bluuebunny/crossref_metadata_2025 huggingface dataset:
Salt stress alters the spectrum of de novo mutation available to selection during experimental adaptation of Chlamydomonas reinhardtii
Authors: Hasan Ahmed R. , Lachapelle Josianne , El-Shawa Sara A. , Potjewyd Roman , Ford Scott A. , Ness Rob W.
Published: April 2022

The genetic basis of adaptation is driven not only by selection, but also by the spectrum of available mutations. Given that the rate of mutation is not uniformly distributed across the genome and varies depending on the environment, understanding the signatures of selection across the genome is aided by first establishing what the expectations of genetic change are from mutation. To determine the interaction between salt stress, selection, and mutation across the genome, we compared the rates and patterns of mutation observed in a selection experiment for salt tolerance in Chlamydomonas reinhardtii to those observed in mutation accumulation experiments with and without salt exposure. We found that salt stress led to an increased rate of indel mutations, but that many of these mutations were removed under selection. Finally, lines adapted to salt also showed excess clustering of mutations in the genome and the co-expression network, suggesting a role for positive selection in retaining mutations in particular compartments of the genome during the evolution of salt tolerance. Our study shows that characterizing mutation rates and spectra expected under stress helps disentangle the effects of environment and selection during adaptation.
On demand nanoliter sampling probe for collection of brain fluid
Authors: Teixidor Joan , Novello Salvatore , Ortiz Daniel , Menin Laure , Lashuel Hilal A. , Bertsch Arnaud , Renaud Philippe
Published: April 2022

Continuous fluidic sampling systems allow collection of brain biomarkers in vivo. Here, we propose a new sampling paradigm, Droplet on Demand (DoD), implemented in a microfabricated neural probe. It allows sampling droplets loaded with molecules from the brain extracellular fluid punctually, without the long transient equilibration periods typical of continuous methods. It uses an accurate fluidic sequence and correct operation is verified by the embedded electrodes. As a proof of concept, we demonstrated the application of this novel approach in vitro and in vivo, to collect glucose in the brain of mice, with a temporal resolution of 1-2 minutes and without transient regime. Absolute quantification of the glucose level in the samples was performed by direct infusion nanoelectrospray ionization Fourier transform mass spectrometry (nanoESI-FTMS). By adjusting the diffusion time and the perfusion volume of DoD, the fraction of molecules recovered in the samples can be tuned to mirror the tissue concentration at accurate points in time. This makes quantification of biomarkers in the brain possible within acute experiments of only 20 to 120 minutes. DoD provides a complementary tool to continuous microdialysis and push-pull sampling probes. The advances allowed by DoD will benefit quantitative molecular studies in the brain, namely for molecules involved in volume transmission or for protein aggregates that form in neurodegenerative diseases over long periods.

Abstract Figure
Immobilised enzyme cascade for targeted glycosylation
Authors: Makrydaki Elli , Donini Roberto , Krueger Anja , Royle Kate , Moya-Ramirez Ignacio , Kuntz Douglas A. , Rose David R. , Haslam Stuart M. , Polizzi Karen , Kontoravdi Cleo
Published: April 2022

Glycosylation is a critical post-translational modification of proteins, improving properties such as folding, half-life and functionality. However, glycosylation is a non-templated and heterogeneous process because of the promiscuity of the enzymes involved. Here we describe a platform for sequential glycosylation reactions for tailored sugar structures (SUGAR-TARGET) that allows bespoke, controlled N-linked glycosylation in vitro. This novel proof-of-concept system is enabled by immobilised enzymes produced with a “one-step immobilisation/purification” method to express, biotinylate in vivo and immobilise glycosyltransferases. The immobilised enzymes are used in a reaction cascade mimicking a human-like N-linked glycosylation pathway where promiscuity naturally exists. The enzyme cascade is applied to free glycans, and a monomeric Fc domain expressed in glycoengineered Pichia pastoris, yielding near homogeneous glycoforms (>95% conversion). Finally, immobilised β-1,4 galactosyltransferase is used to enhance the galactosylation profile of three different IgGs yielding 80.2 – 96.3 % terminal galactosylation. Enzyme recycling was further demonstrated for 7 cycles, with a combined reaction time greater than 140 hours. The novel SUGAR-TARGET platform is easy to implement, modular and reusable, and therefore can lead to the development of homogeneous glycan structures for functional and clinical evaluation. The use of immobilised enzymes enables the economical modification of cell-based material supporting applications at a large industrial scale.
SIQ: easy quantitative measurement of mutation profiles in sequencing data
Authors: van Schendel Robin , Schimmel Joost , Tijsterman Marcel
Published: April 2022

Establishing mutational outcomes after genome editing is of increasing importance with the advent of highly efficient genome-targeting tools. Next-generation sequencing (NGS) has become a vital method to investigate the extent of mutagenesis at specific target sites. Thus, robust and simple-to-use software that enables researchers to retrieve mutation profiles from NGS data is needed. Here, we present Sequence Interrogation and Quantification (SIQ), a tool that can analyse sequence data of any targeted experiment (e.g. CRISPR, I-SceI, TALENs) with a focus on event classification such as deletions, single-nucleotide variations, (templated) insertions and tandem duplications. SIQ results can be directly analysed and visualized via SIQPlotteR, an interactive web tool that we made freely available. Using novel and insightful tornado plot visualizations as outputs we illustrate that SIQ readily identifies differences in mutational signatures obtained from various DNA-repair deficient genetic backgrounds. SIQ greatly facilitates the interpretation of complex sequence data by establishing mutational profiles at specific loci and is, to our knowledge, the first tool that can analyse Sanger sequence data as well as short and long-read NGS data (e.g. Illumina and PacBio).
Flexible Intentions: An Active Inference Theory
Authors: Priorelli Matteo , Stoianov Ivilin Peev
Published: April 2022

Abstract

We present a normative computational theory of how neural circuitry may support visually-guided goal-directed actions in a dynamic environment. The model builds on Active Inference, in which perception and motor control signals are inferred through dynamic minimization of generalized prediction errors. The Posterior Parietal Cortex (PPC) is proposed to maintain constantly updated expectations, or beliefs over the environmental state, and by manipulating them through flexible intentions it is involved in dynamically generating goal-directed actions. In turn, the Dorsal Visual Stream (DVS) and the proprioceptive pathway implement generative models that translate the high-level belief into sensory-level predictions to infer targets, posture, and motor commands. A proof-of-concept agent embodying visual and proprioceptive sensors and an actuated upper limb was tested on target-reaching tasks. The agent behaved correctly under various conditions, including static and dynamic targets, different sensory feedbacks, sensory precisions, intention gains, and movement policies; limit conditions were individuated, too. Active Inference driven by dynamic and flexible intentions can thus support goal-directed behavior in constantly changing environments, and the PPC putatively hosts its core intention mechanism. More broadly, the study provides a normative basis for research on goal-directed behavior in end-to-end settings and further advances mechanistic theories of active biological systems.
Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics
Authors: Luo Songhao , Wang Zihao , Zhang Zhenquan , Zhou Tianshou , Zhang Jiajun
Published: April 2022

Gene expression in mammalian cells is highly variable and episodic, and results in a series of discontinuous bursts of mRNAs. A challenge is understanding how static promoter architecture and dynamic feedback regulations dictate bursting on a genome-wide scale. Although single-cell RNA sequencing (scRNA-seq) provides an opportunity to address this issue, effective analytical methods are scarce. We developed an interpretable and scalable inference framework, which combined experimental data with a mechanistic model to infer transcriptional burst kinetics (sizes and frequencies) and feedback regulations. Applying this framework to scRNA-seq data generated from embryonic mouse fibroblast cells, we found Simpson’s paradoxes, i.e., genome-wide burst kinetics exhibited different characteristics in two cases without and with distinguishing feedback regulations. We show that feedbacks differently modulate burst frequencies and sizes and conceal the effects of transcription start site distributions on burst kinetics. Notably, only in the presence of positive feedback, TATA genes are expressed with high burst frequencies and enhancer-promoter interactions mainly modulate burst frequencies. The developed inference method provided a flexible and efficient way to investigate transcriptional burst kinetics and the obtained results would be helpful for understanding cell development and fate decision.
A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomics
Authors: Daly Kevin G. , Arbuckle Benjamin S. , Rossi Conor , Mattiangeli Valeria , Lawlor Phoebe A. , Mashkour Marjan , Sauer Eberhard , Lesur Joséphine , Atici Levent , Erek Cevdet Merih , Bradley Daniel G.
Published: April 2022

Abstract

Direkli Cave, located in the Taurus Mountains of southern Turkey, was occupied by Late Epipaleolithic hunters-gatherers for the seasonal hunting and processing of game including large numbers of wild goats. We report genomic data from new and publishedCapraspecimens from Direkli Cave and, supplemented with historic genomes from multipleCapraspecies, find a novel lineage best represented by a ∼14,000 year old 2.59X genome sequenced from specimen Direkli4. This newly discovered Capra lineage is a sister clade to the Caucasian tur species (Capra cylindricornisandCapra caucasica), both now limited to the Caucasus region. We identify genomic regions introgressed in domestic goats with high affinity to Direkli4, and find that West Eurasian domestic goats in the past, but not those today, appear enriched for Direkli4-specific alleles at a genome-wide level. This forgotten “Taurasian tur” likely survived Late Pleistocene climatic change in a Taurus Mountain refugia and its genomic fate is unknown.
Humans have distinct repertoires of IgA1
Authors: Dingess Kelly A. , Hoek Max , van Rijswijk Danique M.H. , Tamara Sem , den Boer Maurits A. , Damen Mirjam J.A. , Barendregt Arjan , Romijn Michelle , Juncker Hannah G. , van Keulen Britt J. , Vidarsson Gestur , van Goudoever Johannes B. , Bondt Albert , Heck Albert J.R.
Published: April 2022

The most abundant immunoglobulin present in the human body is IgA1. It has the highest concentrations at the mucosal lining and in biofluids such as milk and is the second most abundant class of antibodies in serum. We assessed the structural diversity and clonal repertoire of IgA1-containing molecular assemblies longitudinally in human serum and milk from three donors using a mass spectrometry-based approach. IgA-containing molecules purified from serum or milk were assessed by the release and subsequent analysis of their Fab fragments. Our data revealed that serum IgA1 consists of two distinct structural populations, namely monomeric IgA1 (∼ 80%) and dimeric joining (J-) chain coupled IgA1 (∼ 20%). Also, we confirmed that IgA1 in milk is present solely as secretory (S)IgA, consisting of two (∼ 50%), three (∼ 33%) or four (∼ 17%) IgA1 molecules assembled with a J-chain and secretory component (SC). Interestingly, the serum and milk IgA1-Fab repertoires were distinct between monomeric, and J-chain coupled dimeric IgA1. The serum dimeric J-chain coupled IgA1 repertoire contained several abundant clones also observed in the milk IgA1 repertoire. The latter repertoire had little to no overlap with the serum monomeric IgA1 repertoire. This suggests that human IgA1s have (at least) two distinct origins; one of these produces dimeric J-chain coupled IgA1 molecules, shared in human serum and milk, and another produces monomeric IgA1 ending up exclusively in serum.
Data Driven Control of Vagus Nerve Stimulation for the Cardiac System
Authors: Branen Andrew , Yao Yuyu , Kothare Mayuresh , Mahmoudi Babak , Kumar Gautam
Published: April 2022

1

Vagus nerve stimulation is an emerging therapy that seeks to offset pathological conditions by electrically stimulating the vagus nerve through cuff electrodes, where an electrical pulse is defined by several parameters such as pulse amplitude, pulse width, and pulse frequency. This electroceutical therapy has been approved for epilepsy, and treatment resistant depression. Currently, vagus nerve stimulation is under investigation for the treatment of heart failure, heart arrhythmia, hypertension, and gastric motility disorders. Through several clinical trials that sought to assess vagus nerve stimulation for the treatment of heart failure, stimulation parameters were determined heuristically and the results were left inconclusive, which has led to the suggestion of using a closed-loop approach to optimize the stimulation parameters. A recent investigation has demonstrated highly specific control of cardiac physiology by selectively activating different fibers in the vagus nerve. When multiple locations and multiple stimulation parameters are considered for optimization, the design of closed-loop control becomes considerably more challenging. To address this challenge, we investigated a data-driven control scheme for both modeling and controlling the rat cardiac system. Using an existingin silicophysiological model of a rat heart to generate synthetic input-output data, we trained a long short-term memory network (LSTM) to map the effect of stimulation on the heart rate and the blood pressure. The trained LSTM was utilized in a model predictive control framework to optimize the vagus nerve stimulation parameters for set point tracking of the heart rate and the blood pressure in closed-loop simulations. Additionally, we altered the underlyingin silicophysiological model to consider intra-patient variability, and diseased dynamics from increased sympathetic tone in designing closed-loop VNS strategies. Throughout the different simulation scenarios, we leveraged the design of the controller to demonstrate alternative clinical objectives. Our results show the controller can optimize stimulation parameters to achieve set-point tracking with nominal offset while remaining computationally efficient. Furthermore, we show a controller formulation that compensates for mismatch due to intra-patient variabilty, and diseased dynamics. This study demonstrates the first application and a proof-of-concept for using a purely data-driven approach for the optimization of vagus nerve stimulation parameters in closed-loop control of the cardiac system.
FollicleFinder: automated three-dimensional segmentation of human ovarian follicles
Authors: Yamauchi Kevin , Biniasch Marieke , Franz Leopold , Gómez Harold , De Geyter Christian , Iber Dagmar
Published: April 2022

In vitro fertilization (IVF) treatment protocols require frequent monitoring of the ovarian follicle growth process. We report FollicleFinder, an open source pipeline for the automated, 3D segmentation of ovarian follicles. FollicleFinder also accurately measures clinically-relevant morphological properties such as diameter, surface area, and volume.

Availability

The FollicleFinder pipeline is available at https://git.bsse.ethz.ch/iber/ovary-analysis and the graphical user interface is available at https://git.bsse.ethz.ch/iber/follicle-tracker.
MOCCS profile analysis clarifies the cell type dependency of transcription factor-binding sequences and cis-regulatory SNPs in humans
Authors: Tahara Saeko , Tsuchiya Takaho , Matsumoto Hirotaka , Ozaki Haruka
Published: April 2022

Transcription factors (TFs) show heterogeneous DNA-binding specificities in individual cells and whole organisms in natural conditions): de novo motif discovery usually provides multiple motifs even from a single ChIP-seq sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored. Here, we propose MOCCS profiles, the new representation of DNA-binding specificity of TFs, which describes a ChIP-seq sample as a profile of TF-binding specificity scores (MOCCS2scores) for every k-mer sequence. Using our k-mer-based motif discovery method MOCCS2, we systematically computed MOCCS profiles for >10,000 human TF ChIP-seq samples across diverse TFs and cell types. Comparison of MOCCS profiles revealed the global distributions of DNA-binding specificities, and found that one-third of the analyzed TFs showed differences in DNA-binding specificities across cell types. Moreover, we showed that the differences in MOCCS2scores (ΔMOCCS2scores) predicted the effect of variants on TF binding, validated by in vitro and in vivo assay datasets. We also demonstrate ΔMOCCS2scores can be used to interpret non-coding GWAS-SNPs as TF-affecting SNPs and provide their candidate responsible TFs and cell types. Our study provides the basis for investigating gene expression regulation and non-coding disease-associated variants in humans.
High-quality haploid genomes corroborate 29 chromosomes and highly conserved synteny of genes inHyleshawkmoths (Lepidoptera: Sphingidae)
Authors: Hundsdoerfer Anna K. , Schell Tilman , Patzold Franziska , Wright Charlotte J. , Yoshido Atsuo , Marec František , Daneck Hana , Winkler Sylke , Greve Carola , Podsiadlowski Lars , Hiller Michael , Pippel Martin
Published: April 2022

Background

Morphological and traditional genetic studies of the young Pliocene genusHyleshave led to the understanding that despite its importance for taxonomy, phenotypic similarity of wing patterns does not correlate with phylogenetic relationship. To gain insights into various aspects of speciation in the Spurge Hawkmoth (Hyles euphorbiae), we assembled a chromosome-level genome and investigated some of its characteristics.

Results

The genome of a maleH. euphorbiaewas sequenced using PacBio and Hi-C data, yielding a 504 Mb assembly (scaffold N50 of 18.2 Mb) with 99.9% of data represented by the 29 largest scaffolds forming the haploid chromosome set. Consistent with this, FISH analysis of the karyotype revealedn= 29 chromosomes and a WZ/ZZ (female/male) sex chromosome system. Estimates of chromosome length based on the karyotype image provided an additional quality metric of assembled chromosome size. Rescaffolding the published maleH. vespertiliogenome resulted in a high-quality assembly (651 Mb, scaffold N50 of 22 Mb) with 98% of sequence data in the 29 chromosomes. The larger genome size ofH. vespertilio(average 1C DNA value of 562 Mb) was accompanied by a proportional increase in repeats from 45% inH. euphorbiae(measured as 472 Mb) to almost 55% inH. vespertilio. Several wing pattern genes were found on the same chromosomes in the two species, with varying amounts and positions of repetitive elements and inversions possibly corrupting their function.

Conclusions

Our two-fold comparative genomics approach revealed high gene synteny of theHylesgenomes to other Sphingidae and high correspondence to intact Merian elements, the ancestral linkage groups of Lepidoptera, with the exception of three simple fusion events. We propose a standardized approach for genome taxonomy using nucleotide homology via scaffold chaining as the primary tool combined with Oxford plots based on Merian elements to infer and visualize directionality of chromosomal rearrangements. The identification of wing pattern genes promises future understanding of the evolution of forewing patterns in the genusHyles, although further sequencing data from more individuals are needed. The genomic data obtained provide additional reliable references for further comparative studies in hawkmoths (Sphingidae).
Social determinants of health and disease in companion dogs: A cohort study from the Dog Aging Project
Authors: McCoy Brianah M. , Brassington Layla , Jin Kelly , Dolby Greer A. , Shrager Sandi , Collins Devin , Dunbar Matthew ,   Dog Aging Project Consortium, Snyder-Mackler Noah
Published: April 2022

Exposure to social environmental adversity is associated with health and survival in many social species, including humans. However, little is known about if and how these health and mortality effects vary across the lifespan, largely due to the difficulty of studying long-lived organisms across much of their lifespan. Here, we leveraged a relatively new and powerful model for human aging, the companion dog, to investigate which components of the social environment are associated with dog health and how these associations vary across the lifespan. We drew on comprehensive survey data collected on 21,410 dogs from the Dog Aging Project and identified five factors that together explained 33.7% of the variation in a dog’s social environment. Factors capturing financial and household adversity were associated with poorer health and lower physical mobility in companion dogs, while factors that captured social support, such as living with other dogs, were associated with better health when controlling for dog age and weight. Some of these associations differed across a dog’s lifespan, including a stronger relationship between owner age and health in younger (as compared to older) dogs. Taken together, these findings suggest the importance of income, stability, and owner age on owner-reported health outcomes in companion dogs and point to potential behavioral and/or environmental modifiers that can be used to promote healthy aging across species.
Kinome Inhibition States and Multiomics Data Enable Prediction of Cell Viability in Diverse Cancer Types
Authors: Berginski Matthew E. , Joisa Chinmaya U. , Golitz Brian T. , Gomez Shawn M.
Published: April 2022

Protein kinases play a vital role in a wide range of cellular processes and compounds that inhibit kinase activity have emerged as a primary focus for targeted therapy development in cancer. This has inspired work that characterizes the spectrum of kinases targeted by specific inhibitors and the inclusion of these inhibitors in large-scale cell viability screening efforts. Previous work with smaller datasets have used baseline profiling of cell lines and limited kinome profiling data to attempt to predict small molecule effects on cell viability, but these efforts did not use multi-dose kinase profiles and achieved low accuracy with very limited external validation. This work focuses on two primary data types, kinase inhibitor profiles and gene expression, to predict the results of cell viability screening. We describe the process by which we combined these data sets, examined their properties in relation to cell viability and finally developed a set of computational models that achieve reasonable prediction accuracy (R2 of 0.78 and RMSE of 0.154). Using these models, we identified a set of kinases, several of which are understudied, that are strongly influential in the cell viability prediction models. In addition, we also tested to see if a wider range of multiomics data sets could improve the model results. Finally, we validated a small subset of the model predictions in several triple-negative and HER2 positive breast cancer cell lines demonstrating that the model performs well with compounds and cell lines that were not included in the training data set. Overall, this result demonstrates that generic knowledge of the kinome is predictive of very specific cell phenotypes, and has the potential to be integrated into targeted therapy development pipelines.
Entropy sorting of single cell RNA sequencing data reveals the inner cell mass in the human pre-implantation embryo
Authors: Radley Arthur , Corujo-Simon Elena , Nichols Jennifer , Smith Austin , Dunn Sara-Jane
Published: April 2022

A major challenge in single cell gene expression analysis is to discern meaningful cellular heterogeneity from technical or biological noise. To address this challenge, we present Entropy Sorting, a mathematical framework that distinguishes genes indicative of cell identity. ES achieves this in an unsupervised manner by quantifying if observed correlations between features are more likely to have occurred due to random chance versus a dependent relationship, without the need for any user defined significance threshold. On synthetic data we demonstrate the removal of noisy signals to reveal a higher resolution of gene expression patterns than commonly used feature selection methods. We then apply ES to human pre-implantation embryo scRNA-seq data. Previous studies failed to unambiguously identify early inner cell mass (ICM), suggesting that the human embryo may diverge from the mouse paradigm. In contrast, ES resolves the ICM and reveals sequential lineage bifurcations as in the classical model. Entropy sorting thus provides a powerful approach for maximising information extraction from high dimensional datasets such as scRNA-seq data.
High-throughput Oligopaint screen identifies druggable regulators of genome folding
Authors: Park Daniel S. , Nguyen Son C. , Isenhart Randi , Shah Parisha P. , Kim Wonho , Barnett R. Jordan , Chandra Aditi , Luppino Jennifer M. , Harke Jailynn , Wai May , Yang Rachel , Lan Yemin , Yoon Sora , Yunker Rebecca , Vahedi Golnaz , Phillips-Cremins Jennifer E. , Jain Rajan , Joyce Eric F.
Published: April 2022

Although the molecular rules governing genome organization are being quickly elucidated, relatively few proteins regulating this process have been identified. To address this gap, we developed a fully automated imaging pipeline, called HiDRO (high-throughput DNA or RNA labeling with optimized Oligopaints), that permits quantitative measurement of chromatin interactions across a large number of samples. Using HiDRO, we screened the human druggable genome and identified >300 factors that regulate chromatin folding during interphase, including 43 validated hits that either increase or decrease interactions between topological associating domains (TADs). We discovered that genetic or chemical inhibition of the ubiquitous kinase GSK3A enhances long-range interactions by dysregulating cohesin-mediated chromatin looping. Collectively, these results highlight a noncanonical role for GSK3A signaling in nuclear architecture and underscore the broader utility of HiDRO-based screening to identify novel mechanisms that drive the spatial organization of the genome.
Protein Kinase C Alpha is a Central Node for Tumorigenic Transcriptional Networks in Human Prostate Cancer
Authors: Cooke Mariana , Zhang Xuyao , Zhang Suli , Lal Priti , Daniel Reba E. , Feldman Michael D. , Abba Martin C. , Kazanietz Marcelo G.
Published: April 2022

Aberrant expression of protein kinase C (PKC) isozymes is a hallmark of cancer. The different members of the PKC family control cellular events associated with cancer development and progression. Whereas the classical/conventional PKCα isozyme has been linked to tumor suppression in most cancer types, here we demonstrate that this kinase is required for the mitogenic activity of aggressive human prostate cancer cells displaying aberrantly high PKCα expression. Immunohistochemical analysis showed abnormal up-regulation of PKCα in human primary prostate tumors. Interestingly, silencing PKCα expression from aggressive prostate cancer cells impairs cell cycle progression, proliferation and invasion, as well as their tumorigenic activity in a mouse xenograft model. Mechanistic analysis revealed that PKCα exerts a profound control of gene expression, particularly over genes and transcriptional networks associated with cell cycle progression and E2F transcription factors. PKCα RNAi depletion from PC3 prostate cancer cells led to reduced expression of pro-inflammatory cytokine and epithelial-to-mesenchymal transition (EMT) genes, as well as a prominent down-regulation in the expression of the immune checkpoint ligand PD-L1. This PKCα-dependent gene expression profile was corroborated in a human prostate cancer database. Our studies established PKCα as a multifunctional kinase that plays pleiotropic roles in prostate cancer, particularly by controlling genetic networks associated with tumor growth and progression. The identification of PKCα as a pro-tumorigenic kinase in human prostate cancer provides strong rationale for developing therapeutic approaches towards targeting PKCα or its effectors.

IMPLICATIONS

Our findings implicate PKCα as a major node for transcriptional regulation of tumorigenic pathways in prostate cancer.
Uncovering the roles of lignin-related genes in disease resistance in maize using mutant and association analysis
Authors: Kolkman Judith M. , Moreta Danilo E. , Repka Ace , Bradbury Peter , Nelson Rebecca J.
Published: April 2022

Brown midrib (BMR) maize harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate NY highlighted the disease susceptibility of commercially grown BMR maize hybrids. We found the bm1, bm2, bm3 and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot, and anthracnose leaf blight) and bacterial (Stewart’s wilt) diseases. The bm1, bm2 and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot, and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot. Co-localization of quantitative trait loci and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high-resolution, genome-wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered SNP associations for resistance to NLB, but did not implicate natural functional variation at bm1-bm5. Strong associations implicated a suite of diverse candidate genes, including lignin-related genes such as a β-glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP-like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and non-silage purposes.

Core Ideas

Brown midrib mutants (bm1-bm4) in maize, characterized as mutations with reduced lignin content, are susceptible to a range of foliar pathogens.

Several brown midrib mutants in maize show enhanced susceptibility to stalk rot and ear rot pathogens.

Genome wide association analysis identified a number of diverse candidate genes associated with resistance to northern leaf blight in maize, including lignin-related genes involved in the monolignol pathway, developmental genes and transcription factors.

Association analysis for resistance to NLB implicated a β-glucosidase gene cluster, including Zmbglu24 and Zmbglu25 known for targeting monolignols and contributing to ∼15% phenotypic variation.

hct11, which plays an important role in the monolignol pathway, was implicated for resistance to northern leaf blight in maize with potential for multiple stress tolerance.
Multi-Head Attention-based U-Nets for Predicting Protein Domain Boundaries Using 1D Sequence Features and 2D Distance Maps
Authors: Mahmud Sajid , Guo Zhiye , Quadir Farhan , Liu Jian , Cheng Jianlin
Published: April 2022

The information about the domain architecture of proteins is useful for studying protein structure and function. However, accurate prediction of protein domain boundaries (i.e., sequence regions separating two domains) from sequence remains a significant challenge. In this work, we develop a deep learning method based on multi-head U-Nets (called DistDom) to predict protein domain boundaries utilizing 1D sequence features and predicted 2D inter-residue distance map as input. The 1D features contain the evolutionary and physicochemical information of protein sequences, whereas the 2D distance map includes the structural information of proteins that was rarely used in domain boundary prediction before. The 1D and 2D features are processed by the 1D and 2D U-Nets respectively to generate hidden features. The hidden features are then used by the multi-head attention to predict the probability of each residue of a protein being in a domain boundary, leveraging both local and global information in the features. The residue-level domain boundary predictions can be used to classify proteins as single-domain or multi-domain proteins. It classifies the CASP14 single-domain and multi-domain targets at the accuracy of 69.1%, 2.67% more accurate than the state-of-the-art method. Tested on the CASP14 multi-domain protein targets with expert annotated domain boundaries, the average per-target F1 measure score of the domain boundary prediction by DistDom is 0.263, 29.56% higher than the state-of-the-art method.
Simulating the Tumor Microenvironment for Immune Cell Interactions via Deployable Extrusion Bioprinting
Authors: Mazzaglia Corrado , Sheng Yaqi , Rodrigues Leonor Nunes , Lei Iek Man , Shields Jacqueline D. , Huang Yan Yan Shery
Published: April 2022

Three-dimensional (3D) bioprinting has emerged as a promising tool for constructing tumor microenvironments (TME) for cancer modelling in vitro. Realizing the translational impacts of 3D bioprinting for cancer research necessitates innovation in bioprinting workflows which integrate affordability, user-friendliness, and biological relevance. Herein, we demonstrate ‘bioArm’, a simple, yet highly effective extrusion bioprinting platform, which can be folded into a carry-on pack, and rapidly deployed between bio-facilities. BioArm enabled TME reconstruction in the form of 3D core-shell tumoroids with cancer-associated fibroblasts (CAFs). Tumoroids showed the presence of a heterogenous population of CAFs with de novo synthesized extracellular matrices, demonstrating more in vivo-like characteristics compared to conventional 2D co-culture models. Embedding the 3D printed tumoroids in an immune cell laden collagen matrix permitted tracking of the interaction between immune cells and tumoroids, and subsequent immunotherapy treatments. Our deployable extrusion bioprinting workflow could significantly widen the accessibility of 3D bioprinting for gaining mechanistic understanding in TME, and for developing strategies in cancer drug testing.
The PAICE Suite Reveals Circadian Post-Transcriptional Timing of Non-Coding RNAs and Spliceosome Components in Mus musculus Macrophages
Authors: Buel Sharleen M. , Debopadhaya Shayom , De los Santos Hannah , Edwards Kaelyn M. , David Alexandra M. , Dao Uyen H. , Bennett Kristin P. , Hurley Jennifer M.
Published: April 2022

Circadian rhythms broadly regulate physiological functions by tuning oscillations in the levels of mRNAs and proteins to the 24-hour day/night cycle. Globally assessing which mRNAs and proteins are timed by the clock necessitates accurate recognition of oscillations in RNA and protein data, particularly in large omics data sets. Tools that employ fixed-amplitude models have previously been used to positive effect. However, the recognition of amplitude-change in circadian oscillations required a new generation of analytical software to enhance the identification of these oscillations. To address this gap, we created the Pipeline for Amplitude Integration of Circadian Exploration (PAICE) suite. Here, we demonstrate the PAICE suite’s increased detection of circadian trends through the joint modeling of the Mus musculus macrophage transcriptome and proteome. Our enhanced detection confirmed extensive circadian post-transcriptional regulation in macrophages, but highlighted that some of the reported discrepancy between mRNA and protein oscillations was due to noise in data. We further applied the PAICE suite to investigate the circadian timing of non-coding RNAs, documenting extensive circadian timing of long non-coding RNAs and small nuclear RNAs, which control the recognition of mRNA in the spliceosome complex. By tracking oscillating spliceosome complex proteins using the PAICE suite, we noted that the clock broadly regulates the spliceosome, particularly the major spliceosome complex. As most of the above-noted rhythms had damped amplitude changes in their oscillations, this work highlights the importance of the PAICE suite in the thorough enumeration of oscillations in omics-scale datasets.
TwinEQTL: Ultra Fast and Powerful Association Analysis for eQTL and GWAS in Twin Studies
Authors: Xia Kai , Shabalin Andrey A. , Yin Zhaoyu , Chung Wonil , Sullivan Patrick F. , Wright Fred A. , Styner Martin , Gilmore John H. , Santelli Rebecca C. , Zou Fei
Published: April 2022

We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model (LMM) for twin genome-wide association study (GWAS) data. Instead of analyzing all twin samples together with LMM, TwinEQTL first splits twin samples into two independent groups on which multiple linear regression analysis can be validly performed separately, followed by an appropriate meta-analysis-like approach to combine the two non-independent test results. Through mathematical derivations, we prove the validity of TwinEQTL algorithm and show that the correlation between two dependent test statistics at each single-nucleotide polymorphism (SNP) are independent of its minor allele frequency (MAF). Thus the correlation is constant across all SNPs. Through simulations, we show empirically that TwinEQTL has well controlled type I error with negligible power loss compared to the gold-standard linear mixed effects models. To accommodate eQTL analysis with twin subjects, we further implement TwinEQTL into a R package with much improved computational efficiency. Our approaches provide a significant leap in terms of computing speed for GWAS and eQTL analysis with twin samples.
Bacterial produce membrane-binding small molecules to regulate horizontal gene transfer in vesicles
Authors: Tran Frances , Gangan Manasi S. , Boedicker James Q.
Published: April 2022

The exchange of bacterial extracellular vesicles facilitates molecular exchange between cells, including the horizontal transfer of genetic material. Given the implications of such transfer events on cell physiology and adaptation, some bacterial cells have likely evolved mechanisms to regulate vesicle exchange. Past work has identified mechanisms that regulate the formation of extracellular vesicles, including the production of small molecules that modulate membrane structure, however whether these mechanisms also regulate vesicle uptake and have an overall impact on the rate of vesicle exchange is unknown. Here we show that membrane-binding molecules produced by microbes regulate both the formation and uptake of extracellular vesicles and have the overall impact of increasing the vesicle exchange rate within a bacterial coculture. In effect, production of compounds that influence vesicle exchange rates enable cells to steal genes from neighboring cells. The ability of several membrane-binding compounds to regulate vesicle exchange was demonstrated. Three of these compounds, nisin, colistin, and polymyxin B, are antimicrobial peptides added at sub-inhibitory concentrations. These results suggest that a key function of exogenous compounds that bind to membranes may be the regulation of vesicle exchange between cells.

Importance

The exchange of bacterial extracellular vesicles is one route of gene transfer between bacteria, although it was unclear if bacteria developed strategies to regulate the rate of gene transfer within vesicles. In eukaryotes, there are many examples of specialized molecules that have evolved to facilitate the production, loading, and uptake of vesicles. Recent work with bacteria has shown that some small molecules influence membrane curvature and induce vesicle formation. Here we show that similar compounds facilitate vesicle uptake, thereby regulating the overall rate of vesicle exchange within bacterial populations. The addition of membrane-binding compounds, several of them antibiotics at sub-inhibitory concentrations, to a bacterial co-culture increased the rate of horizontal gene transfer via vesicle exchange.
Additive and Dominant Loci Jointly Pyramiding the Grain Quality of Hybrid Rice
Authors: Li Lanzhi , Zheng Xingfei , Wang Jiabo , Zhang Xueli , He Xiaogang , Xiong Liwen , Song Shufeng , Su Jing , Tang Wenbang , Diao Ying , Yuan Zheming , Zhang Zhiwu , Hu Zhongli
Published: April 2022

Hybrid rice has an advantage in its heterosis, resulting in high yield and resistance to biotic and abiotic stress. However, genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional complexity, such as the dominant effect. It is critical to identify a path to efficiently develop inbreds and identify their superior crosses for hybrid production. Here, we developed a pipeline for joint analysis of phenotypes, effects, and generations (JPEG) and analysed 113 inbred varieties as male parents, five tester varieties as female parents, and their 565 (113×5) hybrid testcrosses for 12 grain quality traits, including grain length and width, chalkiness, and amylose content. A total of 1,619,588 single nucleotide polymorphisms were obtained for the parent varieties and inferred for the hybrids using whole-genome sequencing with an average sequencing depth of 11×. Genome-wide association studies with JPEG identified 128 loci associated with at least one of the 12 traits. There were 44 and 97 loci with additive and dominant effects, respectively, including 13 overlaps. Among the 128 associated loci, 42 loci are located in or near (<200 kb) 17 known genes. Pyramiding genetic loci with additive and/or dominant effects in genomic selection dramatically improves the accuracy of predicting hybrid performances. More than 45% of genetic variation was explained by the identified markers for all traits except one (30%). These results demonstrate that pyramiding genetically identified additive and dominant loci can afford substantial power for predicting hybrid performances, presenting opportunities to identify superior crosses from existing phenotypes and genotypes of inbreds and hybrids.
The UbiB family member Cqd1 forms a novel membrane contact site in mitochondria
Authors: Khosravi Siavash , Chelius Xenia , Unger Ann-Katrin , Frickel Johanna , Sachsenheimer Timo , Lüchtenborg Christian , Schieweck Rico , Brügger Britta , Westermann Benedikt , Klecker Till , Neupert Walter , Harner Max E.
Published: April 2022

Mitochondria are essential organelles of eukaryotic cells that are characterized by their unique and complex membrane system. They are confined from the cytosol by an envelope consisting of two membranes. Signals, metabolites, proteins and lipids have to be transferred across these membranes via proteinaceous contact sites to keep mitochondria functional. In the present study we identified a novel mitochondrial contact site that is formed by the inner membrane protein Cqd1 and the outer membrane proteins Por1 and Om14. Similar to the mitochondrial porin, Por1, Cqd1 is highly conserved, suggesting that this complex is conserved in form and function from yeast to human. Cqd1 is a member of the UbiB protein kinase-like family (also called aarF domain containing kinases). It was recently shown that Cqd1 in cooperation with Cqd2 controls the cellular distribution of coenzyme Q by a yet unknown mechanism. Our data suggest that Cqd1 in addition is involved in the homeostasis of phospholipids and contributes to the maintenance of mitochondrial morphology and architecture.

Summary statement

Here, we show that the conserved mitochondrial inner membrane protein Cqd1 interacts with the outer membrane proteins Por1 and Om14. Additionally, we provide evidence that Cqd1 is important for maintaining mitochondrial homeostasis.
Autotaxin facilitates selective LPA receptor signaling
Authors: Salgado-Polo Fernando , Borza Razvan , Marsais Florence , Jagerschmidt Catherine , Waeckel Ludovic , Moolenaar Wouter H. , Ford Paul , Heckmann Bertrand , Perrakis Anastassis
Published: April 2022

Autotaxin (ATX; ENPP2) produces the lipid mediator lysophosphatidic acid (LPA) that signals through disparate EDG (LPA1-3) and P2Y (LPA4-6) G protein-coupled receptors. ATX/LPA promote several (patho)physiological processes, including in pulmonary fibrosis, thus serving as attractive drug targets. However, it remains unclear if clinical outcome depends on how different ATX inhibitors modulate the ATX/LPA signaling axis. Here, we show that inhibitors binding to the ATX “tunnel” specifically abrogate key aspects of ATX/LPA signaling. We find that the tunnel is essential for signaling efficacy and dictates cellular responses independent of ATX catalytic activity, with a preference for activation of P2Y LPA receptors. These responses are abrogated by tunnel-binding inhibitors, such as ziritaxestat, but not by inhibitors that exclusively target the active site, as shown in primary lung fibroblasts and a murine model of radiation-induced pulmonary fibrosis. Our results uncover a receptor-selective signaling mechanism for ATX, implying clinical benefit for tunnel-targeting ATX inhibitors.

Highlights

ATX is a dual-function protein acting as an LPA-producing enzyme and LPA chaperone.

Structural integrity of the ATX tunnel is essential to mediate signaling functions.

ATX-bound LPA signals preferentially via P2Y family LPA receptors.

Occupancy of the ATX tunnel is crucial for ziritaxestat to exert inhibition in vivo.
Temperature and resources interact to shape phytoplankton size-abundance relationships at a continental scale
Authors: Gjoni Vojsava , Glazier Douglas S. , Ibelings Bastiaan W. , Thomas Mridul K.
Published: April 2022

Communities contain more individuals of small species and fewer individuals of large species. The observed −3/4 slope relating mean size and mean abundance across communities (the ‘cross-community scaling relationship’ or CCSR) is thought to arise from a 3/4-power scaling of metabolic rate with body size. Assuming that 3/4-power metabolic scaling is universal, as claimed by the metabolic theory of ecology (MTE), size-abundance relationships should also be invariant with a scaling exponent of −3/4 or nearly so, across environmental conditions. However, we find that the CCSR slope is actually −1 overall (perhaps due to isometric metabolic scaling), and varies substantially across temperature and nutrient gradients in 1048 freshwater lake phytoplankton communities in the USA. The size-abundance relationship is most shallow at low temperatures and high nutrients, and steeper and relatively insensitive to nutrients at high temperatures. Phytoplankton communities have orders of magnitude more small or large cells depending on environmental conditions than would be predicted from the MTE. Although based on observational data, these results suggest that the environment alters either metabolic scaling or other poorly understood processes shaping community size distributions.