bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanism of delayed cell death following simultaneous CRISPR-Cas9 targeting in pancreatic cancers
Authors: Teh Selina Shiqing K. , Halper-Stromberg Eitan , Morsberger Laura , Bennett Alexis , Bowland Kirsten , Skaist Alyza , Cai Fidel , Liang Hong , Hruban Ralph H. , Roberts Nicholas J. , Scharpf Robert B. , Zou Ying S. , Eshleman James R.
Published: April 2023

When we transduced pancreatic cancers with sgRNAs that targeted 2-16 target sites in the human genome, we found that increasing the number of CRISPR-Cas9 target sites produced greater cytotoxicity, with >99% growth inhibition observed by targeting only 12 sites. However, cell death was delayed by 2-3 weeks after sgRNA transduction, in contrast to the repair of double strand DNA breaks (DSBs) that happened within 3 days after transduction. To explain this discrepancy, we used both cytogenetics and whole genome sequencing to interrogate the genome. We first detected chromatid and chromosome breaks, followed by radial formations, dicentric, ring chromosomes, and other chromosomal aberrations that peaked at 14 days after transduction. Structural variants (SVs) were detected at sites that were directly targeted by CRISPR-Cas9, including SVs generated from two sites that were targeted, but the vast majority of SVs (89.4%) were detected elsewhere in the genome that arose later than those directly targeted. Cells also underwent polyploidization that peaked at day 10 as detected by XY FISH assay, and ultimately died via apoptosis. Overall, we found that the simultaneous DSBs induced by CRISPR-Cas9 in pancreatic cancers caused chromosomal instability and polyploidization that ultimately led to delayed cell death.

Statement of significance

Using whole genome sequencing and conventional cytogenetics, we discovered that CRISPR-Cas9 cuts led to genomic instability, including chromosomal rearrangements and polyploidization, and ultimately to delayed cell death, 2-3 weeks after the induction of CRISPR-Cas9 DSBs.
Synergistic Integration of Deep Neural Networks and Finite Element Method with Applications for Biomechanical Analysis of Human Aorta
Authors: Liang Liang , Liu Minliang , Elefteriades John , Sun Wei
Published: April 2023

Motivation: Patient-specific finite element analysis (FEA) has the potential to aid in the prognosis of cardiovascular diseases by providing accurate stress and deformation analysis in various scenarios. It is known that patient-specific FEA is time-consuming and unsuitable for time-sensitive clinical applications. To mitigate this challenge, machine learning (ML) techniques, including deep neural networks (DNNs), have been developed to construct fast FEA surrogates. However, due to the data-driven nature of these ML models, they may not generalize well on new data, leading to unacceptable errors.

Methods

We propose a synergistic integration of DNNs and finite element method (FEM) to overcome each other’s limitations. We demonstrated this novel integrative strategy in forward and inverse problems. For the forward problem, we developed DNNs using state-of-the-art architectures, and DNN outputs were then refined by FEM to ensure accuracy. For the inverse problem of heterogeneous material parameter identification, our method employs a DNN as regularization for the inverse analysis process to avoid erroneous material parameter distribution.

Results

We tested our methods on biomechanical analysis of the human aorta. For the forward problem, the DNN-only models yielded acceptable stress errors in majority of test cases; yet, for some test cases that could be out of the training distribution (OOD), the peak stress errors were larger than 50%. The DNN-FEM integration eliminated the large errors for these OOD cases. Moreover, the DNN-FEM integration was magnitudes faster than the FEM-only approach. For the inverse problem, the FEM-only inverse method led to errors larger than 50%, and our DNN-FEM integration significantly improved performance on the inverse problem with errors less than 1%.
Asparagine availability controls B cell homeostasis
Authors: Yazicioglu Yavuz F. , Marin Eros , Andrew Hana F. , Bentkowska Karolina , Johnstone Julia C. , Mitchell Robert , Wong Zhi Yi , Zec Kristina , Fergusson Joannah , Borsa Mariana , Raza Iwan G. A. , Attar Moustafa , Ali Mohammad , Kronsteiner Barbara , Furlani Izadora L. , MacRae James I. , Devine Michael J. , Coles Mark , Buckley Christopher D. , Dunachie Susanna J. , Clarke Alexander J.
Published: April 2023

Germinal centre (GC) B cells proliferate at some of the highest rates of any mammalian cell, yet the metabolic processes which enable this are poorly understood. We performed integrated metabolomic and transcriptomic profiling of GC B cells, and found that metabolism of the non-essential amino acid asparagine (Asn) was highly upregulated. Asn was conditionally essential to B cells, and its synthetic enzyme, asparagine synthetase (ASNS) was upregulated following their activation, particularly more markedly in the absence of Asn, through the integrated stress response sensor general control non-derepressible 2 (GCN2). WhenAsnsis deleted B cell survival and proliferation in low Asn conditions were strongly impaired, and removal of environmental Asn by asparaginase or dietary restriction markedly compromised the GC reaction, impairing affinity maturation and the humoral response to influenza infection. Using stable isotope tracing and single cell RNA sequencing, we found that metabolic adaptation to the absence of Asn requires ASNS, and that oxidative phosphorylation, mitochondrial homeostasis, and synthesis of nucleotides was particularly sensitive to Asn deprivation. Altogether, we reveal that Asn metabolism acts as a key regulator of B cell function and GC homeostasis.

The one sentence summary

Asparagine metabolism is a critical regulator of B cell function, maintaining the germinal centre reaction.
Immune Profiling of Dermatologic Adverse Events from Checkpoint Blockade using Tissue Cyclic Immunofluorescence
Authors: Maliga Zoltan , Kim Daniel Y. , Bui Ai-Tram N. , Lin Jia-Ren , Dewan Anna K. , Murphy George F. , Nirmal Ajit J. , Lian Christine G. , Sorger Peter K. , LeBoeuf Nicole R.
Published: April 2023

In this study, we demonstrate the utility of whole-slide CyCIF (tissue-based cyclic immunofluorescence) imaging for characterizing immune cell infiltrates in immune checkpoint inhibitor (ICI)-induced dermatologic adverse events (dAEs). We analyzed six cases of ICI-induced dAEs, including lichenoid, bullous pemphigoid, psoriasis, and eczematous eruptions, comparing immune profiling results obtained using both standard immunohistochemistry (IHC) and CyCIF. Our findings indicate that CyCIF provides more detailed and precise single-cell characterization of immune cell infiltrates than IHC, which relies on semi-quantitative scoring by pathologists. This pilot study highlights the potential of CyCIF to advance our understanding of the immune environment in dAEs by revealing tissue-level spatial patterns of immune cell infiltrates, allowing for more precise phenotypic distinctions and deeper exploration of disease mechanisms. By demonstrating that CyCIF can be performed on friable tissues, such as bullous pemphigoid, we provide a foundation for future studies to examine the drivers of specific dAEs using larger cohorts of phenotyped toxicity and suggest a broader role for highly multiplexed tissue imaging in phenotyping the immune mediated disease that they resemble.
asmbPLS: Adaptive Sparse Multi-block Partial Least Square for Survival Prediction using Multi-Omics Data
Authors: Zhang Runzhi , Datta Susmita
Published: April 2023

Background

As high-throughput studies advance, more and more high-dimensional multi-omics data are available and collected from the same patient cohort. Using multi-omics data as predictors to predict survival outcomes is challenging due to the complex structure of such data.

Results

In this article, we introduce an adaptive sparse multi-block partial least square (asmbPLS) regression method by assigning different penalty factors to different blocks in different PLS components for feature selection and prediction. We compared the proposed method with several competitive algorithms in many aspects including prediction performance, feature selection and computation efficiency. The performance and the efficiency of our method were demonstrated using both the simulated and the real data.

Conclusions

In summary, asmbPLS achieved a competitive performance in prediction, feature selection, and computation efficiency. We anticipate asmbPLS to be a valuable tool for multi-omics research. An R package calledasmbPLSimplementing this method is made publicly available on GitHub.
BNP-Track: A framework for superresolved tracking
Authors: Sgouralis Ioannis , Xu Lance W.Q. , Jalihal Ameya P. , Walter Nils G. , Pressé Steve
Published: April 2023

Assessing dynamic processes at single molecule scales is key toward capturing life at the level of its molecular actors. Widefield superresolution methods, such as STORM, PALM, and PAINT, provide nanoscale localization accuracy, even when distances between fluorescently labeled single molecules (“emitters”) fall below light’s diffraction limit. However, as these superresolution methods rely on rare photophysical events to distinguish emitters from both each other and background, they are largely limited to static samples. In contrast, here we leverage spatiotemporal correlations of dynamic widefield imaging data to extend superresolution to simultaneous multiple emitter tracking without relying on photodynamics even as emitter distances from one another fall below the diffraction limit. We simultaneously determine emitter numbers and their tracks (localization and linking) with the same localization accuracy per frame as widefield superresolution does for immobilized emitters under similar imaging conditions (≈50 nm). We demonstrate our results for bothin cellulodata and, for benchmarking purposes, on synthetic data. To this end, we avoid the existing tracking paradigm relying on completely or partially separating the tasks of emitter number determination, localization of each emitter, and linking emitter positions across frames. Instead, we develop a fully joint posterior distribution over the quantities of interest, including emitter tracks and their total, otherwise unknown, number within the Bayesian nonparametric paradigm. Our posterior quantifies the full uncertainty over emitter numbers and their associated tracks propagated from origins including shot noise and camera artefacts, pixelation, stochastic background, and out-of-focus motion. Finally, it remains accurate in more crowded regimes where alternative tracking tools cannot be applied.
Fluorescence lifetime analysis of smFRET with contribution of PIFE on donor and acceptor
Authors: Jazani Sina , Ha Taekjip
Published: April 2023

Single-molecule fluorescence resonance energy transfer (FRET) is a powerful technique based on dipole-dipole interaction between donor and acceptor fluorophores to observe inter- and intra-molecular dynamics in realtime with sensitivity to macro-molecular distances (∼ 2.5-10 nm). That said, some fluorophores have an inherent characteristic known as protein induced fluorescence enhancement (PIFE). PIFE is a photo-physical feature of dyes undergoing cis-trans transitions and occurs for protein-dye interactions closer than 3 nm. Here, the challenge is uncoupling the PIFE effect in the FRET data. Ignoring the PIFE effect in the analysis of the FRET data may lead to misinterpretation of the system under investigation. As a solution to this problem, we develop a computational framework based on Bayesian statistics to analyze the fluorescence lifetime signals of the donor and acceptor channels which allows us to uncouple the PIFE effects from the FRET. Our framework can extract any changes in the FRET efficiency simultaneously with any changes in the fluorescence lifetimes of the donor and acceptor due to the PIFE effect. In addition, our framework can provide other parameters, such as the donor and acceptor excitation rates, background photon rates, and detectors’ cross-talk ratios. Our framework extracts all these parameters by analyzing a single photon arrival time trace with only a few thousand photons.
Improving deep models of protein-coding potential with a Fourier-transform architecture and machine translation task
Authors: Valencia Joseph D. , Hendrix David A.
Published: April 2023

Ribosomes are information-processing macromolecular machines that integrate complex sequence patterns in messenger RNA (mRNA) transcripts to synthesize proteins. Studies of the sequence features that distinguish mRNAs from long noncoding RNAs (lncRNAs) may yield insight into the information that directs and regulates translation. Computational methods for calculating protein-coding potential are important for distinguishing mRNAs from lncRNAs during genome annotation, but most machine learning methods for this task rely on previously known rules to define features. Sequence-to-sequence (seq2seq) models, particularly ones using transformer networks, have proven capable of learning complex grammatical relationships between words to perform natural language translation. Seeking to leverage these advancements in the biological domain, we present a seq2seq formulation for predicting protein-coding potential with deep neural networks and demonstrate that simultaneously learning translation from RNA to protein improves classification performance relative to a classification-only training objective. Inspired by classical signal processing methods for gene discovery and Fourier-based image-processing neural networks, we introduce LocalFilterNet (LFNet). LFNet is a network architecture with an inductive bias for modeling the three-nucleotide periodicity apparent in coding sequences. We incorporate LFNet within an encoder-decoder framework to test whether the translation task improves the classification of transcripts and the interpretation of their sequence features. We use the resulting model to compute nucleotide-resolution importance scores, revealing sequence patterns that could assist the cellular machinery in distinguishing mRNAs and lncRNAs. Finally, we develop a novel approach for estimating mutation effects from Integrated Gradients, a backpropagation-based feature attribution, and characterize the difficulty of efficient approximations in this setting.
One-carbon metabolism is required for epigenetic stability in the mouse placenta
Authors: Senner Claire E. , Dong Ziqi , Branco Miguel R. , Watson Erica D.
Published: April 2023

One-carbon metabolism, including the folate cycle, has a crucial role in fetal development though its molecular function is complex and unclear. The hypomorphicMtrrgtallele is known to disrupt one-carbon metabolism, and thus methyl group availability, leading to several developmental phenotypes (e.g., neural tube closure defects, fetal growth anomalies). Remarkably, previous studies showed that some of the phenotypes were transgenerationally inherited. Here, we explored the genome-wide epigenetic impact of one-carbon metabolism in placentas associated with fetal growth phenotypes and determined whether specific DNA methylation changes were inherited. Firstly, methylome analysis ofMtrrgt/gthomozygous placentas revealed genome-wide epigenetic instability. Several DMRs were identified including at theCxcl1gene promoter and at theEn2gene locus, which may have phenotypic implications. Importantly, we discovered hypomethylation and ectopic expression of a subset of ERV elements throughout the genome ofMtrrgt/gtplacentas with broad implications for genomic stability. Next, we determined that sperm DMRs in males from theMtrrgtmodel were reprogrammed in the placenta with little evidence of direct or transgenerational germline DMR inheritance. However, some sperm DMRs were associated with placental gene misexpression despite normalisation of DNA methylation, suggesting the inheritance of an alternative epigenetic mechanism. Integration of published histone ChIP-seq datasets with sperm methylome and placenta transcriptome data from theMtrrgtmodel point towards H3K4me3 deposition at key loci suggesting that histone modifications might play a role in epigenetic inheritance in this context. This study sheds light on the mechanistic complexities of one-carbon metabolism in development and epigenetic inheritance.
Massively parallel single-cell profiling of transcriptome and multiple epigenetic proteins in cell fate regulation
Authors: Xiong Haiqing , Wang Qianhao , Li Chen C. , He Aibin
Published: April 2023

Sculpting the epigenome with a combination of histone modifications and transcription factor (TF) occupancy determines gene transcription and cell fate specification. Here we first develop uCoTarget, utilizing a split-pool barcoding strategy for realizing ultra-high throughput single-cell joint profiling of multiple epigenetic proteins. Through extensive optimization for sensitivity and multimodality resolution, we demonstrate that uCoTarget enables simultaneous detection of five histone modifications (H3K27ac, H3K4me3, H3K4me1, H3K36me3 and H3K27me3) in 19,860 single cells. We applied uCoTarget to thein vitrogeneration of hematopoietic stem/progenitor cells (HSPCs) from human embryonic stem cells, presenting multimodal epigenomic profiles in 26,418 single cells. uCoTarget with high sensitivity per modality reveals establishment of pairing of HSPC enhancers (H3K27ac) and promoters (H3K4me3) along the differentiation trajectory and RUNX1 engagement priming for the H3K27ac activation along the HSPC path. We then develop uCoTargetX, an expansion of uCoTarget to simultaneously measure transcriptome and multiple epigenome targets. Together, our methods enable generalizable, versatile multi-modal profiles for reconstructing comprehensive epigenome and transcriptome landscapes and analyzing the regulatory interplay at single-cell level.
Sensitivity Analysis of Biochemical Systems Using Bond Graphs
Authors: Gawthrop Peter J. , Pan Michael
Published: April 2023

The sensitivity of systems biology models to parameter variation can give insights into which parameters are most important for physiological function, and also direct efforts to estimate parameters. However, in general, kinetic models of biochemical systems do not remain thermodynamically consistent after perturbing parameters. To address this issue, we analyse the sensitivity of biological reaction networks in the context of a bond graph representation. We find that the parameter sensitivities can themselves be represented as bond graph components, mirroring potential mechanisms for controlling biochemistry. In particular asensitivity systemis derived which re-expresses parameter variation as additional system inputs. The sensitivity system is then linearised with respect to these new inputs to derive a linear system which can be used to give local sensitivity to parameters in terms of linear system properties such as gain and time constant. This linear system can also be used to find so-called sloppy parameters in biological models. We verify our approach using a model of the Pentose Phosphate Pathway, confirming the reactions and metabolites most essential to maintaining the function of the pathway.
Microbiome Metabolome Integration Platform (MMIP): a web-based platform for microbiome and metabolome data integration and feature identification
Authors: Gautam Anupam , Bhowmik Debaleena , Basu Sayantani , Zeng Wenhuan , Lahiri Abhishake , Huson Daniel H. , Paul Sandip
Published: April 2023

A microbial community maintains its ecological dynamics via metabolite crosstalk. Hence knowledge of the metabolome, alongside its populace, would help us understand the functionality of a community and also predict how it will change in atypical conditions. Methods that employ low-cost metagenomic sequencing data can predict the metabolic potential of a community, that is, its ability to produce or utilize specific metabolites. These, in turn, can potentially serve as markers of biochemical pathways that are associated with different communities. We developed MMIP (Microbiome Metabolome Integration Platform), a web-based analytical and predictive tool that can be used to compare the taxonomic content, diversity variation and the metabolic potential between two sets of microbial communities from targeted amplicon sequencing data. MMIP is capable of highlighting statistically significant taxonomic, enzymatic and metabolic attributes as well as learning-based features associated with one group in comparison with another. Further MMIP can predict linkages among species or groups of microbes in the community, specific enzyme profiles, compounds or metabolites associated with such a group of organisms. With MMIP, we aim to provide a user-friendly, online web-server for performing key microbiome-associated analyses of targeted amplicon sequencing data, predicting metabolite signature, and using learning-based linkage analysis, without the need for initial metabolomic analysis, and thereby helping in hypothesis generation.
Identifying the limits where variation in consumer stable isotope values reflect variation in diet
Authors: Arnoldi Jean-François , Bortoluzzi Jenny Rose , Rowlands Hugh , Harrod Chris , Parnell Andrew , Payne Nicholas , Donohue Ian , Jackson Andrew L
Published: April 2023

Analysis of stable isotopes in cosumbers is used commonly to study their ecological and/or environmental niche. There is, however, considerable debate regarding how isotopic values relate to diet and how other sources of variation confound this link, which can undermine the utility.

From the analysis of a simple, but general, model of isotopic incorporation in consumer organisms, we examine the relationship between isotopic variance among individuals, and diet variability within a consumer population.

We show that variance in consumer isotope values is directly proportional to variation in diet (through Simpson indices), to the number of isotopically distinct food sources in the diet, and to the baseline variation within and among the isotope values of the food sources. Additionally, when considering temporal diet variation within a consumer we identify the interplay between diet turnover rates and tissue turnover rates that controls the sensitivity of stable isotopes to detect diet variation.

Our work demonstrates that variation in the stable isotope values of consumers reflect variation in their diet. This relationship, however, can be confounded with other factors to the extent that they may mask the signal coming from diet. We show how simple quantitative corrections can recover a direct 1:1 correlation in some situations, and in others we can adjust our interpretation in light of the new understanding arising from our models. Our framework provides guidance for the design and analysis of empirical studies where the goal is to infer niche width from stable isotope data.
Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancer
Authors: Pellecchia Simona , Franchini Melania , Viscido Gaetano , Arnese Riccardo , Gambardella Gennaro
Published: April 2023

Epidermal growth factor receptor (EGFR)-targeted therapies have demonstrated variable and unpredictable clinical responses in triple negative breast cancer (TNBC). To elucidate the underlying mechanisms of this variability, we employ cellular barcoding and single-cell transcriptomics to reconstruct the subclonal dynamics of EGFR-amplified TNBC cells in response to afatinib, a tyrosine kinase inhibitor (TKI) that irreversibly inhibits EGFR. Integrated lineage tracing analysis revealed a rare pre-existing subpopulation of cells with distinct biological signature, including elevated expression levels of IGFBP2 (Insulin-Like Growth Factor Binding Protein 2). We show that IGFBP2 overexpression is sufficient to render TNBC cells tolerant to afatinib treatment by activating the compensatory IGF1-R signalling pathway. Finally, based on reconstructed mechanisms of resistance, we employ deep learning techniques to predict the afatinib sensitivity of TNBC cells. Our strategy proved effective in reconstructing the complex signalling network driving EGFR-targeted therapy resistance, offering new insights for the development of individualized treatment strategies in TNBC.
Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease
Authors: Patidar Krutika , Ford Versypt Ashlee N.
Published: April 2023

Diabetic kidney disease is a complication in one out of three patients with diabetes. Aberrant glucose metabolism in diabetes leads to structural and functional damage in glomerular tissue and a systemic inflammatory immune response. Complex cellular signaling is at the core of metabolic and functional derangement. Unfortunately, the mechanism underlying the role of inflammation in glomerular endothelial cell dysfunction during diabetic kidney disease is not fully understood. Mathematical models in systems biology allow the integration of experimental evidence and cellular signaling networks to understand mechanisms involved in disease progression. This study developed a logic-based ordinary differential equations model to study inflammatory crosstalk between macrophages and glomerular endothelial cells during diabetic kidney disease progression using a protein signaling network stimulated with glucose and lipopolysaccharide. This modeling approach reduced the biological parameters needed to study signaling networks. The model was fitted to and validated against available biochemical data fromin vitroexperiments. The model identified mechanisms for dysregulated signaling in macrophages and glomerular endothelial cells during diabetic kidney disease. In addition, the influence of signaling interactions on glomerular endothelial cell morphology through selective knockdown and downregulation was investigated. Simulation results showed that partial knockdown of VEGF receptor 1, PLC-γ, adherens junction proteins, and calcium partially recovered the intercellular gap width between glomerular endothelial cells. These findings contribute to understanding signaling and molecular perturbations that affect the glomerular endothelial cells in the early stage of diabetic kidney disease.

NEW & NOTEWORTHY

The work provides a novel analysis of signaling crosstalk between macrophages and glomerular endothelial cells in the early stage of diabetic kidney disease. A logic-based mathematical modeling approach identified vital signaling molecules and interactions that regulate glucose-mediated inflammation in the glomerular endothelial cells and cause endothelial dysfunction in the diabetic kidney. Simulated interactions among vascular endothelial growth factor receptor 1, nitric oxide, calcium, and junction proteins significantly affect the intercellular gap between glomerular endothelial cells.
Urbanization and a green corridor do not impact genetic divergence in common milkweed (Asclepias syriaca)
Authors: Breitbart Sophie T. , Agrawal Anurag A. , Wagner Helene H. , Johnson Marc T.J.
Published: April 2023

Urbanization is altering landscapes globally at an unprecedented rate. While ecological differences between urban and rural environments often promote phenotypic divergence among populations, it is unclear to what degree these trait differences arise from genetic divergence as opposed to phenotypic plasticity. Furthermore, little is known about how specific landscape elements, such as green corridors, impact genetic divergence in urban environments. We tested the hypotheses that: 1) urbanization, and 2) proximity to an urban green corridor influence genetic divergence inAsclepias syriaca(common milkweed) populations for phenotypic traits. Using seeds from 52 populations along three urban-to-rural subtransects in the Greater Toronto Area, one of which followed a green corridor, we grew ∼1000 plants in a common garden and observed >20 ecologically-important traits associated with plant defense/damage, reproduction, and growth over four years. We found significant heritable variation for eight traits withinA. syriacapopulations and weak phenotypic divergence among populations. However, neither urbanization nor an urban green corridor influenced genetic divergence in individual traits or multivariate phenotype. These findings contrast with the expanding literature demonstrating that urbanization promotes rapid evolutionary change and offer preliminary insights into the eco- evolutionary role of green corridors in urban environments.
µPhos: a scalable and sensitive platform for functional phosphoproteomics
Authors: Oliinyk Denys , Will Andreas , Schneidmadel Felix R. , Humphrey Sean J. , Meier Florian
Published: April 2023

Mass spectrometry has revolutionized cell signaling research by vastly simplifying the identification and quantification of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to internal or external perturbations in space and time is crucial for further illuminating functionality of the phosphoproteome. Here we describe µPhos, an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture experiments in < 8 hours total processing time. By minimizing transfer steps and reducing liquid volumes to < 200 µL, we demonstrate increased sensitivity, over 90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify more than 20,000 unique phosphopeptides in a human cancer cell line using 20 µg starting material, and confidently localize > 5,000 phosphorylation sites from 5 µg. This depth covers key intracellular signaling pathways, rendering sample-limited applications and extensive perturbation experiments with hundreds of samples viable.

Abstract Figure
Characterization of proteoform post-translational modifications by top-down and bottom-up mass spectrometry in conjunction with UniProt annotations
Authors: Chen Wenrong , Ding Zhengming , Zang Yong , Liu Xiaowen
Published: April 2023

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledgebases, such as UniProt, provide valuable information for PTM characterization and validation. Here, we present a software pipeline called PTM-TBA (PTM characterization by Top-down, Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as UniProt annotations. We identified 1,662 mass shifts from a top-down MS data set of SW480 cells, 545 (33%) of which were matched to 12 common PTMs, and 351 of which were localized. PTM-TBA validated 346 of the 1,662 mass shifts using UniProt annotations or a bottom-up MS data set of SW480 cells.
Impact of diet on jejunal microbiota composition during broiler development with special focus onEnterococcus hiraeandEnterococcus faecium
Authors: Stege Paul B. , Schokker Dirkjan , Harders Frank , Kar Soumya K. , Stockhofe Norbert , Perricone Vera , Rebel Johanna M. J. , de Jong Ingrid C. , Bossers Alex
Published: April 2023

Modern broiler breeds allow for high feed efficiency and rapid growth, but come at a cost of increased susceptibility to pathogens and disease. Broiler growth rate, feed efficiency, and health are furthermore affected by the composition of the gut microbiota, which in turn is influenced by diet composition. In this study we therefore assessed how diet composition alters the broiler jejunal gut microbiota. A total of 96 broiler chickens were divided into four diet groups: control, coated butyrate supplementation, medium chain fatty acid supplementation, or a high-fibre low-protein content. Diet groups were sub-divided into age groups (4, 12 and 33 days of age) resulting in groups of 8 broilers per diet per age. The jejunum content jejunum was used for metagenomic shotgun sequencing to determine the microbiota composition on species level. Among all diet groups, a total of 104 differential abundant bacterial species were detected. Most notably were the changes in the jejunal microbiota induced by butyrate supplementation when compared to the control diet, resulting in the reduced relative abundance of mainlyEnterococcus faeciumand the opportunistic pathogenEnterococcus hiraein broilers 4 days post-hatch. At this early stage of development, the immune system is still immature thereby highlighting the importance to study the relation of diet and the jejunal microbiota. Future studies should furthermore elucidate how diet can be used to promote a beneficial microbiota in the early stages of broiler development.
Genetic modifiers of APOBEC-induced mutagenesis
Authors: Mertz Tony M. , Rice-Reynolds Elizabeth , Nguyen Ly , Wood Anna , Bray Nicholas , Mitchell Debra , Lobachev Kirill , Roberts Steven A.
Published: April 2023

The cytidine deaminases APOBEC3A and APOBEC3B (A3B) are prominent mutators of human cancer genomes. However, tumor-specific genetic modulators of APOBEC-induced mutagenesis are poorly defined. Here, we utilized a screen to identify 61 gene deletions that increase A3B-induced mutations in yeast. Also, we determined whether each deletion was epistatic with UNG1 loss, which indicated whether the encoded factors participate in the error-free bypass of A3B/Ung1-dependent abasic sites or suppress A3B-catalyzed deamination by protecting against aberrant formation of single stranded DNA (ssDNA). Additionally, we determined that the mutation spectra of A3B-induced mutations revealed genotype-specific patterns of strand-specific ssDNA formation and nucleotide incorporation across APOBEC-induced lesions. Combining these three metrics we were able to establish a multifactorial signature of APOBEC-induced mutations specific to (1) failure to remove H3K56 acetylation, which results in extremely high A3B-induced mutagenesis, (2) defective CTF18-RFC complex function, which results in high levels of A3B induced mutations specifically on the leading strand template that synergistically increase with loss of UNG1, and (3) defective HR-mediated bypass of APOBEC-induced lesions, which were epistatic with Ung1 loss and result from increased Rev1-mediated C-to-G substitutions. We extended these results by analyzing mutation data for human tumors and found BRCA1/2-deficient breast cancer tumors display 3- to 4-fold more APOBEC-induced mutations. Mirroring our results in yeast, for BRCA1/2 deficient tumors Rev1-mediated C-to-G substitutions are solely responsible for increased APOBEC-signature mutations and these mutations occur on the lagging strand during DNA replication. Together these results identify important factors that influence the dynamics of DNA replication and likely the abundance of APOBEC-induced mutation during tumor progression as well as a novel mechanistic role for BRCA1/2 during HR-dependent lesion bypass of APOBEC-induced lesions during cancer cell replication.
The role of plasmids in the gut microbiome during the first year of life
Authors: He Wanli , Russel Jakob , Klincke Franziska , Nesme Joseph , Sørensen Søren Johannes
Published: April 2023

Plasmids are extrachromosomal self-replicating genetic elements that play a key role in bacterial ecology and evolution by shuttling diverse host-beneficial traits between bacteria. However, our understanding of plasmids is still limited, particularly in the human gut microbiota, and little is known about how they are acquired and become established in infants. In this study, we explored a longitudinal fecal metagenomic dataset obtained from 98 Swedish children who were followed during their first year of life. For this, we developed a bioinformatics pipeline for the complete sequence assembly and annotation of plasmids, together with the identification of plasmid contigs. We found that gut plasmids in these children were extremely diverse, particularly in the first four months of life, and this diversity decreased with maturation of the gut microbiota. Members of generaBacteroidesandBifidobacteriumwere identified as major hosts of transmissible plasmids and important hubs of horizontal gene transfer in the early human gut microbiota. Additionally, we discovered that plasmids played a substantial role in expanding the gene repertoires of their bacterial hosts: approximately a quarter of unannotated plasmid genes were found only on plasmids and not on chromosomes. Together, our results provide the first characterization of the early acquisition and development of plasmids in the infant gut microbiome. Their diversity and abundance in the first months of life could benefit a variable and rapidly proliferating microbiota by providing increased adaptability in a highly competitive environment.
Safe delivery of AAV vectors to the liver of small weaned pigs by ultrasound-guided percutaneous transhepatic portal vein injection
Authors: Rothgangl Tanja , Hruzova Martina , Gnannt Ralph , Aeberhard Nadja , Kissling Lucas , Grisch-Chan Hiu Man , Klassa Sven , Rimann Nicole , Marquart Kim F. , Ioannidi Eleonora , Wolf Anja , Kupatt Christian , Sidler Xaver , Häberle Johannes , Schwank Gerald , Thöny Beat
Published: April 2023

One challenge for liver-directed gene therapy is sufficient vector delivery to the target tissue while minimizing loss of the applied vector dose to other tissues. Infusion via peripheral veins is the least invasive approach; however, it results in systemic diffusion and substantial vector dilution. Here, we describe a safe and minimally invasive method to deliver adeno-associated virus (AAV) vectors to the liver of small weaned pigs by ultrasound-guided percutaneous trans-hepatic portal vein injection. 4-week-old piglets were infused with ∼2.5×1014vector genomes comprising a dual-rAAV2/9 vector system with a split adenine base editor forin vivoinactivation ofPCSK9to reduce LDL-cholesterol levels. Animals had no signs of discomfort and tolerated the procedure well. However, despite 45% editing of the target site with the applied adenine base editor system in cultivated porcine cells, we only found low amounts of AAV vector genomes and neither detectable transgene-expression nor successful editing in the treated pig livers. We hypothesize that rapid proliferation of pig hepatocytes caused AAV vector dilution, leading to a loss of the vectors from the nucleus, and hence insufficient base editor protein expression for achieving detectable editing rates. Nonetheless, ultrasound-guided percutaneous transhepatic injection to the portal vein is well-tolerated in piglets and has potential for human (neonate) application.
Aging exerts a limited influence on the perception of self-generated and externally generated touch
Authors: Timar Lili , Job Xavier , de Xivry Jean-Jacques Orban , Kilteni Konstantina
Published: April 2023

Touch generated by our voluntary movements is attenuated both at the perceptual and neural level compared to touch of the same intensity delivered to our body by another person or machine. This somatosensory attenuation phenomenon relies on the integration of somatosensory input and predictions about the somatosensory consequences of our actions. Previous studies have reported increased somatosensory attenuation in elderly people, proposing an overreliance on sensorimotor predictions to compensate for age-related declines in somatosensory perception; however, recent results have challenged this direct relationship. In a preregistered study, we used a force-discrimination task to assess whether aging increases somatosensory attenuation and whether this increase is explained by decreased somatosensory precision in elderly individuals. Although 94% of our sample (n = 108, 21–77 years old) perceived their self-generated touches as weaker than externally generated touches of identical intensity (somatosensory attenuation) regardless of age, we did not find a significant increase in somatosensory attenuation in our elderly participants (65–77 years old), but a trend when considering only the oldest subset (69-77 years old). Moreover, we did not observe a significant age-related decline in somatosensory precision or a significant relationship of age with somatosensory attenuation. Together, our results suggest that aging exerts a limited influence on the perception of self-generated and externally generated touch and indicate a less direct relationship between somatosensory precision and attenuation in the elderly individuals than previously proposed.

New and Noteworthy

Self-generated touch is attenuated compared to externally generated touch of identical intensity. This somatosensory attenuation has been previously shown to be increased in elderly participants, but it remains unclear whether it is related to age-related somatosensory decline. In our preregistered study, we observed a trend for increased somatosensory attenuation in our oldest participants (≥69 years), but we found no evidence of an age-related decline in somatosensory function or a relationship of age with somatosensory attenuation.
CRISPR-Cas9-mediated genome engineering exaggerates genomic deletion at 10q23.31 including thePTENgene locus mimicking cancer profiles
Authors: Geng Keyi , Merino Lara G. , Veiga Raül G. , Sommerauer Christian , Epperlein Janine , Brinkman Eva K. , Kutter Claudia
Published: April 2023

The CRISPR-Cas9 system is a powerful tool for studying gene functions and has tremendous potential for disease treatment. However, precise genome editing requires thorough assessments to minimize unintended on- and off-target effects. Here, we report an unexpected deletion of a 287 kb region on Chromosome 10 (10q23.31) in chronic myelogenous leukemia HAP1 cells, which are frequently used in CRISPR screens. The deleted region encodes regulatory genes, includingPAPSS2, ATAD1, KLLN, andPTEN. We found that this deletion was not a direct consequence of CRISPR-Cas9 off-targeting but rather occurred frequently by the process of generating CRISPR-Cas9-modifed cells. The deletion was associated with global changes in histone acetylation and gene expression, affecting fundamental cellular processes such as cell cycle and DNA replication. We detected this deletion in cancer patient genomes. As in HAP1 cells, the deletion contributed to similar gene expression patterns among cancer patients despite interindividual differences. Overall, our findings suggest that the unintended deletion of 10q23.31 can confound CRISPR-Cas9 studies, highlights the importance of assessing unintended genomic changes in CRISPR-Cas9-modified cells and may have clinical significance in cancer research.

Highlights

CRISPR-Cas9-modified HAP1 cells carry an unexpected large genomic deletion at 10q23.31 encompassing four protein-coding genes frequently expressed across various cell types.

The 10q23.31 deletion is accompanied by global changes in histone modification and transcriptomes.

The generation of CRISPR-Cas9-modified cells rather than Cas9 activity increases the frequencies of the deletion at 10q23.31.

The 10q23.31 deletion identified in HAP1 cells resembles a commonly occurring deletion pattern in cancer patients.
Probing Altered Receptor Specificities of Antigenically Drifting Human H3N2 Viruses by Chemoenzymatic Synthesis, NMR and Modeling
Authors: Unione Luca , Ammerlaan Augustinus N.A. , Bosman Gerlof P , Broszeit Frederik , van der Woude Roosmarijn , Liu Yanyan , Ma Shengzhou , Liu Lin , Diercks Tammo , Ardá Ana , de Vries Robert P. , Boons Geert-Jan
Published: April 2023

Prototypic receptors for human influenza viruses are cell surfaceN-glycans carrying α2,6-linked sialosides. Under immune pressure, A/H3N2 influenza viruses have emerged with altered receptor specificities that appear to recognize α2,6-linked sialosides presented on extendedN-acetyl-lactosamine (LacNAc) moieties. Here, molecular recognition features of such drifted hemagglutinin’s (HAs) are examined by chemoenzymatic synthesis of complexN-glycans having13C-labeled monosaccharides at strategic positions. The labeled glycans were employed in 2D STD-1H and13C-HSQC NMR experiments to pinpoint which monosaccharides of the extended LacNAc chain engage with evolutionarily distinct HAs. The NMR data in combination with computational and mutagenesis studies demonstrate that mutations distal to the receptor binding domain of recent HAs have created an extended binding site that can directly interact with the extended LacNAc chain. A fluorine containing sialyl-LacNAc derivative is used as NMR probe to derive relative binding affinities and confirmed the contribution of the extended LacNAc chain for binding.
TREM2 mediates MHCII-associated CD4+T cell response against gliomas
Authors: Zheng Jiaying , Wang Lingxiao , Zhao Shunyi , Zhang Wenjing , Chang Yuzhou , Dheer Aastha , Gao Shan , Xu Shengze , Ayasoufi Katayoun , Al-kharboosh Rawan , Xie Manling , Johnson Aaron J. , Dong Haidong , Quiñones-Hinojosa Alfredo , Wu Long-Jun
Published: April 2023

Triggering receptor expressed on myeloid cells 2 (TREM2) was recently highlighted as a novel immune suppressive marker in peripheral tumors. The aim of this study was to characterizeTREM2expression in gliomas and investigate its contribution in glioma progression by usingTrem2-/-mouse line. Our results showed that higherTREM2expression was correlated with poor prognosis in glioma patients. Unexpectedly, TREM2 deficiency did not have a beneficial effect in a pre-clinical model of glioma. The increasedTREM2expression in glioma was likely due to increased myeloid cell infiltration, as evidenced by our single-cell analysis showing that almost all microglia and macrophages in gliomas were TREM2+. Furthermore, we found that deficiency of TREM2 impaired tumor-myeloid phagocytosis and MHCII presentation, and significantly reduced CD4+T cells in tumor hemispheres. Our results revealed a previously unrecognized protective role of tumor-myeloid TREM2 in promoting MHCII-associated CD4+T cell response against gliomas.

Authors found that although higherTREM2expression is correlated with poor prognosis in glioma patients, its absence has no beneficial effect in a pre-clinical model of glioma. Deficiency of TREM2 impairs myeloid cell phagocytosis of tumor debris, leading to a reduction in MHCII-dependent CD4+anti-glioma immunity.
Hierarchical TAF1-dependent co-translational assembly of the basal transcription factor TFIID
Authors: Bernardini Andrea , Mukherjee Pooja , Scheer Elisabeth , Kamenova Ivanka , Antonova Simona , Sanchez Paulina Karen Mendoza , Yayli Gizem , Morlet Bastien , Timmers H.T. Marc , Tora László
Published: April 2023

Large heteromeric multiprotein complexes play pivotal roles at every step of gene expression in eukaryotic cells. Among them, the 20-subunit basal transcription factor TFIID nucleates RNA polymerase II preinitiation complex at gene promoters. Here, by combining systematic RNA-immunoprecipitation (RIP) experiments, single-molecule imaging, proteomics and structure-function analyses, we show that TFIID biogenesis occurs co-translationally. We discovered that all protein heterodimerization steps happen during protein synthesis. We identify TAF1 – the largest protein in the complex – as a critical factor for TFIID assembly. TAF1 acts as a flexible scaffold that drives the co-translational recruitment of TFIID submodules preassembled in the cytoplasm. Altogether, our data suggest a multistep hierarchical model for TFIID biogenesis that culminates with the co-translational assembly of the complex onto the nascent TAF1 polypeptide. We envision that this assembly strategy could be shared with other large heteromeric protein complexes.