bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteome efficiency of metabolic pathways inEscherichia coliincreases along the nutrient flow
Authors: Hu Xiao-Pan , Schroeder Stefan , Lercher Martin J.
Published: November 2022

Understanding the allocation of the cellular proteome to different cellular processes is central to unraveling the organizing principles of bacterial physiology. Proteome allocation to protein translation itself is maximally efficient, i.e., it represents the minimal allocation of dry mass able to sustain the observed protein production rate. In contrast, recent studies on bacteria have demonstrated that the concentrations of many proteins exceed the minimal level required to support the observed growth rate, indicating some heterogeneity across pathways in their proteome efficiency. Here, we systematically analyze the proteome efficiency of metabolic pathways, which together account for more than half of theE. coliproteome during exponential growth. Comparing the predicted minimal and the observed proteome allocation to different metabolic pathways across growth conditions, we find that the most costly biosynthesis pathways – those for amino acid biosynthesis and cofactor biosynthesis – are expressed for near optimal efficiency. Overall, proteome efficiency increases along the carbon flow through the metabolic network: proteins involved in pathways of nutrient uptake and central metabolism tend to be highly over-abundant, while proteins involved in anabolic pathways and in protein translation are much closer to the expected minimal abundance across conditions. Our work thus provides a bird’s-eye view of metabolic pathway efficiency, demonstrating systematic deviations from optimal cellular efficiency at the network level.

Importance

Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth inE. coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions inE. coliand compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, are near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow inE. coli.
The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous proteasome inhibitor resistant disease
Authors: Bishop Ryan T. , Miller Anna K. , Froid Matthew , Nerlakanti Niveditha , Li Tao , Frieling Jeremy , Nasr Mostafa , Nyman Karl , Sudalagunta Praneeth R , Canevarolo Rafael , Silva Ariosto Siqueira , Shain Kenneth H. , Lynch Conor C. , Basanta David
Published: November 2022

Multiple myeloma (MM) is an osteolytic plasma cell malignancy that, despite being responsive to therapies such as proteasome inhibitors, frequently relapses. Understanding the mechanism and the niches where resistant disease evolves remains of major clinical importance. Cancer cell intrinsic mechanisms and bone ecosystem factors are known contributors to the evolution of resistant MM but the exact contribution of each is difficult to define with currentin vitroandin vivomodels. However, mathematical modeling can help address this gap in knowledge. Here, we describe a novel biology-driven hybrid agent-based model that incorporates key cellular species of the bone ecosystem that control normal bone remodeling and, in MM, yields a protective environment under therapy. Critically, the spatiotemporal nature of the model captures two key features: normal bone homeostasis and how MM interacts with the bone ecosystem to induce bone destruction. We next used the model to examine how the bone ecosystem contributes to the evolutionary dynamics of resistant MM under control and proteasome inhibitor treatment. Our data demonstrates that resistant disease cannot develop without MM intrinsic mechanisms. However, protection from the bone microenvironment dramatically increases the likelihood of developing intrinsic resistance and subsequent relapse. The spatial nature of the model also reveals how the bone ecosystem provides a protective niche for drug sensitive MM cells under treatment, consequently leading to the emergence of a heterogenous and drug resistant disease. In conclusion, our data demonstrates a significant role for the bone ecosystem in MM survival and resistance, and suggests that early intervention with bone ecosystem targeting therapies may prevent the emergence of heterogeneous drug resistant MM.
Long-term storage has minor effects on biobanked neonatal dried blood spot metabolome
Authors: Ottosson Filip , Russo Francesco , Abrahamsson Anna , Jensen MacSween Nadia Sara , Courraud Julie , Krag Nielsen Zaki , Hougaard David M. , Cohen Arieh S. , Ernst Madeleine
Published: November 2022

Over 2.5 million neonatal dried blood spots (DBS) are stored at the Danish National Biobank. These samples offer extraordinary possibilities for metabolomics research, including prediction of disease and understanding of underlying molecular mechanisms of disease development. Nevertheless, Danish neonatal DBS have been little explored in metabolomics studies. One question that remains is the long-term stability of the large number of metabolites typically assessed in untargeted metabolomics over long time periods of storage. Here, we investigate temporal trends of metabolites measured in 200 neonatal DBS collected over a time course of 10 years, using an untargeted LC-MS/MS based metabolomics protocol. We found that a majority (79%) of the metabolome was stable during 10 years of storage at -20°C. However, we found decreasing trends for lipid-related metabolites, such as phosphocholines and acylcarnitines. A few metabolites, including glutathione and methionine, may be strongly influenced by storage, with changes in metabolite levels up to 0.1-0.2 standard deviation units per year. Our findings indicate that untargeted metabolomics of DBS samples, with long-term storage in biobanks, is suitable for retrospective epidemiological studies. We identify metabolites whose stability in DBS should be closely monitored in future studies of DBS samples with long-term storage.
Development of Accurate Long-lead COVID-19 Forecast
Authors: Yang Wan , Shaman Jeffrey
Published: November 2022

Coronavirus disease 2019 (COVID-19) will likely remain a major public health burden; accurate forecast of COVID-19 epidemic outcomes several months into the future is needed to support more proactive planning. Here, we propose strategies to address three major forecast challenges, i.e., error growth, the emergence of new variants, and infection seasonality. Using these strategies in combination we generate retrospective predictions of COVID-19 cases and deaths 6 months in the future for 10 representative US states. Tallied over >25,000 retrospective predictions through September 2022, the forecast approach using all three strategies consistently outperformed a baseline forecast approach without these strategies across different variant waves and locations, for all forecast targets. Overall, probabilistic forecast accuracy improved by 64% and 38% and point prediction accuracy by 133% and 87% for cases and deaths, respectively. Real-time 6-month lead predictions made in early October 2022 suggested large attack rates in most states but a lower burden of deaths than previous waves during October 2022 – March 2023; these predictions are in general accurate compared to reported data. The superior skill of the forecast methods developed here demonstrate means for generating more accurate long-lead forecast of COVID-19 and possibly other infectious diseases.

Author Summary

Infectious disease forecast aims to reliably predict the most likely future outcomes during an epidemic. To date, reliable COVID-19 forecast remains elusive and is needed to support more proactive planning. Here, we pinpoint the major challenges facing COVID-19 forecast and propose three strategies. Comprehensive testing shows the forecast approach using all three strategies consistently outperforms a baseline approach without these strategies across different variant waves and locations in the United States for all forecast targets, improving the probabilistic forecast accuracy by ∼50% and point prediction accuracy by ∼100%. The superior skills of the forecast methods developed here demonstrate means for generating more accurate long-lead COVID-19 forecasts. The methods may be also applicable to other infectious diseases.

One sentence summary:

To support more proactive planning, we develop COVID-19 forecast methods that substantially improve accuracy with lead time up to 6 months.
Phenotypic, molecular and functional characterisation of humanin vitro-generated IL-17A+ CD8+ T-cells
Authors: Gray Elizabeth H. , Srenathan Ushani , Durham Lucy E. , Lalnunhlimi Sylvine , Steel Kathryn J. A. , Catrina Anca , Kirkham Bruce W. , Taams Leonie S.
Published: November 2022

IL-17A+ CD8+ T-cells, often referred to as Tc17 cells, have been identified at sites of inflammation in several immune-mediated inflammatory diseases including psoriasis and spondyloarthritis. Whilst much of our understanding of IL-17A+ CD8+ T-cells has been discerned from murine studies, human IL-17A+ CD8+ T-cells remain less-well characterised. We optimised anin vitropolarisation protocol to expand human IL-17A+ CD8+ T-cells from PBMC or bulk CD8+ T-cell populations for phenotypic and functional assessment. We show that T-cell activation in the presence of IL-1β and IL-23 significantly increased the frequencies of IL-17A+ CD8+ T-cells, which was not further enhanced by the addition of IL-6, IL-2 or anti-IFNγ mAb.In vitro-generatedIL-17A+ CD8+ T-cells from healthy donors displayed a distinct type-17 profile compared with IL-17A- CD8+ T-cells, as defined by transcriptional signature (IL17A, IL17F, RORC, RORA, MAF, IL23R, CCR6, CXCR6); high surface expression of CCR6 and CD161; and polyfunctional production of IL-17A, IL-17F, IL-22, IFNγ, TNFα and GM-CSF. A significant proportion ofin vitro-induced IL-17A+ CD8+ T-cells expressed TCRVα7.2 and bound MR1 tetramers, indicative of a MAIT CD8+ T-cell population. Using an IL-17A secretion assay, we demonstrate that thein vitro-generated IL-17A+ CD8+ T-cells were biologically functional and induced pro-inflammatory IL-6 and IL-8 production by synovial fibroblasts from patients with psoriatic arthritis. Collectively, we report anin vitroculture system to expand IL-17A+ CD8+ T-cells and further characterise their phenotype, transcriptional regulation and functional relevance to human health and disease.
ACNN-6mA Prediction of N6-Methyladenine Loci in Multiple Species Based on Rice Dataset Pre-training Model†
Authors: Bai JianGuo , Yang Hai
Published: November 2022

N6-methyladenine is an epigenetic modification that plays a significant role in various cellular processes. Genome-wide monitoring of methylation sites is conducive to understanding the biological function of methylation. Due to the limitations of traditional dry and wet experiments, a series of machine learning and deep learning methods have been developed to detect methylation sites, but their detection species are single or performance is poor. First of all, we conducted sufficient experiments on the widely studied rice datasets, and compared with the previous research, we have greatly improved in various indicators on the two rice datasets. Then we used the models trained on the rice dataset to fine-tune training in half of the other 11 datasets and predict the other half of the independent datasets. Then we used 11 trained models to test 11 species respectively. It was found that ACNN-6mA could obtain higher AUC, ACC and MCC whether cross-species prediction or independent verification set prediction. ACNN-6mA model and code for follow-up researchers is provided as an open-source tool available athttps://github.com/jrebai/ACNN-6mA.
Engineering CAR-NK cells targeting CD33 with concomitant extracellular secretion of anti-CD16 antibody revealed superior antitumor effects toward myeloid leukemia
Authors: Zhang Rui , Liu Qingxi , Zhou Sa , He Hongpeng , Zhao Mingfeng , Ma Wenjian
Published: November 2022

Acute myeloid leukemia (AML) is a common form of acute leukemia and current drugs are overall unsatisfactory. In the present study, we report an immune cell therapy strategy by employing genetically-modified bifunctional CAR-NK cells that combines efficient targeting of AML cells via the CD33 molecule with the concomitant stimulation of NK cell cytotoxicity through the expression and extracellular secretion of anti-CD16 antibody (B16) that binds back to the FC receptor of NK cells. Comparing to CAR-NK cells that target CD33 only, the bifunctional CD33/B16 CAR-NK cells showed superior killing efficiency toward AML cells in vitro, which increased about 4 times based on the number of cells needed to achieve 80% killing activity. In vivo study with xenograft model also revealed effective clearance of leukemic cells and much longer survival - no relapse or death for at least 60 days. In addition, the safety of CAR-NK is not changed with additional expression of B16 as determined by the release of cytokines. These data revealed a promising CAR-NK approach to treat AML patients, which may improve CAR-NK based treatment in general and have potential applications to deal with other tumors as well.
Blood Transcriptional Correlates of BCG-Induced Protection Against Tuberculosis in Rhesus Macaques
Authors: Liu Yiran E. , Darrah Patricia A. , Zeppa Joseph J. , Kamath Megha , Laboune Farida , Douek Daniel C. , Maiello Pauline , Roederer Mario , Flynn JoAnne L. , Seder Robert A. , Khatri Purvesh
Published: November 2022

Blood-based correlates of vaccine-induced protection against tuberculosis (TB) are urgently needed. We analyzed the blood transcriptome of rhesus macaques immunized with varying doses of intravenous (IV) BCG followed byMycobacterium tuberculosis(Mtb) challenge. We used high-dose IV BCG recipients for “discovery” and validated our findings in low-dose recipients and in an independent cohort of macaques receiving BCG via different routes. We identified seven vaccine-induced gene modules, including an innate module (module 1) enriched for type 1 interferon and RIG-I-like receptor signaling pathways. Module 1 on day 2 post-vaccination was highly correlated with lung antigen-responsive CD4 T cells at week 8 and withMtband granuloma burden following challenge. Parsimonious signatures within module 1 at day 2 post-vaccination predicted protection following challenge with AUROCs ≥ 0.91. Together these results indicate that the early innate transcriptional response to IV BCG in peripheral blood may provide a robust correlate of protection against TB.
Context-Aware Transcript Quantification from Long Read RNA-Seq data with Bambu
Authors: Chen Ying , Sim Andre , Wan Yuk Kei , Yeo Keith , Lee Joseph Jing Xian , Ling Min Hao , Love Michael I. , Göke Jonathan
Published: November 2022

Most approaches to transcript quantification rely on fixed reference annotations. However, the transcriptome is dynamic, and depending on the context, such static annotations contain inactive isoforms for some genes while they are incomplete for others.

To address this, we have developed Bambu, a method that performs machine-learning based transcript discovery to enable quantification specific to the context of interest using long-read RNA-Seq data. To identify novel transcripts, Bambu employs a precision-focused threshold referred to as the novel discovery rate (NDR), which replaces arbitrary per-sample thresholds with a single interpretable parameter. Bambu retains the full-length and unique read counts, enabling accurate quantification in presence of inactive isoforms.

Compared to existing methods for transcript discovery, Bambu achieves greater precision without sacrificing sensitivity. We show that context-aware annotations improve abundance estimates for both novel and known transcripts. We apply Bambu to human embryonic stem cells to quantify isoforms from repetitive HERVH-LTR7 retrotransposons, demonstrating the ability to estimate transcript expression specific to the context of interest.
Multiparameter stimulation mapping of signaling states in single pediatric immune cells reveals heightened tonic activation during puberty
Authors: Farmer Rohit , Apps Richard , Quiel Juan , Sellers Brian A. , Cheung Foo , Chen Jinguo , Mukherjee Amrita , McGuire Peter J. , Tsang John S.
Published: November 2022

Cellular stimulation via factors such as cytokines followed by multiparameter single-cell measurements is a powerful approach to interrogate cellular functions. However, transforming such high-dimensional data into biological insights presents unique challenges, particularly given the extensive response heterogeneity among single cells, such as the presence of bimodal responding versus non-responding subpopulations upon stimulation. Here we present an unsupervisedhigh-dimensional approach for analyzingstimulation responses at the single cell level (HDStIM)and apply it to evaluate how pediatric development may shape peripheral immune cell signaling states and responsiveness to stimulations in 42 subjects (age: 2 - 16). We show that in comparison to the conventional approach of assessing one marker at a time by averaging across single cells, HDStIM can effectively learn, in an unsupervised fashion, the multi-parameter signature of responding versus non-responding cells to accurately quantify responses within cell populations. HDStIM reveals that the extent of pre-stimulation/baseline activation of interferon-related and TCR signaling molecules in myeloid and T cells, respectively, increases during puberty. This suggests that puberty is marked by a heightened “tonic” activation state in these cells, perhaps to strengthen defense against pathogens during this period of human development.
Selecting Chromosomes for Polygenic Traits
Authors: Zuk Or
Published: November 2022

We define and study the problem ofchromosomal selectionfor multiple complex traits. In this problem, it is assumed that one can construct a genome by selecting different genomic parts (e.g. chromosomes) from different cells. The constructed genome is associated with a vector of polygenic scores, obtained by summing the polygenic scores of the different genomic parts, and the goal is to minimize a loss function of this vector. While out of reach today, the problem may become relevant in the future with emerging future technologies, and may yield far greater gains in the loss compared to the present day technology of as embryo selection, provided that technological and ethical barriers are overcome. We suggest and study several natural loss functions relevant for both quantitative traits and disease. We propose two algorithms, a Branch-and-Bound technique, to solve the problem for multiple traits and any monotone loss function, and a convex relaxation algorithm applicable for any differentiable loss. Finally, we use the infinitesimal model for genetic architecture to approximate the potential gain achieved by chromosomal selection for multiple traits.
Genetic architecture of acute hyperthermia resistance in juvenile rainbow trout (Oncorhynchus mykiss) and genetic correlations with production traits
Authors: Lagarde Henri , Lallias Delphine , Patrice Pierre , Prchal Martin , François Yoannah , D’Ambrosio Jonathan , Segret Emilien , Acin-Perez Ana , Cachelou Frederic , Haffray Pierrick , Dehaullon Audrey , Dupont-Nivet Mathilde , Phocas Florence
Published: November 2022

Background

Selective breeding is a promising solution to reduce fish farms vulnerability to heat peaks which intensity and frequency are predicted to increase due to climate change. However, limited information about the genetic architecture of acute hyperthermia resistance in fish is available.

Two batches of sibs from a rainbow trout commercial line were produced. The first batch (N=1,382) was phenotyped for acute hyperthermia resistance at nine months, and the second batch (N=1,506) was phenotyped for main production traits (growth, body length, muscle fat content and carcass yield) at twenty months. Fish were genotyped on a 57K SNP array, and their genotypes were imputed at high-density thanks to their parents being genotyped on a 665K SNP array.

Results

The heritability estimate of resistance to acute hyperthermia in juveniles was 0.29 ± 0.05, confirming the potential of selective breeding for this trait. Genetic correlations between acute hyperthermia resistance and main production traits at near harvest age were all close to zero. Hence, selecting for acute hyperthermia resistance should not impact the main production traits, and reversely.

The genome-wide association study revealed that resistance to acute hyperthermia is highly polygenic; altogether, the six detected QTL explained less than 5% of the genetic variance. Two of these QTL, including the most significant one, might explain acute hyperthermia resistance differences across INRAE isogenic lines of rainbow trout. The phenotypic mean differences between homozygotes at peak SNP were up to 69% of the phenotypic standard deviation, showing promising potential for marker-assisted selection. We identified 89 candidate genes within the six QTL regions, among which the most convincing functional candidate genes werednajc7,hsp70b,nkiras2,cdk12,phb,fkbp10,ddx5,cygb1,enpp7,pdhxandacly.

Conclusions

This study provides valuable insight on the genetic architecture of acute hyperthermia resistance in juvenile rainbow trout. The potential for the selective breeding of this trait was shown to be substantial and should not interfere with selection for main production traits. Identified functional candidate genes give a new insight on physiological mechanisms involved in acute hyperthermia resistance, such as protein chaperoning, oxidative stress response, homeostasis maintenance and cell survival.
Phylogenomic comparative methods: accurate evolutionary inferences in the presence of gene tree discordance
Authors: Hibbins Mark S. , Breithaupt Lara C. , Hahn Matthew W.
Published: November 2022

Phylogenetic comparative methods have long been a mainstay of evolutionary biology, allowing for inferences of the tempo and mode of trait evolution across species while accounting for their common ancestry. These analyses typically assume a single, bifurcating phylogenetic tree that describes the shared history among species. However, modern phylogenomic analyses have shown that genomes are often composed of a mosaic of different histories that can disagree both with the species tree and with each other—so-called discordant gene trees. These gene trees describe shared histories that are not captured by the species tree, and therefore that are unaccounted for in classic comparative approaches. The application of standard phylogenetic comparative methods to species histories containing discordance leads to incorrect inferences about the timing, direction, and rate of evolution. Here, we develop two approaches for incorporating gene tree histories into comparative methods: one involves constructing a fuller phylogenetic variance-covariance matrix that includes relationships not found in the species tree, and another that applies Felsenstein’s pruning algorithm over a set of gene trees to calculate trait histories and likelihoods. Both approaches are agnostic to the biological causes of gene tree discordance, which may include incomplete lineage sorting and introgression. Using simulation, we demonstrate that our new approaches generate much more accurate estimates of tree-wide rates of trait evolution than standard methods. We apply our methods to two clades of the wild tomato genusSolanumwith varying rates of discordance, demonstrating the contribution of gene tree discordance to variation in a set of floral traits and the ability of our approaches to provide more accurate inferences. Our new approaches have the potential to be applied to a broad range of classic inference problems in phylogenetics, including ancestral state reconstruction and the inference of lineage-specific rate shifts.
Expression of retrotransposons contributes to aging inDrosophila
Authors: Schneider Blair K. , Sun Shixiang , Lee Moonsook , Li Wenge , Skvir Nicholas , Neretti Nicola , Vijg Jan , Secombe Julie
Published: November 2022

Retrotransposons are a class of transposable elements capable of self-replication and insertion into new genomic locations. Across species, the mobilization of retrotransposons in somatic cells has been suggested to contribute to the cell and tissue functional decline that occurs during aging. Retrotransposon expression generally increases with age, andde novoinsertions have been observed to occur during tumorigenesis. However, the extent to which new retrotransposon insertions occur during normal aging and their effect on cellular and animal function remains understudied. Here we use a single nucleus whole genome sequencing approach inDrosophilato directly test whether transposon insertions increase with age in somatic cells. Analyses of nuclei from thoraces and indirect flight muscles using a newly developed pipeline, Retrofind, revealed no significant increase in the number of transposon insertions with age. Despite this, reducing the expression of two different retrotransposons,412andRoo,extends lifespan, without increasing stress resistance. This suggests a key role for transposon expression and not insertion in regulating longevity. Transcriptomic analyses revealed similar changes to gene expression in412andRooknockdown flies and highlighted potential changes to genes involved in proteolysis and immune function as potential contributors to the observed changes in longevity. Combined, our data show a clear link between retrotransposon expression and aging.

Author Summary

With the onset of modern medicine, the average age of the population has significantly increased, leading to more individuals living with chronic health issues. Rather than treat each age-associated disorder individually, one approach to target multiple health concerns simultaneously might to be target aging itself. Genomic instability is a hallmark of aging cells that has been proposed to be a key contributor to age-associated cellular decline. Transposons are mobile genetic elements capable of inserting into new genomic locations, thus having the potential to increase genomic instability. Consistent with this, transposon expression generally increases with age. However, the extent to which transposon insertions accumulate to disrupt the genome of cells within aging individuals has remained an open question. We specifically answer this through single cell whole genome sequencing and find that transposon insertions do not increase with age. Even though insertions did not increase, the expression of transposons is linked to aging, as reducing the expression of individual transposons extended lifespan. Transcriptome studies of these long-lived flies revealed increased expression of genes linked to proteolysis genes and to functioning of the immune system. Our study therefore establishes transposon expression, and not insertion, as a critical contributor to animal aging.
Molecular Analyses Place the GenusKerauneaOutside Convolvulaceae
Authors: Muñoz-Rodríguez Pablo , Wood John R.I. , González Lucía Villaescusa , Davis Charles C. , Goodwin Zoë A. , Scotland Robert W.
Published: November 2022

The genusKerauneawas recently described in the Convolvulaceae Juss. family. Two species are currently recognised, both from Brazil. Molecular sequence data using three commonly applied DNA markers (matK, rbcLand thenuclear ribosomal Internal Transcribed Spacer) show that neither species is correctly placed in Convolvulaceae but indicates that the type,K. brasiliensis, should be placed in Malpighiaceae despite several morphological anomalies. The second species,K. capixaba, should be placed in Ehretiaceae. Given the surprising nature of these results, further studies are recommended before formal reclassification of these two taxa is made.
Evidence for Embracing Normative Modeling
Authors: Rutherford Saige , Barkema Pieter , Tso Ivy F. , Sripada Chandra , Beckmann Christian F. , Ruhe Henricus G. , Marquand Andre F.
Published: November 2022

In this work, we expand the normative model repository introduced inRutherford et al. (2022a) to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we confirm the advantage (i.e., stronger effect sizes, more accurate classification and prediction) of using normative modeling features. We intend for these accessible resources to facilitate wider adoption of normative modeling across the neuroimaging community.
Neuroanatomical substrates in Parkinson’s Disease psychosis and their association with serotonergic receptor gene expression: A coordinate-based meta-regression analysis
Authors: Pisani Sara , Gunasekera Brandon , Lu Yining , Vignando Miriam , ffytche Dominic , Aarsland Dag , Chaudhuri K. Ray , Ballard Clive , Lee Jee-Young , Kim Yu Kyeong , Velayudhan Latha , Bhattacharyya Sagnik
Published: November 2022

Background

Common neural underpinning of Parkinson’s Disease (PD) psychosis across different structural magnetic resonance imaging (MRI) studies remains unclear to this day with few studies and even fewer meta-analyses available.

Objectives

Our meta-analysis aimed to identify and summarise studies using MRI approach to identify PD psychosis-specific brain regions and examine the relation between cortical volume loss and dopaminergic and serotonergic receptor density.

Methods

PubMed, Web of Science and Embase were searched for MRI studies of PD psychosis (PDP) compared to PD patients without psychosis (PDnP). Seed-baseddMapping with Permutation of Subject Images was applied in the meta-analysis where coordinates were available. Multiple linear regressions to examine the relationship between grey matter volume loss in PDP and receptor gene expression density (extracted from the Allen Human Brain Atlas) were conducted in R.

Results

We observed lower grey matter volume in parietal-temporo-occipital regions from our meta-analysis (N studies =10, PDP n=211, PDnP, n=298). These results remained significant after adjusting for PD medications and for cognitive scores. Grey matter volume loss in PDP was associated with local expression of 5-HT1a (b=0.109,p=0.012) and 5-HT2a receptors (b=-0.106,p=0.002) also after adjusting for PD medications (5-HT1a,p= 0.005; 5-HT2a,p= 0.001).

Conclusions

Widespread cortical volume loss in the parieto-temporo-occipital regions involved in information processing and integration, as well as attention, could result in PD psychosis symptoms. Neurobiological mechanisms implicating serotonergic receptors may also contribute to this condition.
Identification and Characterization of ML321: a Novel and Highly Selective D2Dopamine Receptor Antagonist with Efficacy in Animal Models that Predict Atypical Antipsychotic Activity
Authors: Free R. Benjamin , Nilson Ashley N. , Boldizsar Noelia M. , Doyle Trevor B. , Rodriguiz Ramona M. , Pogorelov Vladimir M. , Machino Mayako , Lee Kuo Hao , Bertz Jeremiah W. , Xu Jinbin , Lim Herman D. , Dulcey Andrés E. , Mach Robert H. , Woods James H. , Lane J Robert , Shi Lei , Marugan Juan J. , Wetsel William C. , Sibley David R.
Published: November 2022

We have developed and characterized a novel D2R antagonist with exceptional GPCR selectivity – ML321. In functional profiling screens of 168 different GPCRs, ML321 showed little activity beyond potent inhibition of the D2R, and to a lesser extent the D3R, demonstrating excellent receptor selectivity. The D2R selectivity of ML321 may be related to the fact that, unlike other monoaminergic ligands, ML321 lacks a positively charged amine group and adopts a unique binding pose within the orthosteric binding site of the D2R. PET imaging studies in non-human primates demonstrated that ML321 penetrates the CNS and occupies the D2R in a dose-dependent manner. Behavioral paradigms in rats demonstrate that ML321 can selectively antagonize a D2R-mediated response (hypothermia) while not affecting a D3R-mediated response (yawning) using the same dose of drug, thus indicating exceptionalin vivoselectivity. We also investigated the effects of ML321 in animal models that are predictive of antipsychotic efficacy in humans. We found that ML321 attenuates both amphetamine- and phencyclidine-induced locomotor activity and restored pre-pulse inhibition (PPI) of acoustic startle in a dose-dependent manner. Surprisingly, using doses that were maximally effective in both the locomotor and PPI studies, ML321 was relatively ineffective in promoting catalepsy. Kinetic studies revealed that ML321 exhibits slow-on and fast-off receptor binding rates, similar to those observed with atypical antipsychotics with reduced extrapyramidal side effects. Taken together, these observations suggest that ML321, or a derivative thereof, may exhibit “atypical” antipsychotic activity in humans with significantly fewer side effects than observed with currently FDA-approved D2R antagonists.
Host genomic variation shapes gut microbiome diversity in threespine stickleback fish
Authors: Small Clayton M. , Beck Emily A. , Currey Mark C. , Tavalire Hannah F. , Bassham Susan , Cresko William A.
Published: November 2022

Variation among host-associated microbiomes is well documented across species, populations, and individuals. However, the relative importance of host genetic differences for microbiome variation has been difficult to study. While research in humans has shown that genetic variation influences microbiome differences, confounding environmental effects have been very difficult to control. Isogenic laboratory models help isolate host genetic variants to test for influences of the environment or large-effect mutations on the microbiome, but such studies seldom incorporate natural genetic variation. Thus, although many important factors potentially impacting the microbiome have been identified, most studies have failed to test for the direct influence of natural host-genetic variation on microbiome differences within a controlled environment. Understanding the relationship between host-genetic and microbial variation also has biomedical implications, such as understanding why some humans are more susceptible to chronic inflammatory disorders like Crohn’s Disease and Ulcerative Colitis. To directly assess the relationship between host-genetic variation and microbiome variation, we performed a common garden experiment using laboratory lines of genetically divergent populations of threespine stickleback fish – a species that is an outbred model organism commonly used for determining the genetic basis of complex traits in the context of natural genetic variation. Using germ-free derivation and the powerful common garden design with these divergent lines, as well as hybrids between them, we detected clear associations between stickleback genetic dissimilarity and microbiome dissimilarity. Using genome-wide RAD-seq data we also identified regions of the genome underlying differences in microbiome composition. Importantly, we highlight that heritable morphological traits such as body size that are correlated with microbiome dissimilarity also need consideration in future microbiome studies.
Application of a Latent Trait Modeling Method for Missing Data Across Datasets: Guidance on Appropriate Factor Structure
Authors: Bartlett Christopher W. , Gorham Tyler J. , Knapp Emily A. , Kress Amii M. , Klamer Brett G. , Buyske Steven , Lau Bryan , Petrill Stephen A.
Published: November 2022

Latent trait space can be leveraged to harmonize small data into big data when the constituent datasets measure the same underlying (latent) domains using a set of partially overlapping measurement instruments in each domain. The latent trait space then acts as a common metric space for each dataset, thus ensuring the same scale for the latent traits across datasets, despite the use of non-identical sets of measurement instruments within datasets. This approach, as originally published, only applied to a narrow set of circumstances, namely, that each measurement instrument occurred in more than one dataset. Here, we extend the latent trait approach to drop this requirement by using matrix completion methods. Using a simulation study, we evaluate the reliability of this extension and offer guidance on circumstances when the latent trait approach to missing data is robust and practical on real datasets.
CREATE’ing improvements in first-year students’ science efficacy that are independent of instructor rank and experience in a large, multi-section online introductory course
Authors: Garzke Jessica , Steinwand Blaire J.
Published: November 2022

With a primary objective to engage students in the process of science online, we transformed a long-standing laboratory course for first-year science students into a more accessible, immersive experience of current biological research using a narrow and focused set of primary literature and the CREATE pedagogy. The efficacy of the CREATE approach has been demonstrated in a diversity of higher education settings and courses. It is, however, not yet known if CREATE can be successfully implemented online with a large, diverse team of faculty untrained in the CREATE pedagogy. Here, we present the transformation of a large-enrollment, multi-section, multi-instructor course for first-year students in which instructors follow different biological research questions but work together to reach shared goals and outcomes. We assessed students’: (1) science self-efficacy and (2) epistemological beliefs about science throughout an academic year of instruction fully administered online as a result of ongoing threats posed by COVID-19. Our findings demonstrate that novice CREATE instructors with varying levels of teaching experience and ranks can achieve comparable outcomes and improvements in students’ science efficacy in the virtual classroom as a teaching team. This study extends the use of the CREATE strategy to large, team-taught, multi-section courses and shows its utility in the online teaching and learning environment.
Exome sequencing identifies variants associated with semen quality in Holstein Friesian and Hallikar bulls
Authors: Kunnath Sarin K. , Ramesha K.P. , Kataktalware Mukund A. , Kumaresan A. , Jeyakumar S. , Das D.N. , Manimaran A. , Devadasan M. Joel , Ashwitha A. , Mall Shweta , Keshava Prasad T.S.
Published: November 2022

Effective fertility of bulls is dependent on semen quality, often determined based on standard semen evaluation tests. Here we report Whole Exome Sequencing (WES) of 12 bulls from two breeds Holstien Friesian and Hallikar selected based on Ejaculate Rejection Rate (ERR). We explored the possibility of identifying genetic variants from the conserved protein coding regions of genome. A total of 10,510 SNPs and 10.236 INDELs were identified post alignment against reference genome (ARS-UCD 1.2) and were annotated using SnpEff. The number of variants with high and modifier functional impact detected were 145 and 19,122, respectively. Genetic variants common to both high and low ERR group bulls among Holstein Friesian were 08 and in Hallikarthe common variants were 51. Prominentgenesviz.UCP2, PANK2, GPD2, PTPRG, LARP7, EZH1, DENND1BandTDRD9with a role in determining the semen quality were observed to be carriers of the genetic variant.
An attempt at restoring original radiocarbon ages in collagen from bioapatite
Authors: Trindade Dantas Mário André , Cherkinsky Alexander
Published: November 2022

In the literature there is a consensus that radiocarbon dating performed in bioapatite presents younger datings than those performed in collagen, thus, we propose a general regression that could be used to convert the radiocarbon dating performed in bioapatite to the original ones in collagen in fossil samples all of the world. This general regression presents several good indexes of quality, high correlation (R2= 0.98), lower values of percent predicted error (%PE = 0.01), and the standard error of the estimate (%SEE = 25), showing that is a good tool, as the predicted values are similar to those observed. Using this regression we converted the radiocarbon datings in bioapatite to collagen made for several taxa from the Brazilian Intertropical Region, and suggest that these datings could be 1-7 Cal BP kyr older than previously thought.
The City Nature Challenge – A global citizen science phenomenon contributing to biodiversity knowledge and informing local government practices
Authors: Palma Estibaliz , Mata Luis , Cohen Kylie , Evans Doug , Gandy Bernard , Gaskell Nadine , Hatchman Hiliary , Mezzetti Anna , Neumann Deborah , O’Keefe Jessica , Shaw Amy , Wells Millie , Williams Laurence , Hahs Amy K.
Published: November 2022

The bioblitz phenomenon has recently branched into cities, presenting exciting opportunities for local governments to channel participants’ efforts toward local issues. The City Nature Challenge (CNC) is one such initiative that has been quickly uptaken by hundreds of municipalities worldwide. Despite high participation, we still lack a framework for evaluating how the CNC contributes to local biodiversity knowledge and to inform local government practices. Here, we develop such a tool and present a case study that illustrates its applicability. We demonstrate that the collected records contributed to a better understanding of contemporary, local biodiversity patterns and provided a more realistic representation of understudied groups such as insects and fungi. Importantly, we show that the CNC presented local governments with a cost-effective tool to make informed, evidence-based management and policy decisions, improve education and engagement programs, foster cross-council collaborations, and support a stronger sense of environmental stewardship within the local community.
When and why grid cells appear or not in trained path integrators
Authors: Sorscher Ben , Mel Gabriel C. , Nayebi Aran , Giocomo Lisa , Yamins Daniel , Ganguli Surya
Published: November 2022

Recent work has claimed that the emergence of grid cells from trained path-integrator circuits is a more fragile phenomenon than previously reported. In this note we critically assess the main analysis and simulation results underlying this claim, within the proper context of previously published theoretical work. Our assessment reveals that the emergence of grid cells is entirely consistent with this prior theory: hexagonal grid cells robustly emerge precisely when prior theory predicts they should, and don’t when prior theory predicts they should not.
A Peroxiredoxin-P38 MAPK scaffold increases MAPK activity by MAP3K-independent mechanisms
Authors: Cao Min , Day Alison M , Galler Martin , Latimer Heather , Byrne Dominic P , Dwyer Emilia , Bennett Elise , Eyers Patrick A , Veal Elizabeth A
Published: November 2022

Peroxiredoxins (Prdx) utilize reversibly oxidized cysteine residues to reduce peroxides but also to promote H2O2signal transduction, including H2O2-induced activation of P38 MAPK. Prdx form H2O2-induced disulfide complexes with many proteins, including multiple kinases involved in P38 MAPK signaling. Here we show that a genetically-encoded fusion between Prdx and the P38 MAPK is sufficient to hyperactivate the kinase in yeast and human cells by a mechanism that does not require the H2O2-sensing cysteine of the Prdx. In yeast, we demonstrate that a P38-Prdx fusion protein compensates for the loss of a scaffold protein and upstream MAP3K kinase activity, driving entry into mitosis. Based on our findings, we propose that the H2O2-induced formation of Prdx-MAPK disulfide complexes provides a scaffold and signaling platform for MAPKK-MAPK signaling. The demonstration that formation of a complex with a Prdx can be sufficient to modify the activity of a kinase has broad implications for peroxide-based signal transduction in eukaryotes.

Highlights

P38-Prdx complexes increase P38 (Sty1/MAPK14) phosphorylation in yeast and human cells

TheS. pombePrdx promotes transient thioredoxin-mediated oxidation of a MAPK tyrosine phosphatase

P38-Prdx complexes increase P38(Sty1) activity by phosphatase and MAP3K-independent mechanisms

P38-Prdx complexes increase the stability and phosphorylation of theS. pombeP38 MAPKK (Wis1)

Non-canonical, H2O2-induced autophosphorylation contributes to activation of the Wis1 MAPKK
A global survey of host, aquatic, and soil microbiomes reveals shared abundance and genomic features between bacterial and fungal generalists
Authors: Loos Daniel , Pereira da Costa Filho Ailton , Dutilh Bas E. , Barber Amelia E. , Panagiotou Gianni
Published: November 2022

Environmental change coupled with alteration in human lifestyles are profoundly impact-ing the microbial communities that play critical roles in the health of the Earth and its inhabitants. To identify bacteria and fungi that are resistant and susceptible to habitat changes respectively, we retrieved paired 16S and ITS rRNA amplicon sequence data from 1,580 host, soil, and aquatic samples and explored the ecological patterns of the thousands of detected bacterial and fungal genera. Through this large-scale analysis, we identified 48 bacterial and 4 fungal genera that were prevalent and abundant across the three biomes, demonstrating their fitness in diverse environmental conditions. The presence of generalists significantly contributed to the alpha diversity of their respective kingdom. Their distri-bution across samples explained a large percentage of the variation in the cross-kingdom community structure. We also found that the genomes of these generalists were larger and encoded more secondary metabolism and antimicrobial resistance genes, illuminating how they can dominate diverse microbial communities. Conversely, 30 bacterial and 19 fungal genera were only found in a single habitat, suggesting they cannot readily adapt to different and changing environments. These findings can contribute to our understanding of microbial niche breadth and its consequences for global diversity loss.
UNSUPERVISED HARMONIZATION OF BRAIN MRI USING 3D CYCLE GANS AND ITS EFFECT ON BRAIN AGE PREDICTION
Authors: Komandur Dheeraj , Gupta Umang , Chattopadhyay Tamoghna , Dhinagar Nikhil J. , Thomopoulos Sophia I. , Chen Jiu-Chiuan , Beavers Dan , Steeg Greg ver , Thompson Paul M. ,   the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: November 2022

Deep learning methods trained on brain MRI data from one scanner or imaging protocol can fail catastrophically when tested on data from other sites or protocols - a problem known asdomain shift. To address this, here we propose adomain adaptationmethod that trains a 3D CycleGAN (cycle-consistent generative adversarial network) to harmonize brain MRI data from 5 diverse sources (ADNI, WHIMS, OASIS, AIBL, and UK Biobank; total N=4,941 MRIs, age range: 46-96 years). The approach uses 2 generators and 2 discriminators to generate an image harmonized to a specific target dataset given an image from the source domain distribution andvice versa. We train the CycleGAN to jointly optimize an adversarial loss and cyclic consistency. We use a patch-based discriminator and impose identity loss to further regularize model training. To test the benefit of the harmonization, we show that brain age estimation - a common benchmarking task - is more accurate in GAN-harmonized versus raw data.t-SNE maps show the improved distributional overlap of the harmonized data in the latent space.