bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of high pCO2on snow crab larvae: Carryover effects from embryogenesis and oogenesis reduce direct effects on larval survival
Authors: Long W. Christopher , Swiney Katherine M. , Foy Robert J.
Published: October 2022

Ocean acidification, a decrease in ocean pH with increasing anthropogenic CO2concentrations, is expected to affect many marine animals. We determined the effects of ocean acidification on the economically important snow crab,Chionoecetes opilio. By holding females in treatment pH for two brooding cycles and using the resulting larvae, we assessed carryover effects from oogenesis and embryogenesis. Ovigerous females were held at three pHs: ~8.1 (Ambient), 7.8, and 7.5. Larvae were exposed to the same pH treatments in a fully crossed experimental design. Starvation-survival, morphology, condition, and calcium/magnesium content were assessed for larvae. In the first year, starvation-survival of larvae reared at ambient pH but hatched from embryos reared at reduced pH was lowered; however, the negative effect was eliminated when the larvae were reared at reduced pH. In the second year, there was no direct effect of either embryo or larval pH treatment, but larvae reared as embryos at reduced pH survived longer if reared at reduced pH. Larvae hatched from embryos held at pH 7.5 had lower calcium content right after hatching, but the effect was transitory in the second year. There was no effect of larval treatment on calcium content or effect of embryo or larval treatment on magnesium content. Larval morphometrics were slightly altered, though effect sizes were small smaller in the second year. These results suggest both that larvae are highly tolerant of reduced pH, and that embryos are able to acclimate to low pH and this effect carries over to the larval stage.
Host body size, not host population size, predicts genome-wide effective population size of parasites
Authors: Doña Jorge , Johnson Kevin P.
Published: October 2022

The effective population size (Ne) of an organism is expected to be generally proportional to the total number of individuals in a population. In parasites, we might expect the effective population size to be proportional to host population size and host body size, because both are expected to increase the number of parasite individuals. However, among other factors, parasite populations are sometimes so extremely subdivided that high levels of inbreeding may distort these predicted relationships. Here, we used whole-genome sequence data from dove parasites (71 feather louse species of the genusColumbicola) and phylogenetic comparative methods to study the relationship between parasite effective population size and host population size and body size.We found that parasite effective population size is largely explained by host body size but not host population size. These results suggest the potential local population size (infrapopulation or deme size) is more predictive of the long-term effective population size of parasites than is the total number of potential parasite infrapopulations (i.e., host individuals).

Impact Summary

Parasites, among Earth’s most diverse, threatened, and under-protected animals, play a central role in ecosystem function. The effective population size (Ne) of an organism has a profound impact on evolutionary processes, such as the relative contributions of selection and genetic drift to genomic change. Population size is also one of the most important parameters in conservation biology. For free-living organisms, it is expected thatNeis generally proportional to the total number of individuals in a population. However, for parasites, among other factors, populations are sometimes so extremely subdivided that high levels of inbreeding may distort these relationships. In this study, we used whole-genome sequence data from dove parasites and phylogenetic comparative methods to investigate the relationship between parasite effective population size (Ne) and host population size and body size. Our results revealed a positive relationship between parasite effective population size (Ne) and host body size, but not host population size. These results suggest that the size of parasite infrapopulations may be the most important factor when considering parasite effective population size, and have important implications for conservation.
Rapamycin not Dietary Restriction improves resilience against pathogens: a meta-analysis
Authors: Phillips Eleanor J , Simons Mirre J P
Published: October 2022

Dietary Restriction (DR) and rapamycin both increase lifespan across a number of taxa. Despite this positive effect on lifespan and other aspects of health, reductions in some physiological functions have been reported for DR and rapamycin has been used as an immunosuppressant. Perhaps surprisingly, both interventions have been suggested to improve immune function and delay immunosenescence. The immune system is complex and consists of many components. Therefore, arguably, the most holistic measurement of immune function is survival from an acute pathogenic infection. We reanalysed published post-infection short-term survival data of mice (n=1223 from 23 studies comprising 46 effect sizes involving DR (n=17) and rapamycin treatment (n=29) and analysed these results using meta-analysis. Rapamycin treatment significantly increased post infection survival rate (lnHR=-0.72; CI=-1.17, -0.28; p=0.0015). In contrast, DR reduced post-infection survival (lnHR=0.80; CI=0.08, 1.52; p=0.03). Importantly, the overall effect size of rapamycin treatment was significantly lower (P<0.001) than the estimate from DR studies, suggesting opposite effects on immune function. Our results show that immunomodulation caused by rapamycin treatment is beneficial to the survival from acute infection. For DR our results are based on a smaller number of studies, but do warrant caution as they indicate possible immune costs of DR. Our quantitative synthesis suggests that the geroprotective effects of rapamycin extend to the immune system and warrants further clinical trials of rapamycin to boost immunity in humans.
Seeing the future: connectome strength and network efficiency in visual network predict individual ability of episodic future thinking
Authors: Hu Bowen , Zhang Rong , Feng Tingyong
Published: October 2022

Episodic future thinking (EFT) refers to the critical ability that people construct vivid mental imagery about future events and pre-experience it, which helps with individual and group decision-making. Although EFT is generally believed to have a visual nature by theorists, little neuroscience evidence had been provided to verify this assumption. Here, by employing the approach of connectome-based predictive modeling (CPM) and graph-theoretical analysis, we analyzed resting-state functional brain image from 191 participants to predict their variability of EFT ability (leave-one-out cross-validation), and validated the results by applying different parcellation schemas and feature selection thresholds. At the connectome strength level, CPM-based analysis revealed that EFT ability could be predicted by the connectome strength of visual network. Further at the network level, graph-theoretical analysis showed that EFT ability could be predicted by the network efficiency of visual network. Moreover, these findings were replicated using different parcellation schemas and feature selection thresholds. These results robustly and collectively supported the visual network being the neural substrates underlying EFT ability from a comprehensive perspective of resting-state functional connectivity strength and the neural network. This study provides indications on how the function of visual network supports EFT ability, and helps to understand the EFT ability from a neural basis perspective.
Expectation-Maximization enables Phylogenetic Dating under a Categorical Rate Model
Authors: Mai Uyen , Charvel Eduardo , Mirarab Siavash
Published: October 2022

Dating phylogenetic trees to obtain branch lengths in time unit is essential for many downstream applications but has remained challenging. Dating requires inferring substitution rates that can change across the tree. While we can assume to have information about a small subset of nodes from the fossil record or sampling times (for fast-evolving organisms), inferring the ages of the other nodes essentially requires extrapolation and interpolation. Assuming a clock model that defines a distribution over rates, we can formulate dating as a constrained maximum likelihood (ML) estimation problem. While ML dating methods exist, their accuracy degrades in the face of model misspecification where the assumed parametric statistical clock model vastly differs from the true distribution. Notably, existing methods tend to assume rigid, often unimodal rate distributions. A second challenge is that the likelihood function involves an integral over the continuous domain of the rates and often leads to difficult non-convex optimization problems. To tackle these two challenges, we propose a new method called Molecular Dating using Categorical-models (MD-Cat). MD-Cat uses a categorical model of rates inspired by non-parametric statistics and can approximate a large family of models by discretizing the rate distribution into k categories. Under this model, we can use the Expectation-Maximization (EM) algorithm to co-estimate rate categories and branch lengths time units. Our model has fewer assumptions about the true clock model than parametric models such as Gamma or LogNormal distribution. Our results on two simulated and real datasets of Angiosperms and HIV and a wide selection of rate distributions show that MD-Cat is often more accurate than the alternatives, especially on datasets with nonmodal or multimodal clock models.

Code availability

The MD-Cat software is available athttps://github.com/uym2/MD-Cat.

Data availability

Data are available on Githubhttps://github.com/uym2/MD-Cat-paperand Dryadhttps://doi.org/10.5061/dryad.pk0p2ngs0.
The differential impacts of dataset imbalance in single-cell data integration
Authors: Maan Hassaan , Zhang Lin , Yu Chengxin , Geuenich Michael , Campbell Kieran R , Wang Bo
Published: October 2022

Single-cell transcriptomic data measured across distinct samples has led to a surge in computational methods for data integration. Few studies have explicitly examined the common case of cell-type imbalance between datasets to be integrated, and none have characterized its impact on downstream analyses. To address this gap, we developed theIniquitatepipeline for assessing the stability of single-cell RNA sequencing (scRNA-seq) integration results after perturbing the degree of imbalance between datasets. Through benchmarking 5 state-of-the-art scRNA-seq integration techniques in 1600 perturbed integration scenarios for a multi-sample peripheral blood mononuclear cell (PBMC) dataset, our results indicate that sample imbalance has significant impacts on downstream analyses and the biological interpretation of integration results. We observed significant variation in clustering, cell-type classification, marker gene-based annotation, and query-to-reference mapping in imbalanced settings. Two key factors were found to lead to quantitation differences after scRNA-seq integration - the cell-type imbalance within and between samples (relative cell-type support) and the relatedness of cell-types across samples (minimum cell-type center distance). To account for evaluation gaps in imbalanced contexts, we developed novel clustering metrics robust to sample imbalance, including the balanced Adjusted Rand Index (bARI) and balanced Adjusted Mutual Information (bAMI). Our analysis quantifies biologically-relevant effects of dataset imbalance in integration scenarios and introduces guidelines and novel metrics for integration of disparate datasets. The Iniquitate pipeline and balanced clustering metrics are available athttps://github.com/hsmaan/Iniquitateandhttps://github.com/hsmaan/balanced-clustering, respectively.
Preprint peer review enhances undergraduate biology students’ disciplinary literacy and sense of belonging in STEM
Authors: Otto Josie L. , McDowell Gary S , Balgopal Meena M. , Lijek Rebeccah S
Published: October 2022

Undergraduate education on science publishing and peer review is limited compared to the focus on experimental research. Since peer review is integral to the scientific process and central to the identity of a scientist, we envision a paradigm shift that makes teaching peer review integral to undergraduate science education, and hypothesize that this may facilitate the development of students’ scientific literacy and identity formation. To this end, we developed a curriculum for biology undergraduates to learn about the mechanisms of peer review, then write and publish their own peer reviews as a way to authentically join the scientific community of practice. The curriculum was implemented as a semester-long intervention in one class and as a module intervention embedded into a discipline-based class on vaccines. Before and after both interventions, we measured students’ scientific literacy, including peer review ability, using quantitative methods. We also carried out a longitudinal qualitative assessment of students’ perceptions of their scientific literacy and identity using thematic analysis of students’ writing. Here, we present data on the improvement in peer review ability of undergraduates in both classes, and data on the curriculum’s interrelated impact on students’ development of scientific literacy, identity, and belonging in academic and professional spaces. These data suggest that undergraduates can and should be trained in peer review to foster the interrelated development of their scientific literacy, scientific identity, and sense of belonging in science.
Neuronal E93 regulates metabolic homeostasis
Authors: Yip Cecilia , Wyler Steven , Yamazaki Shin , Rothenfluh Adrian , Lee Syann , You Young-Jai , Elmquist Joel
Published: October 2022

Metamorphosis is a transition from growth to reproduction, through which an animal adopts adult behavior and metabolism. Yet the mechanisms underlying the switch is unclear. Here we report that neuronalE93, a transcription factor essential for metamorphosis, regulates the adult metabolism and circadian rhythm inDrosophila melanogaster. WhenE93is specifically knocked down in neurons, the flies become hyperphagic and obese with increased energy stores and disrupted circadian rhythms. A screen of Gal4 lines targeting subsets of neurons and endocrine cells identified neurons producing GABA and myoinhibitory peptide (MIP) as the main sites ofE93action. Knockdown of the ecdysone receptor specifically in MIP neurons partly phenocopies the MIP neuron-specific knockdown ofE93suggesting the steroid signal coordinates adult metabolism viaE93. The circadian disruption caused by neuronal knockdown ofE93is also observed whenE93is knockdown in GABA and MIP neurons. Based on these results we suggest that neuronalE93is a key switch for metabolic transition representing an intersectional node between metabolism and circadian biology.
Genome-Wide Epigenomic Profiling of Primary Non-Small Cell Lung Cancer Reveals Specific and Recurrent DNA Methylation Alterations in Smoker Versus Never-Smoker Patients
Authors: Karlow Jennifer A. , Pehrsson Erica C. , Xing Xiaoyun , Watson Mark , Devarakonda Siddhartha , Govindan Ramaswamy , Wang Ting
Published: October 2022

Epigenetic alterations are widespread in cancer and can complement genetic alterations to influence cancer progression and treatment. To better understand the potential contribution of DNA methylation alterations to tumor phenotype in non-small cell lung cancer (NSCLC) in both smoker and never-smoker patients, we performed a comprehensive, genome-wide profiling of DNA methylation in 17 primary non-small cell lung cancer and 10 matched normal lung samples using the complementary methylation assays MeDIP-seq and MRE-seq. Compared to patient-matched non-malignant lung tissue, we report recurrent methylation changes of several gene promoters, many previously implicated in cancer, including FAM83A and SEPT9 (hypomethylation), and PCDH7, NKX2-1, and SOX17 (hypermethylation). Although smoker and never-smoker patients shared many methylation changes, several were specific and recurrent within a particular smoking status. In particular, never-smokers displayed a greater proportion of hypoDMRs and exhibited a greater number of recurrently hypomethylated promoters, including the promoter of the oncogene ASPSCR1, and others previously linked to cancer, including TOP2A, DPP9, and USP39. Methylation changes outside of promoters were also widespread and often recurrent, particularly the loss of methylation over repetitive elements, highly enriched for ERV1 subfamilies. Recurrent hypoDMRs were also enriched for several transcription factor (TF) binding motifs, often for genes involved in signaling and cell proliferation, including 71% encoding a binding site of NKX2-1, which was found to be significantly upregulated in TCGA LUAD samples. Furthermore, the overwhelming majority of DMRs identified in this study were found to reside in an active chromatin state in at least one tissue profiled using the Roadmap Epigenome data, suggesting that methylation changes may contribute to altered regulatory programs through the adaptation of cell type-specific expression programs.
MAST: Phylogenetic Inference with Mixtures Across Sites and Trees
Authors: Wong Thomas KF , Cherryh Caitlin , Rodrigo Allen G , Hahn Matthew W , Minh Bui Quang , Lanfear Robert
Published: October 2022

Hundreds or thousands of loci are now routinely used in modern phylogenomic studies. Concatenation approaches to tree inference assume that there is a single topology for the entire dataset, but different loci may have different evolutionary histories due to incomplete lineage sorting, introgression, and/or horizontal gene transfer; even single loci may not be treelike due to recombination. To overcome this shortcoming, we introduce the mixture across sites and trees (MAST) model, which uses a mixture of bifurcating trees to represent multiple histories in a single concatenated alignment. The MAST model allows each tree to have its own topology, branch lengths, substitution model, nucleotide or amino acid frequencies, and model of rate heterogeneity across sites. We implemented the MAST model in a maximum-likelihood framework in the popular phylogenetic software, IQ-TREE. Simulations show that we can accurately recover the true model parameters, including branch lengths and tree weights (i.e. frequencies) for a given set of tree topologies. We also show that we can use standard statistical inference approaches to reject a single-tree model when data are simulated under multiple trees (and vice versa). We applied the MAST model to multiple primate datasets and found that it can recover the signal of incomplete lineage sorting in the Great Apes, as well as the asymmetry in minor trees caused by introgression among several macaque species. When applied to a dataset of four Platyrrhine species for which standard concatenated maximum likelihood and gene tree approaches disagree, we find that MAST gives the highest weight to the tree favored by gene tree approaches. These results suggest that the MAST model is able to analyse a concatenated alignment using maximum likelihood, while avoiding some of the biases that come with assuming there is only a single tree. The MAST model can therefore offer unique biological insights when applied to datasets with multiple evolutionary histories. We discuss how it can be extended in the future.
User-friendly high-content imaging analysis on a single desktop: R package H5CellProfiler
Authors: Wink Steven , Burger Gerhard A. , Le Dévédec Sylvia E. , Beltman Joost B. , van de Water Bob
Published: October 2022

Technological development has led to ever-increasing amounts of data in high-content screening. For utilizing such data in an efficient, thorough, and user-friendly manner we developed the R package H5CellProfiler. H5CellProfiler is based on R packages data.table, ggvis, ggplot2 and shiny. H5CellProfiler launches a browser that allows scientists to analyze large single-cell datasets and make statistical summaries and graphs on their local desktop in a fast and memory-efficient manner. In addition, single-cell track labels are calculated and broken tracks are re-connected based on user-defined thresholds resulting in unique sets of annotated tracks.
Elephant trunks use an adaptable prehensile grip
Authors: Schulz Andrew K. , Reidenberg Joy S. , Wu Jia Ning , Tang Cheuk Ying , Seleb Benjamin , Mancebo Josh , Elgart Nathan , Hu David L.
Published: October 2022

Elephants have long been observed to grip objects with their trunk, but little is known about how they adjust their strategy for different weights. In this study, we challenge a female African elephant at Zoo Atlanta to lift 20 to 60 kg barbell weights with only its trunk. We measure the trunk’s shape and wrinkle geometry from a frozen elephant trunk at the Smithsonian. We observe several strategies employed to accommodate heavier weights, including accelerating less, orienting the trunk more vertically, and wrapping the barbell with a greater trunk length. Mathematical models show that increasing barbell weights are associated with constant trunk tensile force and an increasing barbell-wrapping surface area due to the trunk’s wrinkles. Our findings may inspire the design of more adaptable soft robotic grippers that can improve grip using surface morphology such as wrinkles.
Multiple Postsynaptic Protein Levels in Adult Superior Colliculus Are Unaffected by Dark Rearing from Birth
Authors: Juvale Parag S. , Mudd David B. , Shree Nitheyaa , Pallas Sarah L.
Published: October 2022

Visual deprivation by dark rearing in kittens and monkeys delays visual pathway development and prolongs the critical period. In contrast, receptive fields (RFs) in superior colliculus (SC) of Syrian hamsters(Mesocricetus auratus)refine normally with spontaneous activity alone, requiring only brief juvenile visual experience to maintain refined RFs in adulthood (Carrasco et al., 2005). Extending dark rearing past puberty leads to lower GAD and GABA levels due to reduced BDNF-TrkB signaling, resulting in RF re-enlargement (Carrasco et al., 2011; Mudd et al., 2019). Previous studies in kittens and monkeys have reported that dark rearing is associated with changes in both GABA ligand and GABAAreceptor levels. Given the reduced GABA levels in SC of dark reared adult hamsters, we asked if dark rearing also causes changes in GABAAreceptor levels. We examined expression of GABAAreceptor subunits, their anchoring protein gephyrin, and the cation-chloride co-transporters KCC2 and NKCC1 in dark reared hamsters. Surprisingly, we found that dark rearing from birth until puberty had no effect on the levels of any of these postsynaptic elements, revealing a new form of maladaptive, presynaptic only inhibitory plasticity in which, rather than extending the critical period as seen in kittens and monkeys, hamster receptive fields refine normally and then lose refinement in adulthood. These results suggest that attempts to increase plasticity in adulthood for rehabilitation or recovery from injury should consider the possibility of unintended negative consequences. In addition, our results demonstrate the interesting finding that changes in neurotransmitter levels are not necessarily coordinated with changes in postsynaptic components.
Enzymatic reactions of AGO4 in RNA-directed DNA methylation: siRNA duplex loading, passenger strand elimination, target RNA slicing and sliced target retention
Authors: Wang Feng , Huang Hsiao-Yun , Huang Jie , Singh Jasleen , Pikaard Craig S.
Published: October 2022

RNA-directed DNA methylation in plants is guided by 24 nt siRNAs generated in parallel with 23 nt RNAs of unknown function. We show that 23 nt RNAs function as passenger strands during 24 nt siRNA incorporation into AGO4. The 23 nt RNAs are then sliced into 11 and 12 nt fragments, with 12 nt fragments remaining associated with AGO4. Slicing recapitulated with recombinant AGO4 and synthetic RNAs reveals that siRNAs of 21-24 nt, with any 5’ terminal nucleotide, can guide slicing, with sliced RNAs then retained by AGO4. In vivo, RdDM target locus RNAs that copurify with AGO4 also display a sequence signature of slicing. Comparing plants expressing slicing-competent versus slicing-defective AGO4 shows that slicing elevates cytosine methylation levels at virtually all RdDM loci. We propose that siRNA passenger strand elimination and AGO4 tethering to sliced target RNAs are distinct modes by which AGO4 slicing enhances RNA-directed DNA methylation.
Gene knock-outs in human CD34+ hematopoietic stem and progenitor cells and in the human immune system of mice
Authors: Kuppers Daniel A. , Linton Jonathan , Espinosa Sergio Ortiz , McKenna Kelly M. , Rongvaux Anthony , Paddison Patrick J.
Published: October 2022

Human CD34+hematopoietic stem and progenitor cells (HSPCs) are a standard source of cells for clinical HSC transplantations as well as experimental xenotransplantation to generate “humanized mice”. To further extend the range of applications of these humanized mice, we developed a protocol to efficiently edit the genomes of human CD34+HSPCs before transplantation. In the past, manipulating HSPCs has been complicated by the fact that they are inherently difficult to transduce with lentivectors, and rapidly lose their stemness and engraftment potential duringin vitroculture. However, with optimized nucleofection of sgRNA:Cas9 ribonucleoprotein complexes, we are now able to edit a candidate gene in CD34+HSPCs with almost 100% efficiency, and without affecting their potential for engraftment and multilineage differentiation in mice. The result is a humanized mouse from which we knocked out a gene of interest from their human immune system.
A multiparametric anti-aging CRISPR screen uncovers a role for BAF in protein translation
Authors: Breusegem Sophia Y. , Houghton Jack , Romero-Bueno Raquel , Fragoso-Luna Adrián , Kentistou Katherine A. , Ong Ken K. , Janssen Anne F. J. , Bright Nicholas A. , Riedel Christian G. , Perry John R. B. , Askjaer Peter , Larrieu Delphine
Published: October 2022

Progeria syndromes are very rare, incurable premature aging conditions recapitulating most aging features. Here, we report the first whole genome, multiparametric CRISPR anti-aging screen, identifying 43 new genes that can reverse multiple aging phenotypes in progeria. The screen was implemented in fibroblasts from Néstor- Guillermo Progeria Syndrome (NGPS) patients, carrying a homozygous p.Ala12Thr mutation in barrier-to-autointegration factor (BAF A12T). The hits were enriched for genes involved in protein translation, protein and RNA transport and osteoclast formation. We further confirmed that BAF A12T drives increased protein translation and translational errors that could directly contribute to premature aging in patients. This work has highlighted the power of multiparametric whole genome synthetic rescue screens to identify new anti-aging genes and uncover novel biology behind progeria-associated cellular dysfunction.

One-Sentence Summary

A whole genome multiparametric screen in progeria identifies new pathways that can reverse cellular aging phenotypes.
Tuning of cytokine signaling through imbalanced abundances of receptors and kinases
Authors: Sta Léa , Voisinne Guillaume , Cotari Jesse , Adamer Michael F. , Molina-París Carmen , Altan-Bonnet Grégoire
Published: October 2022

Cells use surface receptors to detect extra-cellular ligands (e.g., growth factors or cytokines) and engender signaling cascades. We explore the effect of cell-to-cell variability in receptor subunit copy number for cells responding to γc cytokines (e.g., IL-2, IL-7 and IL-15). We find that primary T cells expressing higher levels of the common γc receptor chain have weaker responses to IL-7, both in terms of lowered STAT5 phosphorylation amplitude and higher EC50. A mathematical model that accounts for abundance imbalance (e.g., insufficient expression of JAK kinases compared to the number of receptors, or γc competition for other receptor subunit chains) predicts the formation of non-signalling complexes, consistent with the observed cellular behaviour. This type of built-in limit on signaling responses illustrates how phenotypic heterogeneity generates biological functional diversity.

Significance Statement

Cells rely on cytokines to coordinate their activation, differentiation, proliferation and survival. In particular, γc cytokines (interleukins IL-2, 4, 7, 9, 15, and 21) regulate the fate of leukocytes. The signaling cascade induced by these cytokines is relatively simple, and involves the phosphorylation of receptor-associated Janus-like kinases (JAK). Here, we explore the cell-to-cell variability of cytokine responses in primary mouse T cells, and find a paradoxical and quantitative imprint of receptor expression levels and other signaling components. For instance, high abundance of the common γc chain reduces cytokine responses (both in terms of signaling amplitudes and characteristic cytokine concentrations triggering 50% of the response). We develop mathematical models to quantify how limited abundances of signaling components (e.g., JAK or other cytokine receptor subunit chains) may explain our experimental observations. We conclude by generalizing this observation of cell-to-cell signaling variability to other ligand-receptor-kinase systems.
Selecting a new electron transfer pathway for nitrogen fixation uncovers an electron bifurcating-like enzyme involved in anaerobic aromatic compound degradation
Authors: Lewis Nathan M. , Sarne Abigail , Fixen Kathryn R.
Published: October 2022

Nitrogenase is the key enzyme involved in nitrogen fixation and uses low potential electrons delivered by ferredoxin (Fd) or flavodoxin (Fld) to reduce dinitrogen gas (N2) to produce ammonia and hydrogen. Although the phototrophic alphaproteobacterium Rhodopseudomonas palustris encodes multiple proteins that can reduce Fd, the FixABCX complex is the only one shown to support nitrogen fixation, and R. palustris Fix- mutants grow poorly in nitrogen-fixing conditions. To investigate how native electron transfer chains (ETCs) can be redirected towards nitrogen fixation, we leveraged the strong selective pressure of nitrogen limitation to isolate a suppressor of R. palustris ΔfixC that grows under nitrogen-fixing conditions. We found two mutations were required to restore growth under nitrogen-fixing conditions in the absence of functional FixABCX. One mutation was in the gene encoding the primary Fd involved in nitrogen fixation, fer1, and the other mutation was in aadN, which encodes a homolog of NAD+-dependent Fd:NADPH oxidoreductase (Nfn). We present evidence that AadN plays a role in electron transfer to benzoyl-CoA reductase, the key enzyme involved in anaerobic aromatic compound degradation. Our data support a model where the ETC for anaerobic aromatic compound degradation was re-purposed to support nitrogen fixation in the suppressor strain.

Importance

There is increasing evidence that protein electron carriers like Fd have evolved to form specific partnerships with select electron donors and acceptors to keep native electron transfer pathways insulated from one another. This makes it challenging to integrate a Fd-dependent pathway like biological nitrogen fixation into non-nitrogen-fixing organisms and provide the high-energy reducing power needed to fix nitrogen. Here we show that amino acid substitutions in an electron donor for anaerobic aromatic compound degradation and a Fd involved in nitrogen fixation enabled electron transfer to nitrogenase. This work provides a model system to understand electron transfer chain specificity and how new electron transfer pathways can be evolved for biotechnologically valuable pathways like nitrogen fixation.
A Novel Mouse Model that Recapitulates the Heterogeneity of Human Triple Negative Breast Cancer
Authors: Doha Zinab O. , Wang Xiaoyan , Calistri Nicholas , Eng Jennifer , Daniel Colin J. , Ternes Luke , Kim Eun Na , Pelz Carl , Munks Michael , Betts Courtney , Kirchberger Nell , Kwon Sunjong , Bucher Elmar , Li Xi , Waugh Trent , Pietenpol Jennifer A. , Sanders Melinda E. , Mills Gordon , Chin Koei , Chang Young Hwan , Coussens Lisa M. , Gray Joe W. , Heiser Laura M. , Sears Rosalie C.
Published: October 2022

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new targeted therapies, but few TNBC mouse models exist. Here, we developed a novel TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl murine model develops TN mammary tumors that display histological and molecular features commonly found in human TNBC. We performed deep omic analyses on Myc;Ptenfl tumors including machine learning for morphologic features, bulk and single-cell RNA-sequencing, multiplex immunohistochemistry and single-cell phenotyping. Through comparison with human TNBC, we demonstrated that this new genetic mouse model develops mammary tumors with differential survival that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC; providing a unique pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Statement of significance

The development of cancer models that mimic triple-negative breast cancer (TNBC) microenvironment complexities is critical to develop effective drugs and enhance disease understanding. This study addresses a critical need in the field by identifying a murine model that faithfully mimics human TNBC heterogeneity and establishing a foundation for translating preclinical findings into effective human clinical trials.
Brevicidine, a bacterial non-ribosomally produced cyclic antimicrobial lipopeptide with a uniquemodus operandi
Authors: Zhao Xinghong , Zhong Xinyi , Wan Hongping , Liu Lu , Song Xu , Zou Yuanfeng , Li Lixia , Jia Renyong , Lin Juchun , Tang Huaqiao , Ye Gang , Yang Jianqing , Zhao Shan , Lang Yifei , Yin Zhongqiong , Kuipers Oscar P.
Published: October 2022

Due to the accelerated appearance of antibiotic-resistant (AMR) pathogens in clinical infections, new first-in-class antibiotics, operating via novel modes of action, are desperately-needed. Brevicidine, a bacterial non-ribosomally produced cyclic lipopeptide, has shown potent and selective antimicrobial activity against Gram-negative pathogens. However, before our investigations, little was known about how brevicidine exerts its potent bactericidal effect against Gram-negative pathogens. In this study, we find that brevicidine has potent antimicrobial activity against AMREnterobacteriaceaepathogens, with a MIC value ranging between 0.5μM (0.8mg/L) and 2μM (3.0mg/L). In addition, brevicidine showed potent anti-biofilm activity against theEnterobacteriaceaepathogens, with same 100% inhibition and 100% eradication concentration of 4μM (6.1mg/L). Further mechanistic studies showed that brevicidine exerts its potent bactericidal activity via interacting with lipopolysaccharide in the outer membrane, targeting phosphatidylglycerol and cardiolipin in the inner membrane, and dissipating the proton motive force of bacteria. This results in metabolic perturbation, including inhibition of adenosine triphosphate synthesis, inhibits the dehydrogenation of nicotinamide adenine dinucleotides, accumulation of reactive oxygen species in bacteria, and inhibition of protein synthesis. Lastly, brevicidine showed a good therapeutic effect in a mouse peritonitis–sepsis model. Our findings pave the way for further research on clinical applications of brevicidine, to combat the prevalent infections caused by AMR Gram-negative pathogens worldwide.
BUB-1 and CENP-C recruit PLK-1 to Control Chromosome Alignment and Segregation During Meiosis I inC. elegansOocytes
Authors: Taylor Samuel J.P. , Borja Laura Bel , Soubigou Flavie , Houston Jack , Cheerambathur Dhanya K. , Pelisch Federico
Published: October 2022

Phosphorylation is a key post-translational modification that is utilised in many biological processes for the rapid and reversible regulation of protein localisation and activity. Polo-like kinase 1 (PLK-1) is essential for both mitotic and meiotic cell divisions, with key functions being conserved in eukaryotes. The roles and regulation of PLK-1 during mitosis have been well characterised. However, the discrete roles and regulation of PLK-1 during meiosis have remained obscure. Here, we usedCaenorhabditis elegans (C. elegans)oocytes to show that PLK-1 plays distinct roles in meiotic spindle assembly and/or stability, chromosome alignment and segregation, and polar body extrusion during meiosis I. Furthermore, by a combination of live imaging and biochemical analysis we identified the chromosomal recruitment mechanisms of PLK-1 duringC. elegansoocyte meiosis. The spindle assembly checkpoint kinase BUB-1 directly recruits PLK-1 to the kinetochore and midbivalent while the chromosome arm population of PLK-1 depends on a direct interaction with the centromeric-associated protein CENP-CHCP-4. We found that perturbing both BUB-1 and CENP-CHCP-4recruitment of PLK-1 leads to severe meiotic defects, resulting in highly aneuploid oocytes. Overall, our results shed light on the roles played by PLK-1 during oocyte meiosis and provide a mechanistic understanding of PLK-1 targeting to meiotic chromosomes.
Plant Breeding in the face of climate change
Authors: Messina Carlos D , Cooper Mark
Published: October 2022

Climate change will have a net negative and inequitable impact on agriculture. Genetics for crop improvement ranks in the top set of technologies that can contribute to human adaptation to climate change. However, a framework for how to breed crops for climate change adaptation is lacking. Here we propose a framework to develop new genotype (G) x management (M) technologies (G x M) to adapt to climate change, and to transition from current to future G x M technologies in a way that future food security does not come at the expense of current food security. The framework integrate genomic, agronomic, and environmental (E) predictors to accomplish two critical goals: 1-predict emergent phenotypes that stems from the dynamic interplay between G, E and M, and thus enable the breeder to consider the behavior of new genetic and trait combinations in environments that plants have not been exposed or tested before, and 2-identify G x M technologies that could increase food and nutritional security while regenerating natural and production resources. We highlight the need to invest in artificial intelligence and information technologies for breeders to harness multiple sources of information to create G x M technologies to address the diverse cultural and geographically granular societal needs.
Hexanematic crossover in epithelial monolayers depends on cell adhesion and cell density
Authors: Eckert Julia , Ladoux Benoît , Mège René-Marc , Giomi Luca , Schmidt Thomas
Published: October 2022

Changes in tissue geometry during developmental processes are associated with collective migration of cells. Recent experimental and numerical results suggest that these changes could leverage on the coexistence of nematic and hexatic orientational order at different length scales. How this multiscale organization is affected by the material properties of the cells and their substrate is presently unknown. In this study, we address these questions in monolayers of Madin-Darby canine kidney cells having various cell densities and molecular repertoires. At small length scales, confluent monolayers are characterized by a prominent hexatic order, independent of the presence of E-cadherin, monolayer density, and underlying substrate stiffness. However, all three properties affect the meso-scale tissue organization. The length scale at which hexatic order transits to nematic order, the “hexanematic” crossover scale, strongly depends on cell-cell adhesions and correlates with monolayer density. Our study demonstrates how epithelial organization is affected by mechanical properties, and provides a robust description of tissue organization during developmental processes.
Inferring pathways of oxidative folding from pre-folding free energy landscapes of disulfide-rich toxins
Authors: Mansbach Rachael A. , Patel Lara A. , Watson Natalya A. , Kubicek-Sutherland Jessica Z. , Gnanakaran S.
Published: October 2022

Short, cysteine-rich peptides can exist in stable or metastable structural ensembles due to the number of possible patterns of formation of their disulfide bonds. One interesting subset of this peptide group is the coonotoxins, which are produced by aquatic snails in the familyConidae. Theµconotoxins, which are antagonists and blockers of the voltage-gated sodium channel, exist in a folding spectrum: on one end of the spectrum are more hirudin-like folders, which form disulfide bonds and then reshuffle them, leading to an ensemble of kinetically trapped isomers–and on the other end are more BPTI-like folders–which form the native disulfide bonds one by one in a particular order, leading to a preponderance of conformations existing in a single stable state. In this article, we employ the composite diffusion map approach to study the unified free energy surface of pre-foldingµ-conotoxin equilibrium. We identify the two most important nonlinear collective modes of the unified folding landscape and demonstrate that in the absence of their disulfides, the conotoxins can be thought of as largely disordered polymers. A small increase in the number of hydrophobic residues in the protein shifts the free energy landscape towards hydrophobically collapsed coil conformations responsible for cysteine proximity in hirudin-like folders, compared to semi-extended coil conformations with more distal cysteines in BPTI-like folders. Overall, this work sheds important light on the folding processes and free energy landscapes of cysteinerich peptides and demonstrates the extent to which sequence and length contribute to these landscapes.
Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo
Authors: May Dennis , Yun Sangwon , Gonzalez David , Park Sangbum , Chen Yanbo , Lathrop Elizabeth , Cai Biao , Xin Tianchi , Zhao Hongyu , Wang Siyuan , Gonzalez Lauren E. , Cockburn Katie , Greco Valentina
Published: October 2022

Stem cell differentiation requires dramatic changes in gene expression and global remodeling of chromatin architecture. How and when chromatin remodels relative to the transcriptional, behavioral, and morphological changes during differentiation remain unclear, particularly in an intact tissue context. Here, we develop a quantitative pipeline which leverages fluorescently-tagged histones and longitudinal imaging to track large-scale chromatin compaction changes within individual cells in a live mouse. Applying this pipeline to epidermal stem cells, we reveal that cell-to-cell chromatin compaction heterogeneity within the stem cell compartment emerges independent of cell cycle status, and instead is reflective of differentiation status. Chromatin compaction state gradually transitions over days as differentiating cells exit the stem cell compartment. Moreover, establishing live imaging of keratin-10 nascent RNA, which marks the onset of stem cell differentiation, we find that keratin-10 transcription is highly dynamic and largely precedes the global chromatin compaction changes associated with differentiation. Together, these analyses reveal that stem cell differentiation involves dynamic transcriptional states and gradual chromatin rearrangement.
Targeting tumour-intrinsic neural vulnerabilities of glioblastoma
Authors: Lee Sohyon , Weiss Tobias , Bühler Marcel , Mena Julien , Lottenbach Zuzanna , Wegmann Rebekka , Sun Miaomiao , Bihl Michel , Augustynek Bartłomiej , Baumann Sven , Goetze Sandra , van Drogen Audrey , Pedrioli Patrick , Kirschenbaum Daniel , Vasella Flavio , Rushing Elisabeth J. , Wollscheid Bernd , Hediger Matthias A. , Michael Weller , Snijder Berend
Published: October 2022

Glioblastoma is the most common yet deadliest primary brain cancer1. The neural behavior of glioblastoma, including the formation of synaptic circuitry and tumour microtubes, is increasingly understood to be pivotal for disease manifestation2–9. Nonetheless, the few approved treatments for glioblastoma target its oncological nature, while its neural vulnerabilities remain incompletely mapped and clinically unexploited. Here, we systematically survey the neural molecular dependencies and cellular heterogeneity across glioblastoma patients and diverse model systems. In 27 surgical patient samples, we identify cancer cell morphologies indicative of poor prognosis, and discover repurposable neuroactive drugs with anti-glioblastoma efficacy by image-based drug screening. Glioblastoma cells exhibit functional dependencies on highly expressed neuroactive drug targets, while interpretable molecular machine learning (COSTAR) reveals their downstream convergence on AP-1-driven tumour suppression. This drug-target connectivity signature is confirmed by accuratein silicodrug screening on >1 million compounds, as well as by multi-omic profiling of glioblastoma drug responses. Thus, Ca2+-driven AP-1 pathway induction represents a tumour-intrinsic vulnerability at the intersection of oncogenesis and neural activity-dependent signaling. Opportunities for clinical translation of this neural vulnerability are epitomized by the antidepressant Vortioxetine synergizing with current standard of care treatmentsin vivo. Together, the results presented here provide a mechanistic foundation and conceptual framework for the treatment of glioblastoma based on its neural origins.
EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation
Authors: Lee Jae Hyeon , Yadollahpour Payman , Watkins Andrew , Frey Nathan C. , Leaver-Fay Andrew , Ra Stephen , Cho Kyunghyun , Gligorijević Vladimir , Regev Aviv , Bonneau Richard
Published: October 2022

Designing proteins to achieve specific functions often requiresin silicomodeling of their properties at high throughput scale and can significantly benefit from fast and accurate protein structure prediction. We introduce EquiFold, a new end-to-end differentiable, SE(3)-equivariant, all-atom protein structure prediction model. EquiFold uses a novel coarse-grained representation of protein structures that does not require multiple sequence alignments or protein language model embeddings, inputs that are commonly used in other state-of-the-art structure prediction models. Our method relies on geometrical structure representation and is substantially smaller than prior state-of-the-art models. In preliminary studies, EquiFold achieved comparable accuracy to AlphaFold but was orders of magnitude faster. The combination of high speed and accuracy make EquiFold suitable for a number of downstream tasks, including protein property prediction and design.