bluuebunny/crossref_metadata_2025 huggingface dataset:
Secure federated Boolean count queries using fully-homomorphic cryptography
Authors: Leighton Alexander T. , Yu Yun William
Published: November 2021

Biomedical data is often distributed between a network of custodians, causing challenges for researchers wishing to securely compute aggregate statistics on those data without centralizing everything—the prototypical ‘count query’ asks how many patients match some multifaceted set of conditions across a network of hospitals. Difficulty arises from two sources: (1) the need to deduplicate patients who may be present in the records of multiple hospitals and (2) the need to unify partial records for the same patient which may be split across hospitals. Although cryptographic tools for secure computation promise to enable collaborative studies with formal privacy guarantees, existing approaches either are computationally impractical or support only simplified analysis pipelines. To the best of our knowledge, no existing practical secure method addresses both of these difficulties simultaneously.

Here, we introduce secure federated Boolean count queries using a novel 2-stage probabilistic sketching and sampling protocol that can be efficiently implemented in off-the-shelf federated homomorphic encryption libraries (Palisade and Lattigo), provably ensuring data security. To this end, we needed several key technological innovations, including re-encoding the LogLog union-cardinality sketch and designing an appropriate sampling for intersection cardinalities. Our benchmarking shows that we can answer federated Boolean count queries in less than 2 CPU-minutes with absolute errors in the range of 6% of the total number of touched records, while revealing only the final answer and the total number of touched records. With modern core-parallelism, we can thus answer queries on the order of seconds. Our study demonstrates that by computing on compressed and encrypted data, it is possible to securely answer federated Boolean count queries in real-time.
Real-time Image Denoising of Mixed Poisson-Gaussian Noise in Fluorescence Microscopy Images using ImageJ
Authors: Mannam Varun , Zhang Yide , Zhu Yinhao , Nichols Evan , Wang Qingfei , Sundaresan Vignesh , Zhang Siyuan , Smith Cody , Bohn Paul W , Howard Scott
Published: November 2021

Abstract

Fluorescence microscopy imaging speed is fundamentally limited by the measurement signal-to-noise ratio (SNR). To improve image SNR for a given image acquisition rate, computational denoising techniques can be used to suppress noise. However, common techniques to estimate a denoised image from a single frame are either computationally expensive or rely on simple noise statistical models. These models assume Poisson or Gaussian noise statistics, which are not appropriate for many fluorescence microscopy applications that contain quantum shot noise and electronic Johnson–Nyquist noise, therefore a mixture of Poisson and Gaussian noise. In this paper, we show convolutional neural networks (CNNs) trained on mixed Poisson and Gaussian noise images to overcome the limitations of existing image denoising methods. The trained CNN is presented as an open-source ImageJ plugin that performs real-time image denoising (within tens of milliseconds) with superior performance (SNR improvement) compared to the conventional fluorescence microscopy denoising methods. The method is validated on external datasets with out-of-distribution noise, contrast, structure, and imaging modalities from the training data and consistently achieves high performance (> 8 dB) denoising in less time than other fluorescence microscopy denoising methods.
Phylogenetic diversity of two commonTrypanosoma cruzilineages in the Southwestern United States
Authors: Flores-López Carlos A. , Mitchell Elizabeth A. , Reisenman Carolina E. , Sarkar Sahotra , Williamson Philip C. , Machado Carlos A.
Published: November 2021

Trypanosoma cruziis the causative agent of Chagas disease, a devastating parasitic disease endemic to Central and South America, Mexico, and the USA. We characterized the genetic diversity ofT. cruzicirculating in five triatomine species (Triatoma gerstaeckeri, T. lecticularia, T. indictiva, T. sanguisugaandT. recurva) collected in Texas and Southern Arizona using nucleotide sequences from four single-copy loci (COII-ND1, MSH2, DHFR-TS, TcCLB.506529.310). AllT. cruzivariants fall in two main genetic lineages: 75% of the samples corresponded toT. cruziDiscrete Typing Unit (DTU) I (TcI), and 25% to a North American specific lineage previously labelled TcIV-USA. Phylogenetic and sequence divergence analyses of our new data plus all previously published sequence data from those 4 genes collected in the USA, show that TcIV-USA is significantly different from any other previously definedT. cruziDTUs. The significant level of genetic divergence between TcIV-USA and otherT. cruzilineages should lead to an increased focus on understanding the epidemiological importance of this lineage, as well as its geographical range and pathogenicity in humans and domestic animals. Our findings further corroborate the fact that there is a high genetic diversity of the parasite in North America and emphasize the need for appropriate surveillance and vector control programs for Chagas disease in southern USA and Mexico.
Molecular, anatomical, and functional organization of lung interoceptors
Authors: Liu Yin , Diaz de Arce Alex J. , Krasnow Mark A.
Published: November 2021

Interoceptors, sensory neurons that monitor internal organs and states, are essential for physiological homeostasis and generating internal perceptions. Here we describe a comprehensive transcriptomic atlas of interoceptors of the mouse lung, defining 10 molecular subtypes that differ in developmental origin, myelination, receptive fields, terminal morphologies, and cell contacts. Each subtype expresses a unique but overlapping combination of sensory receptors that detect diverse physiological and pathological stimuli, and each can signal to distinct sets of lung cells including immune cells, forming a local neuroimmune interaction network. Functional interrogation of two mechanosensory subtypes reveals exquisitely-specific homeostatic roles in breathing, one regulating inspiratory time and the other inspiratory flow. The results suggest that lung interoceptors encode diverse and dynamic sensory information rivaling that of canonical exteroceptors, and this information is used to drive myriad local cellular interactions and enable precision control of breathing, while providing only vague perceptions of organ states.
A series of terribly unfortunate events: How environment and infection synergized to cause the Kihansi spray toad extinction
Authors: Sewell Thomas R , van Dorp Lucy , Ghosh Pria N , Wierzbicki Claudia , Caroe Cristian , Lyakurwa John V , Tonelli Elena , Bowkett Andrew , Marsden Stuart , Cunningham Andrew A , Garner Trenton W J , Gilbert Thomas P , Weldon Ché , Fisher Matthew C
Published: November 2021

Outbreaks of emerging infectious diseases are trained by local biotic and abiotic factors, with host declines occurring when conditions favour the pathogen. Extinction of the Tanzanian Kihansi spray toad (Nectophrynoides asperginis) in 2004 was contemporaneous with the construction of a dam, implicating habitat modification in the loss of this species. However, high burdens of a globally emerging infection, Batrachochytrium dendrobatidis (Bd) were synchronously observed implicating infectious disease in this toads extinction. Here, by shotgun sequencing skin DNA from archived toad mortalities and assembling chytrid mitogenomes, we prove this outbreak was caused by the BdCAPE lineage and not the panzootic lineage BdGPL that is widely associated with global amphibian extinctions. Molecular dating showed an invasion of BdCAPE across Southern Africa overlapping with the timing of the extinction event. However, post-outbreak surveillance of conspecific species inhabiting this mountainous region showed widespread infection by BdCAPE yet no signs of amphibian ill-health or species decline. Our findings show that despite efforts to mitigate the environmental impact caused by dams construction, invasion of the pathogen ultimately led to the loss of the Kihansi spray toad; a synergism between emerging infectious disease and environmental change that likely heralds wider negative impacts on biodiversity in the Anthropocene.
Fish diversity drives regional productivity but not stability in southeastern United States coastal marine fishes
Authors: Caughron Juliane G , Plante Craig J , Reichert Marcel JM , Smart Tracey I , McGlinn Daniel J
Published: November 2021

Aim

Ecosystem-based management requires accurate predictions on how biotic and environmental factors interact to deliver ecosystem services. Biodiversity-ecosystem function (BEF) theory predicts that as diversity increases, the ecosystem will become more productive (positive diversity-productivity relationship – DPR) and more stable (positive diversity-stability relationship – DSR). Support for BEF has been primarily derived from fine-grained, non-harvested systems. The purpose of this study is to examine the robustness of BEF predictions for the DPR and DSR by examining how well fish diversity predicts productivity and stability of fish, shrimp, and flounder at a regional scale.

Location

Southeast coast of United States.

Time Period

1989 - 2015

Major Taxa Studied

Marine Fishes

Methods

We used 27 years of the SEAMAP-SA Coastal Trawl Survey database to derive estimates of fish, shrimp, and flounder biomass (i.e., productivity), temporal stability of biomass (i.e., invariability of productivity), and fish community species richness. We pooled trawls into 22 km x 22 km raster cells and 3-year time bins. We controlled for variation in sampling effort using sample-based rarefaction. We compared the ability of fish species richness, water salinity, and water temperature to predict biomass and stability of all fish, shrimp, and flounder using multiple linear regression.

Results

Both the DPR and DSR exhibited positive log-log linear trends as expected, but the DPR had a much stronger signal. Species richness outperformed the environmental covariates in both the fish and shrimp DPR models. Surface temperature was the most important variable in both flounder models. Overall, our models better explained productivity than stability.

Main Conclusions

The DPR and DSR are relevant at regional scales in a commercially important fishery although support for the DSR is less justified than DPR. Further investigation into the underlying mechanisms driving the DPR and DSR are necessary to design management around BEF theory.
FEASIBILITY OF VASCULAR REMODELING PARAMETER ESTIMATION FOR ASSESSING HYPERTENSIVE PREGNANCY DISORDERS
Authors: Kissas Georgios , Hwuang Eileen , Thompson Elizabeth W. , Schwartz Nadav , Detre John A. , Witschey Walter R. , Perdikaris Paris
Published: November 2021

Hypertensive pregnancy disorders, such as preeclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Non-invasive imaging, such as ultrasound and magnetic resonance imaging (MRI), is an important tool in predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices, the interpretation of such metrics for disease assessment rely on ad-hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer remodeling parameters, such as vascular resistance, compliance and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with carotid and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.
STAT1Gain-of-Function Variants Drive Altered T Cell Prevalence, Metabolism, and Heightened IL-6 Sensitivity
Authors: Kaviany Saara , Bartkowiak Todd , Dulek Daniel E. , Khan Yasmin W. , Hayes Madeline J. , Schaefer Samuel , Dahunsi Debolanle O. , Connelly James A. , Irish Jonathan M. , Rathmell Jeffrey C.
Published: November 2021

Patients with Signal Transducer and Activator of Transcription 1 (STAT1) gain-of-function (GOF) pathogenic variants exhibit susceptibility to infections, autoimmunity, and cancer due to enhanced or prolonged STAT1 phosphorylation following cytokine stimulation. While interferons (IFNs) are canonical STAT1 activators, other cytokines that may also contribute to pathology inSTAT1GOF patients have been less well defined. Here we analyzed the immune profiles and cytokine responses of two patients with heterozygous GOF mutations in theSTAT1coiled-coil domain. A systems immunology approach revealed major changes in the T cell compartment and minor changes in the B cells, NK cells, and myeloid cells. Both patients withSTAT1GOF differed from healthy individuals in the abundance and phenotype of effector memory, Th17, and Treg populations.STAT1GOF T cells displayed a pattern of increased activation and had elevated markers of glycolysis and lipid oxidation. Hypersensitivity of T cells to IL-6 was observed with intense, sustained STAT1 phosphorylation in memory T cell populations that exceeded that induced by IFNs. Together, these results show a role for STAT1 in T cell metabolism and suggest that IL-6 may play a critical role to promote T cell memory formation and activation in patients withSTAT1GOF.
Deeplearning based MHC epitope prediction for cancer neoantigen discovery
Authors: Xie Carolyn , Shi Yu , Zhang Chi
Published: November 2021

Neoantigens are important for cancer immunotherapies or cancer vaccine development, but identification of neoantigens is challenging. The high binding affinity between the mutated peptide and MHC (major histocompatibility complex) molecules of the patients is a necessary factor for a somatic mutation on the tumor genome to form a neoantigen. MHC epitope prediction tools can be used for the identification of neoantigens. This research investigates MHC epitope prediction by utilizing Tri-peptide similarity as features for the XGBoost classifier. This model was tested on experimentally validated cancer neoantigen peptides.
Community composition of coral-associated Symbiodiniaceae is driven by fine-scale environmental gradients
Authors: de Souza Mariana Rocha , Caruso Carlo , Ruiz-Jones Lupita , Dury Crawford , Gates Ruth , Toonen Robert J.
Published: November 2021

The survival of reef-building corals is dependent upon a symbiosis between the coral and the community of Symbiodiniaceae. Montipora capitata, one of the main reef building coral species in Hawaiʻi, is known to host a diversity of symbionts, but it remains unclear how they change spatially and whether environmental factors drive those changes. Here, we surveyed the Symbiodiniaceae community in 600 M. capitata colonies from 30 sites across Kāneʻohe Bay and tested for host specificity and environmental gradients driving spatial patterns of algal symbiont distribution. We found that the Symbiodiniaceae community differed markedly across sites, with M. capitata in the most open-ocean (northern) site hosting few or none of the genus Durusdinium, whereas individuals at other sites had a mix of Durusdinium and Cladocopium. Our study shows that the algal symbiont community composition responds to fine-scale differences in environmental gradients; depth and temperature variability were the most significant predictor of Symbiodiniaceae community, although environmental factors measured in the study explained only about 20% of observed variation. Identifying and mapping Symbiodiniaceae community distribution at multiple scales is an important step in advancing our understanding of algal symbiont diversity, distribution and evolution, and the potential responses of corals to future environmental change.
T1SEstacker: A tri-layer stacking model effectively predicts bacterial type 1 secreted proteins based on C-terminal non-RTX-motif sequence features
Authors: Chen Zewei , Zhao Ziyi , Hui Xinjie , Zhang Junya , Hu Yixue , Chen Runhong , Cai Xuxia , Hu Yueming , Wang Yejun
Published: November 2021

The proteins secreted through type 1 secretion systems often play important roles in pathogenicity of various gram-negative bacteria. However, the type 1 secretion mechanism remains unknown. In this research, we observed the sequence features of RTX proteins, a major class of type 1 secreted substrates. We found striking non-RTX-motif amino acid composition patterns at the C-termini, most typically exemplified by the enriched ‘[FLI][VAI]’ at the most C-terminal two positions. Machine-learning models, including deep-learning models, were trained using these sequence-based non-RTX-motif features, and further combined into a tri-layer stacking model, T1SEstacker, which predicted the RTX proteins accurately, with a 5-fold cross-validated sensitivity of ~0.89 at the specificity of ~0.94. Besides substrates with RTX motifs, T1SEstacker can also well distinguish non-RTX-motif type 1 secreted proteins, further suggesting their potential existence of common secretion signals. In summary, we made comprehensive sequence analysis on the type 1 secreted RTX proteins, identified common sequence-based features at the C-termini, and developed a stacking model that can predict type 1 secreted proteins accurately.
Urbanization and altitude impact on gut microbiome of an Andean frog (Pristimantis unistrigatus)
Authors: Carphio Elena Catelan , Cisneros-Heredia Diego F. , Caicedo Andrés , Cárdenas Paúl A.
Published: November 2021

The analysis of the intestinal microbiome in amphibians provides insights of the anthropogenic environmental impact. Pristimantis unistrigatus is an Andean amphibian species whose distribution has been recorded in Ecuador and Colombia, ranging from endemic elfin forests to urban gardens. In this study, we focus on the analysis of the P. unistrigatus microbiome 16S rRNA gene sequencing. A total of 32 specimens of P. unistrigatus were collected and analyzed from 4 locations in the Valley of Quito, Ecuador, characterized by several urban environments and altitudes. The results show that the relative abundance of bacteria is significantly different amongst groups. Clostridiales are proportionally more abundant in rural and lower altitude locations, while Erysipelotrichaceae, Desulfovibrionaceae, Enterobacteriaceae, Bacteroidaceae and Lachnospiraceae are found at higher elevations. These results highlight the importance of the evolution of the microbiome as a tool of adaptation and survival of amphibians in the present-day changing ecosystems undergoing anthropogenic stresses.

Importance

Amphibians constitutes one of the groups most vulnerable to environmental alterations. Due to their sophisticated reproductive and breeding requirements and their permeable skins to breathe, amphibians are compulsively studied as ecological indicators. The destruction of pristine habitats occurred all over the planet in recent decades has caused a catastrophic decline in amphibian populations for many species everywhere. Ecuador, being one of the most biodiverse country on Earth, hosts a huge variety of amphibians, thus offering a unique possibility of studying the biology of the amphibian species living in its ecosystems, and how they adapt to changing habitats. A direct way to diagnose the status of an amphibian population is to study the gut microbiome of the individual specimens. The gut microbiome is closely related to the host’s health and so to its ability to adapt and survive. An important output of this study is to offer indications and tools useful to conservation programs before irreversible damages are caused to the habitats and the amphibians’ populations still thriving in them.
Genetic variation within the human papillomavirus type 16 genome is associated with oropharyngeal cancer prognosis
Authors: Lang Kuhs Krystle A. , Faden Daniel , Chen Li , Smith Derek K. , Pinheiro Maisa , Wood C. Burton , Davis Seth , Yeager Meredith , Boland Joseph F. , Cullen Michael , Steinberg Mia , Bass Sara , Wang Xiaowei , Liu Ping , Mehrad Mitra , Tucker Thomas , Lewis James S. , Ferris Robert L. , Mirabello Lisa
Published: November 2021

Purpose

A significant barrier to adoption of de-escalated treatment protocols for human papillomavirus-driven oropharyngeal cancer (HPV-OPC) is that few predictors of poor prognosis exist. We conducted the first large whole-genome sequencing (WGS) study to characterize the genetic variation of the HPV16 genome and to evaluate its association with HPV-OPC patient survival.

Patients and Methods

460 OPCs from 2 large US medical centers (1980-2017) underwent HPV16 WGS. Site-specific variable positions (SNPs) across the HPV16 genome were identified. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival by HPV16 SNPs. Harrell C-index and time-dependent positive predictive value (PPV) curves and areas under the PPV curves were used to evaluate the predictive accuracy of HPV16 SNPs for overall survival.

Results

384 OPCs (83.48%) passed quality control filters with sufficient depth and coverage of HPV16 genome sequencing to be analyzed. 284 HPV16 SNPs with a minor allele frequency >1% were identified. Eight HPV16 SNPs were significantly associated with worse survival after false discovery rate (FDR) correction (individual prevalence:1.0%-5.5%; combined prevalence: 15.10%); E1 gene position 1053 (HR for overall survival [HRos]:3.75,95%CI:1.77-7.95;Pfdr=0.0099); L2 gene positions 4410 (HRos:5.32,95%CI:1.91-14.81;Pfdr=0.0120), 4539 (HRos:6.54,95%CI:2.03-21.08;Pfdr=0.0117); 5050 (HRos:6.53,95%CI:2.34-18.24;Pfdr=0.0030) and 5254 (HRos:7.76,95%CI:2.41-24.98;Pfdr=0.0030); and L1 gene positions 5962 (HRos:4.40,95%CI:1.88-10.31;Pfdr=0.0110) and 6025 (HRos:5.71,95%CI:2.43-13.41;Pfdr=0.0008) and position 7173 within the upstream regulatory region (HRos:9.90,95%CI:3.05-32.12;Pfdr=0.0007). Median survival time for patients with ≥1 high-risk HPV16 SNPs was 3.96 years compared to 18.67 years for patients without a high-risk SNP; log-rank test P<0.001. HPV16 SNPs significantly improved the predictive accuracy for overall survival above traditional factors (age, smoking, stage, treatment): increase in C-index was 0.069 (95% CI: 0.019-0.119, P <0.001); increase in area under the PPV curve for predicting 5-year survival was 0.068 (95%CI: 0.015-0.111, P =0.008).

Conclusions

HPV16 genetic variation is associated with HPV-OPC prognosis and can improve prognostic accuracy.
Higher-order interaction of brain microstructural and functional connectome
Authors: Wang Hao , Wu Hui-Jun , Liu Yang-Yu , Lü Linyuan
Published: November 2021

Despite a relatively fixed anatomical structure, the human brain can support rich cognitive functions, triggering particular interest in investigating structure-function relationships. Myelin is a vital brain microstructure marker, yet the individual microstructure-function relationship is poorly understood. Here, we explore the brain microstructure-function relationships using a higher-order framework. Global (network-level) higher-order microstructure-function relationships negatively correlate with male participants’ personality scores and decline with aging. Nodal (node-level) higher-order microstructure-function relationships are not aligned uniformly throughout the brain, being stronger in association cortices and lower in sensory cortices, showing gender differences. Notably, higher-order microstructure-function relationships are maintained from the whole-brain to local circuits, which uncovers a compelling and straightforward principle of brain structure-function interactions. Additionally, targeted artificial attacks can disrupt these higher-order relationships, and the main results are robust against several factors. Together, our results increase the collective knowledge of higher-order structure-function interactions that may underlie cognition, individual differences, and aging.
Identifying common transcriptome signatures of cancer by interpreting deep learning models
Authors: Jha Anupama , Quesnel-Vallières Mathieu , Thomas-Tikhonenko Andrei , Lynch Kristen W. , Barash Yoseph
Published: November 2021

Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified, signifying that cancer cases display common hallmark molecular features. It is not clear however whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. Here, in order to agnostically identify transcriptomic features that are commonly shared between cancer types, we used RNA-Seq datasets encompassing thousands of samples from 19 healthy tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression or splice junction use, to distinguish between healthy and tumor samples. All three models achieve high precision, recall and accuracy on test sets derived from 13 datasets used during training and on an independent test dataset, indicating that our models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints, suggesting that they have important cellular functions. Importantly, we found that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. Finally, our results also highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features across a large array of solid tumor types. The transcriptomic features that we highlight here define cancer signatures that may reflect causal variations or consequences of disease state, or a combination of both.
Behavioral and postural analyses establish sleep-like states for mosquitoes that can impact host landing and blood feeding
Authors: Ajayi Oluwaseun M. , Marlman Justin M. , Gleitz Lucas A. , Smith Evan S. , Piller Benjamin D. , Krupa Justyna A. , Vinauger Clément , Benoit Joshua B.
Published: November 2021

Sleep is an evolutionarily conserved process that has been described in different animal systems. For insects, sleep characterization has been primarily achieved using behavioral and electrophysiological correlates in a few systems. Sleep in mosquitoes, which are important vectors of disease-causing pathogens, has not been directly examined. This is surprising as circadian rhythms, which have been well studied in mosquitoes, influence sleep in other systems. In this study, we characterized sleep in mosquitoes using body posture analysis and behavioral correlates, and quantified the effect of sleep deprivation on sleep rebound, host landing and blood-feeding propensity. Body and appendage position metrics revealed a clear distinction between the posture of mosquitoes in their putative sleep and awake states for multiple species, which correlate with a reduction in responsiveness to host cues. Sleep assessment informed by these posture analyses indicated significantly more sleep during periods of low activity. Nighttime and daytime sleep deprivation resulting from the delivery of vibration stimuli induced sleep rebound in the subsequent phase in day and night active mosquitoes, respectively. Lastly, sleep deprivation suppressed host landing in both laboratory and field settings and also impaired blood feeding of a human host when mosquitoes would normally be active. These results suggest that quantifiable sleep states occur in mosquitoes, and highlight the potential epidemiological importance of mosquito sleep.
Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation
Authors: Jeong Hyobin , Grimes Karen , Bruch Peter-Martin , Rausch Tobias , Hasenfeld Patrick , Sabarinathan Radhakrishnan , Porubsky David , Herbst Sophie A. , Erarslan-Uysal Büşra , Jann Johann-Christoph , Marschall Tobias , Nowak Daniel , Bourquin Jean-Pierre , Kulozik Andreas E. , Dietrich Sascha , Bornhauser Beat , Sanders Ashley D. , Korbel Jan O.
Published: November 2021

Somatic structural variants (SVs) are widespread in cancer genomes, however, their impact on tumorigenesis and intra-tumour heterogeneity is incompletely understood, since methods to functionally characterize the broad spectrum of SVs arising in cancerous single-cells are lacking. We present a computational method, scNOVA, that couples SV discovery with nucleosome occupancy analysis by haplotype-resolved single-cell sequencing, to systematically uncover SV effects on cis-regulatory elements and gene activity. Application to leukemias and cell lines uncovered SV outcomes at several loci, including dysregulated cancer-related pathways and mono-allelic oncogene expression near SV breakpoints. At the intra-patient level, we identified different yet overlapping subclonal SVs that converge on aberrant Wnt signaling. We also deconvoluted the effects of catastrophic chromosomal rearrangements resulting in oncogenic transcription factor dysregulation. scNOVA directly links SVs to their functional consequences, opening the door for single-cell multiomics of SVs in heterogeneous cell populations.
Electrical Stimulated GLUT4 Signaling Attenuates Critical Illness-Associated Muscle Wasting
Authors: Addinsall Alex B , Cacciani Nicola , Backéus Anders , Hedström Yvette , Shevchenko Ganna , Bergquist Jonas , Larsson Lars
Published: November 2021

Background

Critical illness myopathy (CIM) is a debilitating condition characterized by the preferential loss of the motor protein myosin. CIM is a byproduct of critical care, attributed to impaired recovery, long‐term complications, and mortality. CIM pathophysiology is complex, heterogeneous and remains incompletely understood, however loss of mechanical stimuli contributes to critical illness associated muscle atrophy and weakness. Passive mechanical loading (ML) and electrical stimulation (ES) therapies augment muscle mass and function. While having beneficial outcomes, the mechanistic underpinning of these therapies is less known. Therefore, here we aimed to assess the mechanism by which chronic supramaximal ES ameliorates CIM in a unique experimental rat model of critical care.

Methods

Rats were subjected to 8 days critical care conditions entailing deep sedation, controlled mechanical ventilation, and immobilization with and without direct soleus ES. Muscle size and function were assessed at the single cell level. RNAseq and Western blotting were employed to understand the mechanisms driving ES muscle outcomes in CIM.

Results

Following 8 days of controlled mechanical ventilation and immobilization, soleus muscle mass, Myosin:Actin ratio and single muscle fiber maximum force normalized to cross-sectional area (specific force) were reduced by 40-50% (p< 0.0001). ES significantly reduced the loss of soleus muscle fiber cross-sectional area (CSA) and Myosin:Actin ratio by approximately 30% (p< 0.05) yet failed to effect specific force. RNAseq pathway analysis revealed downregulation of insulin signaling in the soleus muscle following critical care and GLUT4 trafficking was reduced by 55% leading to an 85% reduction of muscle glycogen content (p< 0.01). ES promoted phosphofructokinase and insulin signaling pathways to control levels (p< 0.05), consistent with the maintenance of GLUT4 translocation and glycogen levels. AMPK, but not AKT, signaling pathway was stimulated following ES, where the downstream target TBC1D4 increased 3 logFC (p= 0.029) and AMPK-specific P-TBC1D4 levels were increased approximately 2-fold (p= 0.06). Reduction of muscle protein degradation rather than protein synthesis promoted soleus CSA, as ES reduced E3 ubiquitin proteins, Atrogin-1 (p= 0.006) and MuRF1 (p= 0.08) by approximately 50%, downstream of AMPK-FoxO3.

Conclusions

ES maintained GLUT4 translocation through increased AMPK-TBC1D4 signaling leading to improved muscle glucose homeostasis. Soleus CSA and myosin content was promoted through reduced protein degradation via AMPK-FoxO3 E3 ligases, Atrogin-1 and MuRF1. These results demonstrate chronic supramaximal ES reduces critical care associated muscle wasting, preserved glucose signaling and reduced muscle protein degradation in CIM.
GEDI: an R package for integration of transcriptomic data from multiple high-throughput platforms
Authors: Stokholm Mathias N. , Rabaglino Maria B. , Kadarmideen Haja N.
Published: November 2021

Transcriptomic data is often expensive and difficult to generate in large cohorts in comparison to genomic data and therefore is often important to integrate multiple transcriptomic datasets from both microarray and next generation sequencing (NGS) based transcriptomic data across similar experiments or clinical trials to improve analytical power and discovery of novel transcripts and genes. However, transcriptomic data integration presents a few challenges including re-annotation and batch effect removal. We developed the Gene Expression Data Integration (GEDI) R package to enable transcriptomic data integration by combining already existing R packages. With just four functions, the GEDI R package makes constructing a transcriptomic data integration pipeline straightforward. Together, the functions overcome the complications in transcriptomic data integration by automatically re-annotating the data and removing the batch effect. The removal of the batch effect is verified with Principal Component Analysis and the data integration is verified using a logistic regression model with forward stepwise feature selection. To demonstrate the functionalities of the GEDI package, we integrated five bovine endometrial transcriptomic datasets from the NCBI Gene Expression Omnibus. The datasets included Affymetrix, Agilent and RNA-sequencing data. Furthermore, we compared the GEDI package to already existing tools and found that GEDI is the only tool that provides a full transcriptomic data integration pipeline including verification of both batch effect removal and data integration.
MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses
Authors: Devine Jay , Vidal-García Marta , Liu Wei , Neves Amanda , Vercio Lucas D. Lo , Green Rebecca M. , Richbourg Heather A. , Marchini Marta , Unger Colton M. , Nickle Audrey C. , Radford Bethany , Young Nathan M. , Gonzalez Paula N. , Schuler Robert E. , Bugacov Alejandro , Rolian Campbell , Percival Christopher J. , Williams Trevor , Niswander Lee , Calof Anne L. , Lander Arthur D. , Visel Axel , Jirik Frank R. , Cheverud James M. , Klein Ophir , Birnbaum Ramon Y. , Merrill Amy E. , Ackermann Rebecca R. , Graf Daniel , Hemberger Myriam , Dean Wendy , Forkert Nils D. , Murray Stephen A. , Westerberg Henrik , Marcucio Ralph S. , Hallgrímsson Benedikt
Published: November 2021

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N=10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).
High-sensitivity pattern discovery in large, paired multi-omic datasets
Authors: Ghazi Andrew R. , Sucipto Kathleen , Rahnavard Gholamali , Franzosa Eric A. , McIver Lauren J. , Lloyd-Price Jason , Schwager Emma , Weingart George , Moon Yo Sup , Morgan Xochitl C. , Waldron Levi , Huttenhower Curtis
Published: November 2021

Modern biological screens yield enormous numbers of measurements, and identifying and interpreting statistically significant associations among features is essential. Here, we present a novel hierarchical framework, HAllA (Hierarchical All-against-All association testing), for structured association discovery between paired high-dimensional datasets. HAllA efficiently integrates hierarchical hypothesis testing with false discovery rate correction to reveal significant linear and non-linear block-wise relationships among continuous and/or categorical data. We optimized and evaluated HAllA using heterogeneous synthetic datasets of known association structure, where HAllA outperformed all-against-all and other block testing approaches across a range of common similarity measures. We then applied HAllA to a series of real-world multi-omics datasets, revealing new associations between gene expression and host immune activity, the microbiome and host transcriptome, metabolomic profiling, and human health phenotypes. An open-source implementation of HAllA is freely available at http://huttenhower.sph.harvard.edu/halla along with documentation, demo datasets, and a user group.

Author Summary

Modern scientific datasets increasingly include multiple measurements of many complementary data types. Here, we present HAllA, a method and implementation that overcomes the statistical challenges presented by data of this type by using feature similarity within each dataset to find statistically significant groups of features between them. We applied HAllA to simulated and real datasets, showing that HAllA outperformed existing procedures and identified compelling biological relationships. HAllA is widely applicable to diverse data structures and presents the user with grouped results that are easier to interpret than traditional methods.
Oxidative respiration through the bd-I and cbb3 oxidases is required for Vibrio cholerae pathogenicity and proliferation in vivo
Authors: Van Alst Andrew. J. , Demey Lucas M. , DiRita Victor J.
Published: November 2021

Vibrio cholerae respires both aerobically and anaerobically and, while oxygen may be available to it during infection, other terminal electron acceptors are proposed for population expansion during infection. Unlike gastrointestinal pathogens that stimulate significant inflammation leading to elevated levels of oxygen or alternative terminal electron acceptors, V. cholerae infections are not understood to induce a notable inflammatory response. To ascertain the respiration requirements of V. cholerae during infection, we used Multiplex Genome Editing by Natural Transformation (MuGENT) to create V. cholerae strains lacking aerobic or anaerobic respiration. V. cholerae strains lacking aerobic respiration were attenuated in infant mice 105-fold relative to wild type, while strains lacking anaerobic respiration had no colonization defect, contrary to earlier work suggesting a role for anaerobic respiration during infection. Using several approaches, including one we developed for this work termed Comparative Multiplex PCR Amplicon Sequencing (CoMPAS), we determined that the bd-I and cbb3 oxidases are essential for small intestinal colonization of V. cholerae in the infant mouse. The bd-I oxidase was also determined as the primary oxidase during growth outside the host, making V. cholerae the only example of a Gram-negative bacterial pathogen in which a bd-type oxidase is the primary oxidase for energy acquisition inside and outside of a host.

Author Summary

The bacterium that causes cholera, Vibrio cholerae, can grow with or without oxygen. When growing without oxygen it may use other molecules that serve the same purpose as oxygen, acting as a terminal electron acceptor in an energy-generating process known as respiration. Given the largely anaerobic nature of the gastrointestinal tract, and the lack of significant inflammation during cholera infection, a process that can stimulate elevated levels of oxygen and other terminal electron acceptors, we sought to understand the respiratory mechanisms of V. cholerae during infection. We used a powerful genome-editing method to construct mutant strains of V. cholerae lacking some or all of the complement of proteins required for aerobic or anaerobic respiration. By analyzing these mutants in the laboratory and in intestinal colonization of infant mice, we determined that the ability to respire without oxygen is completely dispensable for V. cholerae to thrive during infection. We determined that two of the four oxygen-dependent respiration mechanisms are essential for V. cholerae to grow during infection, with the other two dispensable for wild type levels of colonization.
A novel non-genetic murine model of hyperglycemia and hyperlipidemia-associated aggravated atherosclerosis
Authors: Gaul Susanne , Shahzad Khurrum , Medert Rebekka , Gadi Ihsan , Mäder Christina , Schumacher Dagmar , Wirth Angela , Ambreen Saira , Fatima Sameen , Boeckel Jes-Niels , Khawaja Hamzah , Haas Jan , Brune Maik , Nawroth Peter P , Isermann Berend , Laufs Ulrich , Freichel Marc
Published: November 2021

Objective

Atherosclerosis, the main pathology underlying cardiovascular diseases is accelerated in diabetic patients. Genetic mouse models require breeding efforts which are time-consuming and costly. Our aim was to establish a new nongenetic model of inducible metabolic risk factors that mimics hyperlipidemia, hyperglycemia, or both and allows the detection of phenotypic differences dependent on the metabolic stressor(s).

Methods and Results

Wild-type mice were injected with gain-of-function PCSK9D377Y (proprotein convertase subtilisin/kexin type 9) mutant adeno-associated viral particles (AAV) and streptozotocin and fed either a high-fat diet (HFD) for 12 or 20 weeks or a high-cholesterol/high-fat diet (Paigen diet, PD) for 8 weeks. To evaluate atherosclerosis, two different vascular sites (aortic sinus and the truncus of the brachiocephalic artery) were examined in the mice. Combined hyperlipidemic and hyperglycemic (HGHCi) mice fed a HFD or PD displayed characteristic features of aggravated atherosclerosis when compared to hyperlipidemia (HCi HFD or PD) mice alone. Atherosclerotic plaques of HGHCi HFD animals were larger, showed a less stable phenotype (measured by the increased necrotic core area, reduced fibrous cap thickness, and less α-SMA-positive area) and had more inflammation (increased plasma IL-1β level, aortic pro-inflammatory gene expression, and MOMA-2-positive cells in the BCA) after 20 weeks of HFD. Differences between the HGHCi and HCi HFD models were confirmed using RNA-seq analysis of aortic tissue, revealing that significantly more genes were dysregulated in mice with combined hyperlipidemia and hyperglycemia than in the hyperlipidemia-only group. The HGHCi-associated genes were related to pathways regulating inflammation (increased Cd68, iNos, and Tnfa expression) and extracellular matrix degradation (Adamts4 and Mmp14). When comparing HFD with PD, the PD aggravated atherosclerosis to a greater extent in mice and showed plaque formation after 8 weeks. Hyperlipidemic and hyperglycemic mice fed a PD (HGHCi PD) showed less collagen (Sirius red) and increased inflammation (CD68-positive cells) within aortic plaques than hyperlipidemic mice (HCi PD). HGHCi-PD mice represent a directly inducible hyperglycemic atherosclerosis model compared with HFD-fed mice, in which atherosclerosis is severe by 8 weeks.

Conclusion

We established a nongenetically inducible mouse model allowing comparative analyses of atherosclerosis in HCi and HGHCi conditions and its modification by diet, allowing analyses of multiple metabolic hits in mice.
Hydrodynamic model of fish orientation in a channel Flow
Authors: Porfiri Maurizio , Zhang Peng , Peterson Sean D.
Published: November 2021

For over a century, scientists have sought to understand how fish orient against an incoming flow, even without visual and flow cues. Here, we elucidate a potential hydrodynamic mechanism of rheotaxis through the study of the bidirectional coupling between fish and the surrounding fluid. By modeling a fish as a vortex dipole in an infinite channel with an imposed background flow, we establish a planar dynamical system for the cross-stream coordinate and orientation. The system dynamics captures the existence of a critical flow speed for fish to successfully orient while performing cross-stream, periodic sweeping movements. Model predictions are examined in the context of experimental observations in the literature on the rheotactic behavior of fish deprived of visual and lateral line cues. The crucial role of bidirectional hydrodynamic interactions unveiled by this model points at an overlooked limitation of existing experimental paradigms to study rheotaxis in the laboratory.
Mothers front-load their investment to the egg stage when helped in a wild cooperative bird
Authors: Capilla-Lasheras Pablo , Wilson Alastair J. , Young Andrew J.
Published: November 2021

In many cooperative societies, including our own, helpers assist with the post-natal care of breeders’ young, and may thereby benefit thepost-nataldevelopment of offspring. Here we present evidence of a novel mechanism by which such post-natal helping could also have hitherto unexplored beneficial effects onpre-nataldevelopment: by lightening post-natal maternal workloads, helpers may allow mothers to increase their pre-natal investment per offspring. We present the findings of a decade-long study of cooperatively breeding white-browed sparrow weaver,Plocepasser mahali, societies. Within each social group, reproduction is monopolized by a dominant breeding pair, and non-breeding helpers assist with nestling feeding. Using a within-mother reaction norm approach to formally identify maternal plasticity, we demonstrate that when mothers have more female helpers they decrease their ownpost-natalinvestment per offspring (feed their nestlings at lower rates) but increase theirpre-natalinvestment per offspring (lay larger eggs, which yield heavier hatchlings). That these plastic maternal responses are predicted by female helper number, and not male helper number, implicates the availability of post-natal helpingper seas the likely driver (rather than correlated effects of group size), because female helpers feed nestlings at substantially higher rates than males. We term this novel maternal strategy “maternal front-loading” and hypothesize that the expected availability ofpost-natalhelp allows helped mothers to focus maternal investment on thepre-natalphase, to which helpers cannot contribute directly. Such cryptic maternally mediated helper effects on pre-natal development may markedly complicate attempts to identify and quantify the fitness consequences of helping.