bluuebunny/crossref_metadata_2025 huggingface dataset:
The single-cell spatial landscape of stage III colorectal cancers
Authors: Su Andrew , Lee HoJoon , Tran Minh , Cruz Richard D. , Sathe Anuja , Bai Xiangqi , Wichmann Ignacio , Pflieger Lance , Moulton Bryce , Barker Tyler , Haslem Derrick , Jones David , Nadauld Lincoln , Nguyen Quan , Ji Hanlee P. , Rhodes Terence
Published: November 2024

We conducted a spatial analysis using imaging mass cytometry applied to stage III colorectal adenocarcinomas. This study used multiplexed markers to distinguish individual cells and their spatial organization from 52 colorectal cancers. We determined the landscape features of cellular spatial features in the CRC tumor microenvironment. This spatial single-cell analysis identified 10 unique cell phenotypes in the tumor microenvironment that included stromal and immune cells with a subset which had a proliferative phenotype. These special features included spatial neighborhood interactions between single cells as well as different tissue niches, especially the tumor infiltrating lymphocyte regions. We applied a robust statistical analysis to identify significant correlations of cell features with phenotypes such as microsatellite instability or recurrence. We determined that microsatellite stable (MSS) colorectal cancers had an increased risk of recurrence if they had the following features: 1) a low level of stromal tumor-infiltrating lymphocytes, and 2) low interactions between CD4+ T cells and stromal cells. Our results point to the utility of spatial single-cell interaction analysis in defining novel features of the tumor immune microenvironments and providing useful clinical cell-related spatial biomarkers.
External validation of a treatment decision algorithm for tuberculosis in children living with HIV - a diagnostic cohort study
Authors: Khosa Celso , Nguyet Minh Huyen Ton Nu , Mwanga-Amumpaire Juliet , Chabala Chishala , Moh Raoul , Roucher Clementine , Nansera Denis , Nduna Bwendo , Macassa Eugenia , Folquet Madeleine Amorrissany , Rego Dalila , Mundundu Gae , Natukunda Naome , Shankalala Perfect , Cumbe Saniata , Komena Eric , Steenhoff Andrew P. , Hesseling Anneke C. , Seddon James A , Wobudeya Eric , Bonnet Maryline , Marcy Olivier
Published: November 2024

Introduction

Tuberculosis (TB) is the leading cause of death in children living with HIV (CLHIV) and is challenging to confirm the diagnosis. The PAANTHER treatment decision algorithm (TDA) was developed to improve the diagnosis of TB in CLHIV. We aimed to externally validate the PAANTHER TDA in CLHIV with presumptive TB.

Methods

We conducted a prospective diagnostic cohort study in seven tertiary hospitals across Côte d’Ivoire, Mozambique, Uganda, and Zambia, implementing the PAANTHER TDA in CLHIV aged between 1 month and 14 years with presumptive TB. TDA assessments included Xpert MTB/RIF Ultra (Ultra) on respiratory and stool samples, history of contact, symptoms (fever >2 weeks, unremitting cough, haemoptysis and/or weight loss in previous 4 weeks, tachycardia), chest radiography and abdominal ultrasound. A positive score (>100) prompted TB treatment initiation. Children were followed-up for 6 months, and retrospectively classified as having confirmed, unconfirmed or unlikely TB. The primary outcome was the proportion of missed TB cases (false negative) among children with negative scores; secondary outcomes included TDA diagnostic accuracy, feasibility, and time to treatment initiation. The TDA was considered validated if the negative predictive value (NPV, 1 - rate of false negative) was superior to a 75% pre-established confidence interval lower limit.

Findings

From 2 October 2019 to 31 December 2021, we enrolled 277 CLHIV, including 175 (63·2%) who were on antiretroviral therapy at inclusion. 272 (98·2%) children had a complete TDA evaluation; 215 (75.8%) scored >100, including 24 (8·7%) with positive Ultra. 182 (86·7%) children who scored ≥100, and 12 children who scored negative, initiated TB treatment at a median of 1 (IQR: 0-3) and 27 [8·2; 64] days after inclusion, respectively. 62/215 children (28·8%) who scored ≥100 were classified as having unlikely TB and 4/12 (33·3%) who scored negative were initiated on treatment and were classified as having unconfirmed TB. The proportion of children with TB (confirmed and unconfirmed) was 155/273 (56·8%; 95% CI: 50·9; 62·5). The NPV was 55/67 (93·3%; 95% CI: 84·1; 97·4), reaching protocol-defined validation. The TDA sensitivity was 97·4% (95% CI: 93·6; 90·0) with specificity of 47·5 (95% CI: 38·7; 56·4).

Interpretation

The PAANTHER TDA was validated in CLHIV. Its high sensitivity, excellent feasibility, and short turnaround time to treatment initiation, should allow rapid treatment decision-making and could reduce morbidity and mortality in CLHIV.

Funding

UNITAID
Single-cell transcriptional landscapes ofAedes aegyptimidgut and fat body after a bloodmeal
Authors: Vial Thomas , Lopez-Maestre Hélène , Couderc Elodie , Pinaud Silvain , Howick Virginia , Akorli Jewelna , Lawniczak Mara , Marti Guillaume , Merkling Sarah Hélène
Published: November 2024

Aedes aegyptimosquitoes are vectors for numerous arboviruses that have an increasingly substantial global health burden. Following a bloodmeal, mosquitoes experience significant physiological changes, primarily orchestrated by the midgut and fat body tissues. These changes begin with digestion and culminate in egg production. However, our understanding of those key processes at the cellular and molecular level remains limited. We have created a comprehensive cell atlas of the mosquito midgut and fat body by employing single-cell RNA sequencing and metabolomics techniques. This atlas unveils the dynamic cellular composition and metabolic adaptations that occur following a bloodmeal. Our analyses reveal highly diverse cell populations, specialized in digestion, metabolism, immunity, and reproduction. While the midgut primarily comprises enterocytes, enteroendocrine and intestinal stem cells, the fat body consists not only of trophocytes and oenocytes, but also harbors a substantial hemocyte population and a newly found fat body-yolk cell population. The fat body exhibits a complex cellular and metabolomic profile and exerts a central role in coordinating immune and metabolic processes. Additionally, an insect-specific virus, PCLV (Phasi Charoen-Like Virus) was detected in single cells, mainly in the midgut a week after the bloodmeal. These findings highlight the complexity of the mosquito’s abdominal tissues, and pave the way towards the development of exquisitely refined vector control strategies consisting of genetically targeting specific cell populations and metabolic pathways necessary for egg development after a bloodmeal.
NOODAI: A webserver for network-oriented multi-omics data analysis and integration pipeline
Authors: Totu Tiberiu , Tomasoni Mattia , Bolck Hella Anna , Buljan Marija
Published: November 2024

Omics profiling has proven of great use for unbiased and comprehensive identification of key features that define biological phenotypes and underlie medical conditions. While each omics profile assists characterization of specific molecular components relevant for the studied phenotype, their joint evaluation can offer deeper insights into the overall mechanistic functioning of biological systems. Here, we introduce an approach where starting from representative traits (e.g., differentially expressed elements) obtained for each omics profile, we construct and analyze joint interaction networks. The resulting networks rely on the existing knowledge of confident interactions among biological entities. We use these maps to identify and describe central elements, which connect multiple entities characteristic for the studied phenotypes and we leverage MONET network decomposition tool in order to highlight functionally connected network modules. In order to enable broad usage of this approach, we developed the NOODAI software platform, which enables integrative omics analysis through a user-friendly interface. The analysis outcomes are presented both as raw output tables as well as high-quality summary plots and written reports. Since the MONET tool enables the use of algorithms with strong performance in identifying disease-relevant modules, the NOODAI software platform can be of a high value for the analysis of clinical multi-omics datasets.

Availability and Implementation

The platform is available as a web application freely accessible athttps://omics-oracle.com. The source code is freely available from GitHub under the GPL3 license at:https://github.com/TotuTiberiu/NOODAI.
Long lived liver-resident memory T cells of biased specificities for abundant sporozoite antigens drive malaria protection by radiation-attenuated sporozoite vaccination
Authors: de Menezes Maria N. , Ge Zhengyu , Cozijnsen Anton , Gras Stephanie , Bertolino Patrick , Caminschi Irina , Lahoud Mireille H. , Yui Katsuyuki , McFadden Geoffrey I. , Beattie Lynette , Heath William R. , Fernandez-Ruiz Daniel
Published: November 2024

Vaccination with radiation-attenuated sporozoites (RAS) can provide highly effective protection against malaria in both humans and mice. To extend understanding of malaria immunity and inform the development of future vaccines, we studied the protective response elicited by this vaccine in C57BL/6 mice. We reveal that successive doses ofPlasmodium bergheiRAS favour the generation of liver CD8+tissue-resident memory T cells (TRMcells) over circulating memory cells, and markedly enhance their longevity. Importantly, RAS immunisation strongly skews the composition of the liver CD8+TRMcompartment towards cells specific for abundant sporozoite antigens, such as thrombospondin-related adhesive protein (TRAP) and circumsporozoite protein (CSP), which become major mediators of protection. The increased prevalence of sporozoite specificities is associated with limited intrahepatic parasite development and inhibition of naïve T cell responses to all parasite antigens in previously vaccinated mice. This leads to the exclusive expansion of effector T cells formed upon initial immunisation, ultimately reducing the diversity of the liver TRMpool later established. These findings provide novel insights into the mechanisms governing malaria immunity induced by attenuated sporozoite vaccination and highlight the susceptibility of this vaccine to limitations imposed by strain-specific immunity associated with the abundant, yet highly variable sporozoite antigens CSP and TRAP.

Author Summary

Malaria remains a significant global health challenge. An efficient vaccine could significantly enhance malaria control. Vaccination with radiation-attenuated sporozoites (RAS) can induce highly efficient protection against malaria, and our study brings critical insights into the protective mechanisms elicited by this vaccine. We show that RAS stimulates the formation of parasite-specific cytotoxic memory T cells that permanently reside in the liver (liver TRMcells). These cells are critical mediators of protection. Interestingly, multiple doses of RAS extend the lifespan of these memory cells, potentially improving long term immunity. However, we found that the induced memory T cell response is strongly skewed towards abundant, but highly variable, sporozoite proteins. Thus, this phenomenon exposes a potential limitation of the RAS vaccine against the great parasite diversity in the field, as it focuses the T cell response away from less abundant, but more conserved, parasite antigens.
RNA-Protein Interaction Classification via Sequence Embeddings
Authors: Matus Dominika , Runge Frederic , Franke Jörg K.H. , Gerne Lars , Uhl Michael , Hutter Frank , Backofen Rolf
Published: November 2024

RNA-protein interactions (RPI) are ubiquitous in cellular organisms and essential for gene regulation. In particular, protein interactions with non-coding RNAs (ncRNAs) play a critical role in these processes. Experimental analysis of RPIs is time-consuming and expensive, and existing computational methods rely on small and limited datasets. This work introducesRNAInterAct, a comprehensive RPI dataset, alongsideRPIembeddor, a novel transformer-based model designed for classifying ncRNA-protein interactions. By leveraging two foundation models for sequence embedding, we incorporate essential structural and functional insights into our task. We demonstrate RPIembeddor’s strong performance and generalization capability compared to state-of-the-art methods across different datasets and analyze the impact of the proposed embedding strategy on the performance in an ablation study.
Transcriptomic analysis of benznidazole-resistantTrypanosoma cruziclone reveals nitroreductase I-independent resistance mechanisms
Authors: Mejía-Jaramillo Ana María , Ospina-Zapata Hader , Fernandez Geysson Javier , Triana-Chávez Omar
Published: November 2024

The enzyme nitroreductase I (NTRI) has been implicated as the primary gene responsible for resistance to benznidazole (Bz) and nifurtimox inTrypanosoma cruzi. However, Bz-resistantT. cruzifield isolates carrying the wild-type NTR-I enzyme suggest that additional mechanisms independent of this enzyme may contribute to the resistance phenotype. To investigate these alternative mechanisms, in this paper, we pressured aTrypanosoma cruziclone with a high Bz concentration over several generations to select Bz-resistant clones. Surprisingly, we found a highly drug-resistant clone carrying a wild-type NTRI. However, the knockout of this gene using CRISPR-Cas9 in the sensitive clone showed that NTRI indeed induces resistance to Bz and supports the idea that the resistant one exhibits mechanisms other than NTRI. To explore these new mechanisms, we performed an RNA-seq analysis, which revealed genes involved in metabolic pathways related to oxidative stress, energy metabolism, membrane transporters, DNA repair, and protein synthesis. Our results support the idea that resistance to benznidazole is a multigenic trait. A Deeper understanding of these genes is essential for developing new drugs to treat Chagas disease.
A robust workflow to benchmark deconvolution of multi-omic data
Authors: Amblard Elise , Bertrand Vadim , Pena Luis Martin , Karkar Slim , Chuffart Florent , Ayadi Mira , Baurès Aurélia , Armenoult Lucile , Kermezli Yasmina , Cros Jérôme , Blum Yuna , Richard Magali
Published: November 2024

Tumour heterogeneity significantly affects cancer progression and therapeutic response, yet quantifying it from bulk molecular data remains challenging. Deconvolution algorithms, which estimate cell-type proportions in bulk samples, offer a potential solution. However, there is no consensus on the optimal algorithm for transcriptomic or methylomic data. Here, we present an unbiased evaluation framework for the first comprehensive comparison of deconvolution algorithms across both omic types, including reference-based and -free approaches. Our evaluation covers raw performance, stability, and computational efficiency under varying conditions, such as missing or additional cell types and diverse sample compositions. We apply this framework across multiple benchmark datasets, including a novel multi-omics dataset generated specifically for this study. To ensure transparency and re-usability, we have designed a reproducible work-flow using containerization and publicly available code. Our results highlight the strengths and limitations of various algorithms, and provides practical guidance for selecting the best method based on data type and analysis context. This benchmark sets a new standard for evaluating deconvolution methods and analysing tumour heterogeneity.
Transfer learning and DNA language models enhance transcription factor binding predictions
Authors: Aksu Ekin Deniz , Vingron Martin
Published: November 2024

Identification ofin vivotranscription factor (TF) binding sites is crucial to understand gene regulatory networks, but the lack of scalability in the methods for their experimental identification directs researchers towards computational models. TF binding site prediction models are often specific for a given TF, which also hinders the generalizability of models to previously unseen TFs. Here, we present an approach to predictin vivoTF binding sites using DNA accessibility, TF RNA expression and TF binding motifs. Our novel method leverages DNA language model embeddings and transfer learning to improve its accuracy and generalizability, achieving a mean area under the precision-recall curve (AUPR) of 0.51 in held-out cell types and chromosomes in the ENCODE-DREAMin vivoTFBS prediction challenge, outperforming the top-ranked methods. Furthermore, we show that prediction accuracy increases when TFs are highly active and exhibit cell-type specific expression. We finally test our models in an independent dataset on previously unseen TFs, and report a mean AUPR of 0.36, which is state-of-the-art in a cross-TF, cross-cell type and cross-chromosomal setting.
Cytoplasmic lncRNAs nucleate signalling pathways to define metastable state dynamics and determine phenotypic output
Authors: Shlyakhtina Y , Bloechl B , Moran KL , Maslakova A , Munro AF , Carragher NO , Portal MM
Published: November 2024

Cell plasticity, the ability that cells display to rapidly adapt to environmental cues, is thought to be encoded in non-genetic information reservoirs. Although the concept is widely acknowledged, the molecular mechanisms underlying this phenomenon remain largely undiscovered. Herein, we describe that clonal cell populations inherently display multiple co-existing metastable gene expression states that co-segregate with various phenotypic outputs. We show that transcriptome states are readily inherited and dynamically interconvert; not due to a shift in transcriptional programmes, but rather through yet unidentified post-transcriptional regulatory mechanisms. Remarkably, among phenotypically divergent clonal cell populations enriched in subsets of transcriptome states, we identified a peri-nuclear cytoplasmic structure (Signal Integration Portal – SIP) where state-specific lncRNAs, proteins containing intrinsically disordered regions and diverse active signalling pathways converge. Herein, we propose the SIP as a nucleating reservoir of non-genetic information at the crossroads of cell plasticity and non-genetic heterogeneity where it integrates intra- and extracellular signalling pathways buffering phenotypic output.
Afat-2(wa17)suppressor screen inC. elegansreveals genetic adaptations to polyunsaturated fatty acid deficiency
Authors: Kaper Delaney , Radović Uroš , Bergh Per-Olof , Qvist August , Henricsson Marcus , Borén Jan , Pilon Marc
Published: November 2024

Polyunsaturated fatty acids (PUFAs) are essential for mammalian health and function as membrane fluidizers and precursors for signaling lipids though the primary essential function of PUFAs within organisms has not been established. Unlike mammals who cannot endogenously synthesize PUFAs,C. eleganscande novosynthesize PUFAs starting with the Δ12 desaturase FAT-2 which introduces a second double bond to monounsaturated fatty acids to generate the PUFA linoleic acid. FAT-2 desaturation is essential forC. eleganssurvival sincefat-2null mutants are non-viable; the near-nullfat-2(wa17)allele synthesizes only small amounts of PUFAs and produces extremely sick worms. Using fluorescence recovery after photobleaching (FRAP), we found that thefat-2(wa17)mutant has rigid membranes and can be efficiently rescued by dietarily providing various PUFAs, but not by fluidizing treatments or mutations. With the aim of identifying mechanisms that compensate for PUFA-deficiency, we performed a forward genetics screen to isolate novelfat-2(wa17)suppressors and identified four internal mutations withinfat-2, and six mutations within the HIF-1 pathway. The suppressors increase PUFA levels infat-2(wa17)mutant worms and additionally suppress the activation of thedaf-16, UPRerand UPRmtstress response pathways that are active infat-2(wa17)worms. We hypothesize that the six HIF-1 pathway mutations, found inegl-9,ftn-2, andhif-1all converge on raising Fe2+levels and in this way boost desaturase activity, including that of thefat-2(wa17)allele. We conclude that PUFAs cannot be genetically replaced and that the only genetic mechanism that can alleviate PUFA-deficiency do so by increasing PUFA levels.
Chronic intermittent ethanol produces nociception through endocannabinoid-independent mechanisms in mice
Authors: Miliano C , Dong Y , Proffit M , Corvalan N , Natividad LA , Gregus AM , Buczynski MW
Published: November 2024

Alcohol use disorder (AUD) affects millions of people and represents a significant health and economic burden. Pain represents a frequently under-treated aspect of hyperkatifeia during alcohol withdrawal, yet to date no drugs have received FDA approval for the treatment of this indication in AUD patients. This study aims to evaluate the potential of targeting bioactive lipid signaling pathways as a therapeutic approach for treating alcohol withdrawal-related pain. We utilized a chronic intermittent ethanol (CIE) vapor exposure model in C57BL/6J mice of both sexes to establish alcohol dependence, and demonstrated that CIE mice developed robust tactile allodynia and thermal hyperalgesia during withdrawal that was independent of prior blood alcohol levels. Next, we evaluated four drugs for their efficacy in reversing tactile allodynia during abstinence from CIE using a cross-over treatment design that included FDA-approved naltrexone as well as commercially available inhibitors targeting inflammatory lipid signaling enzymes including fatty acid amide hydrolase (FAAH), monoacylglycerol lipase (MAGL), and 15-Lipoxygenase (LOX). None of these compounds produced significant therapeutic benefit in reversing established CIE-induced tactile allodynia, despite attenuating pain-like behaviors at these doses in other chronic pain models. Additionally, we assessed plasma endocannabinoid levels in both sexes during withdrawal. We found that there is an inherent sex difference in the endogenous anti-inflammatory endocannabinoid tone in naive mice and CIE treatment affected endocannabinoids levels in female mice only. These findings underscore the need to better understand the driving causes of AUD induced pain and to develop novel therapeutic approaches to mitigate pain in AUD patients.
ADP-MoA: a platform for screening antibiotic activity and their mechanism of action inPseudomonas aeruginosa
Authors: Valencia Morante Estela Ynés , Nunes Viviane Abreu , Chambergo Felipe S , Spira Beny
Published: November 2024

The emergence and proliferation of multidrug-resistant bacteria pose a major threat to global public health. To address an imminent crisis, it is essential to identify and characterize new antibacterial molecules. With that in mind, we developed the ADP-MoA platform, that facilitates the discovery of new antibiotics and provides preliminary insights into their mechanisms of action. The basic idea is to simultaneously visualize antibiotic activity – growth inhibition, along with one of the three classic antibiotics mechanisms of action: DNA damage/inhibition of DNA replication, protein synthesis inhibition and cell wall damage. The platform consists of three different chromosomal fusions between the promoters ofrecA, ampCorarmZand theluxCDABEoperon. The platform was constructed and hitherto tested in the pathogenic opportunistic bacteriumPseudomonas aeruginosa. As a proof of concept we showed that the promoter fusions were each activated by the expected antibiotics with known mechanisms of action. ThearmZ::luxCDABEfusion responded to antibiotics that inhibit protein synthesis (macrolides, chloramphenicol, tetracyclines and aminoglycosides),ampC::luxCDABEwas induced by β-lactams andrecA::luxCDABEwas induced by quinolones. Interestingly, ciprofloxacin induced PampCand ParmZas well, albeit at a lower level. The ADP-MoA platform offers a readily implementable, low-cost approach with significant potential for high-throughput screening of antimicrobials againstP. aeruginosaand other bacterial species.
Offset mass carrier proteome improves quantification of multiplexed single cell proteomics
Authors: Cheung Tommy K. , Zhu Ying , Rose Christopher M.
Published: November 2024

Multiplexed single cell proteomics by mass spectrometry (scpMS) approaches currently offer the highest throughput as measured by cells analyzed per day. These methods employ isobaric labels and typically a carrier proteome - a sample added at 20-500x the single cell level that improves peptide sampling and identification. Peptides from the carrier and single cell proteomes exist within the same precursor isotopic cluster and are co-isolated for identification and quantification. This represents a challenge as high levels of carrier proteome limit the sampling of peptide ions from single cell samples and can potentially lead to decreased accuracy of quantitative measurements. Here, we address this limitation by introducing a triggered by offset mass acquisition method for scpMS (toma-scpMS) that utilizes a carrier proteome labeled with non-isobaric tags that have the same chemical composition but different mass as the labels used for quantitative multiplexing. Within toma-scpMS the carrier proteome and single cell proteome are separated at the precursor level, enabling separate isolation, fragmentation, and quantitation of the single cell samples. To enable this workflow we implemented a custom data acquisition scheme within inSeqAPI, an instrument application programming interface program, that performed real-time identification of carrier proteome peptides and subsequent triggering of offset single cell quantification scans. We demonstrate that toma-scpMS is more robust to high-levels of carrier proteome and offers superior quantitative accuracy as compared to traditional multiplexed scpMS approaches when similar carrier proteome levels are employed.
Characterizing the rates and patterns ofde novogermline mutations in the aye-aye (Daubentonia madagascariensis)
Authors: Versoza Cyril J. , Ehmke Erin E. , Jensen Jeffrey D. , Pfeifer Susanne P.
Published: November 2024

Given the many levels of biological variation in mutation rates observed to date in primates – spanning from species to individuals to genomic regions – future steps in our understanding of mutation rate evolution will be aided by both a greater breadth of species coverage across the primate clade, but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection ofde novomutations, and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects as well as sex dependency in mutation rates which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.
Genetic modulation of yield and phenotypic plasticity of yield in winter wheat
Authors: Giordano Nicolas , Sadras Victor O. , Guttieri Mary J. , Cruppe Giovana , Bai Guihua , Fritz Allan , Bernardo Amy , St. Amand Paul , Abbate Pablo , Berger Andres , Boehm Jeffrey , De Oliveira Silva Amanda , Jones-Diamond Sally , Haley Scott , Lingenfelser Jane , Zhang Guorong , Lollato Romulo
Published: November 2024

For winter wheat in the US Central Great Plains, phenotypic plasticity of yield is agronomically adaptive,i.e., genotypes with higher plasticity have higher yield in high yielding environments with no tradeoff in stressful, low yielding environments. Using data from variety trials conducted between 2000 and 2022 and cultivars released between 1967 and 2022, we explored time trends in phenotypic plasticity and heritability of yield. We hypothesize that i) if yield plasticity is agronomically adaptive, then newer cultivars will have higher yield plasticity; ii) heritability of yield is declining in the time series; and iii) genomic regions associated with yield depend on the environment and do not fully overlap with those associated with phenotypic plasticity of yield. Breeding for yield and agronomic adaptation increased phenotypic plasticity of yield at 0.5% year-1; broad sense heritability of yield decreased from 0.23 in 1993 to 0.15 in 2017. Genome-wide-association analysis shows genomic regions associated with yield varied between high yielding and stressful environments and were partially independent of those associated with yield plasticity. Newer cultivars have a higher frequency of alleles associated with yield and its plasticity. We discuss implications for breeding and agronomy aimed to improve wheat phenotypes.
Glioblastoma Drives Protease-Independent Extracellular Matrix Invasion of Microglia
Authors: Chang Chia-Wen , Bale Ashwin , Bhargava Rohit , Harley Brendan A.C.
Published: November 2024

Glioblastoma (GBM) is the most common and lethal form of primary brain cancer. Microglia infiltration into the tumor microenvironment is associated with immunosuppression and poor prognosis. Improved physicochemical understanding of microglia activation and invasion may provide novel GBM therapeutic strategies essential for improving long-term treatment efficacy. Here, we combine microfluidic systems with 3-D collagen hydrogels to systematically investigate microglia activation, invasion, contractility and cytokine secretion in response of GBM-microglia crosstalk. GBM inflammatory biomolecules significantly promote activation and 3D invasion of microglia. Interestingly, microglia invasion is not significantly affected by inhibitors of MMP activity or cellular glycolysis. In contrast, ROCK-pathway inhibition significantly impedes microglia invasion. Infrared microscopy analyses show that GBM co-culture does not significantly alter microglia lipid content. Further, GBM conditioned media resulted in significantly increased collagen hydrogel contraction, suggesting the importance of microglia contractility to physically remodel the local extracellular matrix (ECM). We also identify a panel of soluble proteins that may contribute to microglia chemotaxis, such as TIMP-1 and CXCL12. Taken together, this study suggests that the presence of GBM cells can enhance microglia invasion via increased cellular contractility, independent of MMP activity and cellular glycolysis.
Identification and characterization of vasoactive intestinal peptide receptor antagonists with high-affinity and potent anti-leukemia activity
Authors: Wang Yuou , Sen-Majumdar Anish , Li Jian-Ming , Sarkar Srijon , Passang Tenzin , Li Yiwen , Cohen Jamie , Chen Zihan , Chaudagar Kiranj , Das Pankoj Kumar , Wang Shuhua , Bruk Nabute , Papadantonakis Nikolaos , Giver Cynthia R. , Waller Edmund K.
Published: November 2024

Vasoactive intestinal peptide (VIP) is a neuropeptide involved in tumor growth and immune modulating functions. Previous research indicated that a VIP antagonist (VIPhyb) enhances T-cell activation and induces T-cell-dependent anti-leukemic activity in mice. We created a combinatorial library of VIPhyb C-terminal sequence variations to develop a more potent VIP-receptor (VIP-R) antagonist, hypothesizing that specific amino acid substitutions would improve receptor binding and plasma stability.In silicoscreening analyses identified sequences with improved docking scores predicting increased binding affinity to human VIP receptors VPAC1 and VPAC2. Fifteen peptides were synthesized and tested for their ability to potentiate activation of purified mouse and human T cells and enhance T cell-dependent anti-leukemia responses in murine models of acute myeloid leukemia. Treating C57Bl/6 mice engrafted with a C1498 myeloid leukemia cell line with daily subcutaneous injections of VIP-R antagonist peptides induced T cell activation resulting in specific anti-leukemia responses. Strikingly, the predicted binding affinity of the VIP-R antagonists to VIP receptors correlated positively with their ability to augment mouse T-cell proliferation and anti-leukemia activity. ANT308 and ANT195 emerged as top candidates due to their high predicted VIP-R binding, low EC50forin vitroT cell activation, and potent anti-leukemia activities. ANT308 decreased CREB phosphorylation, a downstream signaling pathway of the VIP receptor, and stimulated granzyme B and perforin expression in CD8+ T cells from AML patients. Combiningin silicomodeling,in vitroT cell activation properties, andin vivoanti-leukemia activity has identified promising VIP-R antagonist candidates for further development as novel immunotherapies for AML, especially for patients with relapsed disease.
How population control of pests is modulated by density dependence: The perspective of genetic biocontrol
Authors: Butler C. D. , Lloyd A. L.
Published: November 2024

Managing pest species relies critically on mechanisms that regulate population dynamics, particularly those factors that change with population size. These density-dependent factors can help or hinder control efforts and are especially relevant considering recent advances in genetic techniques that allow for precise manipulation of the timing and sex-specificity of a control. Despite this importance, density dependence is often poorly characterized owing to limited data and an incomplete understanding of developmental ecology. To address this issue, we construct and analyze a mathematical model of a pest population with a general control under a wide range of density dependence scenarios. Using this model, we investigate how control performance is affected by the strength of density dependence. By modifying the timing and sex-specificity of the control, we tailor our analysis to simulate different pest control strategies, including conventional and genetic biocontrol methods. We pay particular attention to the latter as case studies by extending the baseline model to include genetic dynamics. Finally, we clarify past work on the dynamics of mechanistic models with density dependence. As expected, we find substantial differences in control performance for differing strengths of density dependence, with populations exhibiting strong density dependence being most resilient to suppression. However, these results change with the size and timing of the control load, as well as the target sex. Interestingly, we also find that population invasion by certain genetic biocontrol strategies is affected by the strength of density dependence. While the model is parameterized using the life history traits of the yellow fever mosquito,Aedes aegypti, the principles developed here apply to many pest species. We conclude by discussing what this means for pest population suppression moving forward.
Preprints vs. Journal Articles: Citation Impact in COVID-19 Research
Authors: Tsunoda Hiroyuki , Sun Yuan , Nishizawa Masaki , Liu Xiaomin , Amano Kou , Kominami Rie
Published: November 2024

Focusing on article and citation count, this study examined 110 academic journals whose papers on COVID-19 were indexed in PubMed from 2020 to 2023. To analyze these journals’ characteristics, this study introduced the concepts of paper ratio, citation ratio, and citation impact. Journals with similar trends in paper and citation count were positioned near the diagonal on a two-dimensional graph (y=x) with paper ratio on the x-axis and citation ratio on the y-axis, indicating a slope close to 1. Conversely, the greater the disparity between paper ratio and citation ratio, the wider the angle between the journal’s position and the diagonal. Of the 110 journals in 2020, 83 were above the diagonal with a citation impact greater than 1, while 27 were below the diagonal with a citation impact of 1 or lower. Notably, nine journals—BMC Health Services Research, Genome Medicine, Nature, Annals of Epidemiology, BMC Bioinformatics, Nature Microbiology, PLoS Computational Biology, Medicine (Baltimore), andJournal of Clinical Investigation—showed high citation impact, with preprint-distributed papers being cited nearly five times more than directly submitted papers. This study demonstrates that articles initially distributed as preprints in these journals tend to receive substantially more citations than directly submitted ones.
RNA expression data suggest ALDH2 inhibition as a concept for killing acute myeloid leukemia cells that are resistant to ALDH1 inhibitors: the example of NPM1 mutant AML
Authors: Dancik Garrett M , Vlahopoulos Spiros
Published: November 2024

In this data paper we present a study of RNA expression in association with the disease course of acute myeloid leukemia (AML). We have previously identified aldehyde dehydrogenase genesALDH1A1andALDH2as prospective actionable targets in AML. ALDH1A1 is expected to have key functions in leukemia stem-like cells that are prone to a dormant state in terms of metabolic activity and proliferation. Cells with a higher activity of metabolism as a whole and in mitochondria in particular, are likely to generate a higher abundance of formaldehyde and acetaldehyde. Cell survival necessitates removal of formaldehyde and acetaldehyde, which is to a substantial degree the function of ALDH2. AML cells with a mutantNPM1gene permit higher MYC activity which would lead to increased metabolic activity. Extended MYC activity is allowed by the mutant NPM1 protein, compared to NPM1 wild-type. Here, we show that survival analysis in patients withNPM1mutant AML yields a higher hazard ratio forALDH2RNA than forALDH1A1, which is not the case for patients with wild-type NPM1. This result is consistent with the difference in enzymatic function between ALDH2 and ALDH1A1, the latter of which is not suited for small aldehydes, especially formaldehyde. This should open the door to the examination of ALDH2 inhibitors such as the clinically approved disulfiram, for the treatment of NPM1 mutant AML that proves refractory to ALDH1A1 inhibition.
EMT, angiogenesis, and cell-cycle pathways are significantly impacted in oral cancer patients, among whom a large fraction may potentially respond to immune checkpoint therapy
Authors: Das Debodipta , Maitra Arindam , Panda Chinmay K. , Ghose Sandip , Roy Bidyut , Sarin Rajiv , Majumder Partha P.
Published: November 2024

Background

Oral squamous cell carcinoma of the gingivo-buccal region (OSCC-GB) has the highest incidence among males and the second highest overall among all cancers in India, emphasizing the need for precise molecular classifications to guide personalized therapy.

Methods

We performed bulk RNA sequencing on tumor and adjacent normal tissue samples from 72 OSCC-GB patients, as well as leukoplakia tissue from 25 patients with concurrent leukoplakia.

Findings

Our analysis revealed activated epithelial-mesenchymal transition, angiogenesis, and cell-cycle function in OSCC-GB. We found significant enhancement of glycolysis and reduction in oxidative phosphorylation, which are hallmarks of the Warburg effect. Immune profiling indicated enriched immune-related genes and cells in tumor tissues. We identified two distinct patient subtypes, one of which exhibited higher immune cell infiltration and showed potential for greater responsiveness to immune checkpoint inhibitors.CD226,CD38, andKBTBD8were identified as potential biomarkers for classifying OSCC-GB patients and were validated in an independent cohort. Significantly more M1 macrophages and CD4+ T-cells in leukoplakia tissue than the normal indicate activated host defense mechanisms in pre-malignant lesions, highlighting the potential for early intervention to prevent malignancy. TCGA-HNSC data exhibited similar gene set enrichments, including glycolysis and immune-related pathways. However, unique profiles in a subset of TCGA-HNSC patients highlight the molecular heterogeneity of head and neck cancers.

Conclusion

Our findings underscore the critical role of understanding these pathways in cancer biology and immunology, essential for developing effective treatment strategies for oral cancer and immunotherapy.
Ecological synchrony in human-modified landscapes under a changing climate
Authors: Song Yiluan , Barnes Mallory , Browning Dawn M. , Bybee-Finley K. Ann , Dahlin Kyla M. , Munch Stephan B. , Ponce-Campos Guillermo E. , Youngflesh Casey , Zuckerberg Benjamin , Zhu Kai
Published: November 2024

Different aspects of ecological systems, biotic or abiotic, often fluctuate in coordinated patterns over space and time. Such high concordance between ecological processes is often referred to as ecological synchrony. Anthropogenic activities, including and beyond climate change, have the potential to alter ecological synchrony by disrupting or enhancing existing synchrony. Despite many local studies, we have a limited systematic understanding of how ecological synchrony is shaped by management in human-dominated landscapes at regional to continental scales. From a macrosystems perspective, we review how anthropogenic activities, particularly beyond climate change, alter ecological synchrony across levels of ecological organization, from the ecosystem level to the population level. For each level, we use a large-scale case study to demonstrate ways to quantify the impacts of human modifications on synchrony using big data from remote sensing, surveys, and observatory networks. For example, we detected possible homogenization of population dynamics of bird species in North America. These changes in ecological synchrony, although in different forms, often represent challenges to ecological and social systems. Collaborative research efforts that integrate emerging open data streams moving forward will be able to provide insights into the effects of different anthropogenic drivers and the consequences of changes in synchrony.
scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics
Authors: Bai Ding , Mo Shentong , Zhang Ruiyi , Luo Yingtao , Gao Jiahao , Yang Jeremy Parker , Wu Qiuyang , Singh Digvijay , Rahmani Hamidreza , Amariuta Tiffany , Grotjahn Danielle , Zhong Sheng , Lewis Nathan , Wang Wei , Ideker Trey , Xie Pengtao , Xing Eric
Published: November 2024

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a small subset of highly expressed genes and lack the integration of external genespecific knowledge. To address these limitations, we present sc-Long, a billion-parameter foundation model pretrained on 48 million cells. sc-Long performs self-attention across the entire set of 28,000 genes in the human genome. This enables the model to capture long-range dependencies between all genes, including lowly expressed ones, which often play critical roles in cellular processes but are typically excluded by existing foundation models. Additionally, sc-Long integrates gene knowledge from the Gene Ontology using a graph convolutional network, enriching its contextual understanding of gene functions and relationships. In extensive evaluations, sc-Long surpasses both stateof-the-art scRNA-seq foundation models and task-specific models across diverse tasks, including predicting transcriptional responses to genetic and chemical perturbations, forecasting cancer drug responses, and inferring gene regulatory networks.
Rapid colorimetric detection ofcitrus tristeza viruscombining portable sample preparation and reverse transcription-loop mediated isothermal amplification
Authors: Liu Chia-Wei , Bodaghi Sohrab , Keremane Manjunath L. , Kalish Brent , Vidalakis Georgios , Tsutsui Hideaki
Published: November 2024

Abstracts

A sensing platform combining semi-automated sample preparation protocol and one-step reverse transcription loop-mediated isothermal amplification (RT-LAMP) is reported for rapid colorimetric detection ofcitrus tristeza virus(CTV) in a greenhouse. An OmniLyse micro-homogenizer and cellulose paper disks were integrated for quick sample preparation of total nucleic acids (<15 min). RT-LAMP assays were optimized in terms of primers’ concentrations and minimization of false positives for both CTV and cytochrome oxidase (COX) detections. Specifically, the optimal reaction time for lab-based RT-LAMP assays was determined as 40 minutes with the detection limits of CTV and COX as 43 copies/μL (equivalent to 86 copies/mg of tissue) and 5 copies/μL (equivalent to 10 copies/mg of tissue), respectively. Additionally, an in-greenhouse colorimetric RT-LAMP assay with lyophilized reaction mix for endpoint CTV detection was successfully conducted in 35 minutes without a false response in either colorimetric or fluorometric assays. Overall, this quick sample preparation protocol integrated with the lyophilized RT-LAMP assays showed high efficiency and reliability in plant pathogen detection in a greenhouse. This strategy holds great potential to be integrated into a portable, autonomous system and be universally adopted for in-field diagnosis of different pathogens.
Understanding pollination in urban food production: the importance of data validation and participant feedback for citizen science project design
Authors: Nicholls Elizabeth , Salm Leah , Castellanos Maria Clara , Basu Parthib , Chaterjee Soumik , Ely Adrian , Howe Helena , Goulson Dave
Published: November 2024

There is a significant knowledge gap regarding the pollination needs of urban farming, partly due to barriers for researchers in accessing these growing spaces. Involving growers in data collection offers a potential solution but presents other challenges in terms of data accuracy and participant retention.

We developed a citizen science methodology for monitoring plant-pollinator interactions in urban food systems and evaluated the accuracy of data collected by growers by comparison to data collected by a professionally trained researcher. We also collected feedback from participants at the mid- and endpoints of the project regarding their experiences of taking part.

While there was some agreement between the datasets in terms of the crops most (raspberries and squash) and least attractive (tomatoes) to insects, relying only on the dataset collected by growers themselves (citizen scientists) would lead to an overestimation of the generality of relationships between crops and pollinating insects in urban food production. Possible reasons for discrepancies between the datasets include species misidentification and non-reporting of surveys where no insects were observed by citizen scientists.

Citizen scientists reported lack of time, concerns about data accuracy and too complex methods as barriers to participation. Implementation of their suggestions for improvements led to a 66% increase in participation in the following year, demonstrating the importance of maintaining a two-way dialogue between participants and project organisers. Citizen scientists also reported an increased appreciation and understanding of insect pollinations following participation, highlighting an additional benefit of involving urban growers in data collection.

Social Impact Statement

Growing food in urban areas can contribute towards sustainable food production. We know little about urban crop pollination, and data collection can be challenging due to restricted access to growing spaces. We developed and tested the effectiveness of a method for urban growers themselves to collect data on insects visiting their crops. Comparing data to that collected by a professional researcher, we found similarities in terms of the most and least attractive crops to pollinators, but there were also large discrepancies in the datasets that mean there are limitations to relying on grower-collected data alone to understand urban plant-pollinator interactions.