Pub Date : 2024-08-09DOI: 10.1101/2024.08.07.607109
Jihyun Yu, Seongryong Kim, Hyun-Sup Song, Hye-Young Kim, You-Me Kim
Eosinophils are major effector cells in type 2 immune responses, contributing to host defense and allergic diseases. They also play critical roles in maintaining tissue homeostasis by regulating various immune cell types. However, evidence of the crosstalk between eosinophils and neutrophils is limited. Here, we show that eosinophils directly associate with neutrophils in the lungs of asthma-induced mice. Eosinophil-specific deficiency of the short-chain fatty acid receptor GPR43 results in hyperactivation of eosinophils and increases the expression of neutrophil chemoattractants and PECAM-1, thus enhancing the interaction between eosinophils and neutrophils. This binding event exposes the neutrophils to eosinophil-derived IL-4 and GM-CSF, which induces the conversion of conventional neutrophils into more pathogenic Siglec-Fhi neutrophils that strongly enhance Th17 cell differentiation and aggravate asthma symptoms. These results reveal GPR43 as a critical regulator of eosinophils and highlight that eosinophils have a hitherto little-known ability to directly modulate neutrophil differentiation and function. One Sentence Summary Eosinophils directly recruit neutrophils and induce their differentiation into a pathogenic Siglec-Fhi subset in allergic airway inflammation.
{"title":"GPR43 in eosinophils prevents the emergence of pathogenic Siglec-Fhi neutrophils in allergic airway inflammation","authors":"Jihyun Yu, Seongryong Kim, Hyun-Sup Song, Hye-Young Kim, You-Me Kim","doi":"10.1101/2024.08.07.607109","DOIUrl":"https://doi.org/10.1101/2024.08.07.607109","url":null,"abstract":"Eosinophils are major effector cells in type 2 immune responses, contributing to host defense and allergic diseases. They also play critical roles in maintaining tissue homeostasis by regulating various immune cell types. However, evidence of the crosstalk between eosinophils and neutrophils is limited. Here, we show that eosinophils directly associate with neutrophils in the lungs of asthma-induced mice. Eosinophil-specific deficiency of the short-chain fatty acid receptor GPR43 results in hyperactivation of eosinophils and increases the expression of neutrophil chemoattractants and PECAM-1, thus enhancing the interaction between eosinophils and neutrophils. This binding event exposes the neutrophils to eosinophil-derived IL-4 and GM-CSF, which induces the conversion of conventional neutrophils into more pathogenic Siglec-Fhi neutrophils that strongly enhance Th17 cell differentiation and aggravate asthma symptoms. These results reveal GPR43 as a critical regulator of eosinophils and highlight that eosinophils have a hitherto little-known ability to directly modulate neutrophil differentiation and function. One Sentence Summary Eosinophils directly recruit neutrophils and induce their differentiation into a pathogenic Siglec-Fhi subset in allergic airway inflammation.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-09DOI: 10.1101/2024.08.08.607208
Andrew L. Soborowski, Rylee K Hackley, Sungmin Hwang, Guangyin Zhou, Keely A. Dulmage, Peter Schönheit, Charles Daniels, Alexandre W. Bisson-Filho, Anita Marchfelder, J. Maupin-Furlow, Thorsten Allers, Amy K. Schmid
Because archaea are the evolutionary ancestors of eukaryotes, archaeal molecular biology has been a topic of intense recent research. The hypersaline adapted archaeal species Halobacterium salinarum and Haloferax volcanii serve as important model organisms because facile tools enable genetic manipulation. As a result, the number of strains in circulation among the haloarchaeal research community has increased over the last few decades. However, the degree of genetic divergence and effects on genetic integrity during inter-lab transfers remain unclear. To address this question, we performed whole genome re-sequencing on a cross-section of wild-type, parental, and knockout strains in both model species. Integrating these data with existing repositories of re-sequencing data, we identify mutations that have arisen in a collection of 60 strains, sampled from 2 species across 8 different labs. Independent of sequencing, we construct strain lineages, identifying branch points and significant genetic effects in strain history. Combining this with our sequencing data, we identify small clusters of mutations that definitively separate lab strains. Additionally, an analysis of gene knockout strains suggests that roughly 1 in 3 strains currently in use harbors second-site mutations of potential phenotypic impact. Overall, we find that divergence among lab strains is thus far minimal, though as the archaeal research community continues to grow, careful strain provenance and genomic re-sequencing are required to keep inter-lab divergence to a minimum, prevent the compounding of mutations into fully independent lineages, and maintain the current high degree of reproducible research between lab groups in the haloarchaeal research community. Data Summary Novel sequencing data for this project was submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and can be found under bioproject accession PRJNA1120443. SRA accessions for previously published sequencing data are available in supplementary table 1. R code for performing analysis and generating figures is available at https://github.com/andrew-soborowski/halophile_genome_resequencing. Impact Statement Archaea are important due to their shared evolutionary history with eukaryotes. As the archaeal research community grows, keeping track of the genetic integrity of archaeal strains of interest is necessary. In particular, routine genetic manipulations and the common practice of sharing strains between labs allow mutations to arise in lab stocks. If these mutations affect cellular processes, they may jeopardize the reproducibility of work between research groups and confound the results of future studies. In this work, we examine DNA sequences from 60 strains across two species of archaea. We identify shared and unique mutations occurring between and within strains. Independently, we trace the lineage of each strain, identifying which genetic manipulations lead to observe
{"title":"Genomic re-sequencing reveals mutational divergence across genetically engineered strains of model archaea","authors":"Andrew L. Soborowski, Rylee K Hackley, Sungmin Hwang, Guangyin Zhou, Keely A. Dulmage, Peter Schönheit, Charles Daniels, Alexandre W. Bisson-Filho, Anita Marchfelder, J. Maupin-Furlow, Thorsten Allers, Amy K. Schmid","doi":"10.1101/2024.08.08.607208","DOIUrl":"https://doi.org/10.1101/2024.08.08.607208","url":null,"abstract":"Because archaea are the evolutionary ancestors of eukaryotes, archaeal molecular biology has been a topic of intense recent research. The hypersaline adapted archaeal species Halobacterium salinarum and Haloferax volcanii serve as important model organisms because facile tools enable genetic manipulation. As a result, the number of strains in circulation among the haloarchaeal research community has increased over the last few decades. However, the degree of genetic divergence and effects on genetic integrity during inter-lab transfers remain unclear. To address this question, we performed whole genome re-sequencing on a cross-section of wild-type, parental, and knockout strains in both model species. Integrating these data with existing repositories of re-sequencing data, we identify mutations that have arisen in a collection of 60 strains, sampled from 2 species across 8 different labs. Independent of sequencing, we construct strain lineages, identifying branch points and significant genetic effects in strain history. Combining this with our sequencing data, we identify small clusters of mutations that definitively separate lab strains. Additionally, an analysis of gene knockout strains suggests that roughly 1 in 3 strains currently in use harbors second-site mutations of potential phenotypic impact. Overall, we find that divergence among lab strains is thus far minimal, though as the archaeal research community continues to grow, careful strain provenance and genomic re-sequencing are required to keep inter-lab divergence to a minimum, prevent the compounding of mutations into fully independent lineages, and maintain the current high degree of reproducible research between lab groups in the haloarchaeal research community. Data Summary Novel sequencing data for this project was submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and can be found under bioproject accession PRJNA1120443. SRA accessions for previously published sequencing data are available in supplementary table 1. R code for performing analysis and generating figures is available at https://github.com/andrew-soborowski/halophile_genome_resequencing. Impact Statement Archaea are important due to their shared evolutionary history with eukaryotes. As the archaeal research community grows, keeping track of the genetic integrity of archaeal strains of interest is necessary. In particular, routine genetic manipulations and the common practice of sharing strains between labs allow mutations to arise in lab stocks. If these mutations affect cellular processes, they may jeopardize the reproducibility of work between research groups and confound the results of future studies. In this work, we examine DNA sequences from 60 strains across two species of archaea. We identify shared and unique mutations occurring between and within strains. Independently, we trace the lineage of each strain, identifying which genetic manipulations lead to observe","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.606859
M. Alemu, Shiran Ben‐Zeev, V. Barak, Y. Tutus, Ismail Cakmak, Y. Saranga
Climate change is becoming a global concern, threating agriculture’s capacity to meet the food and nutritional requirements of the growing population. Underutilized crops present an opportunity to address resilience to climate change and nutritional deficiencies. Tef is a stress-resilient cereal crop, producing gluten-free grain of high nutritional quality. However, knowledge is lacking on tef’s diversity of grain nutritional properties, their interaction with environmental conditions (e.g., water availability) and the underlying genomic loci. We assessed the effect of water availability on tef grain nutrient concentrations and identify the associated genomic loci. A collection of 223 tef genotypes, a subset of tef diversity panel 300, were grown in the field under well-watered and water-limited conditions in 2021, and phenotyped for grain protein and mineral concentrations and seed color. A genome-wide association study was conducted using 28,837 single-nucleotide polymorphisms (SNPs) and phenotypic data to identify marker–trait associations (MTAs). Tef grain nutrient concentrations exhibited wide genetic diversity with a significant influence of environment. Protein and most micronutrients were more concentrated under water-limited conditions, whereas most macronutrients were higher in the well-watered environment. A total of 59 SNPs were associated with one or more of the studied traits, resulting in 65 MTAs detected under both water treatments, and providing insights into the genetic basis of grain nutrients. Five SNPs reflected multiple associations, with four detecting the same trait under both treatments (multiple-environment effect), and one associated with both Zn and K (pleiotropic effect). In addition, two pairs of closely linked SNPs reflected multiple-environment effects. While multiple-environment associations provide greater support for the integrity of these MTAs, the pleiotropic locus hints at a common mechanism controlling two mineral ions. The identified MTAs shed new light on the genomic architecture of tef’s nutritional properties and provide the basis to enhance tef grain nutritional quality alongside drought resilience.
{"title":"Genomic Loci Associated with Grain Protein and Mineral Nutrients concentrations in Eragrostis tef under Contrasting Water Regimes","authors":"M. Alemu, Shiran Ben‐Zeev, V. Barak, Y. Tutus, Ismail Cakmak, Y. Saranga","doi":"10.1101/2024.08.06.606859","DOIUrl":"https://doi.org/10.1101/2024.08.06.606859","url":null,"abstract":"Climate change is becoming a global concern, threating agriculture’s capacity to meet the food and nutritional requirements of the growing population. Underutilized crops present an opportunity to address resilience to climate change and nutritional deficiencies. Tef is a stress-resilient cereal crop, producing gluten-free grain of high nutritional quality. However, knowledge is lacking on tef’s diversity of grain nutritional properties, their interaction with environmental conditions (e.g., water availability) and the underlying genomic loci. We assessed the effect of water availability on tef grain nutrient concentrations and identify the associated genomic loci. A collection of 223 tef genotypes, a subset of tef diversity panel 300, were grown in the field under well-watered and water-limited conditions in 2021, and phenotyped for grain protein and mineral concentrations and seed color. A genome-wide association study was conducted using 28,837 single-nucleotide polymorphisms (SNPs) and phenotypic data to identify marker–trait associations (MTAs). Tef grain nutrient concentrations exhibited wide genetic diversity with a significant influence of environment. Protein and most micronutrients were more concentrated under water-limited conditions, whereas most macronutrients were higher in the well-watered environment. A total of 59 SNPs were associated with one or more of the studied traits, resulting in 65 MTAs detected under both water treatments, and providing insights into the genetic basis of grain nutrients. Five SNPs reflected multiple associations, with four detecting the same trait under both treatments (multiple-environment effect), and one associated with both Zn and K (pleiotropic effect). In addition, two pairs of closely linked SNPs reflected multiple-environment effects. While multiple-environment associations provide greater support for the integrity of these MTAs, the pleiotropic locus hints at a common mechanism controlling two mineral ions. The identified MTAs shed new light on the genomic architecture of tef’s nutritional properties and provide the basis to enhance tef grain nutritional quality alongside drought resilience.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141925478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.07.607101
M. Z. Chen, D. Yuen, Victoria M. McLeod, Ken W. Yong, Cameron H Smyth, Bruna Rossi Herling, Thomas Payne, Stewart A. Fabb, M. Belousoff, Azizah Algarni, Patrick M. Sexton, C. J. Porter, Colin W. Pouton, A. Johnston
Efficient and precise delivery of mRNA is critical to advance mRNA therapies beyond their current use as vaccines. Lipid nanoparticles (LNP) efficiently encapsulate and protect mRNA, but non-specific cellular uptake may lead to off-target delivery and minimal delivery to target cells. Functionalizing LNPs with antibodies enables targeted mRNA delivery, but traditional modification techniques require complex conjugation and purification, which often reduces antibody affinity. Here, we present a simple method for capturing antibodies in their optimal orientation on LNPs, without antibody modification or complex purification. This strategy uses an optimally oriented anti-Fc nanobody on the LNP surface to capture antibodies, resulting in protein expression levels >1000 times higher than non-targeted LNPs and >8 times higher than conventional antibody functionalization techniques. These precisely targeted LNPs showed highly efficient in vivo targeting to T cells, with minimal delivery to other immune cells. This approach enables the rapid development of targeted LNPs and has the potential to broaden the use of mRNA therapies.
{"title":"A Versatile Antibody Capture System that Drives Precise In Vivo Delivery of mRNA loaded Lipid Nanoparticles and Enhances Gene Expression","authors":"M. Z. Chen, D. Yuen, Victoria M. McLeod, Ken W. Yong, Cameron H Smyth, Bruna Rossi Herling, Thomas Payne, Stewart A. Fabb, M. Belousoff, Azizah Algarni, Patrick M. Sexton, C. J. Porter, Colin W. Pouton, A. Johnston","doi":"10.1101/2024.08.07.607101","DOIUrl":"https://doi.org/10.1101/2024.08.07.607101","url":null,"abstract":"Efficient and precise delivery of mRNA is critical to advance mRNA therapies beyond their current use as vaccines. Lipid nanoparticles (LNP) efficiently encapsulate and protect mRNA, but non-specific cellular uptake may lead to off-target delivery and minimal delivery to target cells. Functionalizing LNPs with antibodies enables targeted mRNA delivery, but traditional modification techniques require complex conjugation and purification, which often reduces antibody affinity. Here, we present a simple method for capturing antibodies in their optimal orientation on LNPs, without antibody modification or complex purification. This strategy uses an optimally oriented anti-Fc nanobody on the LNP surface to capture antibodies, resulting in protein expression levels >1000 times higher than non-targeted LNPs and >8 times higher than conventional antibody functionalization techniques. These precisely targeted LNPs showed highly efficient in vivo targeting to T cells, with minimal delivery to other immune cells. This approach enables the rapid development of targeted LNPs and has the potential to broaden the use of mRNA therapies.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.606861
Lucy Fallon, Alisha N Jones
The biological function of many classes of RNAs depend on their structures, which can exist as structural ensembles, rather than a single minimum free energy fold. In the past decade, long noncoding RNAs (lncRNAs) have emerged as functional transcripts in gene regulation that behave through their primary sequences and the structures they adopt. Chemical probing experiments, like selective 2’-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), and dimethyl sulfate-MaP (DMS-MaP), facilitate the characterization of RNA secondary structure both inside and outside the cell. But chemical probing experiments yield an average reactivity profile, representative of all the structures a particular RNA transcript adopts at the time of chemical probing, weighted by their relative populations. Chemical probing experiments often struggle to identify coexisting conformations a lncRNA might sample. Computational methods (DRACO, DREEM, DANCE-MaP) have been developed to identify alternate conformations of RNAs by deconvoluting chemical probing data. In this work, we investigate the propensity for lncRNAs to sample multiple structured states, and find each of the studied lncRNAs possess coexisting folds. We discuss the implications of lncRNAs harboring multiple structures and how it may contribute to their multifunctionality in regulating biological processes.
{"title":"Alternative Conformations of lncRNAs Identified Through Structural Deconvolution of SHAPE- and DMS-MaP Datasets","authors":"Lucy Fallon, Alisha N Jones","doi":"10.1101/2024.08.06.606861","DOIUrl":"https://doi.org/10.1101/2024.08.06.606861","url":null,"abstract":"The biological function of many classes of RNAs depend on their structures, which can exist as structural ensembles, rather than a single minimum free energy fold. In the past decade, long noncoding RNAs (lncRNAs) have emerged as functional transcripts in gene regulation that behave through their primary sequences and the structures they adopt. Chemical probing experiments, like selective 2’-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), and dimethyl sulfate-MaP (DMS-MaP), facilitate the characterization of RNA secondary structure both inside and outside the cell. But chemical probing experiments yield an average reactivity profile, representative of all the structures a particular RNA transcript adopts at the time of chemical probing, weighted by their relative populations. Chemical probing experiments often struggle to identify coexisting conformations a lncRNA might sample. Computational methods (DRACO, DREEM, DANCE-MaP) have been developed to identify alternate conformations of RNAs by deconvoluting chemical probing data. In this work, we investigate the propensity for lncRNAs to sample multiple structured states, and find each of the studied lncRNAs possess coexisting folds. We discuss the implications of lncRNAs harboring multiple structures and how it may contribute to their multifunctionality in regulating biological processes.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.606753
Yijingxiu Lu, Sangseon Lee, Soosung Kang, Sun Kim
In recent years, numerous deep learning models have been developed for drug-target interaction (DTI) prediction. These DTI models specialize in handling data with distinct distributions and features, often yielding inconsistent predictions when applied to unseen data points. This inconsistency poses a challenge for researchers aiming to utilize these models in downstream drug development tasks. Particularly in screening potential active compounds, providing a ranked list of candidates that likely interact with the target protein can guide scientists in prioritizing their experimental efforts. However, achieving this is difficult as each current DTI model can provide a different list based on its learned feature space. To address these issues, we propose EnsDTI, a Mixture-of-Experts architecture designed to enhance the performance of existing DTI models for more reliable drug-target interaction predictions. We integrate an inductive conformal predictor to provide confidence scores for each prediction, enabling EnsDTI to offer a reliable list of candidates for a specific target. Empirical evaluations on four benchmark datasets demonstrate that EnsDTI not only improves DTI prediction performance with an average accuracy improvement of 2.7% compared to the best performing baseline, but also offers a reliable ranked list of candidate drugs with the highest confidence, showcasing its potential for ranking potential active compounds in future applications. CCS CONCEPTS • Applied computing → Bioinformatics; • Computing methodologies → Artificial intelligence.
{"title":"Mixture-of-Experts Approach for Enhanced Drug-Target Interaction Prediction and Confidence Assessment","authors":"Yijingxiu Lu, Sangseon Lee, Soosung Kang, Sun Kim","doi":"10.1101/2024.08.06.606753","DOIUrl":"https://doi.org/10.1101/2024.08.06.606753","url":null,"abstract":"In recent years, numerous deep learning models have been developed for drug-target interaction (DTI) prediction. These DTI models specialize in handling data with distinct distributions and features, often yielding inconsistent predictions when applied to unseen data points. This inconsistency poses a challenge for researchers aiming to utilize these models in downstream drug development tasks. Particularly in screening potential active compounds, providing a ranked list of candidates that likely interact with the target protein can guide scientists in prioritizing their experimental efforts. However, achieving this is difficult as each current DTI model can provide a different list based on its learned feature space. To address these issues, we propose EnsDTI, a Mixture-of-Experts architecture designed to enhance the performance of existing DTI models for more reliable drug-target interaction predictions. We integrate an inductive conformal predictor to provide confidence scores for each prediction, enabling EnsDTI to offer a reliable list of candidates for a specific target. Empirical evaluations on four benchmark datasets demonstrate that EnsDTI not only improves DTI prediction performance with an average accuracy improvement of 2.7% compared to the best performing baseline, but also offers a reliable ranked list of candidate drugs with the highest confidence, showcasing its potential for ranking potential active compounds in future applications. CCS CONCEPTS • Applied computing → Bioinformatics; • Computing methodologies → Artificial intelligence.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.02.606350
Tianjian Qin, Koen J. van Benthem, Luis Valente, R. Etienne
Species diversification is characterized by speciation and extinction, the rates of which can, under some assumptions, be estimated from time-calibrated phylogenies. However, maximum likelihood estimation methods (MLE) for inferring rates are limited to simpler models and can show bias, particularly in small phylogenies. Likelihood-free methods to estimate parameters of diversification models using deep learning have started to emerge, but how robust neural network methods are at handling the intricate nature of phylogenetic data remains an open question. Here we present a new ensemble neural network approach to estimate diversification parameters from phylogenetic trees that leverages different classes of neural networks (dense neural network, graph neural network, and long short-term memory recurrent network) and simultaneously learns from graph representations of phylogenies, their branching times and their summary statistics. Our best-performing ensemble neural network (which corrects graph neural network result using a recurrent neural network) can compute estimates faster than MLE and is less affected by tree size. Our analysis suggests that the primary limitation to accurate parameter estimation is the amount of information contained within a phylogeny, as indicated by its size and the strength of effects shaping it. In cases where MLE is unavailable, our neural network method provides a promising alternative for estimating phylogenetic tree parameters. If there are detectable phylogenetic signals present, our approach delivers results that are comparable to MLE but without inherent biases.
{"title":"Performance and Robustness of Parameter Estimation from Phylogenetic Trees Using Neural Networks","authors":"Tianjian Qin, Koen J. van Benthem, Luis Valente, R. Etienne","doi":"10.1101/2024.08.02.606350","DOIUrl":"https://doi.org/10.1101/2024.08.02.606350","url":null,"abstract":"Species diversification is characterized by speciation and extinction, the rates of which can, under some assumptions, be estimated from time-calibrated phylogenies. However, maximum likelihood estimation methods (MLE) for inferring rates are limited to simpler models and can show bias, particularly in small phylogenies. Likelihood-free methods to estimate parameters of diversification models using deep learning have started to emerge, but how robust neural network methods are at handling the intricate nature of phylogenetic data remains an open question. Here we present a new ensemble neural network approach to estimate diversification parameters from phylogenetic trees that leverages different classes of neural networks (dense neural network, graph neural network, and long short-term memory recurrent network) and simultaneously learns from graph representations of phylogenies, their branching times and their summary statistics. Our best-performing ensemble neural network (which corrects graph neural network result using a recurrent neural network) can compute estimates faster than MLE and is less affected by tree size. Our analysis suggests that the primary limitation to accurate parameter estimation is the amount of information contained within a phylogeny, as indicated by its size and the strength of effects shaping it. In cases where MLE is unavailable, our neural network method provides a promising alternative for estimating phylogenetic tree parameters. If there are detectable phylogenetic signals present, our approach delivers results that are comparable to MLE but without inherent biases.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.606693
Nicholas D. Sun, Allison R. Carr, Erica N. Krogman, Yogesh Chawla, Jun Zhong, Matthew C. Guttormson, Mark Chan, Michelle A. Hsu, Haidong Dong, D. Bogunovic, Akhilesh Pandey, Laura M. Rogers, Adrian T. Ting
Cytotoxic T cells produce interferon gamma (IFNγ), which plays a critical role in anti-microbial and anti-tumor responses. However, it is not clear whether T cell-derived IFNγ directly kills infected and tumor target cells, and how this may be regulated. Here, we report that target cell expression of the kinases TBK1 and IKKε regulate IFNγ cytotoxicity by suppressing the ability of T cell-derived IFNγ to kill target cells. In tumor targets lacking TBK1 and IKKε, IFNγ induces expression of TNFR1 and the Z-nucleic acid sensor, ZBP1, to trigger RIPK1-dependent apoptosis, largely in a target cell-autonomous manner. Unexpectedly, IFNγ, which is not known to signal to NFκB, induces hyperactivation of NFκB in TBK1 and IKKε double-deficient cells. TBK1 and IKKε suppress IKKα/β activity and in their absence, IFNγ induces elevated NFκB-dependent expression of inflammatory chemokines and cytokines. Apoptosis is thought to be non-inflammatory, but our observations demonstrate that IFNγ can induce an inflammatory form of apoptosis, and this is suppressed by TBK1 and IKKε. The two kinases provide a critical connection between innate and adaptive immunological responses by regulating three key responses: (1) phosphorylation of IRF3/7 to induce type I IFN; (2) inhibition of RIPK1-dependent death; and (3) inhibition of NFκB-dependent inflammation. We propose that these kinases evolved these functions such that their inhibition by pathogens attempting to block type I IFN expression would enable IFNγ to trigger apoptosis accompanied by an alternative inflammatory response. Our findings show that loss of TBK1 and IKKε in target cells sensitizes them to inflammatory apoptosis induced by T cell-derived IFNγ. Short Summary In the absence of TBK1 and IKKε, target cells are killed by T cells in an IFNγ-dependent manner. In TBK1 and IKKε-deficient cells, IFNγ induces RIPK1-dependent death, as well as hyper-induction of NFκB-dependent inflammatory genes. This suggests that any inhibition of TBK1/IKKε to block type I IFN expression will result in the demise of the cell accompanied by an alternate inflammatory program. Graphical Abstract
{"title":"TBK1 and IKKε protect target cells from IFNγ-mediated T cell killing via an inflammatory apoptotic mechanism","authors":"Nicholas D. Sun, Allison R. Carr, Erica N. Krogman, Yogesh Chawla, Jun Zhong, Matthew C. Guttormson, Mark Chan, Michelle A. Hsu, Haidong Dong, D. Bogunovic, Akhilesh Pandey, Laura M. Rogers, Adrian T. Ting","doi":"10.1101/2024.08.06.606693","DOIUrl":"https://doi.org/10.1101/2024.08.06.606693","url":null,"abstract":"Cytotoxic T cells produce interferon gamma (IFNγ), which plays a critical role in anti-microbial and anti-tumor responses. However, it is not clear whether T cell-derived IFNγ directly kills infected and tumor target cells, and how this may be regulated. Here, we report that target cell expression of the kinases TBK1 and IKKε regulate IFNγ cytotoxicity by suppressing the ability of T cell-derived IFNγ to kill target cells. In tumor targets lacking TBK1 and IKKε, IFNγ induces expression of TNFR1 and the Z-nucleic acid sensor, ZBP1, to trigger RIPK1-dependent apoptosis, largely in a target cell-autonomous manner. Unexpectedly, IFNγ, which is not known to signal to NFκB, induces hyperactivation of NFκB in TBK1 and IKKε double-deficient cells. TBK1 and IKKε suppress IKKα/β activity and in their absence, IFNγ induces elevated NFκB-dependent expression of inflammatory chemokines and cytokines. Apoptosis is thought to be non-inflammatory, but our observations demonstrate that IFNγ can induce an inflammatory form of apoptosis, and this is suppressed by TBK1 and IKKε. The two kinases provide a critical connection between innate and adaptive immunological responses by regulating three key responses: (1) phosphorylation of IRF3/7 to induce type I IFN; (2) inhibition of RIPK1-dependent death; and (3) inhibition of NFκB-dependent inflammation. We propose that these kinases evolved these functions such that their inhibition by pathogens attempting to block type I IFN expression would enable IFNγ to trigger apoptosis accompanied by an alternative inflammatory response. Our findings show that loss of TBK1 and IKKε in target cells sensitizes them to inflammatory apoptosis induced by T cell-derived IFNγ. Short Summary In the absence of TBK1 and IKKε, target cells are killed by T cells in an IFNγ-dependent manner. In TBK1 and IKKε-deficient cells, IFNγ induces RIPK1-dependent death, as well as hyper-induction of NFκB-dependent inflammatory genes. This suggests that any inhibition of TBK1/IKKε to block type I IFN expression will result in the demise of the cell accompanied by an alternate inflammatory program. Graphical Abstract","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.605779
Mitsuo Shintani, H. Bono
Environmental stresses, such as drought and salt, adversely affect plant growth and crop productivity. While many studies have focused on established components of stress signaling pathways, research on unknown elements remains limited. In this study, we collected RNA sequencing (RNA-Seq) data from Oryza sativa subsp. indica and Oryza sativa subsp. japonica registered in public databases and conducted a meta-analysis integrating multiple studies. Focusing on two types of stress conditions (salt and drought), we aimed to identify novel stress-responsive genes in Oryza sativa by comparing RNA-Seq data from stress-resistant and stress-susceptible cultivars. We analyzed 105 paired datasets with different phenotypes under drought and salt stress conditions to identify genes with common expression changes across multiple studies. A meta-analysis identified 10 genes specifically upregulated in resistant cultivars and 12 specifically upregulated in susceptible cultivars under both drought and salt stress conditions. Furthermore, by comparing previously identified stress-responsive genes in Arabidopsis thaliana, we explored genes potentially involved in stress response mechanisms that are conserved across plant species. The genes identified in this data-driven study that potentially determine plant stress resistance or susceptibility phenotypes may serve as research targets for elucidating novel plant stress mechanisms and candidates for genome editing.
{"title":"Meta-analysis of public RNA-sequencing data of drought and salt stresses in different phenotypes of Oryza sativa","authors":"Mitsuo Shintani, H. Bono","doi":"10.1101/2024.08.06.605779","DOIUrl":"https://doi.org/10.1101/2024.08.06.605779","url":null,"abstract":"Environmental stresses, such as drought and salt, adversely affect plant growth and crop productivity. While many studies have focused on established components of stress signaling pathways, research on unknown elements remains limited. In this study, we collected RNA sequencing (RNA-Seq) data from Oryza sativa subsp. indica and Oryza sativa subsp. japonica registered in public databases and conducted a meta-analysis integrating multiple studies. Focusing on two types of stress conditions (salt and drought), we aimed to identify novel stress-responsive genes in Oryza sativa by comparing RNA-Seq data from stress-resistant and stress-susceptible cultivars. We analyzed 105 paired datasets with different phenotypes under drought and salt stress conditions to identify genes with common expression changes across multiple studies. A meta-analysis identified 10 genes specifically upregulated in resistant cultivars and 12 specifically upregulated in susceptible cultivars under both drought and salt stress conditions. Furthermore, by comparing previously identified stress-responsive genes in Arabidopsis thaliana, we explored genes potentially involved in stress response mechanisms that are conserved across plant species. The genes identified in this data-driven study that potentially determine plant stress resistance or susceptibility phenotypes may serve as research targets for elucidating novel plant stress mechanisms and candidates for genome editing.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141925756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1101/2024.08.06.606776
Mohammad Athar, Ratulananda Bhadury, Chayanika Gogoi, Pooja Mishra, Prity Kumari, Manisha Yadav, J. Maras, Devram S. Ghorpade
The recurrent pathological inflammation of the gut is a major concern in diabetic patients. With the failure of anti-inflammatory or diabetic drugs to limit relapse of colon inflammation demands the unearthing of mechanistic details underlying higher incidences of colitis in diabetic patients. Here we report the enrichment of DPP4 in the livers and blood samples of diabetic humans and mice models of diabesity that is in parallel to the development of colitis. Overexpression of DPP4 exacerbates or hepatic silencing of DPP4 impairs experimental colitis induced by DSS and STM. Mechanistically, we identified liver DPP4 attenuates gut-autophagic response to trigger enteric cell apoptosis, reduced mucin secretion, and compromised gut barrier leading to high infiltration of immune cells secreting inflammatory cytokines establishing pathological gut inflammation. Thus, liver-DPP4-mediated gut autophagy inhibition is a key pathway in diabesitic colitis.
{"title":"Diabetic liver-enriched secretory dipeptidyl peptidase 4 (DPP4) fuels gut inflammation via attenuation of autophagy","authors":"Mohammad Athar, Ratulananda Bhadury, Chayanika Gogoi, Pooja Mishra, Prity Kumari, Manisha Yadav, J. Maras, Devram S. Ghorpade","doi":"10.1101/2024.08.06.606776","DOIUrl":"https://doi.org/10.1101/2024.08.06.606776","url":null,"abstract":"The recurrent pathological inflammation of the gut is a major concern in diabetic patients. With the failure of anti-inflammatory or diabetic drugs to limit relapse of colon inflammation demands the unearthing of mechanistic details underlying higher incidences of colitis in diabetic patients. Here we report the enrichment of DPP4 in the livers and blood samples of diabetic humans and mice models of diabesity that is in parallel to the development of colitis. Overexpression of DPP4 exacerbates or hepatic silencing of DPP4 impairs experimental colitis induced by DSS and STM. Mechanistically, we identified liver DPP4 attenuates gut-autophagic response to trigger enteric cell apoptosis, reduced mucin secretion, and compromised gut barrier leading to high infiltration of immune cells secreting inflammatory cytokines establishing pathological gut inflammation. Thus, liver-DPP4-mediated gut autophagy inhibition is a key pathway in diabesitic colitis.","PeriodicalId":505198,"journal":{"name":"bioRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：