bluuebunny/crossref_metadata_2025_split huggingface dataset:
The novel compensatory reciprocal interplay between neutrophils and monocytes drives cancer progression
Authors: Chen Zhihong , Soni Nishant , Pinero Gonzalo , Giotti Bruno , Eddins Devon J. , Lindblad Katherine E. , Ross James L , Tsankova Nadejda , Gutmann David H. , Lira Sergio A. , Lujambio Amaia , Ghosn Eliver E.B. , Tsankov Alexander M. , Hambardzumyan Dolores 
Published: July 2022

SUMMARYMyeloid cells comprise the majority of immune cells in tumors, contributing to tumor growth and therapeutic resistance. Incomplete understanding of myeloid cells response to tumor driver mutation and therapeutic intervention impedes effective therapeutic design. Here, by leveraging CRISPR/Cas9-based genomic editing, we generated a mouse model that is deficient of all monocyte chemoattractant proteins (MCP). Using this strain, we effectively abolished monocyte infiltration in glioblastoma (GBM) and hepatocellular carcinoma (HCC) murine models, which were enriched for monocytes or neutrophils, respectively. Remarkably, eliminating monocyte chemoattraction invokes a significant compensatory neutrophil influx in GBM, but not in HCC. Single-cell RNA sequencing revealed that intratumoral neutrophils promoted proneural-to-mesenchymal transition in GBM, and supported tumor aggression by facilitating hypoxia response via TNF production. Importantly, genetic or pharmacological inhibiting neutrophil in HCC or qMCP-KO GBM extended the survival of tumor-bearing mice. Our findings emphasize the importance of targeting both monocytes and neutrophils simultaneously for cancer immunotherapy.In BriefEliminating monocyte chemoattraction invokes compensatory neutrophil influx in tumor, and vice versa, rendering current myeloid-targeted therapies ineffective. Using genetic and pharmacological approaches combined with novel mouse models of GBM and HCC, we provide credence advocating for combinational therapies aiming at inhibiting both monocytes and neutrophils simultaneously.Highlights•Blocking monocyte chemoattraction results in increased neutrophil infiltration.•Increased neutrophil recruitment induces GBM PN to MES transition.•Inhibiting neutrophil infiltration in monocyte-deficient tumors improves mouse GBM survival.•Blocking neutrophil, but not monocyte, infiltration in HCC prolongs mouse survival.
Decoding the Effects of Spike Receptor Binding Domain Mutations on Antibody Escape Abilities of Omicron Variants
Authors: Chakraborty Sandipan , Saha Aditi , Saha Chiranjeet , Ghosh Sanjana , Mondal Trisha 
Published: July 2022

AbstractRecent times witnessed an upsurge in the number of COVID cases which is primarily attributed to the emergence of several omicron variants, although there is substantial population vaccination coverage across the globe. Currently, many therapeutic antibodies have been approved for emergency usage. The present study critically evaluates the effect of mutations observed in several omicron variants on the binding affinities of different classes of RBD-specific antibodies using a combined approach of immunoinformatics and binding free energy calculations. Our binding affinity data clearly show that omicron variants achieve antibody escape abilities by incorporating mutations at the immunogenic hotspot residues for each specific class of antibody. K417N and Y505H point mutations are primarily accountable for the loss of class I antibody binding affinities. The K417N/Q493R/Q498R/Y505H combined mutant significantly reduces binding affinities for all the class I antibodies. E484A single mutation, on the other hand, drastically reduces binding affinities for most of the class II antibodies. E484A and E484A/Q493R double mutations cause a 33-38% reduction in binding affinity for the approved therapeutic monoclonal antibodies, Bamlanivimab (LY-CoV555). The Q498R RBD mutation observed across all the omicron variants can reduce ~12% binding affinity for REGN10987, a class III therapeutic antibody, and the L452R/Q498R double mutation causes a ~6% decrease in binding affinities for another class III therapeutic antibody, LY-CoV1404. Our data suggest that achieving the immune evasion abilities appears to be the selection pressure behind the emergence of omicron variants.
The chromosome-scale genome assembly of the yellowtail clownfishAmphiprion clarkiiprovides insights into melanic pigmentation of anemonefish
Authors: Moore Billy , Herrera Marcela , Gairin Emma , Li Chengze , Miura Saori , Jolly Jeffrey , Mercader Manon , Izumiyama Michael , Kawai Erina , Ravasi Timothy , Laudet Vincent , Ryu Taewoo 
Published: July 2022

ABSTRACTAnemonefish are an emerging group of model organisms for studying genetic, ecological, evolutionary, and developmental traits of coral reef fish. The yellowtail clownfishAmphiprion clarkiipossesses species-specific characteristics such as inter-species co-habitation, high intra-species color variation, no anemone specificity, and a broad geographic distribution, that can increase our understanding of anemonefish evolutionary history, behavioral strategies, fish-anemone symbiosis, and color pattern evolution. Despite its position as an emerging model species, the genome ofA. clarkiiis yet to be published. Using PacBio long-read sequencing and Hi-C chromatin capture technology, we generated a high-quality chromosome-scale genome assembly initially comprised of 1,840 contigs with an N50 of 1,203,211 bp. These contigs were successfully anchored into 24 chromosomes of 843,582,782 bp and annotated with 25,050 protein-coding genes encompassing 97.0 % of conserved actinopterygian genes, making the quality and completeness of this genome the highest amongst all published anemonefish genomes to date. Transcriptomic analysis identified tissue-specific gene expression patterns, with the brain and optic lobe having the largest number of expressed genes. Further analyses revealed higher copy numbers oferbb3b(a gene involved in melanophore development) inA. clarkiicompared to other anemonefish, thus suggesting a possible link betweenerbb3band the natural melanism polymorphism observed inA. clarkii. The publication of this high-quality genome, along withA. clarkii’s many unique traits, position this species as an ideal model organism for addressing scientific questions across a range of disciplines.
Flexible selection of task-relevant features through population gating
Authors: Barbosa Joao , Proville Remi , Rodgers Chris C. , DeWeese Michael R. , Ostojic Srdjan , Boubenec Yves 
Published: July 2022

AbstractBrains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we propose that population gating, occurring within A1 but controlled by top-down inputs from mPFC, can support across-area stimulus selection. Examining single-unit activity recorded while rats performed an auditory context-dependent task, we found that A1 encoded relevant and irrelevant stimuli along a common dimension of its neural space. Yet, the relevant stimulus encoding was enhanced along an extra dimension. In turn, mPFC encoded only the stimulus relevant to the ongoing context. To identify candidate mechanisms for stimulus selection within A1, we reverse-engineered low-rank RNNs trained on a similar task. Our analyses predicted that two context-modulated neural populations gated their preferred stimulus in opposite contexts, which we confirmed in further analyses of A1. Finally, we show in a two-region RNN how population gating within A1 could be controlled by top-down inputs from PFC, enabling flexible across-area communication despite fixed inter-areal connectivity.
Molecular insight into the enzymatic macrocyclization of multiply backbone N-methylated peptides
Authors: Matabaro Emmanuel , Song Haigang , Sonderegger Lukas , Gherlone Fabio , Giltrap Andrew , Liver Sam , Gossert Alvar , Künzler Markus , Naismith James H 
Published: July 2022

AbstractThe enzyme OphP is essential for the biosynthesis of the macrocyclic peptide omphalotin A, a dodecamer with 9 backbone N-methylations produced by the wood-degrading fungusOmphalotus olearius. Heterologous expression of OphP and the peptide-precursor protein OphMA in yeast, yields omphalotin A. Thus, Oph P was hypothesized to have a dual function; catalyzing both endoproteolytic release of a peptide intermediate from OphMA, and macrocyclization of the multiply α-N-methylated core peptide with concomitant release of a C-terminal follower peptide. In ourin vitroactivity assays, OphP showed robust endoproteolytic and macrocyclase activity on α-N-methylated peptides but was unable to cleave OphMA. The enzyme had a strong preference for hydrophobic, highly α-N-methylated peptides and an α-N-methylated glycine residue at the P1 site. OphP adopts a canonical prolyl oligopeptidase (POP) fold with a predominantly hydrophobic substrate binding cleft, and a small and hydrophobic P1 binding pocket. We demonstrate that OphP is a POP-type macrocyclase with a specificity and a substrate route to the active site different from other members of the family. These results could be exploited for the biotechnological production of macrocyclic peptides with multiple backbone N-methylations, which are interesting due to their favorable pharmacological properties.
Metabolic activity organizes olfactory representations
Authors: Qian Wesley W. , Wei Jennifer N. , Sanchez-Lengeling Benjamin , Lee Brian K. , Luo Yunan , Vlot Marnix , Dechering Koen , Peng Jian , Gerkin Richard C. , Wiltschko Alexander B. 
Published: July 2022

AbstractHearing and vision sensory systems are tuned to the natural statistics of acoustic and electromagnetic energy on earth, and are evolved to be sensitive in ethologically relevant ranges. But what are the natural statistics ofodors, and how do olfactory systems exploit them? Dissecting an accurate machine learning model1for human odor perception, we find a computable representation for odor at the molecular level that can predict the odor-evoked receptor, neural, and behavioral responses of nearly all terrestrial organisms studied in olfactory neuroscience. Using this olfactory representation (PrincipalOdorMap, POM), we find that odorous compounds with similar POM representations are more likely to co-occur within a substance and be metabolically closely related; metabolic reaction sequences2also follow smooth paths in POM despite large jumps in molecular structure. Just as the brain’s visual representations have evolved around the natural statistics of light and shapes, the natural statistics of metabolism appear to shape the brain’s representation of the olfactory world.
Discovering non-additive heritability using additive GWAS summary statistics
Authors: Smith Samuel Pattillo , Darnell Gregory , Udwin Dana , Stamp Julian , Harpak Arbel , Ramachandran Sohini , Crawford Lorin 
Published: July 2022

AbstractLD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the originalLDSCframework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of acis-interaction score (i.e., interactions between a focal variant and proximal variants) recovers genetic variance that is not captured byLDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan,i-LDSCdetects additional variation contributed by genetic interactions. Thei-LDSCsoftware and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.
AutoPhy: Automated phylogenetic identification of novel protein subfamilies
Authors: Ortiz-Velez Adrian , Sukumaran Jeet , Kelley Scott T. 
Published: July 2022

AbstractPhylogenetic analysis of protein sequences provides a powerful means of identifying novel protein functions and subfamilies, and for identifying and resolving annotation errors. However, automation of functional clustering based on phylogenetic trees has been challenging, and most of it is done manually. Clustering phylogenetic trees usually requires the delineation of tree-based thresholds (e.g., distances), leading to an ad hoc problem. We propose a new phylogenetic clustering approach that identifies clusters without using ad hoc distances or other pre-defined values. Our workflow combines uniform manifold approximation and projection (UMAP) with Gaussian mixture models as a k-means like procedure to automatically group sequences into clusters. We then apply a “second pass” clade identification algorithm to resolve non-monophyletic groups. We tested our approach with several well-curated protein families (outer membrane porins, acyltransferase, and dehydrogenases) and showed our automated methods recapitulated known subfamilies. We also applied our methods to a broad range of different protein families from multiple databases, including Pfam, PANTHER, and UNIPROT. Our results showed that AutoPhy rapidly generated monophyletic clusters (subfamilies) within phylogenetic trees evolving at very different rates both within and among phylogenies. The phylogenetic clusters generated by AutoPhy resolved misannotations, determined new protein functional groups, and detected novel viral strains.
A quaternion model for single cell transcriptomics
Authors: Frost H. Robert 
Published: July 2022

AbstractWe present an approach for modeling single cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST) data using quaternions. Quaternions are four dimensional hypercomplex numbers that, along with real numbers, complex numbers and octonions, represent one of the four normed division algebras. Quaternions have been primarily employed to represent three-dimensional rotations in computer graphics with most biomedical applications focused on problems involving the structure and orientation of biomolecules, e.g., protein folding, chromatin conformation, etc. In this paper, we detail an approach for mapping the cells/locations in a scRNA-seq/ST data set to quaternions. According to this model, the quaternion associated with each cell/location represents a vector in ℝ3with vector length capturing sequencing depth and vector direction capturing the relative expression profile. Assuming that biologically interesting features of an scRNA-seq/ST data set are preserved within a rank three reconstruction of the unnormalized counts, this representation has several benefits for data analysis. First, it supports a novel approach for scRNA-seq/ST data visualization that captures cell state uncertainty. Second, the model implies that transformations between cell states can be viewed as three-dimensional rotations, which have a corresponding representation as rotation quaternions. The fact that these rotation quaternions can be interpreted as cells enables a novel approach for characterizing cell state transitions with specific relevance to the analysis of pseudo-temporal ordering trajectories. Most importantly, a quaternion representation supports the genome-wide spectral analysis of scRNA-seq/ST data relative to a single variable, e.g., pseudo-time, or two variables, e.g., spatial coordinates, using a one or two-dimensional hypercomplex discrete Fourier transform. An R package supporting this model and the hypercomplex Fourier analysis of ST data along with several example vignettes is available athttps://hrfrost.host.dartmouth.edu/QSC.
Learning from pre-pandemic data to forecast viral escape
Authors: Thadani Nicole N. , Gurev Sarah , Notin Pascal , Youssef Noor , Rollins Nathan J. , Sander Chris , Gal Yarin , Marks Debora S. 
Published: July 2022

SummaryEffective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses in order to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic – experimental approaches require host polyclonal antibodies to test against and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern. To address this, we developed EVEscape, a generalizable, modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans, or 3D structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available prior to 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including Influenza, HIV, and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually updated escape scores for all current strains of SARS-CoV-2 and predict likely additional mutations to forecast emerging strains as a tool for ongoing vaccine development (evescape.org).
linc-mipep and linc-wrb encode micropeptides that regulate chromatin accessibility in vertebrate-specific neural cells
Authors: Tornini Valerie A. , Lee Ho-Joon , Miao Liyun , Tang Yin , Dube Sarah E. , Gerson Timothy , Schmidt Valeria J. , Du Katherine , Kuchroo Manik , Kroll François , Vejnar Charles E. , Bazzini Ariel A. , Krishnaswamy Smita , Rihel Jason , Giraldez Antonio J. 
Published: July 2022

AbstractThousands of long intergenic non-coding RNAs (lincRNAs) are transcribed throughout the vertebrate genome. A subset of lincRNAs enriched in developing brains has recently been found to contain cryptic open reading frames and are speculated to encode micropeptides. However, systematic identification and functional assessment of these transcripts have been hindered by technical challenges caused by their small size. Here we show that two putative lincRNAs (linc-mipep and linc-wrb) encode micropeptides with homology to the vertebrate-specific chromatin architectural protein, Hmgn1, and demonstrate that they are required for development of vertebrate-specific brain cell types. Specifically, we show that NMDA receptor-mediated pathways are dysregulated in zebrafish lacking these micropeptides and that their loss preferentially alters the gene regulatory networks that establish cerebellar cells and oligodendrocytes – evolutionarily newer cell types that develop postnatally in humans. These findings highlight the power of screening for unexplored micropeptide functions by revealing a key missing link in the evolution of vertebrate brain cell development and illustrating a genetic basis for how some neural cell types are more susceptible to chromatin disruptions, with implications for neurodevelopmental disorders and disease.
Communication under sharply degraded auditory input and the “2-sentence” problem
Authors: Svirsky Mario A , Neukam Jonathan D , Capach Nicole H , Amichetti Nicole M , Lavender Annette , Wingfield Arthur 
Published: July 2022

ABSTRACTIntroductionMany cochlear implant (CI) users who do quite well in standard clinical tests of speech perception report that a great amount of effort is required when listening in real-world situations. We hypothesize that the combined constraints of the sharply degraded signal provided by a CI and finite cognitive resources may lead to a “tipping point” when listeners are confronted with speech material that is more complex than the single words or single sentences that are used in clinical tests. Beyond this tipping point, communication may become too difficult, even for CI users whose standard speech intelligibility scores are above average.MethodsHere, we investigate whether speech identification performance and processing effort (indexed by pupil dilation measures) are affected when CI users or normal hearing control subjects are asked to repeat two sentences presented sequentially instead of just one sentence.ResultsResponse accuracy was minimally affected in normal hearing listeners, but CI users showed a wide range of outcomes, from no change to decrements of up to 45 percentage points. The amount of decrement was not predictable from the CI users’ performance in standard clinical tests. Pupillometry measures tracked closely with effort in both the CI group and the normal hearing group, even though the latter had speech perception scores near ceiling levels for all conditions.DiscussionA communicative tipping point may be reached in many (but not all) CI users in response to input that is only minimally more challenging than standard clinical tests; specifically, when two sentences are presented sequentially before requesting a response, instead of presenting just a single sentence at a time. This potential “2-Sentence Problem” represents one of the simplest possible scenarios that go beyond presentation of a single word or sentence, and it raises the possibility that even good performers in clinical tests of speech perception may be brought beyond the tipping point by other ecologically relevant manipulations. The present findings also raise the possibility that a clinical version of a 2-sentence test may provide actionable information for counseling and rehabilitating CI users.