredini Fabio
Published: October 2023

Viral infections can be detrimental to the foraging ability of the Western honey beeApis mellifera. These include the deformed wing virus (DWV), which is the most common honey bee virus and has been proposed as a possible cause of learning and memory impairment. However, evidence for this phenomenon so far has come from artificially infected bees, while less is known about the implications of natural infections with the virus. Using the proboscis extension reflex (PER), we uncovered no significant association between a simple associative learning task and natural DWV loads. However, when assessed through a reversal associative learning assay, bees with higher DWV loads performed better in the reversal learning phase.

DWV is able to replicate in the honey bee mushroom bodies, where the GABAergic signalling pathway has an antagonistic effect on associative learning but is crucial for reversal learning. Hence, we assessed the pattern of expression of several GABA-related genes in bees with different learning responses. Intriguingly, mushroom body expression of selected genes was positively correlated with DWV load, but only for bees with good reversal learning performance. We hypothesize that DWV might improve olfactory learning performance by enhancing the GABAergic inhibition of responses to unrewarded stimuli, which is consistent with the behavioural patterns that we observed.

Our results suggest that previously reported DWV-driven learning deficits might be exclusive to acute, artificial infections and do not occur in naturally infected bees, stressing the importance of investigating more ecologically relevant scenarios when assessing host-parasite systems.

Summary statement

This study describes a virus-associated increase in learning in honey bees and proposes a mechanism based on GABA to explain the interplay between infection and cognition in the insect brain.
Protein design for evaluating vaccines against future viral variation
Authors: Youssef Noor , Gurev Sarah , Ghantous Fadi , Brock Kelly P. , Jaimes Javier A. , Thadani Nicole N. , Dauphin Ann , Sherman Amy C. , Yurkovetskiy Leonid , Soto Daria , Estanboulieh Ralph , Kotzen Ben , Notin Pascal , Kollasch Aaron W. , Cohen Alexander A. , Dross Sandra E. , Erasmus Jesse , Fuller Deborah H. , Bjorkman Pamela J. , Lemieux Jacob E. , Luban Jeremy , Seaman Michael S. , Marks Debora
Published: October 2023

Recurrent waves of SARS-CoV-2 infection, driven by the periodic emergence of new viral variants, highlight the need for vaccines and therapeutics that remain effective against future strains. Yet, our ability to proactively evaluate such therapeutics is limited to assessing their effectiveness against previous or circulating variants, which may differ significantly in their antibody escape from future viral evolution. To address this challenge, we develop a deep learning method to predict the effect of mutations on fitness and escape from neutralizing antibodies. We use this model to engineer 83 unique SARS-CoV-2 Spike proteins incorporating novel combinations of up to 46 amino acid changes relative to the ancestral B.1 variant. The designed constructs were infectious and evaded neutralization by nine well-characterized panels of human polyclonal anti-SARS-CoV-2 immune sera (from vaccinated, boosted, bivalent boosted, and breakthrough infection individuals). Designed constructs on contemporary SARS-CoV-2 strains displayed similar levels of antibody escape and similar antigenic profiles as variants seen subsequently (up to 12 months later) during the COVID-19 pandemic despite differences in exact mutations. Our approach provides targeted panels of antigenically diverse escape variants for an early evaluation of the protective ability of vaccines and therapeutics to inhibit not only currently circulating but also future variants. This approach is generalizable to other viral pathogens.
Using a modular massively parallel reporter assay to discover context-specific regulatory grammars in type 2 diabetes
Authors: Tovar Adelaide , Kyono Yasuhiro , Nishino Kirsten , Bose Maya , Varshney Arushi , Parker Stephen C.J. , Kitzman Jacob O.
Published: October 2023

Recent genome-wide association studies have established that most complex disease-associated loci are found in noncoding regions where defining their function is nontrivial. In this study, we leverage a modular massively parallel reporter assay (MPRA) to uncover sequence features linked to context-specific regulatory activity. We screened enhancer activity across a panel of 198-bp fragments spanning over 10k type 2 diabetes- and metabolic trait-associated variants in the 832/13 rat insulinoma cell line, a relevant model of pancreatic beta cells. We explored these fragments’ context sensitivity by comparing their activities when placed up-or downstream of a reporter gene, and in combination with either a synthetic housekeeping promoter (SCP1) or a more biologically relevant promoter corresponding to the human insulin gene (INS). We identified clear effects of MPRA construct design on measured fragment enhancer activity. Specifically, a subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preference. A separate set of fragments exhibited promoter bias (n = 698/11,656), mostly towards the cell-specificINSpromoter (73.4%). To identify sequence features associated with promoter preference, we used Lasso regression with 562 genomic annotations and discovered that fragments withINSpromoter-biased activity are enriched for HNF1 motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common T2D-associated regulatory variants. We designed a follow-up MPRA containing HNF1 motif-enriched fragments and observed several instances where deletion or mutation of HNF1 motifs disrupted theINSpromoter-biased enhancer activity, specifically in the beta cell model but not in a skeletal muscle cell line, another diabetes-relevant cell type. Together, our study suggests that cell-specific regulatory activity is partially influenced by enhancer-promoter compatibility and indicates that careful attention should be paid when designing MPRA libraries to capture context-specific regulatory processes at disease-associated genetic signals.
PSEN1M146Vand PSEN1A246Emutations associated with Alzheimer’s disease impair proper microglia differentiation
Authors: Aubert Antoine , Mendoza-Ferri Maria Grazia , Bramoulle Aude , Stüder François , Colombo Bruno Maria , Mendoza-Parra Marco Antonio
Published: October 2023

Genetic variants associated with the late onset of Alzheimer’s disease (AD), were correlated with genes known to be expressed in microglia, suggesting for an AD-genetic component directly influencing microglia behavior. Instead, the role of the familial AD (fAD) genetic mutations was systematically studied from the angle of the Amyloid-Beta pathway; leaving their participation in microglia homeostasis unexplored.

Here we demonstrate that two previously described fAD-related PSEN1 mutations directly impair proper microglia differentiation. While human induced pluripotent stem cells harboring the PSEN1-M146V mutation did not give rise to hematopoietic precursor (HPC) intermediate during microglia differentiation, a PSEN1-A246E mutant line managed to produce HPCs, but died within the first days of microglia differentiation.

Detailed transcriptomics/epigenomics and functional assays revealed the setup of a pro-apoptotic program in the PSEN1-A246E mutant, which was circumvented when HPCs were grafted in brain organoids (BORGs). Microglia obtained in BORGs presented preferentially pro-inflammatory signatures, further supported by their correlation with recent data providing a detailed stratification of the various microglia populations within AD-patient samples.

Overall, this study contributes to reconsider the influence of the previously identified familial mutations in the homeostasis of this immune component of the central nervous system.
PRIME-BSPre: A genome-wide protein-RNA binding sites prediction method based on templates
Authors: Wei Xinhang , Duan Yingtian , Li Danyang , Liu Xudong , Xie Juan , Liu Shiyong
Published: October 2023

Identification of RNA binding sites that potentially interact with RNA-binding proteins facilitates a comprehensive analysis of protein-RNA interactions and enables further investigation into the mechanisms underlying RNA splicing and modification. However, the current experimental data remains limited in comparison to the vast family of RBPs, and deep learning prediction methods are inadequate for those RBPs lacking sufficient interaction data for training. Therefore, we present PRIME-BSPre, a genome-wide method for predicting protein-RNA binding sites based on templates that incorporate both RNA sequence and secondary structure as well as the tertiary structure of corresponding RBPs. We have successfully benchmarked our method on the human genome, demonstrating excellent prediction performance on RBP datasets beyond our library and robustness across cell lines. Additionally, we are pioneers in introducing the low Shannon entropy algorithm to describe binding preferences of RNA motifs. Our predicted results further support the hypothesis that RBPs preferentially bind RNA motifs with low complexity.
TAF7L REGULATES EARLY STAGES OF MALE GERM CELL DEVELOPMENT
Authors: Moreno-Irusta Ayelen , Dominguez Esteban M. , Iqbal Khursheed , Zhang Xiaoyu , Wang Ning , Soares Michael J.
Published: October 2023

Male germ cell development is dependent on the orchestrated regulation of gene networks. TATA-box binding protein associated factors (TAFs) facilitate interactions of TATA-binding protein with the TATA element, which is known to coordinate gene transcription during organogenesis. TAF7 like (Taf7l) is situated on the X chromosome and has been implicated in testis development. We examined the biology of TAF7L in testis development using the rat.Taf7lwas prominently expressed in preleptotene to leptotene spermatocytes. To study the impact of TAF7L on the testis we generated a globalloss-of-functionrat model using CRISPR/Cas9genome editing. Exon 3 of theTaf7lgene was targeted. A founder was generated possessing a 110 bp deletion within theTaf7l locus, which resulted in a frameshift and the premature appearance of a stop codon. The mutation was effectively transmitted through the germline. Deficits in TAF7L did not adversely affect pregnancy or postnatal survival. However, theTaf7ldisruption resulted in male infertility due to compromised testis development and failed sperm production. Mutant germ cells suffer meiotic arrest at the zygotene stage, with defects in sex body formation and meiotic sex chromosome inactivation. This testis phenotype was more pronounced than previously described for the subfertileTaf7lnull mouse. We conclude that TAF7L is essential for male germ cell development in the rat.
Preponderance of generalized chain functions in reconstructed Boolean models of biological networks
Authors: Mitra Suchetana , Sil Priyotosh , Subbaroyan Ajay , Martin Olivier C. , Samal Areejit
Published: October 2023

Boolean networks (BNs) have been extensively used to model the dynamics of gene regulatory networks (GRNs) that underlie cellular decisions. The dynamics of BNs depend on the network architecture andregulatory logic rules(orBoolean functions(BFs)) associated with nodes, both of which have been shown to be far from random in large-scale studies of reconstructed Boolean models. At the level of the BFs, nested canalyzing functions (NCFs) have been shown to be strongly enriched in such GRN models. The central question we address here is whether that enrichment is due to certain sub-types of NCFs. To answer this, we build on one sub-type of NCFs, thechain functions(orchain-0 functions) proposed by Gat-Viks and Shamir. First, we propose 2 other sub-types of NCFs, namely, the class ofchain-1 functionswhich is the dual of the class of chain-0 functions, andgeneralized chain functions, the union of the chain-0 and chain-1 types. Next, we find that the fraction of NCFs that are chain-0 functions decays exponentially with the number of inputs, and exhibits a fractal-like behaviour as a function of the bias for a fixed number of inputs. Moreover, we explain several of these observations analytically. Then, by analyzing 5990 BFs extracted from a large dataset of reconstructed Boolean models, and 2 other datasets, we find that generalized chain functions are significantly enriched within the NCFs. Lastly, we illustrate the severe restriction imposed by generalized chain functions compared to NCFs for 3 biological models and perform model selection on them using known relative stability constraints.
Diverse stimuli induce piloerection and yield varied autonomic responses in humans
Authors: McPhetres Jonathon
Published: October 2023

This research provides an in-depth exploration into the triggers and corresponding autonomic responses of piloerection, a phenomenon prevalent across various species. In non-human species, piloerection occurs in reaction to a variety of environmental changes, including social interactions and temperature shifts. However, its understanding in humans has been confined to emotional contexts. This is problematic because it reflects solely upon subjective experience rather than an objective response to the environment, and because, given our shared evolutionary paths, piloerection should function similarly in humans and other animals. We observed 1,198 piloerection episodes from eight participants while simultaneously recording multiple autonomic and body temperature indices, finding that piloerection in humans can indeed be elicited by thermal, tactile, and audio-visual stimuli. The data also revealed variations in cardiac reactivity measures: audio-visual piloerection was associated with greater sympathetic arousal, while tactile piloerection was linked to greater parasympathetic arousal. Despite prevailing notions of piloerection as a vestigial response in humans, it does respond to decreases in skin temperature and induces a rise in skin temperature during episodes. This research underscores that piloerection in humans is not solely an affective response to emotional stimuli. Rather, it is best understood as a reflexive response to environmental changes, suggesting a shared functional similarity with other species.
Motion Blur Microscopy
Authors: Goreke Utku , Gonzales Ayesha , Shipley Brandon , Tincher Madeleine , Sharma Oshin , Wulftange William , Man Yuncheng , An Ran , Hinczewski Michael , Gurkan Umut A.
Published: October 2023

Imaging and characterizing the dynamics of cellular adhesion in blood samples is of fundamental importance in understanding biological function.In vitromicroscopy methods are widely used for this task, but typically require diluting the blood with a buffer to allow for transmission of light. However whole blood provides crucial mechanical and chemical signaling cues that influence adhesion dynamics, which means that conventional approaches lack the full physiological complexity of living microvasculature. We propose to overcome this challenge by a newin vitroimaging method which we call motion blur microscopy (MBM). By decreasing the source light intensity and increasing the integration time during imaging, flowing cells are blurred, allowing us to identify adhered cells. Combined with an automated analysis using machine learning, we can for the first time reliably image cell interactions in microfluidic channels during whole blood flow. MBM provides a low cost, easy to implement alternative to intravital microscopy, thein vivoapproach for studying how the whole blood environment shapes adhesion dynamics. We demonstrate the method’s reproducibility and accuracy in two example systems where understanding cell interactions, adhesion, and motility is crucial—sickle red blood cells adhering to laminin, and CAR-T cells adhering to E-selectin. We illustrate the wide range of data types that can be extracted from this approach, including distributions of cell size and eccentricity, adhesion durations, trajectories and velocities of adhered cells moving on a functionalized surface, as well as correlations among these different features at the single cell level. In all cases MBM allows for rapid collection and processing of large data sets, ranging from thousands to hundreds of thousands of individual adhesion events. The method is generalizable to study adhesion mechanisms in a variety of diseases, including cancer, blood disorders, thrombosis, inflammatory and autoimmune diseases, as well as providing rich datasets for theoretical modeling of adhesion dynamics.
Modeling dry eye with an air-liquid interface in corneal epithelium-on-a-chip
Authors: Abdalkader Rodi Kado , Chaleckis Romanas , Fujita Takuya , Kamei Ken-ichiro
Published: October 2023

Dry eye syndrome (DES) is a complex ocular condition characterized by an unstable tear film and inadequate tear production, leading to tissue damage. Despite its common occurrence, there is currently no comprehensivein vitromodel that accurately reproduce the cellular characteristics of DES. Here we modified a corneal epithelium-on-a-chip (CEpOC) model to recapitulate DES by subjecting HCE-T human corneal epithelial cells to an air-liquid (AL) interface stimulus. We then assessed the effects of AL stimulation both in the presence and absence of diclofenac (DCF). Transcriptomic analysis revealed distinct gene expression changes in response to AL and AL_DCF, affecting pathways related to development, epithelial structure, inflammation, and extracellular matrix remodeling. Both treatments upregulatedPIEZO2, linked to corneal damage signaling, while downregulatingOCLN, involved in cell-cell junctions. They increased the expression of inflammatory genes (e.g.,IL6) and reduced mucin production genes (e.g.,MUC16), reflecting dry eye characteristics.TGFB1, crucial for corneal wound healing, was slightly downregulated in AL_DCF, potentially affecting wound healing processes rather than reducing inflammation by DCF. Metabolomic analysis showed increased secretion of metabolites associated with cell damage and inflammation (e.g., methyl-2-oxovaleric acid, 3-methyl-2-oxobutanoic acid, lauroyl-carnitine) in response to AL and even more with AL_DCF, indicating a shift in cellular metabolism. This study showcases the utilization of AL stimulus within the CEpOC as a comprehensive approach to faithfully reproduce the cellular characteristics of DES.