bluuebunny/crossref_metadata_2025 huggingface dataset:
Accounting for digestion enzyme bias in Casanovo
Authors: Melendez Carlo , Sanders Justin , Yilmaz Melih , Bittremieux Wout , Fondrie Will , Oh Sewoong , Noble William Stafford
Published: May 2024

A key parameter of any proteomics mass spectrometry experiment is the identity of the enzyme that is used to digest proteins in the sample into peptides. The Casanovode novosequencing model was trained using data that was generated with trypsin digestion; consequently, the model prefers to predict peptides that end with the amino acids “K” or “R.” This bias is desirable when the Casanovo is used to analyze data that was also generated using trypsin but can be problematic if the data was generated using some other digestion enzyme. In this work, we modify Casanovo to take as input the identify of the digestion enzyme, alongside each observed spectrum. We then train Casanovo with data generated using several different restriction enzymes, and we demonstrate that the resulting model successfully learns to capture enzyme-specific behavior. However, we find, surprisingly, that this new model does not yield a significant improvement in sequencing accuracy relative to a model trained without the enzyme information but using the same training set. This observation may have important implications for future attempts to make use of experimental metadata inde novosequencing models.
Enhanced Thompson Sampling by Roulette Wheel Selection for Screening Ultra-Large Combinatorial Libraries
Authors: Zhao Hongtao , Nittinger Eva , Tyrchan Christian
Published: May 2024

Chemical space exploration has gained significant interest with the increase in available building blocks, which enables the creation of ultra-large virtual libraries containing billions or even trillions of compounds. However, the challenge of selecting most suitable compounds for synthesis arises, and one such challenge is hit expansion. Recently, Thompson sampling, a probabilistic search approach, has been proposed by Walterset al. to achieve efficiency gains by operating in the reagent space rather than the product space. Here, we aim to address some of its shortcomings and propose optimizations. We introduce a warmup routine to ensure that initial probabilities are set for all reagents with a minimum number of molecules evaluated. Additionally, a roulette wheel selection is proposed with adapted stop criteria to improve sampling efficiency, and belief distributions of reagents are only updated when they appear in new molecules. We demonstrate that a 100% recovery rate can be achieved by sampling 0.1% of the fully enumerated library, showcasing the effectiveness of our proposed optimizations.
Gastrointestinal germinal center B cell depletion and reduction in IgA+plasma cells in HIV-1 infection
Authors: Cossarini Francesca , Shang Joan , Krek Azra , Al-Taie Zainab , Hou Ruixue , Canales-Herrerias Pablo , Tokuyama Minami , Tankelevich Michael , Tillowiz Adam , Jha Divya , Livanos Alexandra E. , Leyre Louise , Uzzan Mathieu , Martinez-Delgado Gustavo , Taylor Matthew D. , Sharma Keshav , Bourgonje Arno R , Cruz Michael , Ioannou Giorgio , Dawson Travis , D’Souza Darwin , Kim-Schulze Seunghee , Akm Ahmed , Aberg Judith A. , Chen Benjamin K. , Kwon Douglas S. , Gnjatic Sacha , Polydorides Alexandros D. , Cerutti Andrea , Argmann Carmen , Vujkovic-Cvijin Ivan , Suarez-Fariñas Mayte , Petralia Francesca , Faith Jeremiah J. , Mehandru Saurabh
Published: May 2024

Gastrointestinal (GI) B cells and plasma cells (PCs) are critical to mucosal homeostasis and the host response to HIV-1 infection. Here, high resolution mapping of human B cells and PCs sampled from the colon and ileum during both viremic and suppressed HIV-1 infection identified a reduction in germinal center (GC) B cells and follicular dendritic cells (FDCs) during HIV-1 viremia. IgA+PCs are the major cellular output of intestinal GCs and were significantly reduced during viremic HIV-1 infection. PC-associated transcriptional perturbations, including type I interferon signaling, persisted in antiretroviral therapy (ART)-treated individuals, suggesting ongoing disruption of the intestinal immune milieu during ART. GI humoral immune perturbations were associated with changes in the intestinal microbiome composition and systemic inflammation. These findings highlight a key immune defect in the GI mucosa due to HIV-1 viremia.

One Sentence Summary

Intestinal germinal center B cell reduction in HIV-1 infection linked to reduced IgA+plasma cells and systemic inflammation.
Long somatic DNA-repeat expansion drives neurodegeneration in Huntington disease
Authors: Handsaker Robert E. , Kashin Seva , Reed Nora M. , Tan Steven , Lee Won-Seok , McDonald Tara M. , Morris Kiely , Kamitaki Nolan , Mullally Christopher D. , Morakabati Neda , Goldman Melissa , Lind Gabriel , Kohli Rhea , Lawton Elisabeth , Hogan Marina , Ichihara Kiku , Berretta Sabina , McCarroll Steven A.
Published: May 2024

Huntington Disease (HD) is a fatal genetic disease in which most striatal projection neurons (SPNs) degenerate. The central biological question about HD pathogenesis has been how the disease-causing DNA repeat expansion (CAGn) in thehuntingtin(HTT) gene leads to neurodegeneration after decades of apparent latency. InheritedHTTalleles with a longer CAG repeat hasten disease onset; the length of this repeat also changes over time, generating somatic mosaicism, and genes that regulate DNA-repeat stability can influence HD age-at-onset. To understand the relationship between a cell’s CAG-repeat length and its biological state, we developed a single-cell method for measuring CAG-repeat length together with genome-wide RNA expression. We found that theHTTCAG repeat expands from 40-45 CAGs to 100-500+ CAGs in HD-vulnerable SPNs but not in other striatal cell types, with these long DNA-repeat expansions acquired at different times by individual SPNs. Surprisingly, somatic expansion from 40 to 150 CAGs had no apparent effect upon gene expression – but neurons with 150-500+ CAGs shared profound gene-expression changes. These expression changes involved hundreds of genes, escalated alongside further CAG-repeat expansion, eroded positive and then negative features of neuronal identity, and culminated in expression of senescence/apoptosis genes. Rates of striatal neuron loss across HD stages reflected the rates at which neurons entered this biologically distorted state. Our results suggest thatHTTCAG repeats in striatal neurons undergo decades of biologically quiet expansion, then, as they asynchronously cross a high threshold, cause SPNs to degenerate quickly and asynchronously. We conclude that, at any moment in the course of HD, most neurons have an innocuous (but unstable)huntingtingene, and that HD pathogenesis is a DNA process for almost all of a neuron’s life.
Accelerating Genome- and Phenome-Wide Association Studies using GPUs – A case study using data from the Million Veteran Program
Authors: Rodriguez Alex , Kim Youngdae , Nandi Tarak Nath , Keat Karl , Kumar Rachit , Bhukar Rohan , Conery Mitchell , Liu Molei , Hessington John , Maheshwari Ketan , Schmidt Drew ,   VA Million Veteran Program, Begoli Edmon , Tourassi Georgia , Muralidhar Sumitra , Natarajan Pradeep , Voight Benjamin F , Cho Kelly , Gaziano J Michael , Damrauer Scott M , Liao Katherine P , Zhou Wei , Huffman Jennifer E , Verma Anurag , Madduri Ravi K
Published: May 2024

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.
Spatial cell graph analysis reveals skin tissue organization characteristic for cutaneous T cell lymphoma
Authors: Sarkar Suryadipto , Möller Anna , Hartebrodt Anne , Erdmann Michael , Ostalecki Christian , Baur Andreas , Blumenthal David B.
Published: May 2024

Cutaneous T cell lymphomas (CTCLs) are non-Hodgkin lymphomas caused by malignant T cells which migrate to the skin. The cancerous T cells lead to rash-like lesions which can be difficult to distinguish from inflammatory skin conditions like atopic dermatitis (AD) and psoriasis (PSO). To characterize CTCL in comparison to these differential diagnoses, we carried out multi-antigen imaging on 69 skin tissue samples (21 CTCL, 23 AD, 25 PSO). The resulting spatially resolved protein abundance maps were then analyzed via scoring functions to quantify heterogeneity of the individual cells’ neighborhoods within spatial graphs inferred from the cells’ positions in the tissue samples (available as a Python package athttps://github.com/bionetslab/SHouT). Our analyses reveal several characteristic patterns of skin tissue organization in CTCL, including a combination of increased local entropy and egophily as characteristic properties of spatial T cell neighborhoods in CTCL as compared to AD and PSO. These results could not only pave the way for high-precision diagnosis of CTCL, but may also facilitate further insights into cellular disease mechanisms.
Evaluating genomic offset predictions in a forest tree with high population genetic structure
Authors: Archambeau Juliette , Benito-Garzón Marta , de-Miguel Marina , Changenet Alexandre , Bagnoli Francesca , Barraquand Frédéric , Marchi Maurizio , Vendramin Giovanni G. , Cavers Stephen , Perry Annika , González-Martínez Santiago C.
Published: May 2024

Predicting how tree populations will respond to climate change is an urgent societal concern. An increasingly popular way to make such predictions is the genomic offset (GO) approach, which aims to use genomic and climate data to identify populations that may experience climate maladaptation in the near future. More precisely, GO tries to represent the change in allele frequencies required to maintain the current gene-climate relationships under climate change. However, the GO approach has major limitations and, despite promising validation of its predictions using height data from common gardens, it still lacks broad empirical testing. In the present study, we evaluated the consistency and empirical validity of GO predictions in maritime pine (Pinus pinasterAit.), a tree species from southwestern Europe and North Africa with a marked population genetic structure. First, gene-climate relationships were estimated using 9,817 SNPs genotyped in 454 trees from 34 populations; and candidate SNPs potentially involved in climate adaptation were identified. Second, GO was predicted using four methods, namely Gradient Forest (GF), Redundancy Analysis (RDA), latent factor mixed model (LFMM) and Generalised Dissimilarity Modeling (GDM), two sets of SNPs (candidate and control SNPs) and five climate general circulation models (GCMs) to account for uncertainty in future climate predictions. Last, the empirical validity of GO predictions was evaluated within a Bayesian framework by estimating the associations between GO predictions and two independent data sources: mortality data from National Forest Inventories (NFI), and mortality and height data from five common gardens in contrasting environments. We found high variability in GO predictions across methods, SNP sets and GCMs. Regarding validation, GO predictions with GDM and GF (and to a lesser extent RDA) based on the candidate SNPs showed the strongest and most consistent associations with mortality rates in common gardens and NFI plots. We found almost no association between GO predictions and tree height in common gardens, most likely due to the overwhelming effect of population genetic structure on tree height in this species. Our study demonstrates the imperative to validate GO predictions with a range of independent data sources before they can be used as informative and reliable metrics in conservation or management strategies.
No effect of additional education on long-term brain structure – a preregistered natural experiment in thousands of individuals
Authors: Judd Nicholas , Kievit Rogier
Published: May 2024

Education is related to a wide variety of beneficial health, behavioral, and societal outcomes. However, whether education causes long-term structural changes in the brain remains unclear. A pressing challenge is that individuals self-select into continued education, thereby introducing a wide variety of environmental and genetic confounders. Fortunately, natural experiments allow us to isolate the causal impact of increased education from individual (and societal) characteristics. Here, we exploit a policy change in the UK (the 1972 ROSLA act) that increased the amount of mandatory schooling from 15 to 16 years of age to study the impact of education on long-term structural brain outcomes in the UK Biobank. Using regression discontinuity – a causal inference method – we find no evidence of an effect from an additional year of education on any structural neuroimaging outcomes. This null result is robust across modalities, regions, and analysis strategies. An additional year of education is a substantial cognitive intervention, yet we find no evidence for sustained experience-dependent plasticity. Our results provide a challenge for prominent accounts of cognitive or ‘brain reserve’ theories which identify education as a major protective factor to lessen adverse aging effects. Our preregistered findings are one of the first implementations of regression discontinuity on neural data – opening the door for causal inference in population-based neuroimaging.
The CALERIE™ Genomic Data Resource
Authors: Ryan Calen Patrick , Corcoran David L , Banskota Nirad , Eckstein Indik Claire , Floratos Aristidis , Friedman Richard A , Kobor Michael S , Kraus Virginia Byers , Kraus William , MacIsaac Julie L , Orenduff Melissa C , Pieper Carl F , White James P , Ferrucci Luigi , Horvath Steve , Huffman Kim M , Belsky Daniel W
Published: May 2024

Caloric restriction (CR) slows biological aging and prolongs healthy lifespan in model organisms. Findings from CALERIE-2™ – the first ever randomized, controlled trial of long-term CR in healthy, non-obese humans – broadly supports a similar pattern of effects in humans. To expand our understanding of the molecular pathways and biological processes underpinning CR effects in humans, we generated a series of genomic datasets from stored biospecimens collected from n=218 participants during the trial. These data constitute the first publicly-accessible genomic data resource for a randomized controlled trial of an intervention targeting the biology of aging. Datasets include whole-genome SNP genotypes, and three-timepoint-longitudinal DNA methylation, mRNA, and small RNA datasets generated from blood, skeletal muscle, and adipose tissue samples (total sample n=2327). The CALERIE Genomic Data Resource described in this article is available from the Aging Research Biobank. This multi-tissue, multi-omic, longitudinal data resource has great potential to advance translational geroscience.
Novel phylogenomic inference and ‘Out of Asia’ biogeography of cobras, coral snakes, and their allies
Authors: Weinell Jeffrey L. , Burbrink Frank T. , Das Sunandan , Brown Rafe M.
Published: May 2024

Estimation of evolutionary relationships among lineages that rapidly diversified can be challenging, and, in such instances, inaccurate or unresolved phylogenetic estimates can lead to erroneous conclusions regarding historical geographical ranges of lineages. One example underscoring this issue has been the historical challenge posed by untangling the biogeographic origin of elapoid snakes, which includes numerous dangerously venomous species as well as species not known to be dangerous to humans. The worldwide distribution of this lineage makes it an ideal group for testing hypotheses related to historical faunal exchanges among the many continents and other landmasses occupied by contemporary elapoid species. We developed a novel suite of genomic resources, included worldwide sampling, and inferred a robust estimate of evolutionary relationships, which we leveraged to quantitatively estimate geographical range evolution through the deep-time history of this remarkable radiation. Our phylogenetic and biogeographical estimates of historical ranges definitively reject a lingering former ‘Out of Africa’ hypothesis and support an ‘Out of Asia’ scenario involving multiple faunal exchanges between Asia, Africa, Australasia, the Americas, and Europe.
scDecorr - Feature decorrelation representation learning with domain adaptation enables self-supervised alignment of multiple single-cell experiments
Authors: Sanyal Ritabrata , Xu Yang , Kim Hyojin , Kramann Rafael , Hayat Sikander
Published: May 2024

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in complex biological systems. However, analyzing and integrating scRNA-seq data poses unique computational challenges due to sparsity, high variability, and technical batch effects. Here, we propose a novel framework called scDecorr for robust representation learning and data integration for scRNA-seq analysis. Our approach leverages the idea of feature decorrelation-based self-supervised learning (SSL) to obtain efficient low-dimensional representations of individual cells without relying on negative samples. By maximizing similarity among distorted embeddings while decorrelating their components, scDecorr captures the biological signature while eliminating technical noise. Furthermore, scDecorr incorporates unsupervised domain adaptation to bridge the gap between batches with different probability distributions, enabling effective integration of scRNA-seq data from diverse sources. Our framework achieves domain-invariant representations by learning cell embeddings independently across domains and employing domain-specific batch normalization. We evaluate scDecorr on a variety of single cell datasets and demonstrate its ability to integrate batches without losing the inherent biological variance, thereby facilitating optimal clustering. The representations generated by scDecorr also exhibit robustness in label transfer tasks, allowing for effective transfer of cell-type labels from reference to query datasets. Overall, scDecorr offers a powerful tool for efficient analysis and integration of large and complex scRNA-seq datasets, advancing our understanding of cellular processes and disease mechanisms. The code is available here \nolinkurl{https://github.com/hayatlab/scdecorr}.
Carbonyl Reductase 1: a novel regulator of blood pressure in Down Syndrome
Authors: Malbon Alexandra J , Czopek Alicja , Beekman Andrew M , Goddard Zoë R , Boyle Aileen , Ivy Jessica R , Stewart Kevin , Denham Scott , Simpson Joanna P , Homer Natalie Z , Walker Brian R , Dhaun Neeraj , Bailey Matthew A , Morgan Ruth A
Published: May 2024

Background

Approximately one in every 800 children is born with the severe aneuploid condition of Down Syndrome (DS), a trisomy of chromosome 21. Low blood pressure (hypotension) is a common condition associated with DS and can have a significant impact on exercise tolerance and quality of life. Little is known about the factors driving this hypotensive phenotype and therefore therapeutic interventions are limited. Carbonyl reductase 1 (CBR1) is an enzyme contributing to the metabolism of prostaglandins, glucocorticoids, reactive oxygen species and neurotransmitters, encoded by a gene (CBR1) positioned on chromosome 21 with potential to impact blood pressure.

Methods

Utilising genetically modified mice and telemetric blood pressure measurement, we tested the hypothesis that CBR1 influences blood pressure and that its overexpression contributes to hypotension in DS.

Results

In a mouse model of DS (Ts65Dn), which exhibit hypotension, CBR1 activity was increased and pharmacological inhibition of CBR1 increased blood pressure. Mice heterozygous null forCbr1had reduced CBR1 enzyme activity and elevated blood pressure. Further experiments indicate that the underlying mechanisms include alterations in sympathetic tone and prostaglandin metabolism.

Conclusions

We conclude that CBR1 activity contributes to blood pressure homeostasis and inhibition of CBR1 may present a novel therapeutic opportunity to correct symptomatic hypotension in DS.
The Ca2+-activated Cl-channel TMEM16B shapes the response time course of olfactory sensory neurons
Authors: Reisert Johannes , Pifferi Simone , Guarneri Giorgia , Ricci Chiara , Menini Anna , Dibattista Michele
Published: May 2024

Mammalian olfactory sensory neurons (OSNs) generate an odorant-induced response by sequentially activating two ion channels, which are in their ciliary membranes. First, a cationic, Ca2+-permeable cyclic nucleotide-gated channel is opened following odorant stimulation via a G protein-coupled transduction cascade and an ensuing raise in cAMP. Second, the increase in ciliary Ca2+opens the excitatory Ca2+-activated Cl-channel TMEM16B that carries most of the odorant-induced receptor current. While the role of TMEM16B in amplifying the response has been well established, it is less understood how this secondary ion channel contributes to response kinetics and action potential generation during single as well as repeated stimulation and, on the other hand, which response properties the CNG channel determines. We first demonstrate that basic membrane properties such as input resistance, resting potential and voltage-gated currents remained unchanged in OSNs that lack TMEM16B. The CNG channel predominantly determines the response delay and adaptation during odorant exposure, while the absence of the Cl-channels shortens both the time the response requires to reach its maximum as well as to terminate after odorant stimulation. This faster response termination inTmem16bknockout OSNs allows them, somewhat counterintuitively, to fire action potentials more reliably when stimulated repeatedly in rapid succession, a phenomenon that occurs both in isolated OSNs as well as in OSNs within epithelial slices. Thus, while the two olfactory ion channels act in concert to generate the overall response, each one controls specific aspects of the odorant-induced response.
Newton’s Cradle: Cell Cycle Regulation by Two Mutually Inhibitory Oscillators
Authors: Dragoi Calin-Mihai , Tyson John J. , Novák Béla
Published: May 2024

The cell division cycle is a fundamental physiological process displaying a great degree of plasticity during the course of multicellular development. This plasticity is evident in the transition from rapid and stringently-timed divisions of the early embryo to subsequent size-controlled mitotic cycles. Later in development, cells may pause and restart cell proliferation in response to myriads of internal or external signals, or permanently exit the cell cycle following terminal differentiation or senescence. Beyond this, cells can undergo modified cell division variants, such as endoreplication, which increases their ploidy, or meiosis, which reduces their ploidy. This wealth of behaviours has led to numerous conceptual analogies intended as frameworks for understanding the proliferative program. Here, we aim to unify these mechanisms under one dynamical paradigm. To this end, we take a control theoretical approach to frame the cell cycle as a pair of arrestable and mutually-inhibiting, doubly amplified, negative feedback oscillators controlling chromosome replication and segregation events, respectively. Under appropriate conditions, this framework can reproduce fixed-period oscillations, checkpoint arrests of variable duration, and endocycles. Subsequently, we use phase plane and bifurcation analysis to explain the dynamical basis of these properties. Then, using a physiologically realistic, biochemical model, we show that the very same regulatory structure underpins the diverse functions of the cell cycle control network. We conclude that Newton’s cradle may be a suitable mechanical analogy of how the cell cycle is regulated.

Declaration of interest

The authors declare no competing or financial interests.
SARS-CoV-2 variants from long-term, persistently infected immunocompromised patients have altered syncytia formation, temperature-dependent replication, and serum neutralizing antibody escape
Authors: Wouters Camille , Sachithanandham Jaiprasath , Akin Elgin , Pieterse Lisa , Fall Amary , Truong Thao T. , Bard Jennifer Dien , Yee Rebecca , Sullivan David J. , Mostafa Heba H. , Pekosz Andrew
Published: May 2024

SARS-CoV-2 infection of immunocompromised individuals often leads to prolonged detection of viral RNA and infectious virus in nasal specimens, presumably due to the lack of induction of an appropriate adaptive immune response. Mutations identified in virus sequences obtained from persistently infected patients bear signatures of immune evasion and have some overlap with sequences present in variants of concern. We characterized virus isolates from two COVID-19 patients undergoing immunosuppressive cancer therapy, with all isolates obtained greater than 100 days after the initial COVID-19 diagnoses and compared to an isolate from the start of the infection. Isolates from an individual who never mounted an antibody response specific to SARS-CoV-2 despite the administration of convalescent plasma showed slight reductions in plaque size and some showed temperature-dependent replication attenuation on human nasal epithelial cell culture compared to the virus that initiated infection. An isolate from another patient - who did mount a SARS-CoV-2 IgM response – showed temperature dependent changes in plaque size as well as increased syncytia formation and escape from serum neutralizing antibody. Our results indicate that not all virus isolates from immunocompromised COVID-19 patients display clear signs of phenotypic change, but increased attention should be paid to monitoring virus evolution in this patient population.
SLUR(M)-py: A SLURM Powered Pythonic Pipeline for Parallel Processing of 3D (Epi)genomic Profiles
Authors: Roth Cullen , Venu Vrinda , Bacot Sasha , Steadman Christina R. , Starkenburg Shawn R.
Published: May 2024

There is increasing demand to quickly process multiple types of sequencing-based data to completely capture epigenetic alterations and associated changes in chromatin structure underlying cellular responses. Furthermore, the need for a set of bioinformatic tools that leverage high performance computing and parallelization for processing omics data from many experiments has become apparent. Here we present SLUR(M)-py: a flexible command line tool (written in Python) that leverages the Simple Linux Utility for Resource Management system (SLURM) to process, align, and analyze sequencing data from three-dimensional and epigenomic assays in a high-performance computing environment. SLUR(M)-py is designed with host-pathogen infection experiments in mind, and contains unique scripts and functions that automate calls to SLURM for processing paired-end sequenced reads from chromatin characterization experiments, including whole-genome, ChIP-seq, ATAC-seq and Hi-C. ATAC-seq and Hi-C data from viral infection experiments as well as data from the ENCODE project are utilized to demonstrate processing speed, which outpace current high-performance computing pipelines. We explore the effect of dropping duplicate sequenced reads in ATAC-seq data and demonstrate how SLUR(M)-py can be used for quality control and to detect artifacts in Hi-C experiments from viral infection experiments. Finally, we utilize SLUR(M)-py to explore the dynamics of inter-chromosomal contacts in mammalian cells exposed to vaccinia virus, the vaccine for smallpox.
Single-cell genotype-phenotype mapping identifies therapeutic vulnerabilities in VEXAS syndrome
Authors: Ganesan Saravanan , Murray Rebecca M. , Sotelo Jesus , Eton Elliot O. , Takashima Kouhei , Botella Theo , Beattie Kai , Indart Alyssa C. , Chraiki Nada , Croizier Carolyne , Izzo Franco , Potenski Catherine , Marro Samuele , Wu Zhijie , Gao Shouguo , Young Neal S. , Blair John D. , Satija Rahul , Terrier Benjamin , Heiblig Mael , Raimondi Ivan , Papapetrou Eirini P , Sujobert Pierre , Kosmider Olivier , Beck David B. , Landau Dan A.
Published: May 2024

Somatic evolution leads to the emergence of clonal diversity across tissues with broad implications for human health. A striking example of somatic evolution is the VEXAS (Vacuoles E1 enzyme X-linked Autoinflammatory Somatic) syndrome, caused by somaticUBA1mutations in hematopoietic stem cells (HSCs), inducing treatment-refractory, systemic inflammation. However, the mechanisms that lead to survival and expansion of mutant HSCs are unknown, limiting the development of effective therapies. The lack of animal or cellular models ofUBA1-mutant HSCs has hindered such mechanistic understanding, mandating analysis of primary human VEXAS samples, which harbor admixtures of wild-type andUBA1-mutant HSCs. To address these challenges, we applied single-cell multi-omics to comprehensively define mutantUBA1-induced transcriptome, chromatin accessibility and signaling pathway alterations in VEXAS patients, allowing for the direct comparison of mutant versus wild-type cells within the same environment. We confirmed the expected enrichment ofUBA1M41V/Tmutations in myeloid cells, and additionally discovered that these mutations were also prevalent in Natural Killer (NK) cells in VEXAS patients, providing new insights into disease phenotypes. Through mapping genotypes to molecular phenotypes, including transcriptome, chromatin accessibility, cell surface protein or intracellular protein profiles, in HSCs, we found thatUBA1M41V/T-mutant cells showed an increased inflammation signature (interferon alpha and gamma response pathways), as well as activation of unfolded protein response (UPR) via pro-survival, but not pro-apoptotic, mediators of the PERK pathway, compared toUBA1wild-type HSCs. Ex vivo validation experiments showed that inhibitingUBA1in normal CD34+ or usingUBA1-mutant HSCs led to PERK pathway up-regulation, increased myeloid differentiation and cell survival, which was reversed by PERK inhibition. Thus, we demonstrated that human VEXAS HSCs show cell-intrinsic inflammatory phenotypes and survive the proteomic stress caused by compromised ubiquitination through PERK-mediated activation of the UPR. Together, these analyses nominate PERK pathway inhibition as a potential new therapeutic strategy for eradicating the VEXAS-inducing clone, demonstrating the power of single-cell multi-omics profiling of primary patient sample to enable genotype-to-phenotype somatic mapping for the discovery of novel candidates for clinical intervention.
Short-term Electrical Stimulation Impacts Cardiac Cell Structure and Function
Authors: Allen Kristen , Bandl Abigail , Pachter Natalie , Hookway Tracy
Published: May 2024

Induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) are used to model cardiac development and disease. This requires a robust population of mature CMs and external stimuli to mimic the complex environment of the heart. In effort toward this maturation, previous groups have applied electrical stimulation (ES) to CMs with varying results depending on the stimulation duration, frequency, and pattern. As such, there is uncertainty surrounding the timeline on which stimulated iPSC-CMs begin to show early signs of maturation in comparison to their non-stimulated counterparts, leaving room for additional research into when hallmarks of maturity–such as hypertrophy and changes to sarcomere structure–develop in CMs. Here, we introduce a low-cost custom bioreactor capable of delivering tunable electrical stimulation to standard 2D cell monolayers. We show that, after exposure to short-term ES, stimulated CMs express early signs of maturation compared to the non-stimulated control. The changes to contractility and protein expression indicate that the cells undergo hypertrophy in response to short-term ES, but they do not develop transverse-tubules, which is a key component of a fully mature CM structure. Therefore, while early signs of maturation are present after a short stimulation regimen, additional cellular structures must develop to reach complete maturation. We have shown that our custom electrical stimulator can be easily integrated with standardin vitrocell culture platforms to obtain measurable changes to cells, exhibiting its potential for promoting crucial CM maturation for cardiac tissue engineering applications.
iResNetDM: interpretable and comprehensive deep learning model for 4 types of DNA modifications prediction
Authors: Yang Zerui , Shao Wei , Matsuda Yudai , Song Linqi
Published: May 2024

Motivation

Despite the development of several computational methods to predict DNA modifications, two main limitations persist in the current methodologies: 1) All existing models are confined to binary predictor which merely determine the presence or absence of DNA modifications, constraining comprehensive analyses of the interrelations among varied modification types. While multi-class classification models for RNA modifications have been developed, a comparable approach for DNA remains a critical need. 2) The majority of previous studies lack adequate explanations of how models make decisions, relying on the extraction and visualization of attention matrices which identified few motifs, and do not provide sufficient insight into the model decision making process.

Result

In this study, we introduce iResNetDM, a deep learning model that integrates ResNet and self-attention mechanisms. To the best of our knowledge, iResNetDM is the first model capable of distinguishing between four types of DNA modifications. It not only demonstrates high performance across various DNA modifications but also unveils the potential capabilities of CNN and ResNet in this domain. To augment the interpretability of our model, we implemented the integrated gradients technique, which was pivotal in demystifying the model’s decision-making framework, allowing for the successful identification of multiple motifs. Importantly, our model exhibits remarkable robustness, successfully identifying unique motifs across different modifications. Furthermore, we compared the motifs discovered in various modifications, revealing that some motifs share significant sequence similarities which suggests that these motifs may be subjected to different types of modifications, underscoring their potential importance in gene regulation.

Contact

zeruiyang2-c@my.cityu.edu.hk
A Data-Intelligence-Intensive Bioinformatics Copilot System for Large-scale Omics Researches and Scientific Insights
Authors: Liu Yang , Shen Rongbo , Zhou Lu , Xiao Qingyu , Yuan Jiao , Li Yixue
Published: May 2024

Advancements in high-throughput sequencing technologies and artificial intelligence offer unprecedented opportunities for groundbreaking discoveries in bioinformatics research. However, the challenges of exponential growth of omics data and the rapid development of artificial intelligence technologies require automated big biological data analysis capability and interdisciplinary knowledge-driven scientific insight. Here we propose a data-intelligence-intensive bioinformatics copilot (Bio-Copilot) system that synergizes AI capabilities with human expertise to facilitate hypothesis-free exploratory research and inspire novel scientific insights in large-scale omics studies. Bio-Copilot forms high-quality intensive intelligence through close collaboration between multiple agents, driven by large language models (LLMs), and human experts. To augment the capabilities of Bio-Copilot, this study devises an agent group management strategy, an effective human-agent interaction mechanism, a shared interdisciplinary knowledge database, and continuous learning strategies for the agents. We comprehensively compare Bio-Copilot against GPT-4o and several leading AI agents across diverse bioinformatics tasks, using a broad range of evaluation metrics. Bio-Copilot achieves the overall state-of-the-art performance across all tasks, while showcases exceptional task completeness. Furthermore, in the application of constructing a large-scale human lung cell atlas, Bio-Copilot not only reproduces the intricate data integration process detailed in a seminal study but also introduces a hierarchical annotation strategy to capture the continuous nature of cellular states and uncovers the characteristics of rare cell types, highlighting its potential to unravel hidden complexities in biological systems. Beyond the technical achievements, this study also underscores the profound implications of integrating AI capabilities with expert knowledge in accelerating impactful biological discoveries and exploring uncharted territories in life sciences.
Production of four-gene (GTKO/hCD55/hTBM/hCD39)-edited donor pigs and kidney xenotransplantation
Authors: Yang Chang , Wei Yunfang , Li Xinglong , Xu Kaixiang , Huo Xiaoying , Chen Gang , Zhao Heng , Wang Jiaoxiang , Wei Taiyun , Qing Yubo , Guo Jianxiong , Zhao Hongfang , Zhang Xiong , Jiao Deling , Xiong Zhe , Jamal Muhammad Ameen , Zhao Hong-Ye , Wei Hong-Jiang
Published: May 2024

Background

The number of multigene-modified donor pigs for xenotransplantation is increasing with the advent of gene editing technologies. However, which gene combination is suitable for which organ transplantation remains unclear.

Methods

In this study, we utilized CRISPR/Cas9 gene editing technology, PiggyBac transposon system and somatic cell cloning to construct GTKO/hCD55/hTBM/hCD39 four-gene-edited cloned (GEC) pigs and performed kidney transplantation from pig to rhesus monkey to evaluate the effectiveness of these GEC pigs.

Results

First, 107 cell colonies were obtained through drug selection, of which 7 were 4-GE colonies. Two colonies were selected for somatic cell nuclear transfer, resulting in 7 fetuses, of which 4 were GGTA1 biallelic knockout. Both fetuses had higher expression of hCD55, hTBM and hCD39. Therefore, these two fetuses were selected for two consecutive rounds of cloning, resulting in a total of 97 live piglets. After phenotype identification, the GGTA1 gene of these pigs was inactivated, and hCD55, hTBM and hCD39 were expressed in cells and multiple tissues. Furthermore, the numbers of monkey IgM and IgG binding to the peripheral blood mononuclear cells (PBMCs) of the 4-GEC pigs were markedly reduced. Moreover, 4-GEC porcine PBMCs had greater survival rates than those from wild-type pigs through complement-mediated cytolysis assays. In pig-to-monkey kidney xenotransplantation, the kidney xenograft successfully survived for 11 days. All physiological and biochemical indicators were normal, and no hyperacute rejection or coagulation abnormalities were found after transplantation.

Conclusion

These results indicate that the GTKO/hCD55/hTBM/hCD39 four-gene modification effectively alleviates immune rejection, and the pig kidney can functionally support the recipient monkey’s life.
Seclidemstat blocks the transcriptional function of multiple FET-fusion oncoproteins
Authors: Rask Galen C. , Taslim Cenny , Bayanjargal Ariunaa , Cannon Matthew V. , Selich-Anderson Julia , Crow Jesse C. , Duncan Aundrietta , Theisen Emily R.
Published: May 2024

Genes encoding the RNA-binding proteinsFUS,EWSR1, andTAF15 (FET proteins) are involved in chromosomal translocations in rare sarcomas. FET-rearranged sarcomas are often aggressive malignancies affecting patients of all ages. New therapies are needed. These translocations fuse the 5’ portion of the FET gene with a 3’ partner gene encoding a transcription factor (TF). The resulting fusion proteins are oncogenic TFs with a FET protein low complexity domain (LCD) and a DNA binding domain. FET fusion proteins have proven stubbornly difficult to target directly and promising strategies target critical co-regulators. One candidate is lysine specific demethylase 1 (LSD1). LSD1 is recruited by multiple FET fusions, including EWSR1::FLI1. LSD1 promotes EWSR1::FLI1 activity and treatment with the noncompetitive inhibitor SP-2509 blocks EWSR1::FLI1 transcriptional function. A similar molecule, seclidemstat (SP-2577), is currently in clinical trials for FET-rearranged sarcomas (NCT03600649). However, whether seclidemstat has pharmacological activity against FET fusions has not been demonstrated. Here, we evaluate thein vitropotency of seclidemstat against multiple FET-rearranged sarcoma cell lines, including Ewing sarcoma, desmoplastic small round cell tumor, clear cell sarcoma, and myxoid liposarcoma. We also define the transcriptomic effects of seclidemstat treatment and evaluated the activity of seclidemstat against FET fusion transcriptional regulation. Seclidemstat showed potent activity in cell viability assays across FET-rearranged sarcomas and disrupted the transcriptional function of all tested fusions. Though epigenetic and targeted inhibitors are unlikely to be effective as a single agents in the clinic, these data suggest seclidemstat remains a promising new treatment strategy for patients with FET-rearranged sarcomas.

SIGNIFICANCE

Here, we show the noncompetitive inhibitor, seclidemstat, hasin vitroactivity against multiple FET fusion proteins that cause a number of rare and aggressive sarcomas. These data represent one of the largest analyses of FET fusion activity across multiple malignancies and are a valuable resource for those studying FET-rearranged sarcomas.
Transfer Elastic Net for Developing Epigenetic Clocks for the Japanese Population
Authors: Tomo Yui , Nakaki Ryo
Published: May 2024

Motivation

The epigenetic clock evaluates human biological age based on DNA methylation patterns. It takes the form of a regression model where the methylation ratio at CpG sites serves as the predictor, and chronological or adjusted age as the response variable. Due to the large number of CpG sites considered as candidate explanatory variables and their potential correlation, Elastic Net is commonly used to train the regression models. However, existing standard epigenetic clocks, trained on multiracial data, may exhibit biases due to genetic and environmental differences among specific racial groups. The development of epigenetic clocks suitable for a single-race population typically necessitates the collection of hundreds to thousands of samples to measure DNA methylation and other biomarkers, which costs a lot of time and money. Consequently, a method for developing accurate epigenetic clocks with relatively small sample sizes is needed.

Results

We propose Transfer Elastic Net, a transfer learning approach that uses the parameter information from a linear regression model trained with the Elastic Net to estimate another model. Using this method, we constructed Horvath’s, Hannum’s, and Levine’s types of epigenetic clocks using DNA methylation data from blood samples of 143 Japanese subjects. The data were transformed through principal component analysis to obtain more reliable clocks. The developed clocks demonstrated the smallest prediction errors compared to both the original clocks and those trained with the Elastic Net on the same Japanese data. Furthermore, the bias relative to the original clocks was reduced. Thus, we successfully developed epigenetic clocks that are well-suited for the Japanese population. Transfer Elastic Net can also be applied to develop epigenetic clocks for other specific populations, and is expected to be applied in various fields.

Availability

https://github.com/t-yui/TransferENet-EpigeneticClock
A nitrogenase-like enzyme is involved in the novel anaerobic assimilation pathway of a sulfonate, isethionate, in the photosynthetic bacteriumRhodobacter capsulatus
Authors: Morimoto Yoshiki , Uesaka Kazuma , Fujita Yuichi , Yamamoto Haruki
Published: May 2024

Prokaryotes contribute to the global sulfur cycle by using diverse sulfur compounds as sulfur sources or electron acceptors. Here we report that a nitrogenase-like enzyme (NFL) and a radical SAM enzyme (RSE) are involved in the novel anaerobic assimilation pathway of a sulfonate, isethionate, in the photosynthetic bacteriumRhodobacter capsulatus. ThenflHDKgenes for NFL are localized at a locus containing genes for known sulfonate metabolism in the genome. A genenflBencoding an RSE is present just upstream ofnflH, forming a small gene clusternflBHDK. Mutants lacking anynflBHDKgenes lost the ability to grow with isethionate as the sole sulfur source under anaerobic photosynthetic conditions, indicating that all four NflBHDK proteins are essential for the isethionate assimilation pathway. Heterologous expression of theislABgenes encoding a known isethionate lyase that degrades isethionate to sulfite and acetaldehyde restored the isethionate-dependent growth of a mutant lackingnflDK, indicating that the enzyme encodingnflBHDKis involved in an isethionate assimilation reaction to release sulfite. Furthermore, heterologous expression ofnflBHDKandssuCABencoding an isethionate transporter in the closely related speciesR. sphaeroides, which does not havenflBHDKand cannot grow with isethionate as the sole sulfur source, conferred isethionate-dependent growth ability to this species. We propose to renamenflBHDKasisrBHDK(isethionate reductase). TheisrBHDKgenes are widely distributed among various prokaryote phyla. Discovery of the isethionate assimilation pathway by IsrBHDK provides a missing piece for the anaerobic sulfur cycle and for understanding the evolution of ancient sulfur metabolism.

Importance

Nitrogenase is an important enzyme found in prokaryotes that reduces atmospheric nitrogen to ammonia and plays a fundamental role in the global nitrogen cycle. It has been noted that nitrogenase-like enzymes (NFLs), which share an evolutionary origin with nitrogenase, have evolved to catalyze diverse reactions such as chlorophyll biosynthesis (photosynthesis), coenzyme F430biosynthesis (methanogenesis), and methionine biosynthesis. In this study, we discovered that an NFL with unknown function in the photosynthetic bacteriumRhodobacter capsulatusis a novel isethionate reductase (Isr), which catalyzes the assimilatory degradation of isethionate, a sulfonate, releasing sulfite used as the sulfur source under anaerobic conditions. Isr is widely distributed among various bacterial phyla, including intestinal bacteria, and is presumed to play an important role in sulfur metabolism in anaerobic environments such as animal guts and microbial mats. This finding provides a clue for understanding ancient metabolism that evolved under anaerobic environments at the dawn of life.