bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerated MRI using intelligent protocolling and subject-specific denoising applied to Alzheimer’s disease imaging
Authors: Ravi Keerthi Sravan , Nandakumar Gautham , Thomas Nikita , Lim Mason , Qian Enlin , Manso Jimeno Marina , Poojar Pavan , Jin Zhezhen , Quarterman Patrick , Srinivasan Girish , Fung Maggie , Vaughan John Thomas , Geethanath Sairam ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: October 2022

Magnetic Resonance Imaging (MRI) is expensive and time-consuming. Protocol optimization to accelerate MRI requires local expertise since each MR sequence involves multiple configurable parameters that need optimization for contrast, acquisition time, and signal-to-noise ratio (SNR). The availability and access to technical training are limited in under-served regions, resulting in a scarcity of local expertise required to operate the hardware and perform MR examinations. Along with other cultural and temporal constraints, these factors contribute to the highly inefficient utilization of MRI services diminishing their clinical value. In this work, we extend our previous effort and demonstrate accelerated MRI via intelligent protocolling of the modified brain screen protocol, referred to as the Gold Standard (GS) protocol. We leverage deep learning-based contrast-specific image-denoising to improve the image quality of data acquired using the accelerated protocol. Since the SNR of MR acquisitions depends on the volume of the object being imaged, we demonstrate subject-specific (SS) image-denoising. Utilizing the accelerated protocol resulted in a 1.94x gain in imaging throughput over the GS protocol. The minimum /maximum PSNR gains (measured in dB) were 1.18/11.68 and 1.04/13.15, from the baseline and SS image-denoising models, respectively.

Alzheimer’s Disease (AD) accounts for up to 60-80% of dementia cases and a global trend of longer lifespans has resulted in an increase in the prevalence of dementia/AD. Therefore, an accurate differential diagnosis of AD is crucial to determine the right course of treatment. The GS protocol constitutes 44.44% of the comprehensive AD imaging protocol defined by the European Prevention of Alzheimer’s Disease project. Therefore, we also demonstrate the potential for AD-imaging via automated volumetry of relevant brain anatomies whose atrophies have been shown to be reliable indicators of the onset of the disease. The volumetric measurements of the hippocampus and amygdala from the GS and accelerated protocols were in excellent agreement, as measured by the intra-class correlation coefficient.

In conclusion, accelerated brain imaging with the potential for AD imaging was demonstrated, and image quality was recovered post-acquisition using DL-based image denoising models.
Airborne environmental DNA captures terrestrial vertebrate diversity in nature
Authors: Lynggaard Christina , Frøslev Tobias Guldberg , Johnson Matthew S. , Olsen Morten Tange , Bohmann Kristine
Published: October 2022

The current biodiversity and climate crises highlight the need for efficient tools to monitor terrestrial ecosystems. Here, we provide evidence for the use of airborne eDNA analyses as a novel method to detect terrestrial vertebrate communities in nature. Metabarcoding of 143 airborne eDNA samples collected during three days in Åmosen Nature Park, Denmark yielded 64 bird, mammal, fish and amphibian taxa, representing about a quarter of the around 210 wild terrestrial vertebrates that have been registered in the greater Åmosen area through years of compiling observational data. We provide evidence for the spatial movement and temporal patterns of airborne eDNA and for the influence of weather conditions on vertebrate detections. This study demonstrates airborne eDNA for high-resolution biomonitoring of vertebrates in terrestrial systems and elucidates its potential to guide global nature management and conservation efforts in the ongoing biodiversity crisis.
Graphicacy across age, education, and culture: a new tool to assess intuitive graphics skills
Authors: Ciccione Lorenzo , Sablé-Meyer Mathias , Boissin Esther , Josserand Mathilde , Potier-Watkins Cassandra , Caparos Serge , Dehaene Stanislas
Published: October 2022

Data plots are widely used in science, journalism and politics, since they efficiently allow to depict a large amount of information. Graphicacy, the ability to understand graphs, thus became a fundamental cultural skill. Here, we introduce a new measure of graphicacy that assesses the ability to detect a trend in noisy scatterplots (“does this graph go up or down?”). In 3943 educated participants, responses vary as a sigmoid function of thet-value that a statistician would compute to detect a significant trend. We find a minimum level of core graphicacy even in unschooled participants living in remote Namibian villages (N=87) and 6-year-old 1st-graders who never read a graph (N=27). However, the sigmoid slope (the “graphicacy index”) varies across participants, increases with education, and tightly correlates with statistical knowledge, showing that experience contributes to refining graphical intuitions. Our tool is publicly available online and allows to quickly evaluate intuitive graphics skills.

STATEMENT OF RELEVANCE

The rising cost of gas, the number of Covid deaths, the evolution of temperatures during the summer months: we often face graphs depicting these phenomena. The scientific literature has shown that human adults can intuit, within milliseconds, the statistical trend of these graphs. However, we do not know if these intuitions generalized to unschooled people and, most importantly, how to measure their variations in the population. In this study we show that intuitive graphics skills are present even in 6-year-old children who never saw a graph and in the Himba of Namibia, an indigenous people with no access to formal schooling. Furthermore, we developed a quantitative assessment of such intuitive graphics skills (which we called the “graphicacy index”), that everyone can easily obtain for free, through a short (10 minutes) online test:https://neurospin-data.cea.fr/exp/lorenzo-ciccione/graphicacy-index/. In summary, our study provides the first attempt to formally quantify human intuitions of statistical graphs.
Extremely-fast construction and querying of compacted and colored de Bruijn graphs with GGCAT
Authors: Cracco Andrea , Tomescu Alexandru I.
Published: October 2022

Compacted de Bruijn graphs are one of the most fundamental data structures in computational genomics. Colored compacted graphs Bruijn graphs are a variant built on acollectionof sequences, and associate to eachk-mer the sequences in which it appears. We present GGCAT, a tool for constructing both types of graphs, based on a new approach merging thek-mer counting step with the unitig construction step, and on numerous practical optimizations.

For compacted de Bruijn graph construction, GGCAT achieves speed-ups of 3–21× compared to the state-of-the-art tool Cuttlefish 2 (Khan and Patro, Genome Biology, 2022). When constructing the colored variant, GGCAT achieves speed-ups of 5–39× compared to the state-of-the-art tool BiFrost (Holley and Melsted, Genome Biology, 2020). Additionally, GGCAT is up to 480× faster than BiFrost for batch sequence queries on colored graphs.
Over two orders of magnitude difference in rate of single chromosome loss among sundew (DroseraL., Droseraceae) lineages
Authors: Mohn Rebekah A. , Zenil-Ferguson Rosana , Krueger Thilo A. , Fleischmann Andreas S. , Cross Adam T. , Yang Ya
Published: October 2022

Chromosome number change is a driver of speciation in eukaryotic organisms. Carnivorous sundews, the plant genusDroseraL., exhibit single chromosome number variation among and within species, especially in the AustralianDroserasubg.ErgaleiumD.C., potentially linked to the presence of holocentromeres. We reviewed literature, verified chromosome counts, and using anrbcL chronogram, tested alternate models where the gain, loss, and doubling rates (+1, −1, ×2) were the same or different betweenD. subg.Ergaleiumand the other subgenera. Ancestral chromosome number estimations were performed, and the distributions of self-compatibility and genome size were visualized across the genus. The best model for chromosome evolution had equal rates of polyploidy (0.014 per million years; Myr) but higher rates of single chromosome number gain (0.19 and 0.027 per Myr) and loss (0.23 and 0.00059 per Myr) inD. subg.Ergaleiumcompared to the other subgenera. We found no evidence for differences in single chromosome evolution to be due to differences in diploidization after polyploidy or to holocentromeres as had been proposed. This study highlights the complexity of factors influencing rates of chromosome number evolution.
A general approach for selection of epitope-directed binders to proteins
Authors: Zhou Jie , Le Chau Q. , Zhang Yun , Wells James A.
Published: October 2022

Directing antibodies to a particular epitope among many possible on a target protein is a significant challenge. Here we present a simple and general method for epitope-directed selection (EDS) using a differential phage selection strategy. This involves engineering the protein of interest (POI) with the epitope of interest (EOI) mutated using a systematic bioinformatics algorithm to guide the local design of an EOI decoy variant. Using several alternating rounds of negative selection with the EOI decoy variant followed by positive selection on the wild-type (WT) POI, we were able to identify highly specific and potent antibodies to five different EOI antigens that bind and functionally block known sites of proteolysis. Among these we developed highly specific antibodies that target the proteolytic site on the CUB domain containing protein 1 (CDCP1) to prevent its proteolysis allowing us to study the cellular maturation of this event that triggers malignancy. We generated antibodies that recognize the junction between the pro and catalytic domains for four different matrix metalloproteases (MMPs), such as MMP1, MMP3, and MMP9, that selectively block activation of each of these enzymes and impairs cell migration. We targeted a proteolytic epitope on the cell surface receptor, EPH Receptor A2, that is known to transform it from a tumor suppressor to an oncoprotein. We believe the EDS method greatly facilitates the generation antibodies to specific EOIs on a wide range of proteins and enzymes for broad therapeutic and diagnostic applications.

Significance

We have developed a highly efficient platform to facilitate the directed selectionin vitroof antibodies to a wide range of functional epitopes on proteins. This method uses a bioinformatic program to guide mutations in the local site of interest to create a decoy antigen that can effectively remove antibodies not binding the site of interest by negative selection, followed by positive selection with the WT antigen to identify antibodies to the epitope of interest. We demonstrate the generality and versatility of this method by successfully producing functional antibodies to block specific proteolytically sensitive epitopes on five different proteins including enzymes important in cancer. The epitope-directed selection (EDS) approach greatly facilitates the identification of binders to specific sites of interest on proteins to probe function and as potential immunotherapeutics.
Graves’ disease-associated TSHR gene is demethylated and expressed in human regulatory T cells
Authors: Salumets Ahto , Tserel Liina , Kasela Silva , Limbach Maia , Milani Lili , Peterson Hedi , Kisand Kai , Peterson Pärt
Published: October 2022

Epigenetic changes at specific genetic loci and the activation of transcriptional repressor FOXP3 are needed to establish and maintain the regulatory T cell (Treg) lineage. Here we studied the DNA methylation profiles in CD4+CD25+Tregs and CD4+CD25−conventional T cells (Tconvs) from healthy individuals and identified a wide range of differentially methylated CpG sites (DMPs). Overall, Tregs had more hypomethylated DMPs and contained more CpG sites, which on the cell population level were less defined in their methylation status. We identified top hypomethylated CpGs in Tregs close to CENPM, IKZF2, and LYST and hypermethylated sites at the THEMIS, SCML4, and ADD3 genes. Among others, DMPs were enriched for the transcriptional repressor Kaiso binding motifs. Interestingly, in Tregs we found hypomethylation and increased expression of the TSHR gene, which is a risk gene for Graves’ disease (GD). However, subsequent DNA methylation profiling in healthy individuals and GD patients revealed only 19 DMPs and no change at the TSHR locus, indicating that Tregs in GD patients share a similar methylation pattern with healthy controls. Together, we show Treg-specific hypomethylation and expression of the TSHR gene, prompting additional scenarios to explain the genetic link and role of anti-TSHR autoantibodies in GD.
GBP1 promotes killing of multidrug-resistantAcinetobacter baumanniiand promotes host protection via interferon signalling and inflammasome activation
Authors: Li Fei-Ju , Starrs Lora , Mathur Anukriti , Enosi Tuipulotu Daniel , Man Si Ming , Burgio Gaetan
Published: October 2022

Multidrug resistant (MDR)Acinetobacter baumanniiare of major concern worldwide due to their resistance to last resort carbapenem and polymyxin antibiotics. To develop an effective treatment strategy, it is critical to better understand how anA. baumanniiMDR bacterium interacts with its mammalian host. Pattern-recognition receptors sense microbes, and activate the inflammasome pathway, leading to pro-inflammatory cytokine production and programmed cell death. Here, we found that MDRA. baumanniiactivate the NLRP3 inflammasome complex predominantly via the non-canonical caspase-11-dependent pathway. We show that caspase-11-deficient mice are protected from a virulent MDRA. baumanniistrain by maintaining a balance between protective and deleterious inflammation via IL-1. Caspase-11-deficient mice also compromise between effector cell recruitment, phagocytosis, and programmed cell death in the lung during infection. Importantly, we found that cytosolic immunity - mediated by guanylate-binding protein 1 (GBP1) and type I interferon signalling - orchestrates caspase-11-dependent inflammasome activation. This exerts a bactericidal activity against carbapenem- and colistin-resistant, lipooligosaccharide (LOS)- deficient bacteria. Together, our results suggest that developing therapeutic strategies targeting GBP1 might pave the way as a host-directed therapy to overcome multidrug resistance inA. baumanniiinfection.
DeepSelectNet: Deep Neural Network Based Selective Sequencing for Oxford Nanopore Sequencing
Authors: Senanayake Anjana , Gamaarachchi Hasindu , Herath Damayanthi , Ragel Roshan
Published: October 2022

Background:

Nanopore sequencing allows selective sequencing, the ability to programmatically reject unwanted reads in a sample. Selective sequencing has many present and future applications in genomics research and the classification of species from a pool of species is an example. Existing methods for selective sequencing for species classification are still immature and the accuracy highly varies depending on the datasets. For the five datasets we tested, the accuracy of existing methods varied in the range of ~77%-97% (average accuracy <89%). Here we present DeepSelectNet, an accurate deep-learning-based method that can directly classify nanopore current signals belonging to a particular species. DeepSelectNet utilizes novel data preprocessing techniques and improved neural network architecture for regularization.

Results:

For the five datasets tested, DeepSelectNet’s accuracy varied between ~91%-99% (average accuracy ~95%). At its best performance, DeepSelectNet achieved a nearly 12% accuracy increase compared to its deep learning-based predecessor SquiggleNet. Furthermore, precision and recall evaluated for DeepSelectNet on average were always >89% (average ~95%). In terms of execution performance, DeepSelectNet outperformed SquiggleNet by ~13% on average. Thus, DeepSelectNet is a practically viable method to improve the effectiveness of selective sequencing.

Conclusions:

Compared to base alignment and deep learning predecessors, DeepSelectNet can significantly improve the accuracy to enable real-time species classification using selective sequencing. The source code of DeepSelectNet is available athttps://github.com/AnjanaSenanayake/DeepSelectNet.
Weddell seals near the fastest melting glacier in Antarctica prefer shallow, coastal and partially ice-covered waters
Authors: Bortolotto Guilherme A. , Heywood Karen J. , Boehme Lars
Published: October 2022

Antarctic ice-shelves melting is accelerating, and the highest rates for the continent are observed in the Amundsen Sea, where Weddell seals are understudied. By modelling an unrivalled telemetry tracking dataset, we show that this top predator in the area is more likely found in shallower waters, closer to the coast, half-covered by ice and where the temperature at the ocean bottom is around 0.5°C or colder. Their distribution during winter is more restricted to coastal areas in the eastern Amundsen Sea and spread out in warmer months. That fluctuation reflects the drastic variation in their habitat illustrating their potential sensitivity to the upcoming impacts of climate changes. We discuss their overlap with Antarctic toothfish fisheries in the area and the potential consequences of global warming to the ecology of the seals.
Alternative culture systems for bovine oocytein vitromaturation: liquid marbles and differentially shaped 96-well plates
Authors: Fernández-Montoro Andrea , Angel-Velez Daniel , Benedetti Camilla , Azari-Dolatabad Nima , Pascottini Osvaldo Bogado , Pavani Krishna Chaitanya , Van Soom Ann
Published: October 2022

In vivomatured oocytes exhibit higher developmental competence than those maturedin vitro, but mimicking thein vivoenvironment byin vitroconditions has been challenging. Till now, conventional two-dimensional (2D) systems have been used forin vitromaturation of bovine cumulus-oocytes-complexes (COCs). However, using such systems may cause cell flattening and does not allow cumulus expansion in all dimensions, which is less physiological. Therefore, implementing a low-cost and highly effectivein vivo-like microenvironment methodology may help to optimize oocytein vitromaturation. Here, we used two different systems to culture COCs and evaluate their potential influence on embryo development and quality. In the first system, we used treated fumed silica particles to create a 3D microenvironment (liquid marbles; LM) to mature COCs. In the second system, we cultured COCs in 96-well plates with different dimensions (flat, ultra-low attachment round-bottom, and V-shaped 96-well plates). In both systems, the nuclear maturation rate remained similar to the control in 2D, showing that most oocytes reached metaphase II. However, the subsequent blastocyst rate remained lower in the liquid marble system compared to 96-well plates and control 2D systems. Interestingly, a lower total cell number was found in the resulting embryos from both systems (LM and 96-well plates) compared to the control. In conclusion, oocytes matured in liquid marbles or 96-well plates showed no remarkable change in terms of meiotic resumption, embryo development, and quality in both systems. None of the surface geometries influenced embryo development. These findings provide important inferences in many aspects of oocyte and embryo development. Further investigation is needed to determine other aspects like toxicity testing and ultrastructural changes in oocytes.
The geometry of hidden representations of protein language models
Authors: Valeriani Lucrezia , Cuturello Francesca , Ansuini Alessio , Cazzaniga Alberto
Published: October 2022

Protein language models (pLMs) transform their input into a sequence of hidden representations whose geometric behavior changes across layers. Looking at fundamental geometric properties such as the intrinsic dimension and the neighbor composition of these representations, we observe that these changes highlight a pattern characterized by three distinct phases. This phenomenon emerges across many models trained on diverse datasets, thus revealing a general computational strategy learned by pLMs to reconstruct missing parts of the data. These analyses show the existence of low-dimensional maps that encode evolutionary and biological properties such as remote homology and structural information. Our geometric approach sets the foundations for future systematic attempts to understand thespaceof protein sequences with representation learning techniques.
Accuratede novoprediction of RNA 3D structure with transformer network
Authors: Feng Chenjie , Wang Wenkai , Han Renmin , Wang Ziyi , Ye Lisa , Du Zongyang , Wei Hong , Zhang Fa , Peng Zhenling , Yang Jianyi
Published: October 2022

RNA 3D structure prediction remains challenging though after years of efforts. Inspired by the recent breakthrough in protein structure prediction, we developed trRosettaRNA, a novel deep learning-based approach tode novoprediction of RNA 3D structure. Like trRosetta, the trRosettaRNA pipeline comprises two major steps: 1D and 2D geometries prediction by a transformer network; and full-atom 3D structure folding by energy minimization with constraints from the predicted geometries. We benchmarked trRosettaRNA on two independent datasets. The results show that trRosettaRNA outperforms other conventional methods by a large margin. For example, on 25 targets from the RNA-Puzzles experiments, the mean RMSD of the models predicted by trRosettaRNA is 5.5 Å, compared with 10.5 Å from the state-of-the-art human group (i.e., Das). Further comparisons with two recently released deep learning-based methods (i.e., DeepFoldRNA and RoseTTAFoldNA) show that all three methods have similar accuracy. However, trRosettaRNA yields more accurate and physically more realistic side-chain atoms than DeepFoldRNA and RoseTTAFoldNA. Finally, we apply trRosettaRNA to predict the structures for the Rfam families that do not have known structures. Analysis shows that for 263 families, the predicted structure models are estimated to be accurate with RMSD < 4 Å. The trRosettaRNA server and the package are available at:https://yanglab.nankai.edu.cn/trRosettaRNA/.
Fear of missing out (FOMO) associates with reduced cortical thickness in core regions of the posterior default mode network and higher levels of problematic smartphone and social media use
Authors: Wang Lan , Zhou Xinqi , Song Xinwei , Gan Xianyang , Zhang Ran , Liu Xiqin , Xu Ting , Jiao Guojuan , Ferraro Stefania , Bore Mercy Chepngetich , Yu Fangwen , Zhao Weihua , Montag Christian , Becker Benjamin
Published: October 2022

Fear of missing out (FOMO) promotes the desire or urge to stay continuously connected with a social reference group and updated on their activities, which may result in escalating and potentially addictive smartphone and social media use. The present study aimed to determine whether the neurobiological basis of FOMO encompasses core regions of the reward or social brain, and the associations with the level of problematic smartphone or social media use. We capitalized on a dimensional neuroimaging approach to examine cortical thickness and subcortical volume associations in a comparably large sample of healthy young individuals (n = 167). Meta-analytic network and behavioral decoding were employed to further characterize the identified regions. Higher levels of FOMO associated with lower cortical thickness in the precuneus. In contrast, no associations between FOMO and variations in striatal morphology were observed. Meta-analysis decoding revealed that the identified precuneus region exhibited a strong functional interaction with the default mode network (DMN) engaged in social cognitive and self-referential domains. Together the present findings suggest that individual variations in FOMO are associated with the brain structural architecture of the right precuneus, a core hub within a large-scale functional network resembling the DMN involved in social and self-referential processes. FOMO may promote escalating social media and smartphone use via social and self-referential processes rather than reward-related processes per se.
Cholinergic Modulation Shifts the Response of CA1 Pyramidal Cells to Depolarizing Ramps via TRPM4 Channels with Potential Implications for Place Field Firing
Authors: Combe Crescent , Upchurch Carol , Canavier Carmen C. , Gasparini Sonia
Published: October 2022

A synergistic combination ofin vitroelectrophysiology and multicompartmental modeling of rat CA1 pyramidal neurons identified TRPM4 channels as major drivers of cholinergic modulation of the firing rate during a triangular current ramp, which emulates the bump in synaptic input received while traversing the place field. In control, fewer spikes at lower frequencies are elicited on the down-ramp compared to the up-ramp due to long-term inactivation of the NaVchannel. The cholinergic agonist carbachol (CCh) removes or even reverses this spike rate adaptation, causing more spikes to be elicited on the down-ramp than the up-ramp. CCh application during Schaffer collateral stimulation designed to simulate a ramp produces similar shifts in the center of mass of firing to later in the ramp. The non-specific TRP antagonist flufenamic acid and the TRPM4-specific blockers CBA and 9-phenanthrol, but not the TRPC-specific antagonist SKF96365, reverse the effect of CCh; this implicates the Ca2+-activated nonspecific cation current, ICAN, carried by TRPM4 channels. The cholinergic shift of the center of mass of firing is prevented by strong intracellular Ca2+buffering but not by antagonists for IP3and ryanodine receptors, ruling out a role for known mechanisms of release from intracellular Ca2+stores. Pharmacology combined with modeling suggest that [Ca2+] in a nanodomain near the TRPM4 channel is elevated through an unknown source that requires both muscarinic receptor activation and depolarization-induced Ca2+influx during the ramp. Activation of the regenerative inward TRPM4 current in the model qualitatively replicates and provides putative underlying mechanisms for the experimental observations.
A Process Model Account of the Role of Dopamine in Intertemporal Choice
Authors: Soutschek Alexander , Tobler Philippe N.
Published: October 2022

Theoretical accounts disagree on the role of dopamine in intertemporal choice and assume that dopamine either promotes delay of gratification by increasing the preference for larger rewards or that dopamine reduces patience by enhancing the sensitivity to waiting costs. Here, we reconcile these conflicting accounts by providing empirical support for a novel process model according to which dopamine contributes to two dissociable components of the decision process, evidence accumulation and starting bias. We re-analyzed a previously published data set where intertemporal decisions were made either under the D2 antagonist amisulpride or under placebo by fitting a hierarchical drift diffusion model that distinguishes between dopaminergic effects on the speed of evidence accumulation and the starting point of the accumulation process. Blocking dopaminergic neurotransmission not only strengthened the sensitivity to whether a reward is perceived as worth the delay costs during evidence accumulation (drift rate) but also attenuated the impact of waiting costs on the starting point of the evidence accumulation process (bias). Taken together, our findings support a novel, process-based account of the role of dopamine for cost-benefit decision making, highlight the potential benefits of process-informed analyses and advance our understanding of dopaminergic contributions to decision making.
meTCRs - Learning a metric for T-cell receptors
Authors: Drost Felix , Schiefelbein Lennard , Schubert Benjamin
Published: October 2022

T cell receptors (TCRs) bind to pathogen- or self-derived epitopes to elicit a T cell response as part of the adaptive immune system. Determining the specificity of TCRs provides context for immunological studies and can be used to identify candidates for novel immunotherapies. To avoid costly experiments, large-scale TCR-epitope databases are queried for similar sequences via various distance functions. Here, we developed the deep-learning based distancemeTCRs. Contrary to most previous approaches, the method avoids computational expansive pairwise string operations by comparing TCRs in a numeric embedding. In contrast to models which are trained specificity-agnostic, we directly utilize epitope information by applying deep metric learning to guide the training. Summarizing, we presentmeTCRsas a scalable alternative to embed TCR repertoires for clustering, visualisation, and querying against the ever-increasing amount TCR-epitope pairs in publicly available databases.
A common neural code for representing imagined and inferred tastes
Authors: Avery Jason A. , Carrington Madeline , Martin Alex
Published: October 2022

Inferences about the taste of foods are a key aspect of our everyday experience of food choice. Despite this, gustatory mental imagery is a relatively under-studied aspect of our mental lives. In the present study, we examined subjects during high-field fMRI as they actively imagined basic tastes and subsequently viewed pictures of foods dominant in those specific taste qualities. Imagined tastes elicited activity in the bilateral dorsal mid-insula, one of the primary cortical regions responsive to the experience of taste. In addition, within this region we reliably decoded imagined tastes according to their dominant quality - sweet, sour, or salty – thus indicating that, like actual taste, imagined taste activates distinct quality-specific neural patterns. Using a cross-task decoding analysis, we found that the neural patterns for imagined tastes and food pictures in the mid-insula were reliably similar and quality-specific, suggesting a common code for representing taste quality regardless of whether explicitly imagined or automatically inferred when viewing food. These findings have important implications for our understanding of the mechanisms of mental imagery and the multimodal nature of presumably primary sensory brain regions like the dorsal mid-insula.
Complete sequencing of a cynomolgus macaque major histocompatibility complex haplotype
Authors: Karl Julie A. , Prall Trent M. , Bussan Hailey E. , Varghese Joshua M. , Pal Aparna , Wiseman Roger W. , O’Connor David H.
Published: October 2022

Macaques provide the most widely used nonhuman primate models for studying immunology and pathogenesis of human diseases. While the macaque major histocompatibility complex (MHC) region shares most features with the human leukocyte antigen (HLA) region, macaques have an expanded repertoire of MHC class I genes. Although a chimera of two rhesus macaque MHC haplotypes was first published in 2004, the structural diversity of MHC genomic organization in macaques remains poorly understood due to a lack of adequate genomic reference sequences. We used ultra-long Oxford Nanopore and high-accuracy PacBio HiFi sequences to fully assemble the ∼5.2 Mb M3 haplotype of an MHC-homozygous, Mauritian-origin cynomolgus macaque (Macaca fascicularis). The MHC homozygosity allowed us to assemble a single MHC haplotype unambiguously and avoid chimeric assemblies that hampered previous efforts to characterize this exceptionally complex genomic region in macaques. The high quality of this new assembly is exemplified by the identification of an extended cluster of sixMafa-AGgenes that contains a recent duplication with a remarkably similar ∼48.5 kb block of sequence. The MHC class II region of this M3 haplotype is similar to the previously sequenced rhesus macaque haplotype and HLA class II haplotypes. The MHC class I region, in contrast, contains 13MHC-Bgenes, fourMHC-Agenes, and threeMHC-Egenes (versus 19MHC-B, twoMHC-A, and oneMHC-Ein the previously sequenced haplotype). These results provide an unambiguously assembled single contiguous cynomolgus macaque MHC haplotype with fully curated gene annotations that will inform infectious disease and transplantation research.
Granulin Loss of Function in Human Mature Brain Organoids Implicates Astrocytes in TDP-43 Pathology
Authors: de Majo Martina , Koontz Mark , Marsan Elise , Salinas Nir , Ramsey Arren , Kuo Yien-Ming , Seo Kyounghee , Li Huinan , Dräger Nina M , Leng Kun , Gonzales Santiago L , Kurnellas Michael , Miyaoka Yuichiro , Klim Joseph R , Kampmann Martin , Ward Michael E , Huang Eric J , Ullian Erik M
Published: October 2022

Loss of function (LoF) of Tar-binding protein 43 (TDP-43) and mislocalization, together with TDP-43-positive and hyperphosphorylated inclusions, are found in postmortem tissue of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those carrying LoF variants in the progranulin gene (GRN). Modelling TDP-43 pathology has been challengingin vivoandin vitro. We present a 3D-induced pluripotent stem cell (iPSC)-derived paradigm - mature brain organoids (mbOrg) - composed of cortical-like-astrocytes (iA) and neurons (iN). When devoid ofGRN, mbOrgs spontaneously recapitulate TDP-43 mislocalization, hyperphosphorylation and LoF phenotypes. Mixing-and-matching genotypes in mbOrgs showed thatGRN−/−iA are drivers for TDP-43 pathology. Finally, we rescued TDP-43 LoF by adding exogenous progranulin, demonstrating a link between TDP-43 LoF and progranulin expression. In conclusion, we present an iPSC-derived platform that shows striking features of human TDP-43 proteinopathy and provides a tool for mechanistic modelling of TDP-43 pathology and patient-tailored therapeutic screening for FTD and ALS.

Highlights

GRN−/−iPSC-derived 3D paradigm (mbOrg) composed of mature cortical-like astrocytes and neurons recapitulates features of TDP-43 proteinopathy

GRN−/−cortical-like astrocytes are necessary and sufficient for the development of the TDP-43 loss of function phenotype in mbOrg.

A TDP-43 phenotype can be rescued in neurons by treating neuron and astrocyte co-cultures with progranulin full length protein.

eTOC blurb

In this article, de Majo and colleagues present a novel 3D iPSC-derived model to study neurodegenerative disorders such as ALS and FTD. When devoid ofGRNexpression, these cultures present features of ALS and FTD associated pathology hardly ever observedin vitro. These phenotypes are shown to be primarily driven by diseased astrocytes and can be rescued by progranulin supplementation.
hgtseq: a standard pipeline to study horizontal gene transfer
Authors: Carpanzano Simone , Santorsola Mariangela ,   nf-core community, Lescai Francesco
Published: October 2022

Horizontal gene transfer (HGT) is well described in prokaryotes, it plays a crucial role in evolution, and has functional consequences in insects and plants: less is known about HGT in Humans. Studies have reported bacterial integrations in cancer patients, and microbial sequences have been detected in data from well-known Human sequencing projects. Few of the existing tools to investigate HGT are highly automated. Thanks to the adoption of Nextflow for life sciences work-flows, and the standards and best practices curated by communities such as nf-core, fully automated, portable, and scalable pipelines can now be developed. Here we present nf-core/hgtseq, to facilitate the analysis of HGT from sequencing data in different organisms. We showcase its performance by analysing six exome datasets from five mammals. Hgtseq can be run seamlessly in any computing environment and accepts data generated by existing exome and whole-genome sequencing projects: this will enable researchers to expand their analyses into this area. Fundamental questions are still open, about the mechanisms and the extent or the role of horizontal gene transfer: by releasing hgtseq we provide a standardised tool which will enable a systematic investigation of this phenomenon, thus paving the way for a better understanding of HGT.
Development and application of genetic ancestry reconstruction methods to study diversity of patient-derived models in the NCI PDXNet Consortium
Authors: Sanderson Brian J. , Lott Paul , Chiu Katherine , Quino Juanita Elizabeth , Vang April Pangia , Lloyd Michael W. , Srivastava Anuj ,   PDXNet Consortium, Chuang Jeffrey H. , Carvajal-Carmona Luis G.
Published: October 2022

Personalized medicine holds great promise for improving cancer outcomes, yet there is a large inequity in the demographics of patients from whom genomic data and models, including patient derived xenografts (PDX), are developed and for whom treatments are optimized. In this study we develop a genetic ancestry pipeline for the Cancer Genomics Cloud, which we use to assess the diversity of models currently available in the National Cancer Institute (NCI) supported PDX Development and Trial Centers Research Network (PDXNet). We show that there is an over-representation of models derived from patients of European ancestry, which is consistent with other cancer model resources. We discuss these findings in the context of disparities in cancer incidence and outcomes among demographic groups in the US. For example, for the top cancer health disparities affecting African Americans and Latinos, there is a significant lack of ethnic/race appropriate models needed to advance pre-clinical research and personalized clinical treatment. For stomach and liver tumors, which represent disparities in these two minority populations, there are only three available models derived from patients from such backgrounds. Fortunately, ongoing NCI-funded efforts in minority focused PDXNet centers are actively addressing these gaps. We further discuss these results in the context of power analyses to highlight the immediate need for the development of models from minority populations to address cancer health equity in personalized medicine.
EUGENe: A Python toolkit for predictive analyses of regulatory sequences
Authors: Klie Adam , Stites Hayden , Jores Tobias , Solvason Joe J , Farley Emma K , Carter Hannah
Published: October 2022

Deep learning (DL) has become a popular tool to study cis-regulatory element function. Yet efforts to design software for DL analyses in genomics that are Findable, Accessible, Interoperable and Reusable (FAIR) have fallen short of fully meeting these criteria. Here we present EUGENe (Elucidating theUtility ofGenomicElements withNeural Nets), a FAIR toolkit for the analysis of labeled sets of nucleotide sequences with DL. EUGENe consists of a set of modules that empower users to execute the key functionality of a DL workflow: 1) extracting, transforming and loading sequence data from many common file formats, 2) instantiating, initializing and training diverse model architectures, and 3) evaluating and interpreting model behavior. We designed EUGENe to be simple; users can develop workflows on new or existing datasets with two customizable Python objects, annotated sequence data (SeqData) and PyTorch models (BaseModel). The modularity and simplicity of EUGENe also make it highly extensible and we illustrate these principles through application of the toolkit to three predictive modeling tasks. First, we train and compare a set of built-in models along with a custom architecture for the accurate prediction of activities of plant promoters from STARR-seq data. Next, we apply EUGENe to an RNA binding prediction task and showcase how seminal model architectures can be retrained in EUGENe or imported from Kipoi. Finally, we train models to classify transcription factor binding by wrapping functionality from Janngu, which can efficiently extract sequences in BED file format from the human genome. We emphasize that the code used in each use case is simple, readable, and well documented (https://eugene-tools.readthedocs.io/en/latest/index.html). We believe that EUGENe represents a springboard toward a collaborative ecosystem for DL applications in genomics research. EUGENe is available for download on GitHub (https://github.com/cartercompbio/EUGENe) along with several introductory tutorials and for installation on PyPi (https://pypi.org/project/eugene-tools/).
The Impact of Model Misspecification on Phylogenetic Network Inference
Authors: Cao Zhen , Li Meng , Ogilvie Huw A , Nakhleh Luay
Published: October 2022

1

The development of statistical methods to infer species phylogenies with reticulations (species networks) has led to many discoveries of gene flow between distinct species. These methods typically assume only incomplete lineage sorting and introgression. Given that phylogenetic networks can be arbitrarily complex, these methods might compensate for model misspecification by increasing the number of dimensions beyond the true value. Herein, we explore the effect of potential model misspecification, including the negligence of gene tree estimation error (GTEE) and assumption of a single substitution rate for all genomic loci, on the accuracy of phylogenetic network inference using both simulated and biological data. In particular, we assess the accuracy of estimated phylogenetic networks as well as test statistics for determining whether a network is the correct evolutionary history, as opposed to the simpler model that is a tree.

We found that while GTEE negatively impacts the performance of test statistics to determine the “tree-ness” of the evolutionary history of a data set, running those tests on triplets of taxa and correcting for multiple testing significantly ameliorates the problem. We also found that accounting for substitution rate heterogeneity improves the reliability of full Bayesian inference methods of phylogenetic networks, whereas summary statistic methods are robust to GTEE and rate heterogeneity, though currently require manual inspection to determine the network complexity.
OzFAD: Ozone-enabled fatty acid discovery reveals unexpected diversity in the human lipidome
Authors: Menzel Jan Philipp , Young Reuben S.E. , Benfield Aurélie H. , Scott Julia , Butler Lisa M. , Henriques Sónia Troeira , Poad Berwyck L.J. , Blanksby Stephen J.
Published: October 2022

Fatty acid isomers are responsible for an under-reported lipidome diversity across all kingdoms of life. Isomers of unsaturated fatty acid are often masked in contemporary analysis by incomplete separation and the absence of sufficiently diagnostic methods for structure elucidation. Here, we introduce a comprehensive workflow to discover new unsaturated fatty acids through coupling liquid chromatography and mass spectrometry with gas-phase ozonolysis of double bonds. The workflow encompasses semi-automated data analysis and enablesde novoidentification in complex media including human plasma, cancer cell lines and human sebaceous wax (i.e., vernix caseosa). The targeted analysis including ozonolysis enables structural assignment over a dynamic range of five orders of magnitude, even in instances of incomplete chromatographic separation. Thereby we expand the number of identified plasma fatty acids two-fold, including non-methylene interrupted fatty acids. Detection, without prior knowledge, allows discovery of non-canonical double bond positions. Changes in relative isomer abundances reflect underlying perturbations in lipid metabolism.
Hortaea werneckiiisolates exhibit different pathogenic potential in the invertebrate infection modelGalleria mellonella
Authors: Anthonies Stephanie , Vargas-Muñiz José M.
Published: October 2022

Hortaea werneckiiis a black yeast with a remarkable tolerance to salt. Most studies have been dedicated to understanding howH. werneckiiadapt to hypersaline environments.H. werneckiihas an unconventional cell cycle in which it alternates between fission and budding, which is modulated by cell density. Additionally,H. werneckiican cause superficial mycosis of the palm and sole of humans. Here, we determine the impact of salt concentration on the EXF-2000 strain’s cell division pattern and morphology. At low density and no salt, EXF-2000 primarily grows as pseudohyphae dividing mainly by septation. When grown in the presence of salt at a similar concentration to saltwater or hypersaline environments, we observe it grows by first by undergoing fission followed by budding at the poles. Then, we examined a collection of 16 isolates, including isolates from marine and hypersaline environments and isolates from patients. Isolates exhibit a wide diversity in colony shape and cellular morphology. The isolates grew as yeast, pseudohyphae, and true hyphae, indicating that isolates can exhibit various cell morphologies under similar environmental conditions. We used the insect larvaeGalleria mellonellato determine the pathogenic potential of our isolates. We observe that only a subset of isolates can cause death in our model, and there was no correlation betweenH. werneckiimorphology and capacity to cause disease. Taken together,H. werneckiigenomic and phenotypic diversity can serve as a model to better understand how phenotypes and pathogenic potential evolve in environmental fungi.
A ZTF-7/RPS-2 complex mediates the cold-warm response inC. elegans
Authors: Xu Ting , Liao Shimiao , Zhu Chengming , Jin Qile , Xu Demin , Fu Chuanhai , Chen Xiangyang , Feng Xuezhu , Guang Shouhong
Published: October 2022

Temperature greatly affects numerous biological processes in all organisms. How multicellular organisms respond to and are impacted by hypothermic stress remains elusive. Here, we found that cold-warm stimuli induced depletion of the RNA exosome complex in the nucleoli but enriched it in the nucleoplasm. To further understand the function and mechanism of cold-warm stimuli, we conducted forward genetic screening and identified ZTF-7, which is required for RNA exosome depletion from nucleoli upon transient cold-warm exposure inC. elegans. ZTF-7 is a putative ortholog of human ZNF277 that may contribute to language impairments. Immunoprecipitation followed by mass spectrometry (IP-MS) found that ZTF-7 interacted with RPS-2, which is a ribosomal protein of the small subunit and participates in pre-rRNA processing. A partial depletion of RPS-2 and other proteins of the small ribosomal subunit blocked the cold-warm stimuli-induced reduction of exosome subunits from the nucleoli. These results established a novel mechanism by whichC. elegansresponds to environmental cold-warm exposure.