bluuebunny/crossref_metadata_2025 huggingface dataset:
Cyclocreatine suppresses prostate tumorigenesis through dual effects on SAM and creatine metabolism
Authors: Patel Rachana , Rodgers Lisa , Ford Catriona A. , Rushworth Linda K , Fleming Janis , Mui Ernest , Zhang Tong , Watson David , Mackay Gillian , Sumpton David , Sansom Owen J. , Leung Hing Y.
Published: February 2021

Prostate cancer is highly prevalent, being the second most common cause of cancer mortality in men worldwide. Applying a novel genetically engineered mouse model (GEMM) of aggressive prostate cancer driven by deficiency of PTEN and SPRY2 (Sprouty 2) tumour suppressors, we identified enhanced creatine metabolism within the phosphagen system in progressive disease. Altered creatine metabolism was validated inin vitroandin vivoprostate cancer models and in clinical cases. Upregulated creatine levels were due to increased uptake through the SLC6A8 creatine transporter andde novosynthesis, resulting in enhanced cellular basal respiration. Treatment with cyclocreatine (a creatine analogue that potently and specifically blocks the phosphagen system) dramatically reduces creatine and phosphocreatine levels. Blockade of creatine biosynthesis by cyclocreatine leads to cellular accumulation of S-adenosyl methionine (SAM), an intermediary of creatine biosynthesis, and suppresses prostate cancer growthin vitro. Furthermore, cyclocreatine treatment impairs cancer progression in our GEMM and in a xenograft liver metastasis model. Hence, by targeting the phosphagen system, cyclocreatine results in anti-tumourigenic effects from both SAM accumulation and suppressed phosphagen system.
The Epstein-Barr virus ubiquitin deconjugase BPLF1 regulates the activity of Topoisomerase II during virus replication
Authors: Li Jinlin , Nagy Noemi , Liu Jiangnan , Gupta Soham , Frisan Teresa , Hennig Thomas , Cameron Donald P. , Baranello Laura , Masucci Maria G.
Published: February 2021

Topoisomerases are essential for the replication of herpesviruses but the mechanisms by which the viruses hijack the cellular enzymes are largely unknown. We found that topoisomerase-II (TOP2) is a substrate of the Epstein-Barr virus (EBV) ubiquitin deconjugase BPLF1. BPLF1 selectively inhibited the ubiquitination of TOP2 following treatment with topoisomerase poisons, interacted with TOP2α and TOP2β in co-immunoprecipitation andin vitropull-down, stabilized Etoposide-trapped TOP2 cleavage complexes (TOP2cc) and promoted TOP2 SUMOylation, which halted the DNA-damage response and reduced Etoposide toxicity. Induction of the productive virus cycle promoted the accumulation of TOP2βcc, enhanced TOP2β SUMOylation, and reduced Etoposide toxicity in lymphoblastoid cell lines carrying recombinant EBV encoding the active enzyme. Attenuation of this phenotype upon expression of a catalytic mutant BPLF1-C61A impaired viral DNA synthesis and virus release. These findings highlight a previously unrecognized function of BPLF1 in promoting non-proteolytic pathways for TOP2cc debulking that favor cell survival and virus production.
Integrative network analysis interweaves the missing links in cardiomyopathy diseasome
Authors: Chauhan Pankaj Kumar , Sowdhamini Ramanathan
Published: February 2021

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy’s genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, includingNOS3, MMP2andSIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research.
Extended numerical analysis of an eyeball injury under direct impact
Authors: Koberda M. , Skorek A. , Kłosowski P. , Żmuda-Trzebiatowski M. , Żerdzicki K. , Lemski P. , Stodolska-Koberda U.
Published: February 2021

The objective of this study was to develop a numerical model of the eyeball and orbit to simulate a blunt injury to the eyeball leading to its rupture, as well as to conduct a comparative analysis of the results obtained using the finite element method against the clinical material concerning patients who had suffered an eyeball rupture due to a blunt force trauma. Using available sclera biometric and strength data, a numerical model of the eyeball, the orbital contents, and the bony walls were developed from the ground up. Then, eight different blunt force injury scenarios were simulated. The results of numerical analyses made it possible to identify possible locations and configurations of scleral rupture. The obtained results were compared against the clinical picture of patients hospitalized at the Clinic of Ophthalmology in 2010–2016 due to isolated blunt force trauma to the eyeball. It has been demonstrated that the extent of damage observed on the numerical model that indicated a possible location of eyeball rupture did not differ from the clinically observed configurations of the scleral injuries, however this applies to injuries the extend of which did not exceed 2–3 clock-hours on the eyeball. It has been found that the direction of the impact applied determines the location of eyeball rupture. Most often the rupture occurs at the point opposite to the clock-hour of the impact application. The eyeball rupture occurs in the first 7–8 milliseconds after the contact with the striking object, assuming that it strikes at a speed close to the speed of a human fist. It has been established that the injuries most often affected the upper sectors of the eyeball. Men are definitely more likely to sustain such injuries. Eyeball ruptures lead to significant impairment of visual acuity being most often degraded to light perception in front of the eye. Despite immediate specialist treatment, it is possible to achieve, on average, a visual acuity of 0.26 as per the Snellen scale. This study may contribute to a better understanding of injury mechanisms and better treatment planning. It may also contribute to the development of eyeball protection methods for persons exposed to the above-mentioned injuries.
THz irradiation inhibits cell division by affecting actin dynamics
Authors: Yamazaki Shota , Ueno Yuya , Hosoki Ryosuke , Saito Takanori , Idehara Toshitaka , Yamaguchi Yuusuke , Otani Chiko , Ogawa Yuichi , Harata Masahiko , Hoshina Hiromichi
Published: February 2021

Biological phenomena induced by terahertz (THz) irradiation are described in recent reports, but underlying mechanisms, structural and dynamical change of specific molecules are still unclear. In this paper, we performed time-lapse morphological analysis of human cells and found that THz irradiation halts cell division at cytokinesis. At the end of cytokinesis, the contractile ring, which consists of filamentous actin (F-actin), needs to disappear; however, it remained for 1 hour under THz irradiation. Induction of the functional structures of F-actin was also observed in interphase cells. Similar phenomena were also observed under chemical treatment (jasplakinolide), indicating that THz irradiation assists actin polymerization. We previously reported that THz irradiation enhances the polymerization of purified actin in vitro; our current work shows that it increases cytoplasmic F-actin in vivo. Thus, we identified one of the key biomechanisms affected by THz waves.
Global genetic heterogeneity in adaptive traits
Authors: Lopez-Arboleda William Andres , Reinert Stephan , Nordborg Magnus , Korte Arthur
Published: February 2021

Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS for a variety of phenotypes in the model plant speciesArabididopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, while others are affected by variants specific to subpopulations. Remarkably, the former are essentially allcis-regulated, whereas the latter are predominately affected bytrans-acting variants. Our result illustrate that conclusions about genetic architecture can be incredibly sensitive to sampling and population structure.
Dynamics of the most common pathogenic mtDNA variant m.3243A>G demonstrate frequency-dependency in blood and positive selection in the germline
Authors: Franco Melissa , Pickett Sarah J. , Fleischmann Zoe , Khrapko Mark , Cote-L’Heureux Auden , Aidlen Dylan , Stein David , Markuzon Natasha , Popadin Konstantin , Braverman Maxim , Woods Dori C. , Tilly Jonathan L. , Turnbull Doug M. , Khrapko Konstantin
Published: February 2021

The A-to-G point mutation at position 3243 in the human mitochondrial genome (m.3243A>G) is the most common pathogenic mtDNA variant responsible for disease in humans. It is widely accepted that m.3243A>G levels decrease in blood with age, and an age correction representing ∼2% annual decline is often applied to account for this change in mutation level. Here we report that recent data indicate the dynamics of m.3243A>G are more complex and depend on the mutation level in blood in a bi-phasic way. Consequently, the traditional 2% correction, which is adequate ‘on average’, creates opposite predictive biases at high and low mutation levels. Unbiased age correction is needed to circumvent these drawbacks of the standard model. We propose to eliminate both biases by using an approach where age correction depends on mutation level in a biphasic way to account for the dynamics of m.3243A>G in blood. The utility of this approach was further tested in estimating germline selection of m.3243A>G. The biphasic approach permitted us to uncover patterns consistent with the possibility of positive selection for m.3243A>G. Germline selection of m.3243A>G shows an ‘arching’ profile by which selection is positive at intermediate mutant fractions and declines at high and low mutant fractions. We conclude that use of this biphasic approach will greatly improve the accuracy of modelling changes in mtDNA mutation frequencies in the germline and in somatic cells during aging.
Machine learning for cell classification and neighborhood analysis in glioma tissue
Authors: Solorzano Leslie , Wik Lina , Bontell Thomas Olsson , Wang Yuyu , Klemm Anna H. , Öfverstedt Johan , Jakola Asgeir S. , Östman Arne , Wählby Carolina
Published: February 2021

Multiplexed and spatially resolved single-cell analyses that intend to study tissue heterogeneity and cell organization invariably face as a first step the challenge of cell classification. Accuracy and reproducibility are important for the down-stream process of counting cells, quantifying cell-cell interactions, and extracting information on disease-specific localized cell niches. Novel staining techniques make it possible to visualize and quantify large numbers of cell-specific molecular markers in parallel. However, due to variations in sample handling and artefacts from staining and scanning, cells of the same type may present different marker profiles both within and across samples. We address multiplexed immunofluorescence data from tissue microarrays of low grade gliomas and present a methodology using two different machine learning architectures and features insensitive to illumination to perform cell classification. The fully automated cell classification provides a measure of confidence for the decision and requires a comparably small annotated dataset for training, which can be created using freely available tools. Using the proposed method, we reached an accuracy of 83.1% on cell classification without the need for standardization of samples. Using our confidence measure, cells with low-confidence classifications could be excluded, pushing the classification accuracy to 94.5%. Next, we used the cell classification results to search for cell niches with an unsupervised learning approach based on graph neural networks. We show that the approach can re-detect specialized tissue niches in previously published data, and that our proposed cell classification leads to niche definitions that may be relevant for sub-groups of glioma, if applied to larger datasets.
5S-IGS rDNA in wind-pollinated trees (FagusL.) encapsulates 55 million years of reticulate evolution and hybrid origins of modern species
Authors: Cardoni Simone , Piredda Roberta , Denk Thomas , Grimm Guido W. , Papageorgiou Aristotelis C. , Schulze Ernst-Detlef , Scoppola Anna , Shanjani Parvin Salehi , Suyama Yoshihisa , Tomaru Nobuhiro , Worth James R.P. , Simeone Marco Cosimo
Published: February 2021

Standard models of plant speciation assume strictly dichotomous genealogies in which a species, the ancestor, is replaced by two offspring species. The reality in wind-pollinated trees with long evolutionary histories is more complex: species evolve from other species through isolation when genetic drift exceeds gene flow; lineage mixing can give rise to new species (hybrid taxa such as nothospecies and allopolyploids). The multi-copy, potentially multi-locus 5S rDNA is one of few gene regions conserving signal from dichotomous and reticulate evolutionary processes down to the level of intra-genomic recombination. Therefore, it can provide unique insights into the dynamic speciation processes of lineages that diversified tens of millions of years ago. Here, we provide the first high-throughput sequencing (HTS) of the 5S intergenic spacers (5S-IGS) for a lineage of wind-pollinated subtropical to temperate trees, theFagus crenata – F. sylvaticas.l. lineage, and its distant relativeF. japonica.The observed 4,963 unique 5S-IGS variants reflect a complex history of hybrid origins, lineage sorting, mixing via secondary gene flow, and intra-genomic competition between two or more paralogous-homoeologous 5S rDNA lineages. We show that modern species are genetic mosaics and represent a striking case of ongoing reticulate evolution during the past 55 million years.

Significance statement

The evolution of extra-tropical wind-pollinated tree genera involves dynamic speciation processes. High-throughput sequencing of the multi-copy, potentially multi-locus 5S rDNA reveals a complex history of hybrid origins, lineage sorting and mixing, and intra-genomic competition between paralogous-homeologous loci in the core group of Eurasian beech trees (genusFagus) and their distant relative,F. japonica. The modern species are genetic mosaics and represent a striking case of at least 55 million years of ongoing reticulate evolution.
Distribution of methionine sulfoxide reductases in fungi and conservation of the free-methionine-R-sulfoxide reductase in multicellular eukaryotes
Authors: Hage Hayat , Rosso Marie-Noëlle , Tarrago Lionel
Published: February 2021

Methionine, either as a free amino acid or included in proteins, can be oxidized into methionine sulfoxide (MetO), which exists as R and S diastereomers. Almost all characterized organisms possess thiol-oxidoreductases named methionine sulfoxide reductase (Msr) enzymes to reduce MetO back to Met. MsrA and MsrB reduce the S and R diastereomers of MetO, respectively, with strict stereospecificity and are found in almost all organisms. Another type of thiol-oxidoreductase, the free-methionine-R-sulfoxide reductase (fRMsr), identified so far in prokaryotes and a few unicellular eukaryotes, reduces the R MetO diastereomer of the free amino acid. Moreover, some bacteria possess molybdenum-containing enzymes that reduce MetO, either in the free or protein-bound forms. All these Msrs play important roles in the protection of organisms against oxidative stress. Fungi are heterotrophic eukaryotes that colonize all niches on Earth and play fundamental functions, in organic matter recycling, as symbionts, or as pathogens of numerous organisms. However, our knowledge on fungal Msrs is still limited. Here, we performed a survey of msr genes in almost 700 genomes across the fungal kingdom. We show that most fungi possess one gene coding for each type of methionine sulfoxide reductase: MsrA, MsrB, and fRMsr. However, several fungi living in anaerobic environments or as obligate intracellular parasites were devoid of msr genes. Sequence inspection and phylogenetic analyses allowed us to identify non-canonical sequences with potentially novel enzymatic properties. Finaly, we identified several ocurences of msr horizontal gene transfer from bacteria to fungi.

Highlights

Free and protein-bound methionine can be oxidized into methionine sulfoxide (MetO).

Methionine sulfoxide reductases (Msr) reduce MetO in most organisms.

Sequence characterization and phylogenomics revealed strong conservation of Msr in fungi.

fRMsr is widely conserved in unicellular and multicellular fungi.

Some msr genes were acquired from bacteria via horizontal gene transfers.
NMR Hydrogen Exchange and Relaxation Reveal Positions Stabilized by p53 Rescue Mutants N239Y and N235K
Authors: Soto Jenaro , Moody Colleen , Alhoshani Ali , Sanchez-Bonilla Marilyn , Martinon Daisy , Cocco Melanie J
Published: February 2021

Inactivation of p53 is found in over 50% of all cancers; p53 disfunction is often caused by a single missense mutation localized in the DNA binding domain (DBD). Rescue mutants N235K and N239Y stabilize and restore function to multiple p53 cancer mutants. Here, we use NMR to compare protein dynamics between WT and rescue mutants to understand the mechanism of stabilization. We measured and compared folding dynamics by calculating protection factors (PFs) from NMR hydrogen exchange rates of backbone amides. We find that both rescue mutants impose a global stabilizing effect that dampens their motions compared to WT DBD, predominantly in the β-sandwich. However, a few regions become more flexible in rescue mutants. Notably, positions that have increased PFs map to cancer mutants rescued by each mutant. We also compared relaxation results to obtain flexibility information in the ps to ns timescale regime. Protein sequence analysis was used to determine the occurrence of these rescue mutants in nature and showed that 235K is found in mice and rats, but there is no evidence of 239Y occurring naturally in any species. Understanding the mechanism by which stabilizing mutants rescue p53 may reveal novel avenues for the development of cancer therapeutics. Our findings suggest that cancer therapeutics aimed at restoring p53 function could consider protein dynamics as a metric of drug efficacy.

Statement of Significance

Two mutations (N235K and N239Y) within the DNA binding domain of p53 are known to reverse the effects of multiple cancer mutants. However, the mechanism of rescue is not clear since the crystal structures of these mutants are virtually identical to that of the WT. Here we use NMR methods to show that the protein dynamics of the rescue mutants are significantly different compared to WT, allowing us to describe the stability on a per-residue basis. Although these mutations are only four residues apart, they stabilize the structure distinctly in different regions, consistent with the specific cancer mutations they to which they restore function.
Multidimensional molecular differences between artificial and wildArtemisia rupestrisL.
Authors: Zhou Zhi , Xie Bin , He Bingshu , Zhang Chen , Chen Lulu , Wang Zhonghua , Chen Yanhua , Abliz Zeper
Published: February 2021

Different ecological environments affect the active ingredients and molecular content of medicinal plants.Artemisia rupestrisL. is a kind of traditional medicinal plant, and the shortages of the wild resource have led to increased use of artificial varieties. However, there have few investigations referring to molecular differences between them in a systematic manner. In the present study, artificial and wildArtemisia rupestrisL. plants were collected in the Altay–Fuyun region, Xinjian, China. Untargeted metabolomics method based on liquid chromatography-mass spectrometry (LC-MS) technology was applied to profile flower, stem, and leaf samples, respectively, and levels of a panel of representative known metabolites in this plant were simultaneously analyzed. The genetic basis of these samples was explored using ade novotranscriptomics approach to investigate differentially expressed genes (DEGs) and their pathway annotations. Results indicated metabolic differences between the two varieties mainly reflected in flavonoids and chlorogenic acid/caffeic acid derivatives. 34 chemical markers (CMs) belonging to these two structural categories were discovered after validation using another batch of samples, including 19 potentially new compounds. After correlation analysis, total of six DEGs in different organs relating to 24 CMs were confirmed using quantitative real-time PCR (qPCR). These findings provided novel insight into the molecular landscape of this medicinal plant through metabolomics-transcriptomics integration strategy, and reference information of its quality control and species identification.

ONE SENTENCE SUMMARY

A metabolomics-transcriptomics research on Artemisia rupestris L. to discover metabolite differences and the genetic basis between artificial and wild varieties in systematic and novel manner.
Multiple Loci Selection with Multi-way Epistasis in Coalescence with Recombination
Authors: Bose Aritra , Utro Filippo , Platt Daniel E. , Parida Laxmi
Published: February 2021

As studies move into deeper characterization of the impact of selection through non-neutral mutations in whole genome population genetics, modeling for selection becomes crucial. Moreover, epistasis has long been recognized as a significant component in understanding evolution of complex genetic systems. We present a backward coalescent model EpiSimRA, that builds multiple loci selection, with multi-way (k-way) epistasis for any arbitraryk. Starting from arbitrary extant populations with epistatic sites, we trace the Ancestral Recombination Graph (ARG), sampling relevant recombination and coalescent events. Our framework allows for studying different complex evolutionary scenarios in the presence of selective sweeps, positive and negative selection with multiway epistasis. We also present a forward counterpart of the coalescent model based on a Wright-Fisher (WF) process which we use as a validation framework, comparing the hallmarks of the ARG between the two. We provide the first framework that allows a nose-to-nose comparison of multiway epistasis in a coalescent simulator with its forward counterpart with respect to the hallmarks of the ARG. We demonstrate through extensive experiments, that EpiSimRA is consistently superior in term of performance (seconds vs. hours) in comparison to the forward model without compromising on its accuracy. EpiSimRA (both backward and forward) source, executable, user manuals are available at:https://github.com/ComputationalGenomics/SimRA.
Evolution of myoglobin in avian lineages: positive selection for aggregation resistance in penguins and high purifying selection in galliforms
Authors: Rizvi Syed M. , Zheng Wei , Zhang Chengxin , Zhang Yang
Published: February 2021

Myoglobin is the major oxygen carrying protein of vertebrate muscle, and high myoglobin net charge is known to hold evolutionary significance as a molecular signature of secondarily aquatic diving capacity in mammals. However, the evolution of myoglobin’s electrostatic properties in non-mammalian vertebrates, such as birds, has not been investigated. Here, we used a new deep learning-based protein folding algorithm to model the tertiary structures of myoglobin from 302 vertebrate species and performed a comparative analysis of their net charge, positively charged solvent-accessible surface area, and negatively charged solvent-accessible surface area. For avian myoglobins, we also calculated selection pressure (ω). The results suggest that the myoglobins of diving avians, specifically those of the penguins (Sphenisciformes) and diving ducks (Aythyini), have highly positively charged electrostatic surfaces, which evolved via positive selection to reduce aggregation propensity and allow greater storage of oxygen for extended underwater foraging. In contrast, galliform myoglobins are under high purifying selection. Distribution of charged atoms on myoglobin surface was more indicative of high myoglobin content than net charge. We also found inter-class differences in net charge; bird myoglobins are the most positively charged and reptile and amphibian myoglobins are the most negatively charged, and net charge seems to be negatively associated with herbivory within mammals. Finally, we propose an equation that describes the relationship between myoglobin net charge and concentration better than the previously suggested logarithmic function. Our findings offer novel insights into the diversification of myoglobin in vertebrate clades and highlight the power of computational structural approaches for zoological and evolutionary research.
Comprehensive analysis of chemical and biological problems associated with browning agents used in aquatic studies
Authors: Scharnweber Kristin , Peura Sari , Attermeyer Katrin , Bertilsson Stefan , Bolender Lucas , Buck Moritz , Einarsdóttir Karólína , Garcia Sarahi L. , Gollnisch Raphael , Grasset Charlotte , Groeneveld Marloes , Hawkes Jeffrey A. , Lindström Eva S. , Manthey Christin , Övergaard Robyn , Rengefors Karin , Sedano-Núñez Vicente T. , Tranvik Lars J. , Székely Anna J.
Published: February 2021

Inland waters receive and process large amounts of colored organic matter from the terrestrial surroundings. These inputs dramatically affect the chemical, physical, and biological properties of water bodies, as well as their roles as global carbon sinks and sources. To understand the complex changes associated with allochthonous inputs, experiments are needed. However, manipulative studies, especially at ecosystem scales, require large amounts of dissolved organic matter with optical and chemical properties resembling indigenous organic matter. Here we compared the chemical and biological impacts of two leonardite products (HuminFeed (HF) and SuperHume (SH)) and a freshly derived reverse osmosis concentrate of organic matter (RO) in a set of comprehensive mesocosm- and laboratory-scale experiments and analyses.

The chemical properties of RO concentrate and the leonardite products were very different with leonardite products being low and RO being high in carboxylic functional groups. Light had a strong impact on the properties of leonardite products, including loss of color and increased particle formation. Furthermore, HF had drastic impacts on bacteria as light stimulated bacterial production and modified community composition, while dark conditions appeared to inhibit bacterial processes. While none of the browning agents inhibited the growth of the tested phytoplankton,Gonyostomum semen, leonardite products had detrimental effects on zooplankton abundance andDaphniareproduction. We conclude that the effects of browning agents extracted from leonardite are in sharp contrast to those originating from terrestrially-derived DOM. Hence, they should be used with great caution in experimental studies on the consequences of terrestrial carbon for aquatic systems.
Plague risk in the western United States over seven decades of environmental change
Authors: Carlson Colin J. , Bevins Sarah N. , Schmid Boris V.
Published: February 2021

After several pandemics over the last two millennia, the wildlife reservoirs of plague (Yersinia pestis) now persist around the world, including in the western United States. Routine surveillance in this region has generated comprehensive records of human cases and animal seroprevalence, creating a unique opportunity to test how plague reservoirs are responding to environmental change. Here, we develop a new method to detect the signal of climate change in infectious disease distributions, and test whether plague reservoirs and spillover risk have shifted since 1950. We find that plague foci are associated with high-elevation rodent communities, and soil biochemistry may play a key role in the geography of long-term persistence. In addition, we find that human cases are concentrated only in a small subset of endemic areas, and that spillover events are driven by higher rodent species richness (the amplification hypothesis) and climatic anomalies (the trophic cascade hypothesis). Using our detection model, we find that due to the changing climate, rodent communities at high elevations have become more conducive to the establishment of plague reservoirs—with suitability increasing up to 40% in some places—and that spillover risk to humans at mid-elevations has increased as well, although more gradually. These results highlight opportunities for deeper investigation of plague ecology, the value of integrative surveillance for infectious disease geography, and the need for further research into ongoing climate change impacts.
Discover Your Potential: The Influence of Kinematics on a Muscle’s Ability to Contribute to the Sit-to-Stand Transfer
Authors: Roelker Sarah A. , Schmitt Laura C. , Chaudhari Ajit M.W. , Siston Robert A.
Published: February 2021

Existing methods for estimating how individual muscles contribute to a movement require extensive time and experimental resources. In this study we developed an efficient method for determining how changes to lower extremity joint kinematics affect the potential of individual muscles to contribute to whole-body center-of-mass vertical (support) and anteroposterior (progression) accelerations. A 4-link 2-dimensional model was used to assess the effect of kinematic changes on muscle function. Joint kinematics were systematically varied throughout ranges observed during the momentum transfer phase of the sit-to-stand transfer. Each muscle’s potential to contribute to support and progression was computed and compared to simulated potentials estimated by traditional dynamic simulation methods for young adults and individuals with knee osteoarthritis (KOA). The new method required 4-10s to compute muscle potentials per kinematic state and computed potentials were consistent with simulated potentials. The new method identified differences in muscle potentials between groups due to kinematic differences, particularly decreased anterior pelvic tilt in young adults, and revealed kinematic and muscle strengthening modifications to increase support. The methods presented provide an efficient, systematic approach to evaluate how joint kinematic adjustments alter a muscle’s ability to contribute to movement and can identify potential sources of pathologic movement and rehabilitation strategies.
Multiple metabolic signals including AMPK and PKA regulate glucose-stimulated double strand break resection in yeast
Authors: Lomonaco Stephanie , Bazzano Dominic , Wilson Thomas E.
Published: February 2021

DNA double strand breaks (DSBs) are cytotoxic lesions repaired by non-homologous end joining (NHEJ) and homologous recombination (HR), with 5’ strand resection being the committed step in transition from NHEJ to HR. We previously discovered thatgal1yeast, which cannot metabolize galactose, were unable to perform efficient 5’ resection even though DSBs were formed. Adding glucose or restoringGAL1restored resection, suggesting that carbon source metabolism signals to DSB repair. Here we demonstrate that any fermentable carbon source, including raffinose, can stimulate resection and that the stimulatory effect of glucose was associated with decreased, not increased, cellular ATP. The effect was cell cycle dependent and did not occur in G1, while glucose augmented the G2/M checkpoint arrest even in cells deficient in resection. AMP-activated protein kinase pathway mutants showed only low basal resection despite glucose addition but had normal checkpoint arrest, indicating a primary role for Snf1 specifically in glucose-stimulated resection. The metabolic inputs to resection were multifactorial, however, with loss of the transcriptional repressor Mig1 leading to increased basal resection, three distinct patterns of deficiency with loss of the protein kinase A catalytic subunits, Tpk1, Tpk2 andTpk3, and a resection delay in yeast lacking the lysine demethylase Rph1 that helped separate early and late phase responses to glucose. These results reveal multiple interrelated metabolic signals that optimize DSB resection efficiency while independently amplifying the G2/M checkpoint response.
Programmatic modeling for biological systems
Authors: Lubbock Alexander L.R. , Lopez Carlos F.
Published: February 2021

Computational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with SBML used for interchange. Models are typically simulated, calibrated, and analyzed either within a single application, or using import and export from various tools. Here, we describe a programmatic modeling paradigm, in which modeling is augmented with best practices from software engineering. We focus on Python - a popular, user-friendly programming language with a large scientific package ecosystem. Models themselves can be encoded as programs, adding benefits such as modularity, testing, and automated documentation generators while still being exportable to SBML. Automated version control and testing ensures models and their modules have expected properties and behavior. Programmatic modeling is a key technology to enable collaborative model development and enhance dissemination, transparency, and reproducibility.

Highlights

Programmatic modeling combines computational modeling with software engineering best practices.

An executable model enables users to leverage all available resources from the language.

Community benefits include improved collaboration, reusability, and reproducibility.

Python has multiple modeling frameworks with a broad, active scientific ecosystem.
Representation learning applications in biological sequence analysis
Authors: Iuchi Hitoshi , Matsutani Taro , Yamada Keisuke , Iwano Natsuki , Sumi Shunsuke , Hosoda Shion , Zhao Shitao , Fukunaga Tsukasa , Hamada Michiaki
Published: February 2021

Remarkable advances in high-throughput sequencing have resulted in rapid data accumulation, and analyzing biological (DNA/RNA/protein) sequences to discover new insights in biology has become more critical and challenging. To tackle this issue, the application of natural language processing (NLP) to biological sequence analysis has received increased attention, because biological sequences are regarded as sentences and k-mers in these sequences as words. Embedding is an essential step in NLP, which converts words into vectors. This transformation is called representation learning and can be applied to biological sequences. Vectorized biological sequences can be used for function and structure estimation, or as inputs for other probabilistic models. Given the importance and growing trend in the application of representation learning in biology, here, we review the existing knowledge in representation learning for biological sequence analysis.
Novel epitopes of human monoclonal antibodies targeting the influenza virus N1 neuraminidase
Authors: Roubidoux Ericka Kirkpatrick , McMahon Meagan , Carreño Juan Manuel , Capuano Christina , Jiang Kaijun , Simon Viviana , Bakel Harm van , Wilson Patrick , Krammer Florian
Published: February 2021

Influenza virus neuraminidase (NA) targeting antibodies are an independent correlate of protection against infection. Antibodies against the NA act by blocking enzymatic activity, preventing virus release and transmission. As we advance the development of improved influenza virus vaccines that incorporate standard amounts of NA antigen, it is important to identify the antigenic targets of human monoclonal antibodies (mAbs). Additionally, it is important to understand how escape from mAbs changes viral fitness. Here, we describe escape mutants generated by serial passage of A/Netherlands/602/2009 (H1N1) in the presence of human anti-N1 mAbs. We observed escape mutations on the N1 protein around the enzymatic site (S364N, N369T and R430Q) and also detected escape mutations located on the sides and bottom of the NA (N88D, N270D and Q313K/R). We found that a majority of escape mutant viruses had increased fitnessin vitrobut notin vivo. This work increases our understanding of how human antibody responses target the N1 protein.

Importance

As improved influenza virus vaccines are being developed, the influenza virus neuraminidase (NA) is becoming an important new target for immune responses. By identifying novel epitopes of anti-NA antibodies, we can improve vaccine design. Additionally, characterizing changes in viruses containing mutations in these epitopes aids in identifying effects of NA antigenic drift.
DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution
Authors: Satas Gryte , Zaccaria Simone , El-Kebir Mohammed , Raphael Benjamin J.
Published: February 2021

Most tumors are heterogeneous mixtures of normal cells and cancer cells, with individual cancer cells distinguished by somatic mutations that accumulated during the evolution of the tumor. The fundamental quantity used to measure tumor heterogeneity from somatic single-nucleotide variants (SNVs) is the Cancer Cell Fraction (CCF), or proportion of cancer cells that contain the SNV. However, in tumors containing copy-number aberrations (CNAs) – e.g. most solid tumors – the estimation of CCFs from DNA sequencing data is challenging because a CNA may alter themutation multiplicity, or number of copies of an SNV. Existing methods to estimate CCFs rely on the restrictive Constant Mutation Multiplicity (CMM) assumption that the mutation multiplicity is constant across all tumor cells containing the mutation. However, the CMM assumption is commonly violated in tumors containing CNAs, and thus CCFs computed under the CMM assumption may yield unrealistic conclusions about tumor heterogeneity and evolution. The CCF also has a second limitation for phylogenetic analysis: the CCF measures the presence of a mutation at the present time, but SNVs may be lost during the evolution of a tumor due to deletions of chromosomal segments. Thus, SNVs that co-occur on the same phylogenetic branch may have different CCFs.

In this work, we address these limitations of the CCF in two ways. First, we show how to compute the CCF of an SNV under a less restrictive and more realistic assumption called the Single Split Copy Number (SSCN) assumption. Second, we introduce a novel statistic, thedescendant cell fraction(DCF), that quantifies both the prevalence of an SNVandthe past evolutionary history of SNVs under an evolutionary model that allows for mutation losses. That is, SNVs that co-occur on the same phylogenetic branch will have the same DCF. We implement these ideas in an algorithm named DeCiFer. DeCiFer computes the DCFs of SNVs from read counts and copy-number proportions and also infers clusters of mutations that are suitable for phylogenetic analysis. We show that DeCiFer clusters SNVs more accurately than existing methods on simulated data containing mutation losses. We apply DeCiFer to sequencing data from 49 metastatic prostate cancer samples and show that DeCiFer produces more parsimonious and reasonable reconstructions of tumor evolution compared to previous approaches. Thus, DeCiFer enables more accurate quantification of intra-tumor heterogeneity and improves downstream inference of tumor evolution.

Code availability

Software is available athttps://github.com/raphael-group/decifer
Whole Genome and Exome Sequencing Reference Datasets from A Multi-center and Cross-platform Benchmark Study
Authors: Zhao Yongmei , Fang Li Tai , Shen Tsai-wei , Choudhari Sulbha , Talsania Keyur , Chen Xiongfong , Shetty Jyoti , Kriga Yuliya , Tran Bao , Zhu Bin , Chen Zhong , Chen Wangqiu , Wang Charles , Jaeger Erich , Meerzaman Daoud , Lu Charles , Idler Kenneth , Zheng Yuanting , Shi Leming , Petitjean Virginie , Sultan Marc , Hung Tiffany , Peters Eric , Drabek Jiri , Vojta Petr , Maestro Roberta , Gasparotto Daniela , Kõks Sulev , Reimann Ene , Scherer Andreas , Nordlund Jessica , Liljedahl Ulrika , Foox Jonathan , Mason Christopher , Xiao Chunlin , Xiao Wenming
Published: February 2021

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.
APOBEC Mutagenesis is Concordant Between Tumor and Viral Genomes in HPV Positive Head and Neck Squamous Cell Carcinoma
Authors: Faden Daniel L , Kuhs Krystle A. Lang , Lin Maoxuan , Langenbucher Adam , Pinheiro Maisa , Yeager Meredith , Cullen Michael , Boland Joseph F. , Steinberg Mia , Bass Sara , Lewis James S. , Lawrence Michael S , Ferris Robert L , Mirabello Lisa
Published: February 2021

APOBEC (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like) is a major mutagenic source in human papillomavirus positive oropharyngeal squamous cell carcinoma (HPV+ OPSCC). Why APOBEC mutations predominate in HPV+OPSCC remains an area of active investigation. Prevailing theories focus on APOBECs role as a viral restriction agent. APOBEC-induced mutations have been identified in both human cancers and HPV genomes, but whether they are directly linked in HPV+OPSCCs remains unknown. We performed sequencing of host somatic exomes, transcriptomes and HPV16 genomes from 79 HPV+ OPSCC samples, quantifying APOBEC mutational burden and activity in both the host and virus. APOBEC was the dominant mutational signature in somatic exomes. APOBEC vulnerable PIK3CA hotspot mutations were exclusively present in APOBEC enriched samples. In viral genomes, there was a mean (range) of 5 (0-29) mutations per genome. Mean (range) of APOBEC mutations in the viral genomes was 1 (0-5). Viral APOBEC mutations, compared to non-APOBEC mutations, were more likely to be low-variant allele frequency mutations, suggesting that APOBEC mutagenesis is actively occurring in viral genomes during infection. Paired host and viral analyses revealed that APOBEC-enriched tumor samples had higher viral APOBEC mutation rates (p=0.028), and APOBEC-associated RNA editing (p=0.008) suggesting that APOBEC mutagenesis in host and viral genomes are directly linked. Using paired sequencing of host somatic exomes, transcriptomes, and viral genomes from HPV+OPSCC samples, here, we show concordance between tumor and viral APOBEC mutagenesis, suggesting that APOBEC-mediated viral restriction results in off-target host-genome mutations. These data provide a missing link connecting APOBEC mutagenesis in host and virus and support a common mechanism driving APOBEC dysregulation.
The coronavirus pandemic, short-term employment support schemes and undeclared work: some lessons from Europe
Authors: Williams Colin C. , Oz-Yalaman Gamze
Published: February 2021

Purpose

The temporary enforced closure of businesses in response to the coronavirus pandemic has resulted in governments in Europe and beyond offering short-term financial support to the businesses and workers affected. The purpose of this paper is to evaluate a group of workers unable to benefit from the short-term job retention schemes and support to the self-employed made available by governments, namely, those whose paid work is comprised wholly of undeclared work, and how this could be addressed.

Design/methodology/approach

To identify those whose paid work is entirely undeclared, a Eurobarometer survey of undeclared work in Europe is reported conducted in September 2019, just prior to the pandemic, and involving 27,565 face-to-face interviews in 28 European countries.

Findings

The finding is that the paid work of one in every 132 European citizens is comprised wholly of undeclared work, and these workers are concentrated in non-essential businesses and activities severely affected by the lockdown. These workers whose paid work is comprised wholly of undeclared work are significantly more likely to be widowed or divorced/separated, living in households with three or more adults, without children and most of the time have financial difficulties in making ends meet.

Practical implications

Given that businesses and workers in the undeclared economy are largely unable to work under lockdown, it is argued that providing access to short-term financial support, through a regularisation initiative based on voluntary disclosure, would not only provide the income support these workers need but also bring them out of the shadows and put them on the radar of the state authorities, thus transforming undeclared work into declared work.

Originality/value

This paper shows how in the current or repeat lockdowns, the short-term financial support made available by governments can be used to transform undeclared work into declared work.