bluuebunny/crossref_metadata_2025 huggingface dataset:
Systematic Single Cell Pathway Analysis (SCPA) reveals novel pathways engaged during early T cell activation
Authors: Bibby Jack A. , Agarwal Divyansh , Freiwald Tilo , Kunz Natalia , Merle Nicolas S. , West Erin E. , Larochelle Andre , Chinian Fariba , Mukherjee Somabha , Afzali Behdad , Kemper Claudia , Zhang Nancy R.
Published: February 2022

Next generation sequencing technologies have revolutionized the study of T cell biology, capturing previously unrecognized diversity in cellular states and functions. Pathway analysis is a key analytical stage in the interpretation of such transcriptomic data, providing a powerful method for detecting alterations in important biological processes. Current pathway analysis tools are built on models developed for bulk-RNA sequencing, limiting their effectiveness when applied to more complex single cell RNA-sequencing (scRNA-seq) datasets. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package Single Cell Pathway Analysis (SCPA). After demonstrating the effectiveness of SCPA over commonly used methods, we generate a scRNA-seq T cell dataset and characterize pathway activity over early cellular activation and between T cell populations. This revealed unexpected regulatory pathways in T cells, such as an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems level characterization of pathway activity in T cells across multiple human tissues also revealed alpha defensin expression as a hallmark of bone marrow derived T cells. Overall, our work here provides a widely applicable tool for single cell pathway analysis, and highlights unexpected regulatory mechanisms of T cells using a novel T cell dataset.
Transient oscillations of neural firing rate associated with routing of evidence in a perceptual decision
Authors: Odean Naomi N , Sanayei Mehdi , Shadlen Michael N
Published: February 2022

To form a perceptual decision the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se.
Genome-wide analysis and evolutionary history of the Necrosis and Ethylene-inducing peptide 1-like protein (NLP) superfamily across the Dothideomycetes class of fungi
Authors: Dal’Sasso Thaís C. S. , Rody Hugo V. S. , Oliveira Luiz O.
Published: February 2022

Necrosis and Ethylene-inducing peptide 1-like proteins (NLPs) are broadly distributed across bacteria, fungi and oomycetes. Cytotoxic NLPs are usually secreted into the host apoplast where they can induce cell death and trigger plant immune responses in eudicots. To investigate the evolutionary history of the NLPs, we accessed the genomic resources of 79 species from 15 orders of Dothideomycetes. Phylogenetic approaches searched for biased patterns of NLP gene evolution and aimed to provide a phylogenetic framework for the cytotoxic activities of NLPs. Among Dothideomycetes, the NLP superfamily sizes varied, but usually contained from one to six members. Superfamily sizes were higher among pathogenic fungi, with family members that were mostly effector NLPs. Across species, members of the NLP1 family (Type I NLPs) were predominant (84%) over members of the NLP2 family (Type II NLPs). The NLP1 family split into two subfamilies (NLP1.1 and NLP1.2). The NLP1.1 subfamily was broadly distributed across Dothideomycetes. There was strong agreement between the phylogenomics of Dothideomycetes and the phylogenetic tree based on members of the NLP1 subfamilies. To a lesser extent, phylogenomics also agreed with the phylogeny based on members of the NLP2 family. While gene losses seem to have shaped the evolutionary history of NLP2 family, ancient gene duplications followed by descent with modification characterized the NLP1 family. The strongest cytotoxic activities were recorded on NLPs of the NLP1.1 subfamily, suggesting that biased NLP gene retention in this subfamily favored the cytotoxic paralogs.
iDESC: Identifying differential expression in single-cell RNA sequencing data with multiple subjects
Authors: Liu Yunqing , Wang Ningya , Adams Taylor S. , Schupp Jonas C. , Wu Weimiao , McDonough John E. , Chupp Geoffrey L. , Kaminski Naftali , Wang Zuoheng , Yan Xiting
Published: February 2022

Single-cell RNA sequencing (scRNA-seq) enables assessment of transcriptome-wide changes at single-cell resolution. However, dominant subject effect in scRNA-seq datasets with multiple subjects severely confounds cell-type-specific differential expression (DE) analysis. We developed iDESC to separate subject effect from disease effect with consideration of dropouts to identify DE genes. iDESC was shown to have well-controlled type I error and high power compared to existing methods and obtained the best consistency between datasets and disease relevance in two scRNA-seq datasets from same disease, suggesting the importance of considering subject effect and dropouts in the DE analysis of scRNA-seq data with multiple subjects.
Haplotype-enhanced inference of somatic copy number profiles from single-cell transcriptomes
Authors: Gao Teng , Soldatov Ruslan , Sarkar Hirak , Kurkiewicz Adam , Biederstedt Evan , Loh Po-Ru , Kharchenko Peter
Published: February 2022

Genome instability and aberrant alterations of transcriptional programs both play important roles in cancer. However, their relationship and relative contribution to tumor evolution and therapy resistance are not well-understood. Single-cell RNA sequencing (scRNA-seq) has the potential to investigate both genetic and non-genetic sources of tumor heterogeneity in a single assay. Here we present a computational method, Numbat, that integrates haplotype information obtained from population-based phasing with allele and expression signals to enhance detection of CNVs from scRNA-seq data. To resolve tumor clonal architecture, Numbat exploits the evolutionary relationships between subclones to iteratively infer the single-cell copy number profiles and tumor clonal phylogeny. Analyzing 21 tumor samples composed of multiple myeloma, breast, and thyroid cancers, we show that Numbat can accurately reconstruct the tumor copy number profile and precisely identify malignant cells in the tumor microenvironment. We uncover additional subclonal complexity contributed by allele-specific alterations, and identify genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. We hope that the increased power to characterize genomic aberrations and tumor subclonal phylogenies provided by Numbat will help delineate contributions of genetic and non-genetic mechanisms in cancer.
Converging pathways found in copy number variation syndromes with high schizophrenia risk
Authors: Ehrhart Friederike , Silva Ana , van Amelsvoort Therese , von Scheibler Emma , Evelo Chris , Linden David E.J.
Published: February 2022

Schizophrenia genetics is complex, and the contribution of common and rare variants are not fully understood. Several specific copy number variations (CNVs) confer increased risk for schizophrenia, and the study of their effects is central to molecular models of mental illness. However, these CNVs – microdeletions or -duplications – are spread across the genome and differ in the number of genes affected and classes of coded proteins. This suggests that, in order to fully understand the contribution of these genetic variants to mental illness, we need to look beyond the deleted or duplicated genes, to their interaction partners and involved molecular pathways.

In this study, we developed machine-readable interactive pathways to enable analysis of downstream effects of genes within CNV loci and identify common pathways between CNVs with high schizophrenia risk using the WikiPathways database, and schizophrenia risk gene collections from GWAS studies and a gene-disease association database. For CNVs that are pathogenic for schizophrenia, we found overlapping pathways, including BDNF signaling, cytoskeleton, cell-cell connections, inflammation and MAPK3 signaling. Common schizophrenia risk genes identified by different studies are found in all CNV pathways but not enriched.

Our findings suggest that specific pathways – such as BDNF signaling – may be critical contributors to schizophrenia risk conferred by rare CNVs, and common risk variants may operate through distinct mechanisms. Our approach also highlights the importance of not only investigating deleted or duplicated genes within pathogenic CNV loci, but also study their direct interaction partners, which may explain pleiotropic effects of CNVs on schizophrenia risk.
Landscape functional connectivity for butterflies under different scenarios of land-use, land-cover, and climate change in Australia
Authors: Diengdoh Vishesh L. , Ondei Stefania , Amin Rahil J. , Hunt Mark , Brook Barry W.
Published: February 2022

Pollinating invertebrates are vital to terrestrial ecosystems but are impacted by anthropogenic habitat loss/fragmentation and climate change. Conserving and improving landscape connectivity is important to offset those threats, yet its assessment for invertebrates is lacking. In this study, we evaluated the functional connectivity between protected areas in Australia for 59 butterfly species, under present conditions and different future scenarios (for 2050 and 2090) of land-use, land-cover, and climate change. Using circuit-theory analysis, we found that functional connectivity under present conditions varies widely between species, even when their estimated geographical ranges are similar. Under future scenarios, functional connectivity is predicted to decrease overall, with negative changes worsening from 2050 to 2090, although a few species are positive exceptions. We have made our results available as spatial datasets to allow comparisons with taxa from other studies and can be used to identify priority areas for conservation in terms of establishing ecological corridors or stepping-stone habitat patches. Our study highlights the importance of considering pollinating invertebrates when seeking holistic conservation and restoration of a landscape’s functional connectivity, underscoring the need to expand and promote protected areas to facilitate functional connectivity under future scenarios of global change.

Research Data

The habitat suitability maps and functional connectivity maps are made available as GeoTiff images via Figshare (10.6084/m9.figshare.19130078).
An Analysis of Protein Language Model Embeddings for Fold Prediction
Authors: Villegas-Morcillo Amelia , Gomez Angel M. , Sanchez Victoria
Published: February 2022

The identification of the protein fold class is a challenging problem in structural biology. Recent computational methods for fold prediction leverage deep learning techniques to extract protein fold-representative embeddings mainly using evolutionary information in the form of multiple sequence alignment (MSA) as input source. In contrast, protein language models (LM) have reshaped the field thanks to their ability to learn efficient protein representations (protein-LM embeddings) from purely sequential information in a self-supervised manner. In this paper, we analyze a framework for protein fold prediction using pre-trained protein-LM embeddings as input to several fine-tuning neural network models which are supervisedly trained with fold labels. In particular, we compare the performance of six protein-LM embeddings: the LSTM-based UniRep and SeqVec, and the transformer-based ESM-1b, ESM-MSA, ProtBERT, and ProtT5; as well as three neural networks: Multi-Layer Perceptron (MLP), ResCNN-BGRU (RBG), and Light-Attention (LAT). We separately evaluated the pairwise fold recognition (PFR) and direct fold classification (DFC) tasks on well-known benchmark datasets. The results indicate that the combination of transformer-based embeddings, particularly those obtained at amino acid-level, with the RBG and LAT fine-tuning models performs remarkably well in both tasks. To further increase prediction accuracy, we propose several ensemble strategies for PFR and DFC, which provide a significant performance boost over the current state-of-the-art results. All this suggests that moving from traditional protein representations to protein-LM embeddings is a very promising approach to protein fold-related tasks.
Fine-Tuning Transformers For Genomic Tasks
Authors: Martinek Vlastimil , Cechak David , Gresova Katarina , Alexiou Panagiotis , Simecek Petr
Published: February 2022

Transformers are a type of neural network architecture that has been successfully used to achieve state-of-the-art performance in numerous natural language processing tasks. However, what about DNA, the language life written in the four-letter alphabet? In this paper, we review the current state of Transformers usage in genomics and molecular biology in general, introduce a collection of benchmark datasets for the classification of genomic sequences, and compare the performance of several model architectures on those benchmarks, including a BERT-like model for DNA sequences DNABERT as implemented in HuggingFace (armheb/DNA_bert_6 model). In particular, we explore the effect of pre-training on a large DNA corpus vs training from scratch (with randomized weights). The results presented here can be used for identification of functional elements in human and other genomes.
Latitudinal gradient in species diversity provides high niche opportunities for a range-expanding phytophagous insect
Authors: Jones Dylan G. , Kobelt Julia , Ross Jenna M. , Powell Thomas H.Q. , Prior Kirsten M.
Published: February 2022

When species undergo poleward range expansions in response to anthropogenic change, they likely encounter less diverse communities in new locations. If low diversity communities provide weak biotic interactions, such as reduced competition for resources or predation, range-expanding species may experience ‘high niche opportunities.’

Here, we uncover if oak gall wasp communities experience a latitudinal diversity gradient (LDG) and weaker interactions at the poles that might create high niche opportunities for a range-expanding community member.

We performed systematic surveys of oak gall wasps on a dominant oak, Quercus garryana, throughout most of its range, from northern California to Vancouver Island, British Columbia. On 540 trees at 18 sites, we identified 23 species in three guilds (leaf detachable, leaf integral, and stem galls). We performed regressions between oak gall wasp diversity, latitude, and other abiotic and habitat factors to reveal if cynipid communities follow an LDG. To uncover patterns in local interactions, we performed partial correlations on oak gall wasps co-occurring on trees within regions. Finally, we performed regressions between abundances of co-occurring gall wasps on trees to reveal potential interactions.

Q. garryana-gall wasp communities followed an LDG, with lower diversity at higher latitudes, particularly with a loss of detachable leaf gall species. Detachable leaf gall wasps, including the range-expanding species, co-occurred most on trees and had weak interactions in the northern region. Abundances of the range-expander and detachable and integral leaf galls co-occurring on trees were negatively related, suggesting antagonistic interactions. Overall, we found that LDGs create communities with weaker antagonistic interactions at the poles that might facilitate ecological release in a range-expanding community member.

Here, we uncover how regional and local scale patterns and processes create high niche opportunities for a range-expanding community member. This research provides insight into how biogeographical patterns in communities and species interactions influence the outcome of range expansions. Given the ubiquity of LDGs, these outcomes might be expected in other phytophagous insect communities.
Longitudinal examination of perfusion and angiogenesis markers in primary colorectal tumors shows distinct signatures for metronomic and maximum-tolerated dose strategies
Authors: Mundo Ariel I. , Muhammad Abdussaboor , Balza Kerlin , Nelson Christopher E. , Muldoon Timothy J.
Published: February 2022

1

Metronomic chemotherapy (MET) has been developed to address the shortcomings of maximum-tolerated chemotherapy (MTD) in regard to toxicity and development of resistance mechanisms in the tumor. In colorectal cancer (CRC), MET is a promising novel strategy to treat locally advanced malignancies when used as neoadjuvant chemotherapy (NAC). However, so far there are no preclinical studies to assess the impact of MET NAC in CRC to assess the benefits and challenges of this approach. Here, we used a primary model of CRC (via azoxymethane) to analyze longitudinal changes in angiogenesis in primary tumors under MET and MTD NAC using a combination of diffuse reflectance spectroscopy and mRNA expression (via qPCR). Our results show that MET and MTD NAC lead to increased mean tissue oxygen saturation (8% and 5%, respectively) and oxyhemoglobin (15% and 10%) between weeks 2 and 5 of NAC, and that such increases are caused by distinct molecular signatures in the angiogenic program. Specifically, we find that in the MET group there is a sustained increase in Hif-1a, Aldoa, and Pgk1 expression, suggesting upregulated glycolysis, whereas MTD NAC causes a significant reduction in the expression of the aforementioned genes and of Vegf, leading to vascular remodeling in MTD-treated tumors. Taken together, this study demonstrates the ability of combined optical and molecular methodologies to provide a holistic picture of tumor response to therapy in CRC in a minimally invasive manner.
Tree of Mutually Exclusive Oncogenes
Authors: Neyshabouri Mohammadreza Mohaghegh , Lagergren Jens
Published: February 2022

Identifying cancer driver genes and their interrelations is critical in understanding cancer progression mechanisms. In this paper, we introduce ToMExO, a probabilistic method to infer cancer driver genes and how they affect each other, using cross-sectional data from cohorts of tumors. We model cancer progression dynamics using a tree with sets of driver genes in the nodes. This model explains the temporal orders among driver mutations and their mutual exclusivity patterns. We introduce a dynamic programming procedure for the likelihood calculation and build an MCMC inference algorithm. Together with our engineered MCMC moves, our efficient likelihood calculations enable us to work with datasets having hundreds of genes and thousands of tumors in the datasets. We demonstrate our method’s performance on several synthetic datasets covering various scenarios for cancer progression dynamics. We then present the analyses of several biological datasets using the ToMExO method and validate the results using a set of method-independent metrics.
Forward and backward blocking in statistical learning
Authors: Nazlı İlayda , Ferrari Ambra , Huber-Huber Christoph , de Lange Floris P.
Published: February 2022

Prediction errors have a prominent role in many forms of learning. For example, in reinforcement learning, agents learn by updating the association between states and outcomes as a function of the prediction error elicited by the event. One paradigm often used to study error-driven learning is blocking. In forward blocking, participants are first presented with stimulus A, followed by outcome X (A→X). In the second phase, A and B are presented together, followed by X (AB→X). Here, A→X blocks the formation of B→X, given that X is already fully predicted by A. In backward blocking, the order of phases is reversed. Here, the association between B and X that is formed during the first learning phase of AB→X is weakened when participants learn exclusively A→X in the second phase. The present study asked the question whether forward and backward blocking occur during visual statistical learning, the largely automatic and incidental learning of the statistical structure of the environment. In a series of studies, using both forward and backward blocking, we observed robust statistical learning of temporal associations among pairs of images. While we found no compelling evidence for forward blocking, we observed reliable backward blocking in visual statistical learning.
Looming stimuli reliably drive innate, but not learned, defensive responses in rats
Authors: Heinemans Mirjam , Moita Marta A.
Published: February 2022

Survival relies on an organism’s intrinsic ability to instinctively react to stimuli such as food, water, and threats, ensuring the fundamental ability to feed, drink, and avoid danger even in the absence of prior experience. These natural, unconditioned stimuli can also facilitate associative learning, where pairing them consistently with neutral cues will elicit responses to those cue. Threat conditioning, a well-explored form of associative learning, commonly employs painful electric shocks, mimicking injury, as unconditioned stimuli. It remains elusive whether actual injury or pain is necessary for effective learning, or whether the threat of harm is sufficient. Approaching predators create looming shadows and sounds, triggering strong innate defensive responses like escape and freezing. This study investigates whether visual looming stimuli can induce learned freezing or learned escape responses to a conditioned stimulus in rats. Surprisingly, pairing a neutral tone with a looming stimulus only weakly evokes learned defensive responses, in contrast to the strong responses observed when the looming stimulus is replaced by a shock. This dissociation sheds light on the boundaries for learned defensive responses thereby impacting our comprehension of learning processes and defensive strategies.
Locomotor strategies inside the blind walks: freely moving previsual rat pups in the open field test
Authors: Midzyanovskaya I.S. , Strelkov V. V.
Published: February 2022

Blind walks of previsual rat pups in the open field test were considered as a supposedly random process. At this age, immature rats should rely only on non-visual modalities for sampling a novel space and constructing putative cognitive maps. Spontaneous locomotion of outbred Wistar rat infants (n=51) on their 13th postnatal day was tracked for 2 minutes and analyzed offline for the presence of random components and/or strategies of locomotion. Three distinct patterns were observed. A large portion of the pups (n=22) performed sub-diffusive localized walks in the center. A smaller cohort (n=9) undertook almost immediate quasi-linear raids in a random direction, thus succeeded in reaching a shelter (i.e., walls’ vicinity). The rest (n=20) demonstrated a mixed strategy: localized walks interspersed with quasi-linear raids. An algorithm for automated segmentation of the open field trajectories into the localized walks and quasi-linear fragments was developed; the fragments were analyzed separately.

Statistical analysis shows the localized walks to be diffusive (i.e., Brownian) only within 2-3 seconds, but essentially sub-diffusive for longer time scales. The autocorrelation function shows that sub-diffusion was caused by the trajectories’ re-attraction. Self-odor traces can be a physical cue ensuring the effect.

Gender or body weights were not significant predictors for any locomotor parameters. The localized walks can be considered as a primary level of idiothetically-cued path integration in previsual pups, whereas the run trials can be a form of an active escape response. The applied method of space potentials avails the automated functional segmentation of locomotor tracks and thus brings advantages of big data analysis for studying non-visual navigation in animals.
Continuous two-phase in vitro co-culture model of the enthesis
Authors: Park Hyeree , Cooke Megan E. , Lacombe Jean-Gabriel , Weber Michael H. , Martineau Paul A. , Nazhat Showan N. , Rosenzweig Derek H.
Published: February 2022

The enthesis is the interfacial tissue between ligament or tendon, and bone, which connects tissues of distinctly different mechanical properties. Although ligament and enthesis injury is commonplace, the development and healing mechanisms of these tissues are yet unclear. Current models for investigating these mechanisms are primarily in vivo animal models as in vitro models have been limited. In this study, an in vitro enthesis model was developed using a modified gel aspiration-ejection (GAE) method. Continuous two-phase aligned dense collagen (ADC) hydrogels with an overlapping interface were fabricated within 2 hours. The mechanical properties of acellular two-phase ADC confirmed the continuous nature of this model, as the mechanical properties showed no significant difference compared to single-phase ADC and maintained comparable structural and mechanical characteristics of immature ligaments and unmineralized bone. Human anterior cruciate ligament (ACL) fibroblasts and human spine vertebral osteoblasts were isolated from donor tissues and were seeded to form the enthesis model. These were cultured for 14 days, at which the viability and proliferation was observed to be 85 ± 7.5% and 230 ± 52%, respectively. Histological and immunofluorescence analyses at day 14 revealed extensive cell-driven matrix remodelling, and the seeded fibroblasts and osteoblasts maintained their phenotype within their compartments of the layered co-culture model. These results demonstrate the rapid fabrication of a two-phase co-culture system that can be utilized as an in vitro model to further understand the degenerative and regenerative mechanisms within the enthesis.
Correlative imaging of spatio-angular dynamics of molecular assemblies and cells with multimodal instant polarization microscope
Authors: Ivanov Ivan E. , Yeh Li-Hao , Perez-Bermejo Juan A. , Byrum Janie R. , Kim James Y.S. , Leonetti Manuel D. , Mehta Shalin B.
Published: February 2022

Biological function depends on the spatio-angular architecture of macromolecules - for example, functions of lipid membrane and cytoskeletal polymers arise from both the spatial and the angular organization of the constituent molecules. Correlative imaging of cellular and molecular architecture is valuable across cell biology and pathology. However, current live imaging methods primarily focus on spatial component of the architecture. Imaging the dynamic angular architecture of cells and organelles requires fast polarization-, depth-, and wavelength-diverse measurement of intrinsic optical properties and fluorophore concentration, but remains challenging with current designs. We report a multimodal instant polarization microscope (miPolScope) that combines a broadband polarization-resolved detector, automation, and reconstruction algorithms to enable label-free imaging of phase, retardance, and orientation, multiplexed with fluorescence imaging of concentration, anisotropy, and orientation of molecules at diffraction-limited resolution and high speed. miPolScope enabled multimodal imaging of myofibril architecture and contractile activity of beating cardiomyocytes, cell and organelle architecture of live HEK293T and U2OS cells, and density and anisotropy of white and grey matter of mouse brain tissue across the visible spectrum. We anticipate these developments in joint quantitative imaging of density and anisotropy to enable new studies in tissue pathology, mechanobiology, and imaging-based screens.
Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome
Authors: Madrigal Pedro , Singh Nitin K. , Wood Jason M. , Gaudioso Elena , Hernández-del-Olmo Félix , Mason Christopher E. , Venkateswaran Kasthuri , Beheshti Afshin
Published: February 2022

Background

Antimicrobial Resistance (AMR) has a detrimental impact on human health on Earth and it is equally concerning in other environments such as space due to microgravity, radiation and confinement, especially for long-distance space travel. The International Space Station (ISS) is ideal for investigating microbial diversity and virulence. The shotgun metagenomics data of the ISS generated during the Microbial Tracking – 1 (MT-1) project and resulting metagenome-assembled genomes (MAGs) across three flights in eight different locations during 12 months were used in this study. The objective of this study was to identify the AMR genes associated with whole genomes of 227 cultivable strains, 21 shotgun metagenome sequences, and 24 MAGs retrieved from the ISS environmental samples that were treated with propidium monoazide (PMA; viable microbes).

Results

We have analyzed the data using a deep learning model, allowing us to go beyond traditional cut-offs based only on high DNA sequence similarity and extending the catalog of AMR genes. Our results in PMA treated samples revealed AMR dominance in the last flight for Kalamiella piersonii, a bacteria related to urinary tract infection in humans. The analysis of 227 pure strains isolated from the MT-1 project revealed hundreds of antibiotic resistance genes from many isolates, including two top-ranking species that corresponded to strains of Enterobacter bugandensis and Bacillus cereus. Computational predictions were experimentally validated by antibiotic resistance profiles in these two species, showing a high degree of concordance. Specifically, disc assay data confirmed the high resistance of these two pathogens to various beta-lactam antibiotics.

Conclusion

Overall, our computational predictions and validation analyses demonstrate the advantages of machine learning to uncover concealed AMR determinants in metagenomics datasets, expanding the understanding of the ISS environmental microbiomes and their pathogenic potential in humans.
A Sulfonated Thermoresponsive Injectable Gel for Sequential Release of Therapeutic Proteins to Protect Cardiac Function After a Myocardial Infarction
Authors: Rocker Adam J. , Cavasin Maria , Johnson Noah , Shandas Robin , Park Daewon
Published: February 2022

Myocardial infarction causes cardiomyocyte death and persistent inflammatory responses, which generates adverse pathological remodeling. Delivering therapeutic proteins from injectable materials in a controlled release manner may present an effective biomedical approach for treating this disease. A thermoresponsive injectable gel composed of chitosan, conjugated with poly(N-isopropylacrylamide) and sulfonate groups, was developed for spatiotemporal protein delivery to protect cardiac function after a myocardial infarction. The thermoresponsive gel delivered VEGF, IL-10 and PDGF in a sequential and sustained manner in vitro. An acute myocardial infarction mouse model was used to evaluate polymer biocompatibility and to determine therapeutic effects from the delivery system on cardiac function. Immunohistochemistry showed biocompatibility of the hydrogel, while the controlled delivery of the proteins reduced macrophage infiltration and increased vascularization. Echocardiography showed an improvement in ejection fraction and fractional shortening after injecting the thermal gel and proteins. A factorial design of experiments study was implemented to optimize the delivery system for the best combination and doses of proteins for further increasing stable vascularization and reducing inflammation using a subcutaneous injection mouse model. The results showed that VEGF, IL-10, and FGF-2 demonstrated significant contributions towards promoting long-term vascularization, while PDGF’s effect was minimal.
The direction and timing of theta and alpha traveling waves modulate human memory processing
Authors: Mohan Uma R. , Zhang Honghui , Jacobs Joshua
Published: February 2022

To support a range of behaviors, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a traveling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions1,2. Although traveling waves are present across the brain in various species3–5, their potential functional relevance remained unknown. Here, using rare direct human brain recordings, we demonstrate two novel functional roles for traveling waves of theta- and alpha-band (2–13 Hz) oscillations in the cortex. First, traveling waves propagate in different directions during separate cognitive processes. In episodic memory, traveling waves tended to propagate in posterior-to-anterior and anterior-to-posterior directions, respectively, during encoding and retrieval. Second, traveling waves are informative about the timing of behavior, with the phase of ongoing traveling waves indicating when subjects would retrieve memories. Because traveling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain with different directions and timing for separate behaviors. More broadly, our results suggest a fundamental role for traveling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behavior.
Building an atlas of transposable elements reveals the extensive roles of young SINE in gene regulation, genetic diversity, and complex traits in pigs
Authors: Zhao Pengju , Gu Lihong , Gao Yahui , Pan Zhangyuan , Liu Lei , Li Xingzheng , Zhou Huaijun , Yu Dongyou , Han Xinyan , Qian Lichun , Liu George E. , Fang Lingzhao , Wang Zhengguang
Published: February 2022

Transposable elements (TEs) are an extensive source of genetic polymorphisms and play an indispensable role in chromatin architecture, transcriptional regulatory networks, and genomic evolution. The pig is an important source of animal protein and serves as a biomedical model for humans, yet the functional role of TEs in pigs and their contributions to complex traits are largely unknown. Here, we built a comprehensive catalog of TEs (n = 3,087,929) in pigs by a newly developed pipeline. Through integrating multi-omics data from 21 tissues, we found that SINEs with different ages were significantly associated with genomic regions with distinct functions across tissues. The majority of young SINEs were predominantly silenced by histone modifications, DNA methylation, and decreased accessibility. However, the expression of transcripts that were derived from the remaining active young SINEs exhibited strong tissue specificity through cross-examining 3,570 RNA-seq from 79 tissues and cell types. Furthermore, we detected 211,067 polymorphic SINEs (polySINEs) in 374 individuals genome-wide and found that they clearly recapitulated known patterns of population admixture in pigs. Out of them, 340 population-specific polySINEs were associated with local adaptation. Mapping these polySINEs to genome-wide associations of 97 complex traits in pigs, we found 54 candidate genes (e.g., ANK2 and VRTN) that might be mediated by TEs. Our findings highlight the important roles of young SINEs in functional genomics and provide a supplement for genotype-to-phenotype associations and modern breeding in pigs.
Genome-wide profiling of histone H3K4me3 and H3K27me3 modifications in individual blastocysts by CUT&Tag without a solid support (NON-TiE-UP CUT&Tag)
Authors: Susami Kazuki , Ikeda Shuntaro , Hoshino Yoichiro , Honda Shinnosuke , Minami Naojiro
Published: February 2022

Individual analysis of the epigenome of preimplantation embryos is useful for characterizing each embryo and for investigating the effects of environmental factors on their epigenome. However, it is difficult to analyze genome-wide epigenetic modifications, especially histone modifications, in a large number of single embryos due to the small number of cells and the complexity of the analysis methods. To solve this problem, we further modified the CUT&Tag method, which can analyze histone modifications in a small number of cells, such that the embryo is handled as a cell mass in the reaction solutions in the absence of the solid-phase magnetic beads that are used for antibody and enzyme reactions in the original method (NON-TiE-UP CUT&Tag; NTU-CAT). By using bovine blastocysts as a model, we showed that genome-wide profiles of representative histone modifications, H3K4me3 and H3K27me3, could be obtained by NTU-CAT that are in overall agreement with the conventional chromatin immunoprecipitation-sequencing (ChIP-seq) method, even from single embryos. However, this new approach has limitations that require attention, including false positive peaks and lower resolution for broad modifications. Despite these limitations, we conclude that NTU-CAT is a promising replacement for ChIP-seq with the great advantage of being able to analyze individual embryos.
SAI: Fast and automated quantification of stomatal parameters on microscope images
Authors: Sai Na , Bockman James Paul , Chen Hao , Watson-Haigh Nathan , Xu Bo , Feng Xueying , Piechatzek Adriane , Shen Chunhua , Gilliham Matthew
Published: February 2022

Using microscopy to investigate stomatal behaviour is a common technique in plant physiology research. Manual inspection and measurement of stomatal features is a low throughput process in terms of time and human effort, which relies on expert knowledge to identify and measure stomata accurately. This process represents a significant bottleneck in research pipelines, adding significant researcher time to any project that requires it. To alleviate this, we introduce StomaAI (SAI): a reliable and user-friendly tool that measures stomata of the model plant Arabidopsis (dicot) and the crop plant barley (monocot grass) via the application of deep computer vision. We evaluated the reliability of predicted measurements: SAI is capable of producing measurements consistent with human experts and successfully reproduced conclusions of published datasets. Hence, SAI boosts the number of images that biologists can evaluate in a fraction of the time so is capable of obtaining more accurate and representative results.
Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: A bioinformatics analytic workflow
Authors: Silva Kushan De , Demmer Ryan T. , Jönsson Daniel , Mousa Aya , Forbes Andrew , Enticott Joanne
Published: February 2022

Introduction

Type 2 diabetes (T2D) has a complex etiology which is not fully elucidated. Identification of gene perturbations and hub genes of T2D may assist in personalizing care.

Objectives

We aimed to identify highly perturbed genes and hub genes associated with T2D in different tissues of adult humans via an extensive workflow.

Methods

Workflow comprised five sequential steps: systematic review of NCBI GEO database; identification and classification of differentially expressed genes (DEG); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; downstream analyses. Three meta-analytic strategies: random effects model (REM); vote counting approach (VC);p-value combining approach (CA), were applied. Nodes having above average betweenness, closeness, and degree in the network were defined as hub genes. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19 related genes, and Genotype-Tissue Expression profiles.

Results

Analysis of 27 eligible microarrays identified 6284 DEG (4592 down-regulated and 1692 up-regulated) within four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Meta-analysis of DEG identified 49, 27, and 8 highly perturbed genes via REM, VC, and CA, respectively, producing a compiled set of 79 highly perturbed (41 down-regulated and 38 up-regulated) genes. The 28 hub genes comprised 13 up-regulated, 9 down-regulated, and 6 predicted genes. Downstream analyses identified enrichments of: shared genes with other diabetes phenotypes; insulin synthesis and action related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways, COVID-19 related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D.

Conclusions

We identified highly perturbed genes and hub genes of T2D and revealed their associations with other diabetes phenotypes and COVID-19 as well as pathophysiological manifestations such as those related to insulin, immunity, and apoptosis. Broader utility of the proposed pipeline is envisaged.
Food Insecurity Among Older Adults with a History of Incarceration
Authors: Jordan Tamara , Sneed Rodlescia
Published: February 2022

Objectives

To examine the association between history of incarceration (HOI) and food insecurity (FI) among older adults.

Methods

This is a secondary analysis utilizing data from 12,702 respondents aged 51+ who participated in the 2012 and 2014 waves of The Health and Retirement Study. Multiple logistic regression was used to estimate the association between HOI and FI, adjusting for demographic variables using odds ratios (OR) and 95% confidence intervals (CI).

Results

In our sample, 12.8% of participants reported FI. Having a HOI increased odds of FI (OR 1.83; 95% CI 1.52-2.21), especially among Blacks (OR 1.78; 95% CI 1.29-2.46) and Whites (OR 2.27; 95% CI 1.74-2.97), but not Hispanics (OR 1.11; 95% CI 0.69-1.77) or other racial/ethnic groups (OR 1.79; 95% CI 0.71-4.52).

Discussion

FI is an important issue among older adults with a HOI. Stronger linkages between formerly incarcerated older adults and existing food assistance programs are needed.
Physical behaviours and their association with type 2 diabetes risk in urban South African middle-aged adults: An isotemporal substitution approach
Authors: Kufe Clement N. , Goedecke Julia H. , Masemola Maphoko , Chikowore Tinashe , Soboyisi Melikhaya , Smith Antonia , Westgate Kate , Brage Soren , Micklesfield Lisa K.
Published: February 2022

Introduction

To examine the associations between physical behaviours and type 2 diabetes mellitus (T2DM) risk in middle-aged South African men and women.

Research design and methods

This cross-sectional study included middle-aged men (n=403; age: median [IQR], 53.0 [47.8–58.8] years) and women (n=324; 53.4 [49.1–58.1] years) from Soweto, South Africa. Total movement volume (average movement in milli-g) and time (minutes/day) spent in different physical behaviours, including awake sitting/lying, standing, light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA), were determined by combining the signals from two triaxial accelerometers worn simultaneously on the hip and thigh. All participants completed an oral glucose tolerance test, from which indicators of diabetes risk were derived. Associations between physical behaviours and T2DM risk were adjusted for sociodemographic factors and body composition.

Results

Total movement volume was inversely associated with measures of fasting and 2-h glucose and directly associated with insulin sensitivity, basal insulin clearance, beta-cell function, but these associations were not independent of fat mass, except for basal insulin clearance in women. In men, replacing 30 minutes of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 1.2–1.4 mmol/L lower fasting glucose and 12.3–13.4 mgl2/mUmin higher insulin sensitivity. In women, substituting sitting/lying with the same amount of standing time or LPA was associated with 0.5–0.8 mmol/L lower fasting glucose. Substituting 30 minutes sitting/lying with the same amount of standing time was also associated with 3.2 mgl2/mUmin higher insulin sensitivity, and substituting 30 minutes of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 0.25-0.29 ng/mIU higher basal insulin clearance in women.

Conclusion

MVPA is important in reducing T2DM risk in men and women but LPA appears to be important in women only. Recommendations for PA may differ by sex.
Where is Omicron? Comparison of SARS-CoV-2 RT-PCR and Antigen Test Sensitivity at Commonly Sampled Anatomic Sites Over the Course of Disease
Authors: Lin Jessica , Frediani Jennifer K , Damhorst Gregory L , Sullivan Julie A , Westbrook Adrianna , McLendon Kaleb , Baugh Tyler J , O’Sick William H , Roback John D , Piantadosi Anne L , Waggoner Jesse J , Bassit Leda , Rao Anuradha , Greenleaf Morgan , O’Neal Jared W , Swanson Seegar , Pollock Nira R , Martin Greg S , Lam Wilbur A , Levy Joshua M
Published: February 2022

Background

Upper respiratory samples for SARS-CoV-2 detection include the gold standard nasopharyngeal (NP) swab, and mid-turbinate (MT) nasal swabs, oropharyngeal (OP) swabs, and saliva. Following the emergence of the omicron (B.1.1.529) variant, limited preliminary data suggest that OP swabs or saliva samples may be more sensitive than nasal swabs, highlighting the need to understand differences in viral load across different sites.

Methods

MT, OP, and saliva samples were collected from symptomatic individuals presenting for evaluation in Atlanta, GA, in January 2022. Longitudinal samples were collected from a family cohort following COVID-19 exposure to describe detection of viral targets over the course of infection.

Results

SARS-CoV-2 RNA and nucleocapsid antigen measurements demonstrated a nares-predominant phenotype in a familial cohort. A consistent dominant location for SARS-CoV-2 was not found among 54 individuals. Positive percent agreement for virus detection in MT, OP and saliva specimens were 66.7 [54.1–79.2], 82.2 [71.1–93.4], and 72.5 [60.3–84.8] by RT-PCR, respectively, and 46.2 [32.6–59.7], 51.2 [36.2–66.1], and 72.0 [59.6–84.4] by ultrasensitive antigen assay. The composite of positive MT or OP assay was not significantly different than either alone for both RT-PCR and antigen assay (PPA 86.7 [76.7–96.6] and 59.5 [44.7–74.4], respectively).

Conclusions

Our data suggest that SARS-CoV-2 nucleocapsid and RNA exhibited similar kinetics and diagnostic yield in three upper respiratory sample types across the duration of symptomatic disease. Collection of OP or combined nasal and OP samples does not appear to increase sensitivity versus validated nasal sampling for rapid detection of viral antigen.