bluuebunny/crossref_metadata_2025 huggingface dataset:
Relative abundance data can misrepresent heritability of the microbiome
Authors: Bruijning Marjolein , Ayroles Julien F. , Henry Lucas P. , Koskella Britt , Meyer Kyle M. , Metcalf C. Jessica E.
Published: May 2022

Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this question can be addressed by estimating the heritability (h2) of the microbiome – the proportion of variance in the abundance of each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample. We derived an analytical approximation for the heritability that one obtains when using such relative abundances and we uncovered three problems: 1) The interdependency between taxa leads to imprecise heritability estimates. 2) Large sample size leads to high false discovery rates, overestimating the number of heritable taxa. 3) Microbial co-abundances lead to biased heritability estimates. We conclude that caution must be taken when interpreting heritability estimates and comparing values across studies.
Reducing CRISPR dark matter reveals a strong association between the bacterial membranome and CRISPR-Cas systems
Authors: Rubio Alejandro , Sprang Maximilian , Garzón Andrés , Pachón-Ibáñez Maria Eugenia , Pachón Jerónimo , Andrade-Navarro Miguel A. , Pérez-Pulido Antonio J.
Published: May 2022

Antimicrobial resistance is widely recognized as a serious global public health problem. To combat this threat, a thorough understanding of bacterial genomes is necessary. The current wide availability of bacterial genomes provides us with an in-depth understanding of the great variability of dispensable genes and their relationship with antimicrobials. Some of these accessory genes are those involved in CRISPR-Cas systems, which are acquired immunity systems that are present in part of bacterial genomes. They prevent viral infections through small DNA fragments called spacers. But the vast majority of these spacers have not yet been associated with the virus they recognize, and this has been named CRISPR dark matter. By analyzing the spacers of tens of thousands of genomes from six bacterial species highly resistant to antibiotics, we have been able to reduce the CRISPR dark matter from 80-90% to as low as 15% in some of the species. In addition, we have observed that, when a genome presents CRISPR-Cas systems, this is accompanied by particular collections of membrane proteins. Our results suggest that when a bacterium presents membrane proteins that make it compete better in its environment, and these proteins are in turn receptors for specific phages, it would be forced to acquire CRISPR-Cas immunity systems to avoid infection by these phages.
Donor strand complementation, isopeptide bonds and glycosylation reinforce highly resilient archaeal thread filaments
Authors: Gaines Matthew C. , Isupov Michail N. , Sivabalasarma Shamphavi , Haque Risat Ul , McLaren Mathew , Tripp Patrick , Neuhaus Alexander , Gold Vicki , Albers Sonja-Verena , Daum Bertram
Published: May 2022

Pili are ubiquitous filamentous surface extensions that play crucial roles for bacterial and archaeal cellular processes such as adhesion, biofilm formation, motility, cell-cell communication, DNA uptake and horizontal gene transfer to name a few. Here we report on the discovery and structure of the archaeal thread – a remarkably stable archaeal pilus that belongs to a so-far largely unknown class of protein filaments. We find that the filament is highly glycosylated and interconnected via donor strand complementation, as well as isopeptide bonds, reminiscent of bacterial type I pili. Despite striking structural similarity with bacterial type-1 pili, archaeal threads appear to have evolved independently and are likely assembled by a markedly distinct mechanism.
Assessing pyrethroid resistance status in the Culex pipiens complex (Diptera: Culicidae) from the northwest suburbs of Chicago, Illinois using Cox regression of bottle bioassays and other detection tools
Authors: Burgess Edwin R. , Lopez Kristina , Irwin Patrick , Jaeger Collin P. , Estep Alden S.
Published: May 2022

Culex pipiens complex is an important vector of epizootic and zoonotic pathogens, including West Nile virus. Chicago, Illinois and its suburbs have suffered high incidence of human West Nile virus infections in the past. This makes abatement programs in and around the Chicago area an essential service. The control of Cx. pipiens is often complicated by rapidly evolving resistance to pyrethroids, which are the most widely used chemical class in US mosquito abatement programs. The present study assessed Sumithrin® resistance in Cx. pipiens collected from five locations around Cook County, Illinois, neighboring the city limits of Chicago. According to CDC guidelines, samples from all five locations demonstrated some resistance to Sumithrin®. When assessed with Anvil®, a formulated product made of Sumithrin® synergized with piperonyl butoxide, susceptibility was rescued in mosquitoes from three out of the five locations, suggesting involvement of mixed-function oxidases and/or carboxylesterases in Sumithrin® resistance at these locations. Not all locations had susceptibility rescued by Anvil®, but these locations had relatively low knockdown resistance allele frequencies, suggesting that mechanisms other than knockdown resistance may be involved. Enzyme activities did not reveal any marked trends that could be related back to mortality in the bottle bioassays, which highlights the need for multiple types of assays to infer enzymatic involvement in resistance. Future directions in pyrethroid resistance management in Chicago area Cx. pipiens are discussed.
Mechanical confinement and DDR1 signalling synergise to regulate collagen-induced apoptosis in rhabdomyosarcoma cells
Authors: Gonzalez-Molina Jordi , Kirchhof Katharina Miria , Rathod Bhavik , Moyano-Galceran Lidia , Calvo-Noriega Maria , Kokaraki Georgia , Bjørkøy Astrid , Ehnman Monika , Carlson Joseph W. , Lehti Kaisa
Published: May 2022

Fibrillar collagens promote cell proliferation, migration, and survival in various epithelial cancers and are generally associated with tumour aggressiveness. However, the impact of fibrillar collagens on soft tissue sarcoma behaviour remains poorly understood.

Unexpectedly, we find here that fibrillar collagen-related gene expression is associated with favourable patient prognosis in rhabdomyosarcoma. By developing and using collagen matrices with distinct stiffness and in vivo-like microarchitectures, we uncover that the activation of DDR1 has pro-apoptotic and integrin β1 pro-survival function, specifically in 3D rhabdomyosarcoma cell cultures. We demonstrate that rhabdomyosarcoma cell-intrinsic or extrinsic matrix remodelling promotes cell survival. Mechanistically, we find that the 3D-specific collagen-induced apoptosis results from a dual DDR1-independent and a synergistic DDR1-dependent TRPV4-mediated response to mechanical confinement. Altogether, our results indicate that dense microfibrillar collagen-rich microenvironments are detrimental to rhabdomyosarcoma cells through an apoptotic response orchestrated by the induction of DDR1 signalling and mechanical confinement. This mechanism helps to explain the preference of rhabdomyosarcoma cells to grow in and metastasise to low fibrillar collagen microenvironments such as the lung.
A cocktail containing two synergetic antibodies broadly neutralizes SARS-CoV-2 and its variants including Omicron BA.1 and BA.2
Authors: Zhang Xinghai , Luo Feiyang , Zhang huajun , Guo Hangtian , Zhou Junhui , Li Tingting , Chen Shaohong , Song Shuyi , Shen Meiying , Wu Yan , Gao Yan , Han Xiaojian , Wang Yingming , Hu Chao , Lu Yuchi , Wang Wei , Wang Kai , Tang Ni , Jin Tengchuan , Yang Chengyong , Cheng Guofeng , Yang Haitao , Jin Aishun , Ji Xiaoyun , Gong Rui , Chiu Sandra , Huang Ailong
Published: May 2022

Neutralizing antibodies (NAbs) can prevent and treat infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, continuously emerging variants, such as Omicron, have significantly reduced the potency of most known NAbs. The selection of NAbs with broad neutralizing activities and the identification of conserved critical epitopes are still urgently needed. Here, we identified an extremely potent antibody (55A8) by single B-cell sorting from convalescent SARS-CoV-2-infected patients that recognized the receptor-binding domain (RBD) in the SARS-CoV-2 spike (S) protein. 55A8 could bind to wild-type SARS-CoV-2, Omicron BA.1 and Omicron BA.2 simultaneously with 58G6, a NAb previously identified by our group. Importantly, an antibody cocktail containing 55A8 and 58G6 (2-cocktail) showed synergetic neutralizing activity with a half-maximal inhibitory concentration (IC50) in the picomolar range in vitro and prophylactic efficacy in hamsters challenged with Omicron (BA.1) through intranasal delivery at an extraordinarily low dosage (25 μg of each antibody daily) at 3 days post-infection. Structural analysis by cryo-electron microscopy (cryo-EM) revealed that 55A8 is a Class III NAb that recognizes a highly conserved epitope. It could block angiotensin-converting enzyme 2 (ACE2) binding to the RBD in the S protein trimer via steric hindrance. The epitopes in the RBD recognized by 55A8 and 58G6 were found to be different and complementary, which could explain the synergetic mechanism of these two NAbs. Our findings not only provide a potential antibody cocktail for clinical use against infection with current SARS-CoV-2 strains and future variants but also identify critical epitope information for the development of better antiviral agents.
Achieving improved accuracy for imputation of ancient DNA
Authors: Ausmees Kristiina , Nettelblad Carl
Published: May 2022

Genotype imputation has the potential to increase the amount of information that can be gained from the often limited biological material available in ancient samples. As many widely used tools have been developed with modern data in mind, their design is not necessarily reflective of the requirements in studies of ancient DNA. Here, we investigate if an imputation method based on the full probabilistic Li and Stephens model of haplotype frequencies might be beneficial for the particular challenges posed by ancient data. We present an implementation called prophaser, and compare imputation performance to two alternative pipelines that have been used in the ancient DNA community based on the Beagle software. Considering empirical ancient data downsampled to lower coverages as well as present-day samples with artificially thinned genotypes, we show that the proposed method is advantageous at lower coverages, where it yields improved accuracy and ability to capture rare variation. The software prophaser is optimized for running in a massively parallel manner and achieved reasonable runtimes on the experiments performed when executed on a GPU.
Approximating Solutions of the Chemical Master Equation using Neural Networks
Authors: Sukys Augustinas , Öcal Kaan , Grima Ramon
Published: May 2022

The Chemical Master Equation (CME) provides an accurate description of stochastic biochemical reaction networks in well-mixed conditions, but it cannot be solved analytically for most systems of practical interest. While Monte Carlo methods provide a principled means to probe the system dynamics, their high computational cost can render the estimation of molecule number distributions and other numerical tasks infeasible due to the large number of repeated simulations typically required. In this paper we aim to leverage the representational power of neural networks to approximate the solutions of the CME and propose a framework for Neural Estimation of Stochastic Simulations for Inference and Exploration (Nessie). Our approach is based on training a neural network to learn the distributions predicted by the CME from a relatively small number of stochastic simulations, thereby accelerating computationally intensive tasks such as parameter exploration and inference. We show on biologically relevant examples that simple neural networks with one hidden layer are able to capture highly complex distributions across parameter space. We provide a detailed discussion of the neural network implementation and code for easy reproducibility.
Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome
Authors: Smith Rebecca H. , Glendinning Laura , Walker Alan W. , Watson Mick
Published: May 2022

Microbiome analysis is quickly moving towards high-throughput methods such as metagenomic sequencing. Accurate taxonomic classification of metagenomic data relies on reference sequence databases, and their associated taxonomy. However, for understudied environments such as the rumen microbiome many sequences will be derived from novel or uncultured microbes that are not present in reference databases. As a result, taxonomic classification of metagenomic data from understudied environments may be inaccurate. To assess the accuracy of taxonomic read classification, this study classified metagenomic data that had been simulated from cultured rumen microbial genomes from the Hungate collection. To assess the impact of reference databases on the accuracy of taxonomic classification, the data was classified with Kraken 2 using several reference databases. We found that the choice and composition of reference database significantly impacted on taxonomic classification results, and accuracy. In particular, NCBI RefSeq proved to be a poor choice of database. Our results indicate that inaccurate read classification is likely to be a significant problem, affecting all studies that use insufficient reference databases. We observe that adding cultured reference genomes from the rumen to the reference database greatly improves classification rate and accuracy. We also demonstrate that metagenome-assembled genomes (MAGs) have the potential to further enhance classification accuracy by representing uncultivated microbes, sequences of which would otherwise be unclassified or incorrectly classified. However, classification accuracy was strongly dependent on the taxonomic labels assigned to these MAGs. We therefore highlight the importance of accurate reference taxonomic information and suggest that, with formal taxonomic lineages, MAGs have the potential to improve classification rate and accuracy, particularly in environments such as the rumen that are understudied or contain many novel genomes.
Trimethylamine N-oxide (TMAO) enhances substrate mechanical stability probed by single molecule magnetic tweezers
Authors: Chaudhuri Deep , Chowdhury Debojyoti , Chakraborty Soham , Dutta Akashdeep , Mistry Ayush , Haldar Shubhasis
Published: May 2022

Trimethylamine N-oxide (TMAO) is a well-known osmolyte to stabilize the folded proteins through a variety of mechanisms. Since mechanical strength of proteins is a critical determinant of its stabilization, TMAO might play a relevant role by favoring its folding dynamics or by enhancing its mechanical stability. To address this question, we have performed the single-molecule magnetic tweezers experiment to explore the TMAO effect on two structurally distinct substrates-protein L and talin. We observed that TMAO increases the mechanical stability of these proteins through increasing their unfolding force. Additionally, we are able to demonstrate that TMAO retards the unfolding kinetics, while accelerating the refolding kinetics under force; which eventually tilts the energy landscape towards the folded state. Interestingly, this TMAO-enhanced protein folding generates mechanical work output upto ∼67 zJ, allowing the protein folding under higher force regime. Overall this TMAO-enhanced mechanical stability provides a significant implication to folding-induced structural stability of proteins.
On the Prediction of non-CG DNA Methylation
Authors: Sereshki Saleh , Omirou Michalis , Fasoula Dionysia , Lonardi Stefano
Published: May 2022

DNA cytosine methylation is an epigenetic modification that has a critical role in gene regulation and genome stability. DNA methylation can be detected and measured using sequencing instruments after sodium bisulfite conversion, but experiments can be expensive for large eukaryotic genomes. Sequencing non-uniformity and mapping biases can leave parts of the genome with low or no coverage, thus hampering the ability of obtaining DNA methylation levels for all cytosines. To address these limitations, several computational methods have been proposed that can predict DNA methylation from the DNA sequence around the cytosine, or from the methylation level of nearby cytosines. Most of these methods are, however, entirely focused on CG methylation in humans and other mammals. In this work, we study for the first time the problem of predicting cytosine methylation for CG, CHG, and CHH contexts on five plant species, either from the DNA primary sequence around the cytosine or the methylation levels of neighboring cytosines. In this framework, we also study (1) the cross-species prediction problem, i.e., the classification performance when training on one species and testing on another species, and the (2) the cross-context prediction problem, i.e., the classification performance when training on one context and testing on another context (within the same species). Finally, we show that providing the classifier with gene annotation information allows our classifier to outperform the prediction accuracy of state-of-the-art methods.
Action initiation and punishment learning differ from childhood to adolescence while reward learning remains stable
Authors: Pauli Ruth , Brazil Inti , Kohls Gregor , Klein-Flügge Miriam C. , Rogers Jack C. , Dikeos Dimitris , Dochnal Roberta , Fairchild Graeme , Fernández-Rivas Aranzazu , Herpertz-Dahlmann Beate , Hervas Amaia , Konrad Kerstin , Popma Arne , Stadler Christina , Freitag Christine M. , De Brito Stephane A. , Lockwood Patricia L.
Published: May 2022

Theoretical and empirical accounts suggest that adolescence is associated with heightened reward learning and impulsivity. Experimental tasks and computational models that can dissociate reward learning from the tendency to initiate actions impulsively (action initiation bias) are thus critical to characterise the mechanisms that drive developmental differences. However, existing work has rarely quantified both learning ability and action initiation, or it has tested small samples. Here, using computational modelling of a learning task collected from a large sample (N=742, 9-18 years, 11 countries), we tested differences in reward and punishment learning and action initiation from childhood to adolescence. Computational modelling revealed that whilst punishment learning rates increased with age, reward learning remained stable. In parallel, action initiation biases decreased with age. Results were similar when considering pubertal stage instead of chronological age. We conclude that heightened reward responsivity in adolescence can reflect differences in action initiation rather than enhanced reward learning.
habCluster: Identifying Geographical Boundary among Intraspecific Units Using Community Detection Algorithm in R
Authors: Zhang Chengcheng , Li Juan , Yang Biao , Dai Qiang
Published: May 2022

Conservation management for a species generally rests on intraspecific units, while identification of their geographic boundaries is necessary for the implementation. Intraspecific units can be discriminated using population genetic methods, yet an analytical approach is still lacking for detecting their geographic boundaries. Here, based on landscape connectivity, we present a geographical boundary delineation method, habCluster, using community detection algorithm. Community detection is an algorithm in graph theory used to identify clusters of highly connected nodes within a network. We assume that the habitat raster cells with better connections tend to form a continuous habitat patch than the others, thus making the range of an intraspecific unit. The method is tested on grey wolf (Canis lupus) habitat in Europe and on giant panda (Ailuropoda melanoleuca) habitat in China. The habitat suitability for grey wolves and giant pandas were evaluated using species distribution modeling. Each cell in the habitat suitability index (HSI) raster is treated as a node and directly connected with its eight neighbor cells. The edge weight between nodes is the distance between the center of them weighted by the average of their HSI values. We implement habCluster using R programming language with inline C++ code to speed up the computing. The geographical clusters detected were compared with the HSI maps for both species and with the nature reserves for giant panda. We found the boundaries of the clusters delineated using habCluster could serve as a good indicator of habitat patches, and they match generally well with nature reserves in the giant panda case. habCluster can provide spatial analysis basis for conservation management plans such as monitoring, translocation and reintroduction, as well as for population structure research.
Assembly-free discovery of human novel sequences using long reads
Authors: Li Qiuhui , Yan Bin , Lam Tak-Wah , Luo Ruibang
Published: May 2022

DNA sequences that are absent in the human reference genome are classified as novel sequences. The discovery of these missed sequences is crucial for exploring the genomic diversity of populations and understanding the genetic basis of human diseases. However, various DNA lengths of reads generated from different sequencing technologies can significantly affect the results of novel sequences. In this work, we designed an Assembly-Free Novel Sequence (AF-NS) approach to identify novel sequences from Oxford Nanopore Technology long reads. Among the newly detected sequences using AF-NS, more than 95% were omitted from those using long-read assemblers, and 85% were not present in short reads of Illumina. We identified the common novel sequences among all the samples and revealed their association with the binding motifs of transcription factors. Regarding the placements of the novel sequences, we found about 70% enriched in repeat regions and generated 430 for one specific subpopulation that might be related to their evolution. Our study demonstrates the advance of the Assembly-Free approach to capture more novel sequences over other assembler based methods. Combining the long-read data with powerful analytical methods can be a robust way to improve the completeness of novel sequences.
DeepLUAD: An efficient approach for lung adenocarcinoma pattern classification
Authors: Bouziane Ahmed , Boudemia Ala Eddine , Bourega Taib Abderaouf , Hamdi Mahdjoub
Published: May 2022

Histopathological analysis of whole-slide images is the gold standard technique for diagnosis of lung cancer and classifying it into types and subtypes by specialized pathologists. This labor-based approach is time and effort consuming, which led to development of automatic approaches to assist in reducing the time and effort. Deep learning is a supervised classification approach that is well adapted for automatic classification of histopathological images. We aimed to develop a deep learning-based approach for lung adenocarcinoma pattern classification and generalize the proposed approach to the classification of the major non-small cell lung cancer types. Three publicly available datasets were used in this study. A deep learning approach for histopathological image analysis using convolutional neural networks was developed and incorporated into automatic pipelines to accurately classify the predominant patterns on the whole-slide images level and non-small cell lung cancer types on patch-level. The models were evaluated using the confusion matrix to perform an error analysis and the classification report to compute F1-score, recall and precision. As results, the three models have shown an excellent performance with best combination of hyper-parameters for training models. First and second models predicted adenocarcinoma predominant patterns on two different datasets with an accuracy, respectively, of 96.15% and 89.51%. The third model has exceeded an accuracy of 99.72% in classifying major non-small cell lung cancer types. The proposed deep learning-based lung cancer classification approach can be used to assist pathologists in identifying of lung adenocarcinomas patterns.
Inhibition of Aromatase by Hops, Licorice Species, and their bioactive compounds in Postmenopausal Breast Tissue
Authors: Hajirahimkhan Atieh , Howell Caitlin , Chen Shao-Nong , Clare Susan E. , Pauli Guido F. , Khan Seema A. , Bolton Judy L. , Dietz Birgit M.
Published: May 2022

Breast cancer risk continues to rise post menopause. Endocrine therapies are employed to prevent postmenopausal breast cancer in high-risk women. However, their adverse effects have reduced acceptability and overall success in cancer preventionatural products such as hops (Humulus lupulus) and pharmacopoeial licorice (Glycyrrhiza) species, which are used for managing menopausal symptoms, have demonstrated estrogenic and chemopreventive properties. Their beneficial effects on aromatase activity and expression as important factors in postmenopausal breast carcinogenesis are understudied. The presented data show that Gycyrrhiza inflata (GI) has the highest aromatase inhibition potency among these plants. Moreover, phytoestrogens such as 8-prenylnaringenin from hops as well as liquiritigenin and 8-prenylapigenin from licorice are shown to be potent bioactives, in line with computational docking studies. 8-Prenylnaringenin, GI extract, liquiritigenin, and licochalcone A all suppress aromatase expression in postmenopausal women’s breast tissue. Collectively, these data suggest that these natural products may have breast cancer prevention potential for high-risk postmenopausal women.
Quorum sensing regulation of a major facilitator superfamily transporter affects multiple streptococcal virulence factors
Authors: Chang Jennifer C. , Wilkening Reid V. , Rahbari Kate M. , Federle Michael J.
Published: May 2022

Cell-cell signaling mediated by Rgg-family transcription factors and their cognate pheromones is conserved in Firmicutes, including all streptococci. In Streptococcus pyogenes, or Group A strep, one of these systems, the Rgg2/3 quorum sensing (QS) system, has been shown to regulate phenotypes including cellular aggregation and biofilm formation, lysozyme resistance, and macrophage immunosuppression. Here, we show that the abundance of several secreted virulence factors (streptolysin O, SpyCEP, and M protein) decreases upon induction of QS. The main mechanism underlying the changes in protein levels appears to be transcriptional, occurs downstream of the QS circuit and is dysregulated by the deletion of an Rgg2/3 QS-regulated major facilitator superfamily (MFS) transporter. Additionally, we identify this MFS transporter as the factor responsible for a previously observed increase in aminoglycoside sensitivity in QS-induced cells.

Importance

The production of virulence factors is a tightly regulated process in bacterial pathogens. Efforts to elucidate the mechanisms by which genes are regulated may advance the understanding of factors influencing pathogen behavior or cellular physiology. This work finds that expression of a major facilitator superfamily (MFS) transporter, which is governed by a quorum sensing (QS) system, impacts the expression of multiple secreted virulence factors and accounts for a documented QS-dependent antibiotic susceptibility. Although the mechanism underlying this effect is not clear, MFS orthologs with high sequence similarity from S. pneumoniae and S. porcinus were unable to substitute indicating substrate specificity of the GAS MFS gene. These findings demonstrate novel associations between the expression of a transmembrane transporter and virulence factor expression and aminoglycoside transport.
The funny current If is essential for the fight-or-flight response in cardiac pacemaker cells
Authors: Peters Colin H , Rickert Christian , Morotti Stefano , Grandi Eleonora , Proenza Catherine
Published: May 2022

The sympathetic nervous system fight-or-flight response is characterized by a rapid increase in heart rate, which is mediated by an increase in the spontaneous action potential (AP) firing rate of pacemaker cells in the sinoatrial node. Sympathetic neurons stimulate sinoatrial myocytes (SAMs) by activating β adrenergic receptors (βARs) and increasing cAMP. The funny current (If) is among the cAMP-sensitive currents in SAMs. If is critical for pacemaker activity, however, its role in the fight-or-flight response remains controversial. In this study, we used AP waveform analysis, machine learning, and dynamic clamp experiments in acutely-isolated SAMs from mice to quantitatively define the AP waveform changes and role of If in the fight-or-flight response. We found that while βAR stimulation significantly altered nearly all AP waveform parameters, the increase in AP firing rate was only correlated with changes in a subset of parameters (diastolic duration, late AP duration, and diastolic depolarization rate). Dynamic clamp injection of the βAR-sensitive component of If showed that it accounts for approximately 41% of the fight-or-flight increase in AP firing rate and 60% of the decrease in the interval between APs. Thus, If is an essential contributor to the fight-or-flight increase in heart rate.
Food resources drive rodent population demography mediated by seasonality and inter-specific competition
Authors: Giulia Ferrari , Olivier Devineau , Valentina Tagliapietra , Kaja Johnsen , Ossi Federico , Francesca Cagnacci
Published: May 2022

As fast reproducing species, rodents present proximate numerical responses to resource availability that have been assessed by experimental manipulation of food, with contrasting results. Other intrinsic and extrinsic factors, such as climate severity, species life cycles, and sympatry of potential competitors in the community, may interplay to modulate such responses, but their effects have rarely been evaluatedensemble.

We applied a niche-based approach to experimentally determine the effect of bottom-up (food availability) and top-down (climate severity) extrinsic factors, as well as intrinsic seasonal cycles, on rodent demography, also in presence of sympatry between species in the community.

To this end, we live-trapped rodents at two latitudinal extremes of the boreal-temperate gradient (Italian Alps and Norway) deploying control/treatment designs of food manipulation. We applied a multistate open robust design model to estimate population patterns and survival rate.

Yellow-necked and wood mouse (Apodemusspp.) were sympatric with bank vole in Italy, while the latter was the only species trapped in Norway. At northern latitudes, where harsher climatic conditions occurred, vole survival was principally regulated by intrinsic seasonal cycles, with a positive effect of food also on population abundance. At southern latitudes, mice and voles exhibited asynchronous population patterns across seasons, with survival depending from seasonal cycles. When concentratedad libitumfood was experimentally provided, though, population size and survival of voles strongly decreased, while mice abundance benefited from food supplementation.

Our results evidence that rodent demography is regulated by a combination of top-down (climate severity) and bottom-up (food availability) extrinsic factors, together with intrinsic seasonal ones. Moreover, we showed that the seasonal niche partitioning of mice and voles could be disrupted by availability of abundant resources that favour the demography of the more opportunisticApodemusspp. at the expense ofMyodes glareolus, suggesting competitive mechanisms. We conclude putting our results in the context of climate change, where shifts in vegetation productivity may affect the diversity of the rodent community via demographic effects.
Generalizable strategy to analyze domains in the context of parent protein architecture: A CheW case study
Authors: Vass Luke R. , Branscum Katie M. , Bourret Robert B. , Foster Clay A.
Published: May 2022

Domains are the three-dimensional building blocks of proteins. An individual domain can occur in a variety of domain architectures that perform unique functions and are subject to different evolutionary selective pressures. We describe an approach to evaluate the variability in amino acid sequences of a single domain across architectural contexts. The ability to distinguish different evolutionary outcomes of one protein domain can help determine whether existing knowledge about a specific domain will apply to an uncharacterized protein, lead to insights and hypotheses about function, and guide experimental priorities.

We developed and tested our approach on CheW-like domains (PF01584), which mediate protein/protein interactions and are difficult to compare experimentally. CheW-like domains occur in CheW scaffolding proteins, CheA kinases, and CheV proteins that regulate bacterial chemotaxis. We analyzed 16 domain architectures that included 94% of all CheW-like domains found in nature. We identified six Classes of CheW-like domains with presumed functional differences. CheV and most CheW proteins contained Class 1 domains, whereas some CheW proteins contained Class 6 (∼20%) or Class 2 (∼1%) domains instead. Most CheA proteins contained Class 3 domains. CheA proteins with multiple Hpt domains contained Class 4 domains. CheA proteins with two CheW-like domains contained one Class 3 and one Class 5.

We also created SimpLogo, an innovative method for visualizing amino acid composition across large sets of multiple sequence alignments of arbitrary length. SimpLogo offers substantial advantages over standard sequence logos for comparison and analysis of related protein sequences. The R package for SimpLogo is freely available.
Structural heterogeneity of amyloid aggregates identified by spatially resolved nanoscale infrared spectroscopy
Authors: Banerjee Siddhartha , Holcombe Brooke , Ringold Sydney , Foes Abigail , Ghosh Ayanjeet
Published: May 2022

Amyloid plaques, composed of aggregates of the amyloid beta (Aβ) protein, are one of the central manifestations of Alzheimer’s disease pathology. Aggregation of Aβ from amorphous oligomeric species to mature fibrils has been extensively studied. However, significantly less in known about early-stage aggregates compared to fibrils. In particular, structural heterogeneities in prefibrillar species, and how that affects the structure of later stage aggregates are not yet well understood. Conventional spectroscopies cannot attribute structural facets to specific aggregates due to lack of spatial resolution, and hence aggregates at any stage of aggregation must be viewed as having the same average structure. The integration of infrared spectroscopy with Atomic Force Microscopy (AFM-IR) allows for identifying the signatures of individual nanoscale aggregates by spatially resolving spectra. In this report, we use AFM-IR to demonstrate that amyloid oligomers exhibit significant structural variations as evidenced in their infrared spectra, ranging from ordered beta structure to disordered conformations with predominant random coil and beta turns. This heterogeneity is transmitted to and retained in protofibrils and fibrils. We show for the first time that amyloid fibrils do not always conform to their putative ordered structure and structurally different domains can exist in the same fibril. We further show the implications of these results in amyloid plaques in Alzheimer’s tissue using infrared imaging, where these structural heterogeneities manifest themselves as lack of expected beta sheet structure.
Human variation impacting MCOLN2 restricts Salmonella Typhi replication by magnesium deprivation
Authors: Gibbs Kyle D. , Wang Liuyang , Anderson Caroline E. , Bourgeois Jeffrey S. , Cao Yanlu , Gaggioli Margaret R. , Puertollano Rosa , Ko Dennis C.
Published: May 2022

Human genetic diversity can reveal critical factors in host-pathogen interactions. This is especially useful for human-restricted pathogens like Salmonella enterica serovar Typhi (S. Typhi), the cause of Typhoid fever. One key dynamic during infection is competition for nutrients: host cells attempt to restrict intracellular replication by depriving bacteria of key nutrients or delivering toxic metabolites in a process called nutritional immunity. Here, a cellular genome-wide association study of intracellular replication by S. Typhi in nearly a thousand cell lines from around the world—and extensive follow-up using intracellular S. Typhi transcriptomics and manipulation of magnesium concentrations—demonstrates that the divalent cation channel mucolipin-2 (MCOLN2) restricts S. Typhi intracellular replication through magnesium deprivation. Our results reveal natural diversity in Mg2+ limitation as a key component of nutritional immunity against S. Typhi.

One-Sentence Summary

Human immune cells genetically vary in their ability to use magnesium deprivation to restrict growth of the typhoid fever bacterium.
Specific binding of Hsp27 and phosphorylated Tau mitigates abnormal Tau aggregation-induced pathology
Authors: Zhang Shengnan , Zhu Yi , Lu Jinxia , Liu Zhenying , Lobato Amanda G. , Liu Jiaqi , Qiang Jiali , Zeng Wen , Zhang Yaoyang , Liu Cong , He Zhuohao , Zhai R. Grace , Li Dan
Published: May 2022

Amyloid aggregation of phosphorylated Tau (pTau) into neurofibrillary tangles is closely associated with Alzheimer’s disease (AD). Several molecular chaperones have been reported to bind Tau and impede its pathological aggregation. Recent findings of elevated levels of Hsp27 in the brains of patients with AD suggested its important role in pTau pathology. However, the molecular mechanism of Hsp27 in pTau aggregation remains poorly understood. Here, we show that Hsp27 partially co-localizes with pTau tangles in the brains of patients with AD. Notably, phosphorylation of Tau by microtubule affinity regulating kinase 2 (MARK2), dramatically enhances the binding affinity of Hsp27 to Tau. Moreover, Hsp27 efficiently prevents pTau fibrillation in vitro and mitigates neuropathology of pTau aggregation in a Drosophila tauopathy model. Further mechanistic study reveals that Hsp27 employs its N-terminal domain to directly interact with multiple phosphorylation sites of pTau for specific binding. Our work provides the structural basis for the specific recognition of Hsp27 to pathogenic pTau, and highlights the important role of Hsp27 in preventing abnormal aggregation and pathology of pTau in AD.
A framework for summarizing chromatin state annotations within and identifying differential annotations across groups of samples
Authors: Vu Ha , Koch Zane , Fiziev Petko , Ernst Jason
Published: May 2022

Motivation

Genome-wide maps of epigenetic modifications are powerful resources for non-coding genome annotation. Maps of multiple epigenetics marks have been integrated into cell or tissue type-specific chromatin state annotations for many cell or tissue types. With the increasing availability of multiple chromatin state maps for biologically similar samples, there is a need for methods that can effectively summarize the information about chromatin state annotations within groups of samples and identify differences across groups of samples at a high resolution.

Results

We developed CSREP, which takes as input chromatin state annotations for a group of samples and then probabilistically estimates the state at each genomic position and derives a representative chromatin state map for the group. CSREP uses an ensemble of multi-class logistic regression classifiers to predict the chromatin state assignment of each sample given the state maps from all other samples. The difference of CSREP’s probability assignments for two groups can be used to identify genomic locations with differential chromatin state patterns.

Using groups of chromatin state maps of a diverse set of cell and tissue types, we demonstrate the advantages of using CSREP to summarize chromatin state maps and identify biologically relevant differences between groups at a high resolution.

Availability and implementation

The CSREP source code is openly available under http://github.com/ernstlab/csrep.

Contact: jason.ernst@ucla.edu
Prenatal inflammation perturbs fetal hematopoietic development and causes persistent changes to postnatal immunity
Authors: Apostol April C. , López Diego A. , Lebish Eric J. , Valencia Clint H. , Romero-Mulero Mari Carmen , Pavlovich Polina , Hernandez Gloria E. , Forsberg E. Camilla , Cabezas-Wallscheid Nina , Beaudin Anna E.
Published: May 2022

Adult hematopoietic stem and progenitor cells (HSPCs) respond directly to inflammation and infection, resulting in both acute and persistent changes to quiescence, mobilization, and differentiation. Here we show that fetal HSPCs respond to prenatal inflammation in utero, and that the fetal response shapes postnatal hematopoiesis and immunity. Heterogenous fetal HSPCs showed divergent responses to maternal immune activation (MIA), including changes in quiescence, expansion, and lineage-biased output. Single cell transcriptomic analysis of fetal HSPCs in response to MIA revealed specific upregulation of inflammatory gene profiles in discrete, transient HSC populations, that propagated expansion of lymphoid-biased progenitors. Beyond fetal development, MIA caused the inappropriate expansion and persistence of fetal lymphoid-biased progenitors postnatally, concomitant with increased cellularity and hyperresponsiveness of fetal-derived innate-like lymphocytes. Our investigation demonstrates how inflammation in utero can direct the trajectory of output and function of fetal-derived immune cells by reshaping fetal HSC establishment.
Evolution and diversity of the TopoVI and TopoVI-like subunits with extensive divergence of the TOPOVIBL subunit
Authors: Brinkmeier Julia , Coelho Susana M. , de Massy Bernard , Bourbon Henri-Marc
Published: May 2022

Type II DNA topoisomerases regulate topology by double-stranded DNA cleavage and ligation. The TopoVI family of DNA topoisomerase, first identified and biochemically characterized in Archaea, represents, with TopoVIII and mini-A, the type IIB family. TopoVI has several intriguing features in terms of function and evolution. TopoVI has been identified in some eucaryotes, and a global view is lacking to understand its evolutionary pattern. In addition, in eucaryotes, the two TopoVI subunits (TopoVIA and TopoVIB) have duplicated and evolved to give rise to Spo11 and TopoVIBL, forming TopoVI-like (TopoVIL), a complex essential for generating DNA breaks that initiation homologous recombination during meiosis. TopoVIL is essential for sexual reproduction. How the TopoVI subunits have evolved to ensure this meiotic function is unclear. Here, we investigated the phylogenetic conservation of TopoVI and TopoVIL. We demonstrate that BIN4 and RHL1, potentially interacting with TopoVIB, have co-evolved with TopoVI. Based on model structures, this observation supports the hypothesis for a role of TopoVI in decatenation of replicated chromatids and predicts that in eucaryotes the TopoVI catalytic complex includes BIN4 and RHL1. For TopoVIL, the phylogenetic analysis of Spo11, which is highly conserved among Eukarya, highlighted a eukaryal-specific N-terminal domain that may be important for its regulation. Conversely, TopoVIBL was poorly conserved and rapidly evolving, giving rise to ATP hydrolysis-mutated or -truncated protein variants, or was undetected in some species. This remarkable plasticity of TopoVIBL provides important information for the activity and function of TopoVIL during meiosis.
Developmentally regulated alternate 3’ end cleavage of nascent transcripts controls dynamic changes in protein expression in an adult stem cell lineage
Authors: Berry Cameron W. , Olivares Gonzalo H. , Gallicchio Lorenzo , Ramaswami Gokul , Glavic Alvaro , Olguín Patricio , Li Jin Billy , Fuller Margaret T.
Published: May 2022

Alternative polyadenylation (APA) generates transcript isoforms that differ in the position of the 3’ cleavage site, resulting in the production of mRNA isoforms with different length 3’UTRs. Although widespread, the role of APA in the biology of cells, tissues and organisms has been controversial. We identified over 500Drosophilagenes that express mRNA isoforms with a long 3’UTR in proliferating spermatogonia but a short 3’UTR in differentiating spermatocytes due to APA. We show that the stage-specific choice of the 3’ end cleavage site can be regulated by the arrangement of a canonical polyadenylation signal (PAS) near the distal cleavage site but a variant or no recognizable PAS near the proximal cleavage site. The emergence of transcripts with shorter 3’UTRs in differentiating cells correlated with changes in expression of the encoded proteins, either from off in spermatogonia to on in spermatocytes or vice versa. Polysome gradient fractionation revealed over 250 genes where the long 3’UTR versus short 3’UTR mRNA isoforms migrated differently, consistent with dramatic stage-specific changes in translation state. Thus, the developmentally regulated choice of an alternative site at which to make the 3’end cut that terminates nascent transcripts can profoundly affect the suite of proteins expressed as cells advance through sequential steps in a differentiation lineage.
A comparison of marker gene selection methods for single-cell RNA sequencing data
Authors: Pullin Jeffrey M. , McCarthy Davis J.
Published: May 2022

The development of single-cell RNA sequencing (scRNA-seq) has enabled scientists to catalogue and probe the transcriptional heterogeneity of individual cells in unprecedented detail. A common step in the analysis of scRNA-seq data is the selection of so-called marker genes, most commonly to enable annotation of the biological cell types present in the sample. In this paper we benchmarked 56 computational methods for selecting marker genes in scRNA-seq data. The performance of the methods was compared using 10 real scRNA-seq datasets and over 170 additional simulated datasets. Methods were compared on their ability to recover simulated and expert-annotated marker genes, the predictive performance and characteristics of the gene sets they select, their memory usage and speed and their implementation quality. In addition, various case studies were used to scrutinise the most commonly used methods, highlighting issues and inconsistencies. Overall, we present a comprehensive evaluation of methods for selecting marker genes in scRNA-seq data. Our results highlight the efficacy of simple methods, especially the Wilcoxon rank-sum test, Student’s t-test and logistic regression. All code used in the evaluation, including an extensible Snakemake pipeline, is available at:https://gitlab.svi.edu.au/biocellgen-public/mage_2020_marker-gene-benchmarking.