bluuebunny/crossref_metadata_2025 huggingface dataset:
Hinge Influences in Murine IgG Binding toCryptococcus neoformansCapsule
Authors: de Oliveira Diane Sthefany Lima , Paredes Verenice , Caixeta Adrielle Veloso , Henriques Nicole Moreira , Wear Maggie P. , Albuquerque Patrícia , Felipe Maria Sueli Soares , Casadevall Arturo , Nicola André Moraes
Published: January 2021

Decades of studies on antibody structure led to the tenet that the V region binds antigens while the C region interacts with immune effectors. In some antibodies, however, the C region affects affinity and/or specificity for the antigen. One such case is that of the 3E5 antibodies, a family of monoclonal murine IgGs in which the mIgG3 isotype has different fine specificity to theCryptococcus neoformanscapsule polysaccharide than the other mIgG isotypes. Our group serendipitously found another pair of mIgG1/mIgG3 antibodies based on the 2H1 hybridoma to theC. neoformanscapsule that recapitulated the differences observed with 3E5. In this work, we report the molecular basis of the constant domain effects on antigen binding using recombinant antibodies. As with 3E5, immunofluorescence experiments show a punctate pattern for 2H1-mIgG3 and an annular pattern for 2H1-mIgG1. Also as observed with 3E5, 2H1-mIgG3 bound on ELISA to both acetylated and non-acetylated capsular polysaccharide, whereas 2H1-mIgG1 only bound well to the acetylated form, consistent with differences in fine specificity. In engineering hybrid mIgG1/mIgG3 antibodies, we found that switching the 2H1-mIgG3 hinge for its mIgG1 counterpart changed the immunofluorescence pattern to annular, but a 2H1-mIgG1 antibody with a mIgG3 hinge still had an annular pattern. The hinge is thus necessary but not sufficient for these changes in binding to the antigen. This important role for the constant region in binding of antibodies to the antigen could affect the design of therapeutic antibodies and our understanding of their function in immunity.

Key points

Key point 1- 2H1 antibodies recapitulate differences between mIgG isotypes observed with 3E5.

Key point 2 – The hinge region is necessary but not sufficient for these differences.

Key point 3 - The antibody constant region can also play a role in mIgG binding to antigen.
The long non-coding RNASAMMSONis essential for uveal melanoma cell survival
Authors: Dewaele Shanna , Delhaye Louis , De Paepe Boel , De Bony Eric , De Wilde Jilke , Vanderheyden Katrien , Anckaert Jasper , Yigit Nurten , Eynde Eveline Vanden , Nemati Fariba , Decaudin Didier , Jochemsen Aart , Leucci Eleonora , Vandesompele Jo , Dorpe Jo Van , Marine Chris , Van Coster Rudy , Eyckerman Sven , Mestdagh Pieter
Published: January 2021

Purpose

Long non-coding RNAs (lncRNAs) can exhibit cell-type and cancer-type specific expression profiles, making them highly attractive as therapeutic targets. Pan-cancer RNA sequencing data revealed broad expression of theSAMMSONlncRNA in uveal melanoma (UM), the most common primary intraocular malignancy in adults. Currently, there are no effective treatments for UM patients with metastatic disease, resulting in a median survival time of 6-12 months. We aimed to investigate the therapeutic potential ofSAMMSONinhibition in UM.

Experimental Design

The impact of antisense oligonucleotide (ASO)-mediatedSAMMSONinhibition was evaluated in a panel of UM cell lines and patient derived xenograft (PDX) models. Cell proliferation and apoptosis were quantifiedin vitroandin vivoand complemented with molecular profiles established through RNA-sequencing.SAMMSONinteraction partners were identified using ChIRP-MS.

Results

SAMMSONinhibition impaired the growth and viability of a genetically diverse panel of uveal melanoma cell lines. These effects were accompanied by an induction of apoptosis and were recapitulated in two uveal melanoma PDX models through subcutaneous ASO delivery.SAMMSONpulldown revealed several candidate interaction partners, including various proteins involved in mitochondrial translation. Consequently, inhibition ofSAMMSONimpaired global protein translation levels and mitochondrial function in uveal melanoma cells.

Conclusion

SAMMSONexpression is essential for uveal melanoma cell survival. ASO-mediated silencing ofSAMMSONmay provide an effective treatment strategy to treat primary and metastatic uveal melanoma patients.
Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science
Authors: Phillips Mick A , Pinto David Miguel Susano , Hall Nicholas , Mateos-Langerak Julio , Parton Richard M , Titlow Josh , Stoychev Danail V , Parks Thomas , Pinto Tiago Susano , Sedat John W , Booth Martin J , Davis Ilan , Dobbie Ian M
Published: January 2021

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based GUI environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near-instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

Highlights

User-friendly setup and use for simple to complex bespoke microscopes.

Facilitates collaborations between biomedical scientists and microscope technologists.

Touchscreen for near-instantaneous navigation of specimen landscape.

Uses Python-Microscope, for abstracted open source hardware device control.

Well-suited for user training of AI-algorithms for automated microscopy.
Long-term changes in the breeding biology of a New Zealand bellbird population suggest plasticity in life-history responses to ecological restoration
Authors: Roper Michelle M. , Aaron M.T. Harmer , Brunton Dianne H
Published: January 2021

Ecological restoration projects provide excellent opportunities to study how animals adapt their life-history strategies in response to changeable environments. A fundamental way animals can optimise reproductive success in changing conditions is trading-off aspects of their breeding system. The New Zealand bellbird (Anthornis melanura) has had a long-term presence on the small restoration island, Tiritiri Matangi Island (Tiri), spanning the island’s degraded agricultural past to its current extensively restored state. We studied the breeding biology of this bellbird population to assess how their reproductive life-history strategies have responded over time to the restoration on Tiri. We compared the current breeding data (2012–2016) of the bellbirds with data from between 2001–2010 (including Baillie, 2011, Cope, 2007), and from 1977–1978 (Anderson and Craig, 2003), prior to the island’s restoration. We also explored associations between abiotic/biotic factors and bellbird reproductive success for the most recent period (2012–2016). Our main finding was that clutch size significantly declined over time from a mean of 3.6 to 2.4 eggs per nest and this decline correlated with increasing population density. This is consistent with a density dependent effect, although further data are required to empirically test this conclusion. Overall, the earliest spring laying dates were in late August and the latest extended to January, with all chicks fledged by the end of February. Nest success was 47% (range 40 – 54%) across 2012–2016, falling within a similar range as previous studies. We found little effect of year, weather, parental age or morphometrics on reproductive success. We observed directional change in patterns of parental investment between 1977–1978 and 2012–2016; in 2012–2016, parents persisted with raising single broods rather than abandoning and re-nesting to raise larger broods. These results suggest that the bellbirds’ life-history traits are plastic in response to local conditions which provides an advantage when repopulating a regenerating or changing habitat.
Modelling the COVID-19 Fatality Rate in England and its Regions
Authors: Saunders Nigel
Published: January 2021

A model to account for the fatality rate in England and its regions is proposed. It follows the clear observation that, rather than two connected waves, there have been many waves of infections and fatalities in the regions of England of various magnitudes, usually overlapping. The waves are self-limiting, in that clear peaks are seen, particularly in reported positive test rates. The present model considers fatalities as the data reported are more reliable than positive test rates, particularly so during the first wave when so little testing was done.

The model considers the observed waves are essentially similar in form and can be modelled using a single wave form, whose final state is only dependent on its peak height and start date. The basic wave form was modelled using the observed fatality rates for London, which unlike the other regions, exhibited almost completely as a single wave in the “first wave”. Its form matches rather well with the “Do Nothing” model reported by Imperial College on 16th March 2020, but reduced substantially from its expected peak.

There are, essentially, only two adjustable parameters used in the model, the start date of the relevant wave and its height. The modelled fatalities for each wave are summated per day and a cumulative curve is matched to that reported. The minimal number of adjustable parameters, alongside the fact that the waves invariably overlap, provides highly stringent conditions on the fitting process.

Results are presented for each region for both the “first” and “second’ waves. High levels of accuracy are obtained with R2 values approaching 100% against the ideal fit for both waves. It can also be seen that there are fundamental differences between the underlying behaviour of the “first” and “second” waves and reasons as to why those differences have arisen is briefly discussed.
The COVID-19 Infodemic: The complex task of elevating signal and eliminating noise
Authors: Desai Tejas , Conjeevaram Arvind
Published: January 2021

In Situation Report #3 and 39 days before declaring COVID-19 a pandemic, the WHO declared a -19 infodemic. The volume of coronavirus tweets was far too great for one to find accurate or reliable information. Healthcare workers were flooded with which drowned the of valuable COVID-19 information. To combat the infodemic, physicians created healthcare-specific micro-communities to share scientific information with other providers. We analyzed the content of eight physician-created communities and categorized each message in one of five domains. We coded 1) an application programming interface to download tweets and their metadata in JavaScript Object Notation and 2) a reading algorithm using visual basic application in Excel to categorize the content. We superimposed the publication date of each tweet into a timeline of key pandemic events. Finally, we created NephTwitterArchive.com to help healthcare workers find COVID-19-related signal tweets when treating patients. We collected 21071 tweets from the eight hashtags studied. Only 9051 tweets were considered signal: tweets categorized into both a domain and subdomain. There was a trend towards fewer signal tweets as the pandemic progressed, with a daily median of 22% (IQR 0-42%. The most popular subdomain in Prevention was PPE (2448 signal tweets). In Therapeutics, Hydroxychloroquine/chloroquine wwo Azithromycin and Mechanical Ventilation were the most popular subdomains. During the active Infodemic phase (Days 0 to 49), a total of 2021 searches were completed in NephTwitterArchive.com, which was a 26% increase from the same time period before the pandemic was declared (Days −50 to −1). The COVID-19 Infodemic indicates that future endeavors must be undertaken to eliminate noise and elevate signal in all aspects of scientific discourse on Twitter. In the absence of any algorithm-based strategy, healthcare providers will be left with the nearly impossible task of manually finding high-quality tweets from amongst a tidal wave of noise.
Incidence and Relative Risk of infection with SARS-CoV-2 virus in European Soccer Players
Authors: Andersen Thomas B. , Dahl Andreas B. , Carstensen Jeppe B.
Published: January 2021

The purpose of the present study was to investigate the incidence and relative risk of infection Covid-virus in soccer players. Data from five leagues was used and compared to data from the normal population in each country. Our results revealed that the relative risk was higher in soccer players in three countries when correcting for the estimated true number of infected people in the populations. We discuss that the reason for the higher incidence in soccer players is caused by the virus entering a group of players that work closely together.
Wild-captive contrasts in non-vocal communicative repertoires and functional specificity in orang-utans
Authors: Fröhlich Marlen , Bartolotta Natasha , Fryns Caroline , Wagner Colin , Momon Laurene , Jaffrezic Marvin , Setia Tatang Mitra , Schuppli Caroline , van Noordwijk Maria , van Schaik Carel P.
Published: January 2021

The creation of novel communicative acts is an essential element of human language. Although some research suggests the presence of this ability in great apes, this claim remains controversial. Here, we use orang-utans (Pongospp.) to systematically assess the effect of the wild-captive contrast on the repertoire size of communicative acts. We find that individual communicative repertoires are significantly larger in captive compared to wild settings, irrespective of species, age-sex class or sampling effort. Twenty percent of the orang-utan repertoire in captivity were not observed in the wild. In Sumatran orang-utans, the more sociable species, functional specificity was also higher in captive versus wild settings. We thus conclude that orang-utans, when exposed to a more sociable and terrestrial lifestyle, have the behavioural plasticity to invent new communicative behaviours that are highly functionally specific. This productive capacity by great apes is a major prerequisite for the evolution of language and seems to be ancestral in the hominid lineage.
Control over patch encounters changes foraging behaviour
Authors: Hall-McMaster Sam , Dayan Peter , Schuck Nicolas W.
Published: January 2021

Foraging is a common decision problem in natural environments. When new exploitable sites are always available, a simple optimal strategy is to leave a current site when its return falls below a single average reward rate. Here, we examined foraging in a more structured environment, with a limited number of sites that replenished at different rates and had to be revisited. When participants could choose sites, they visited fast-replenishing sites more often, left sites at higher levels of reward, and achieved a higher net reward rate. Decisions to exploit-or-leave a site were best explained with a computational model that included both the average reward rate for the environment and reward information about the unattended sites. This suggests that unattended sites influence leave decisions, in foraging environments where sites can be revisited.

Highlights

Being able to select sites during foraging increased visits to high value sites

This visitation pattern was efficient, producing higher average reward rates

Decisions to leave a site were influenced by information about alternative sites

Graphical Abstract
PERK-dependent reciprocal crosstalk between ER and non-centrosomal microtubules coordinates ER architecture and cell shape
Authors: Sánchez-Álvarez Miguel , Lolo Fidel , Sailem Heba , Pascual-Vargas Patricia , Fulgoni Giulio , Arias-García Mar , del Pozo Miguel Ángel , Bakal Chris
Published: January 2021

The architecture of the endoplasmic reticulum (ER) is tightly controlled as a key determinant of its function. Its dynamics are linked to those of the cytoskeleton, but our understanding of how this coordination occurs and what its functional relevance is, is limited. We found the Unfolded Protein Response (UPR) transducer EIF2AK3/PERK is essential for acute stress-induced peripheral redistribution and remodeling of the ER, through eIF2a phosphorylation and translation initiation shutdown. PERK-mediated eIF2a phosphorylation can be bypassed by blocking ribosome activity; by depleting microtubule-anchoring ER proteins such as REEP4, p180/RRBP1 and Climp63/CKAP4; or by disrupting the microtubule cytoskeleton. Notably, specific disruption of non-centrosomal microtubules, but not centrosome depletion, relieved blockade of ER redistribution in PERK-deficient cells. Conversely, PERK deficiency stabilized non-centrosomal microtubules, promoting polarized protrusiveness in epithelial cells and neuroblasts. We propose that PERK coordinates ER architecture and homeostasis with cell morphogenesis by coupling ER remodeling and non-centrosomal MT dynamics.
The impact of antigenic escape on the evolution of virulence
Authors: Sasaki Akira , Lion Sébastien , Boots Mike
Published: January 2021

Understanding the evolutionary drivers determining the transmission rate and virulence of pathogens remains an important challenge for evolutionary theory with clear implications to the control of human, agricultural and wildlife infectious disease. Although disease is often very dynamic, classical theory examines the long-term outcome of evolution at equilibrium and, in simple models, typically predicts that R0is maximized. For example, immune escape may lead to complex disease dynamics including repeated epidemics, fluctuating selection and diversification. Here we model the impact of antigenic drift and escape on the evolution of virulence and show analytically that these non-equilibrium dynamics select for more acute pathogens with higher virulence. Specifically, under antigenic drift and when partial cross immunity leads to antigenic escape, our analysis predicts the long-term maximization of the intrinsic growth rate of the parasite resulting in more acute and virulent pathogens than those predicted by classic R0maximization. Furthermore, it follows that these pathogens will have a lower R0leading to implications for epidemic, endemic behavior and control. Our analysis predicts both the timings and outcomes of antigenic shifts leading to repeated epidemics and predicts the increase in variation in both antigenicity and virulence before antigenic escape. There is considerable variation in the degree of antigenic escape that occurs across pathogens and our results may help to explain the difference in virulence between related pathogens most clearly seen in the human A, B and C influenzas. More generally our results show the importance of examining the evolutionary consequences of non-equilibrium dynamics.
Silencing of lncRNA NEAT1 inhibits esophageal squamous cell carcinoma proliferation, migration, and invasion via regulation of the miR-1299/MMP2 axis
Authors: Yang Zhanfeng , Zhu Meilin , Zhang Jingjing , Zhang Guangchong , Hu Jun , He Qunli
Published: January 2021

Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer worldwide. Considerable evidence has verified that abnormal expression of lncRNAs can effectively influence the progression of various malignant tumors. However, the regulatory mechanisms of lncRNAs underlying ESCC development and progression remain poorly defined. Here, we investigated the role of lncRNA nuclear-enriched abundant transcript 1 (NEAT1) in ESCC via regulating microRNA 1299 (miR-1299) and matrix metalloproteinase 2 (MMP2). A total of 32 ESCC tissue samples were obtained from the First Affiliated Hospital of Zhengzhou University. The mRNA levels of lncRNA NEAT1, miR-1299, and MMP2 mRNA were measured via quantitative real-time PCR. Interactions among miR-1299, lncRNA NEAT1, and MMP2 mRNA in EC9706 cells were confirmed by dual-luciferase reporter assays and RNA immunoprecipitation (RIP) assays. The proliferation and migration/invasion of ESCC cells were verified by CCK-8 and transwell assays, respectively. lncRNA NEAT1 was up-regulated in ESCC tissues and cells. lncRNA NEAT1 silencing inhibited migration, invasion, and proliferation of ESCC cells. Furthermore, lncRNA NEAT1 sponged and negatively regulated miR-1299, thus giving rise to increased expression of MMP2. Moreover, miR-1299 inhibitors and MMP2 rescued the invasion of ESCC cells following silencing of lncRNA NEAT1. lncRNA NEAT1 was overexpressed in ESCC tissues and cells. Silencing of lncRNA NEAT1 inhibited ESCC proliferation, migration, and invasion via reducing competitive binding of lncRNA NEAT1 with miR-1299 and enhancing miR-1299-targeted suppression of MMP2. Taken together, our findings suggest that lncRNA NEAT1 is a potential target for ESCC therapy and rehabilitation.
VEGF-A/VEGFR-1: a painful astrocyte-mediated signaling blocked by the anti-VEGFR-1 mAb D16F7
Authors: Micheli Laura , Parisio Carmen , Lucarini Elena , Vona Alessia , Toti Alessandra , Pacini Alessandra , Mello Tommaso , Boccella Serena , Ricciardi Flavia , Maione Sabatino , Graziani Grazia , Lacal Pedro Miguel , Failli Paola , Ghelardini Carla , Mannelli Lorenzo Di Cesare
Published: January 2021

Chemotherapy-induced neuropathic pain is a clinically relevant adverse effect of several anticancer drugs leading to dose reduction or therapy discontinuation. The lack of knowledge about the mechanisms of neuropathy development and pain chronicization makes chemotherapy-induced neuropathic pain treatment an unmet medical need. In this context, the vascular endothelial growth factor A (VEGF-A) has emerged as a neurotoxicity biomarker in a model of chemotherapy-induced neuropathy, and its decrease has been related to pain relief. Aim of this study was to clarify the VEGF-A-dependent pain signaling in the CNS for individuating new targeted therapeutic approaches. In mice, the intrathecal infusion of VEGF-A induced a dose-dependent noxious hypersensitivity mediated by the VEGF receptor 1 (VEGFR-1) as demonstrated by pharmacological and genetic tools. In electrophysiological study, VEGF-A stimulated the spinal nociceptive neurons activity through VEGFR-1. In the dorsal horn of the spinal cord, VEGF-A increased in astrocytes of animals affected by neuropathy suggesting this cell population as a source of the potent pain mediator. Accordingly, the selective knockdown of astrocytic VEGF-A, by shRNAmir, blocked the development of oxaliplatin-induced neuropathic pain. Besides, the anti-VEGFR-1 mAb D16F7 (previously described as anticancer) effectively relieved neuropathic pain induced by chemotherapeutic agents. In conclusion, astrocyte-released VEGF-A is a new player in the complex neuron-glia network that oversees physiological and pathological pain and D16F7 mAb rises as a potent pain killer strategy.
High-speed large-scale 4D activities mapping of moving C. elegans by deep-learning-enabled light-field microscopy on a chip
Authors: Zhu Tingting , Zhu Lanxin , Li Yi , Chen Xiaopeng , He Mingyang , Li Guo , Zhang Hao , Gao Shangbang , Fei Peng
Published: January 2021

We report a novel fusion of microfluidics and light-field microscopy, to achieve high-speed 4D (space + time) imaging of moving C. elegans on a chip. Our approach combines automatic chip-based worm loading / compartmentalization / flushing / reloading with instantaneous deep-learning light-field imaging of moving worm. Taken together, we realized intoto image-based screening of wild-type and uncoordinated-type worms at a volume rate of 33 Hz, with sustained observation of 1 minute per worm, and overall throughput of 42 worms per hour. With quickly yielding over 80000 image volumes that four-dimensionally visualize the dynamics of all the worms, we can quantitatively analyse their behaviours as well as the neural activities, and correlate the phenotypes with the neuron functions. The different types of worms can be readily identified as a result of the high-throughput activity mapping. Our approach shows great potential for various lab-on-a-chip biological studies, such as embryo sorting and cell growth assays.
Conductivity of the phloem inMangifera indicaL.
Authors: Miguel Barceló-Anguiano , Hormaza José I , Losada Juan M
Published: January 2021

Mangifera indicais the fifth most consumed fruit worldwide, and the most important in tropical regions, but its anatomy is quite unexplored. Previous studies examined the effect of chemicals on the xylem structure in the stems of mango, but the anatomy of the phloem has remained elusive, leaving the long distance transport of photo assimilates understudied.

In this work, we used a combination of fluorescence and electron microscopy to evaluate in detail the structure of the sieve tube elements composing the phloem tissue in the tapering branches of mango trees. We then used this information to better understand the hydraulic conductivity of the sieve tubes following current models of fluid transport in trees.

Our results revealed that the anatomy of the phloem in the stems changes from current year branches, where it was protected by pericyclic fibers, to older ones, where the lack of fibers was concomitant with laticiferous canals embedded in the phloem tissue. Callose was present in the sieve plates, but also in the walls of the phloem conduits, making them discernible from other phloem cells in fresh sections. A scaling geometry of the sieve tube elements, including the number of sieve areas and the pore size across tapering branches resulted in an exponential conductivity from current year branches to the base of the tree.

Our measurements of the phloem in mango fit with measurements of the phloem architecture in the stems of forest woody species, and imply that, despite agronomic pruning practices, the sieve conduits of the phloem scale with the tapering branches. As a result, the pipe model theory applied to the continuous tubing system of the phloem appears as a good approach to understand the “long distance” hydraulic transport of photoassimilates in fruit trees.
Evolution of phenotypic variance provides insights into the genetic basis of adaptation
Authors: Lai Wei-Yun , Nolte Viola , Jakšić Ana Marija , Schlötterer Christian
Published: January 2021

Most traits are polygenic and the contributing loci can be identified by GWAS. Their adaptive architecture is, however, difficult to characterize. Here, we propose to study the adaptive architecture of traits by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures. We compared gene expression variance in maleDrosophila simulansbefore and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We suggest that a majority of adaptive gene expression evolution can be explained by a polygenic architecture. We propose that tracking the evolution of phenotypic variance across generations can provide an approach to characterize the adaptive architecture.

Significant Statement

It is widely accepted that most complex traits have a polygenic basis. Nevertheless, it is difficult to predict which of these loci are responding to selection when a population is exposed to a new selection regime. To address this situation, we propose to infer the adaptive architecture for traits by tracking the evolution of their phenotypic variance during adaptation to a new environment. As a case study, we analyze the evolution of gene expression variance in outbredDrosophila simulanspopulations adapting to a new temperature regime to infer the genetic architecture of adaptive gene expression evolution. We suggested that the adaptive gene expression evolution is better explained by a polygenic architecture.
H2A.B is a cancer/testis factor involved in activation of ribosome biogenesis in Hodgkin Lymphoma
Authors: Jiang Xuanzhao , Wen Jiayu , Paver Elizabeth , Yu-Huan Wu , Sun Gege , Bullman Amanda , Dahlstrom Jane E. , Tremethick David J. , Soboleva Tatiana A.
Published: January 2021

Testis-specific regulators of chromatin function are commonly ectopically expressed in human cancers, but their roles are poorly understood. Examination of 81 primary Hodgkin Lymphoma (HL) samples showed that the ectopic expression of the eutherian testis-specific histone variant H2A.B is an inherent feature of HL. In experiments using two HL-derived cell lines derived from different subtypes of HL, H2A.B knockdown inhibited cell proliferation. H2A.B was enriched in both the nucleoli of these HL cell lines and primary HL samples. We found that H2A.B enhanced ribosomal DNA (rDNA) transcription, was enriched at the rDNA promoter and transcribed regions, and interacted with RNA Pol I. Depletion of H2A.B caused the loss of RNA Pol I from rDNA chromatin. Remarkably, H2A.B was also required for high levels of ribosomal protein gene expression being located at the transcriptional start site and within the gene body. H2A.B knockdown reduced gene body chromatin accessibility of active RNA Pol II genes concurrent with a decrease in transcription. Taken together, our data show that in HL H2A.B has acquired a new function, the ability to increase ribosome biogenesis.
Significance of linkage disequilibrium and epistasis on the genetic variances and covariance between relatives in non-inbred and inbred populations
Authors: Viana José Marcelo Soriano , Garcia Antonio Augusto Franco
Published: January 2021

Because no feasible theoretical model can depict the complexity of phenotype development from a genotype, the joint significance of linkage disequilibrium (LD), epistasis, and inbreeding on the genetic variances remains unclear. The objective of this investigation was to assess the impact of LD and epistasis on the genetic variances and covariances between relatives in non-inbred and inbred populations using simulated data. We provided the theoretical background and simulated grain yield assuming 400 genes in 10 chromosomes of 200 and 50 cM. We generated five populations with low to high LD levels, assuming 10 generations of random cross and selfing. The analysis of the parametric LD in the populations shows that the LD level depends mainly on the gene density. The significance of the LD level is impressive on the magnitude of the genotypic and additive variances, which is the most important component of the genotypic variance, regardless of the LD level and the degree of inbreeding. Regardless of the type of epistasis, the ratio epistatic variance/genotypic variance is proportional to the percentage of the epistatic genes. For the epistatic variances, except for duplicate epistasis and dominant and recessive epistasis, with 100% of epistatic genes, their magnitudes are much lower than the magnitude of the additive variance. The additive x additive variance is the most important epistatic variance. Our results explain why LD for genes and relationship information are key factors affecting the genomic prediction accuracy of complex traits and the efficacy of association studies.
Recovering Single-cell Heterogeneity Through Information-based Dimensionality Reduction
Authors: DeMeo Benjamin , Berger Bonnie
Published: January 2021

Dimensionality reduction is crucial to summarizing the complex transcriptomic landscape of single cell datasets for downstream analyses. However, current dimensionality reduction approaches favor large cellular populations defined by many genes, at the expense of smaller and more subtly-defined populations. Here, we present surprisal component analysis (SCA), a technique that leverages the information-theoretic notion of surprisal for dimensionality reduction, and demonstrate its ability to improve the representation of clinically important populations that are indistinguishable using existing pipelines. For example, in cytotoxic T-cell data, SCA cleanly separates the gamma-delta and MAIT cell subpopulations, which are not detectable via PCA, ICA, scVI, or a wide array of specialized rare cell recovery tools. We also show that, when used instead of PCA, SCA improves downstream imputation to more accurately restore mRNA dropouts and recover important gene-gene relationships. SCA’s information-theoretic paradigm opens the door to more meaningful signal extraction, with broad applications to the study of complex biological tissues in health and disease.
A scalable pipeline for local ancestry inference using tens of thousands of reference haplotypes
Authors: Durand Eric Y. , Do Chuong B. , Wilton Peter R. , Mountain Joanna L. , Auton Adam , Poznik G. David , Macpherson J. Michael
Published: January 2021

Ancestry deconvolution is the task of identifying the ancestral origins of chromosomal segments of admixed individuals. It has important applications, from mapping disease genes to identifying loci potentially under natural selection. However, most existing methods are limited to a small number of ancestral populations and are unsuitable for large-scale applications.

In this article, we describe Ancestry Composition, a modular pipeline for accurate and efficient ancestry deconvolution. In the first stage, a string-kernel support-vector-machines classifier assigns provisional ancestry labels to short statistically phased genomic segments. In the second stage, an autoregressive pair hidden Markov model corrects phasing errors, smooths local ancestry estimates, and computes confidence scores.

Using publicly available datasets and more than 12,000 individuals from the customer database of the personal genetics company, 23andMe, Inc., we have constructed a reference panel containing more than 14,000 unrelated individuals of unadmixed ancestry. We used principal components analysis (PCA) and uniform manifold approximation and projection (UMAP) to identify genetic clusters and define 45 distinct reference populations upon which to train our method. In cross-validation experiments, Ancestry Composition achieves high precision and recall.
AutoSmarTrace: Automated Chain Tracing and Flexibility Analysis of Biological Filaments
Authors: Schneider Mathew , Al-Shaer Alaa , Forde Nancy R.
Published: January 2021

Single-molecule imaging is widely used to determine statistical distributions of molecular properties. One such characteristic is the bending flexibility of biological filaments, which can be parameterized via the persistence length. Quantitative extraction of persistence length from images of individual filaments requires both the ability to trace the backbone of the chains in the images and sufficient chain statistics to accurately assess the persistence length. Chain tracing can be a tedious task, performed manually or using algorithms that require user input and/or supervision. Such interventions have the potential to introduce user-dependent bias into the chain selection and tracing. Here, we introduce a fully automated algorithm for chain tracing and determination of persistence lengths. Dubbed “AutoSmarTrace”, the algorithm is built off a neural network, trained via machine learning to identify filaments within images recorded using atomic force microscopy (AFM). We validate the performance of AutoSmarTrace on simulated images with widely varying levels of noise, demonstrating its ability to return persistence lengths in agreement with the ground truth. Persistence lengths returned from analysis of experimental images of collagen and DNA agree with previous values obtained from these images with different chain-tracing approaches. While trained on AFM-like images, the algorithm also shows promise to identify chains in other single-molecule imaging approaches, such as rotary shadowing electron microscopy and fluorescence imaging.

Statement of Significance

Machine learning presents powerful capabilities to the analysis of large data sets. Here, we apply this approach to the determination of bending flexibility – described through persistence length – from single-molecule images of biological filaments. We present AutoSmarTrace, a tool for automated tracing and analysis of chain flexibility. Built on a neural network trained via machine learning, we show that AutoSmarTrace can determine persistence lengths from AFM images of a variety of biological macromolecules including collagen and DNA. While trained on AFM-like images, the algorithm works well to identify filaments in other types of images. This technique can free researchers from tedious tracing of chains in images, removing user bias and standardizing determination of chain mechanical parameters from single-molecule conformational images.
Methylome dynamic upon proteasome inhibition by thePseudomonas syringaevirulence factor Syringolin A
Authors: Bonnet DMV , Grob S , Tirot L , Jullien PE
Published: January 2021

DNA methylation is an important epigenetic mark required for proper gene expression and silencing of transposable elements. DNA methylation patterns can be modified by environmental factors such as pathogen infection, where modification of DNA methylation can be associated with plant resistance. To counter the plant defense pathways, pathogens produce effectors molecule, several of which act as proteasome inhibitors. Here we investigated the effect of proteasome inhibition by the bacterial virulence factor Syringolin A on genome-wide DNA methylation. We show that Syringolin A treatment results in an increase of DNA methylation at centromeric and pericentromeric regions ofArabidopsischromosomes. We identify several CHH DMRs that are enriched in the proximity of transcriptional start sites. Syringolin A treatment does not result in significant changes in small RNA composition. However, significant changes in genome transcriptional activity can be observed, including a strong upregulation of resistance genes that are located on chromosomal arms. We hypothesize that DNA methylation changes could be linked to the upregulation of some atypical members of thede novoDNA methylation pathway:AGO3,AGO9andDRM1. Our data suggests that modification of genome-wide DNA methylation resulting from an inhibition of the proteasome by bacterial effectors could be part of a epi-genomic arms race against pathogens.
CometChip Enables Parallel Analysis of Multiple DNA Repair Activities
Authors: Ge Jing , Ngo Le P. , Kaushal Simran , Tay Ian J. , Thadhani Elina , Kay Jennifer E. , Mazzucato Patrizia , Chow Danielle N. , Fessler Jessica L. , Weingeist David M. , Sobol Robert W. , Samson Leona D. , Floyd Scott R. , Engelward Bevin P.
Published: January 2021

DNA damage can be cytotoxic and mutagenic and is directly linked to aging, cancer, and heritable diseases. To counteract the deleterious effects of DNA damage, cells have evolved highly conserved DNA repair pathways. Many commonly used DNA repair assays are relatively low throughput and are limited to analysis of one protein or one pathway. Here, we have explored the capacity of the CometChip platform for parallel analysis of multiple DNA repair activities. Taking advantage of the versatility of the traditional comet assay and leveraging micropatterning techniques, the CometChip platform offers increased throughput and sensitivity compared to the traditional comet assay. By exposing cells to DNA damaging agents that create substrates of Base Excision Repair, Nucleotide Excision Repair, and Non-Homologous End Joining, we show that the CometChip is an effective method for assessing repair deficiencies in all three pathways. With these advanced applications of the CometChip platform, we expand the efficacy of the comet assay for precise, high-throughput, parallel analysis of multiple DNA repair activities.
Close-kin methods to estimate census size and effective population size
Authors: Waples Robin S. , Feutry Pierre
Published: January 2021

The last two decades have witnessed rapid developments and increasing interest in use of (1) genetic methods to estimate effective population size (Ne) and (2) close-kin mark-recapture (CKMR) methods to estimate abundance based on the incidence of close relatives. WhereasNeestimation methods have been applied to a wide range of taxa, all CKMR applications to date have been for aquatic species. These two fields of inquiry have developed largely independently, and this is unfortunate because deeper insights can be gained by joint evaluation of eco-evolutionary processes. In this synthesis, we use simple analytical models and simulated pedigree data to illustrate how various factors (life-history traits; patterns of variation in individual reproductive success; experimental design; stochasticity; marker type) can affect performance of the estimators. We show that theNe/Nratio and the probability of a close-kin match both depend on a vector of parental weights that specify relative probabilities that different individuals will produce offspring. Although age-specific vital rates are central to both methodologies, for CKMR they can potentially bias abundance estimates unless properly accounted for, whereas they represent the signals of genetic drift thatNeestimation methods depend upon. CoordinatingNeand CKMR estimation methods using the same or overlapping datasets would facilitate joint evaluation of both the ecological and evolutionary consequences of abundance.
Impact of sterilization on a conjugated polymer based bioelectronic patch
Authors: Yan Yihan , Travaglini Lorenzo , Lau Kieran , Rnjak-Kovacina Jelena , Eslami Minoo , Yang Shaohua , Lauto Antonio , Officer David , Mawad Damia
Published: January 2021

Translation into the clinic of organic bioelectronic devices having conjugated polymers as the active material will hinge on their long-term operationin vivo. This will require the device to be subject to clinically approved sterilization techniques without a deterioration in its physical and electronic properties. To date, there remains a gap in the literature addressing the impact of this critical pre-operative procedure on the properties of conjugated polymers. This study aims to address this gap by assessing the physical and electronic properties of a sterilized porous bioelectronic patch having polyaniline as the conjugated polymer. The patch was sterilized by autoclave, ethylene oxide and gamma (γ-) irradiation at 15, 25, and 50 kGy doses. Autoclaving resulted in cracking and macroscopic degradation of the patch, while patches sterilized by γ-irradiation at 50 kGy exhibited reduced mechanical and electronic properties, attributed to chain scission and non-uniform crosslinking caused by the high dose irradiation. Ethylene oxide and γ-irradiation at 15 and 25 kGy sterilization appeared to be the most effective at maintaining the mechanical and electronic properties of the patch, as well as inducing a minimal immune response as revealed by a receding fibrotic capsule after 4 weeks implantation. Our findings pave the way towards closing the gap for the translation of organic bioelectronic devices from acute to long-termin vivomodels.
Increased elastase sensitivity and decreased intramolecular interactions in the more transmissible SARS-CoV-2 variants’ spike protein: Analysis of the new UK and SA SARS-CoV-2 variants
Authors: Pokhrel S. , Lee L. , Kraemer B.R. , Samardzic K. , Mochly-Rosen D.
Published: January 2021

Two SARS-CoV-2 variants showing increased transmissibility relative to the Wuhan virus have recently been identified. Although neither variant causes more severe illness or increased risk of death, the faster spread of the virus is a major threat. Using computational tools, we found that the new SARS-CoV-2 variants may acquire an increased transmissibility by increasing the propensity of its spike protein to expose the receptor binding domain. This information leads to the identification of potential treatments to avert the imminent threat of these more transmittable SARS-CoV-2 variants.

Teaser

The more infective SARS-CoV-2 variants may expose its Achilles Heel – an opportunity to reduce their spreading.
Thermodynamic and Kinetic Characterization of Protein Conformational Dynamics within a Riemannian Framework
Authors: Goolsby Curtis , Fakharzadeh Ashkan , Moradi Mahmoud
Published: January 2021

We have formulated a Riemannian framework for describing the geometry of collective variable spaces of biomolecules within the context of molecular dynamics (MD) simulations. The formalism provides a theoretical framework to develop enhanced sampling techniques, path-finding algorithms, and transition rate estimators consistent with a Riemannian treatment of the collective variable space, where the quantities of interest such as the potential of mean force (PMF) and minimum free energy path (MFEP) remain invariant under coordinate transformation. Specific algorithms within this framework are discussed such as the Riemannian umbrella sampling, the Riemannian string method, and a Riemannian-Bayesian estimator of free energy and diffusion constant, which can be used to estimate the transition rate along an MFEP.
Simulating freely-diffusing single-molecule FRET data with consideration of protein conformational dynamics
Authors: Losey James , Jauch Michael , Cortes-Cubero Axel , Wu Haoxuan , Polasa Adithya , Sauve Stephanie , Rivera Roberto , Matteson David S , Moradi Mahmoud
Published: January 2021

Single-molecule Förster resonance energy transfer experiments have added a great deal to the understanding of conformational states of biologically important molecules. While great progress has been made in studying structural dynamics of biomolecular systems, much is still unknown for systems with conformational heterogeneity particularly those with high flexibility. For instance, with currently available techniques, it is difficult to work with intrinsically disordered proteins, particularly when freely diffusing smFRET experiments are used. Simulated smFRET data allows for the control of the underlying process that generates the data to examine if a given smFRET data analysis technique can detect these underlying differences. Here, we include a distribution of inter-dye distances generated using Langevin dynamics to simulated freely-diffusing smFRET timestamp data in order to model proteins with conformational flexibility within a given state. We compare standard analysis techniques for smFRET data to validate the new module relative to the base PyBroMo software and observe qualitative agreement in the results of standard analysis for the two timestamp generation methods. The Langevin dynamics module provides a framework for generating timestamp data with a known underlying heterogeneity of inter-dye distances that will be necessary for the development of new analysis techniques that study flexible proteins or other biomolecular systems.