bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Clinical Use of Molecular Profiling of Intrahepatic Cholangiocarcinoma in a Comprehensive Multidisciplinary Clinic
Authors: Purchla Julia , Ghabi Elie M , Burns William R , Lafaro Kelly J , Burkhart Richard A , Cameron John L , Yarchoan Mark , Shubert Christopher R , Baretti Marina , He Jin
Published: January 2024

BACKGROUND:

Molecular profiling of intrahepatic cholangiocarcinoma (ICC) can detect actionable molecular alterations and guide targeted therapies. We explore the clinical use of molecular profiling of ICC in our comprehensive multidisciplinary clinic.

STUDY DESIGN:

Patients with a tissue diagnosis of ICC seen between 2019 and 2023 were identified. A retrospective review was performed to identify their molecular profiles and targeted therapy. The association between the detection of actionable molecular alterations and overall survival (OS) from the first clinic visit date was studied. Patients with an OS of less than 2 months were excluded.

RESULTS:

Among 194 patients with ICC, 125 had molecular profiling. Actionable molecular alterations were detected in 56 (45%) patients, including microsatellite instability (n = 3), high tumor mutational burden (>10 muts/mb; n = 5), isocitrate dehydrogenase 1 and 2 mutations (n = 22 and 6, respectively), BRAF V600E mutations (n = 2), phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha mutations (n = 7), breast cancer 1 and breast cancer 2 mutations (n = 5), mesenchymal epithelial transition amplification (n = 2), fibroblast growth factor receptor 2 and 3 fusions (n = 13), erb-b2 receptor tyrosine kinase 2 overexpression (n = 6), and receptor tyrosine kinase 1 fusion (n = 1). Twenty-one patients received targeted therapies during their treatment course. Survival analysis revealed that for 120 patients with molecular profiling, the detection of an actionable molecular alteration was associated with improved mean OS (34.1 vs 23.6 months, p = 0.008). Among 70 patients with nonmetastatic ICC, the detection of an actionable molecular alteration was associated with improved mean OS (32.1 vs 27.5 months, p = 0.02).

CONCLUSIONS:

Actionable molecular alterations were frequently observed in patients with ICC. Detection of actionable alterations was associated with improved OS. The role of targeted therapy needs further exploration in prospective multicenter studies.
Evolutionary relationships between metabolism and behaviour require genetic correlations
Authors: Crespel Amélie , Lindström Jan , Elmer Kathryn R. , Killen Shaun S.
Published: January 2024

As selection acts on multivariate phenotypes, the evolution of traits within populations not only depends on the genetic basis of each trait, but also on the genetic relationships among traits. As metabolic rate is often related to vital traits such as growth, physiology and behaviour, its variation and evolution is expected to have important repercussions on individual fitness. However, the majority of the correlations between metabolic rate and other traits has been based on phenotypic correlations, while genetic correlations, basis for indirect selection and evolution, have been overlooked. Using a case study, we explore the importance of properly estimating genetic correlations to understand and predict evolution of multivariate phenotypes. We show that selection on metabolic traits could result in indirect selection mainly on growth-related traits, owing to strong genetic correlations, but not on swimming or risk-taking and sociability behaviour even if they covary phenotypically. While phenotypic correlation can inform about genetic correlation direction, caution is needed in predicting the magnitude of genetic correlation. Therefore, even though phenotypic correlations among physiological and behavioural traits could be useful, deriving evolutionary conclusions based purely on them is not robust. In short, proper estimation of genetic correlations is needed when predicting evolutionary consequences.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Temperature and nutrition do not interact to shape the evolution of metabolic rate
Authors: Alton Lesley A. , Kutz Teresa , Bywater Candice L. , Lombardi Emily , Cockerell Fiona E. , Layh Sean , Winwood-Smith Hugh , Arnold Pieter A. , Beaman Julian E. , Walter Greg M. , Monro Keyne , Mirth Christen K. , Sgrò Carla M. , White Craig R.
Published: January 2024

Metabolic cold adaptation, or Krogh's rule, is the controversial hypothesis that predicts a monotonically negative relationship between metabolic rate and environmental temperature for ectotherms living along thermal clines measured at a common temperature. Macrophysiological patterns consistent with Krogh's rule are not always evident in nature, and experimentally evolved responses to temperature have failed to replicate such patterns. Hence, temperature may not be the sole driver of observed variation in metabolic rate. We tested the hypothesis that temperature, as a driver of energy demand, interacts with nutrition, a driver of energy supply, to shape the evolution of metabolic rate to produce a pattern resembling Krogh's rule. To do this, we evolved replicate lines of
Drosophila melanogaster
at 18, 25 or 28°C on control, low-calorie or low-protein diets. Contrary to our prediction, we observed no effect of nutrition, alone or interacting with temperature, on adult female and male metabolic rates. Moreover, support for Krogh's rule was only in females at lower temperatures. We, therefore, hypothesize that observed variation in metabolic rate along environmental clines arises from the metabolic consequences of environment-specific life-history optimization, rather than because of the direct effect of temperature on metabolic rate.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Among-individual variation in thermal plasticity of fish metabolic rates causes profound variation in temperature-specific trait repeatability, but does not co-vary with behavioural plasticity
Authors: Norin Tommy , Rowsey Lauren E. , Houslay Thomas M. , Reeve Connor , Speers-Roesch Ben
Published: January 2024

Conspecifics of the same age and size differ consistently in the pace with which they expend energy. This among-individual variation in metabolic rate is thought to influence behavioural variation, since differences in energy requirements should motivate behaviours that facilitate energy acquisition, such as being bold or active in foraging. While there is evidence for links between metabolic rate and behaviour in constant environments, we know little about whether metabolic rate and behaviour change together when the environment changes—that is, if metabolic and behavioural plasticity co-vary. We investigated this using a fish that becomes dormant in winter and strongly reduces its activity when the environment cools, the cunner (
Tautogolabrus adspersus
). We found strong and predictable among-individual variation in thermal plasticity of metabolic rates, from resting to maximum levels, but no evidence for among-individual variation in thermal plasticity of movement activity, meaning that these key physiological and behavioural traits change independently when the environment changes. The strong among-individual variation in metabolic rate plasticity resulted in much higher repeatability (among-individual consistency) of metabolic rates at warm than cold temperatures, indicating that the potential for metabolic rate to evolve under selection is temperature-dependent, as repeatability can set the upper limit to heritability.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Estimating the relationship between fitness and metabolic rate: which rate should we use?
Authors: Cameron Hayley , Marshall Dustin
Published: January 2024

As physiologists seek to better understand how and why metabolism varies, they have focused on how metabolic rate covaries with fitness—that is, selection. Evolutionary biologists have developed a sophisticated framework for exploring selection, but there are particular challenges associated with estimating selection on metabolic rate owing to its allometric relationship with body mass. Most researchers estimate selection on mass and absolute metabolic rate; or selection on mass and mass-independent metabolic rate (MIMR)—the residuals generated from a nonlinear regression. These approaches are sometimes treated as synonymous: their coefficients are often interpreted in the same way. Here, we show that these approaches are not equivalent because absolute metabolic rate and MIMR are different traits. We also show that it is difficult to make sound biological inferences about selection on absolute metabolic rate because its causal relationship with mass is enigmatic. By contrast, MIMR requires less-desirable statistical practices (i.e. residuals as a predictor), but provides clearer causal pathways. Moreover, we argue that estimates of selection on MIMR have more meaningful interpretations for physiologists interested in the drivers of variation in metabolic allometry.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Metabolic scaling as an emergent outcome of variation in metabolic rate
Authors: Naug Dhruba
Published: January 2024

The allometric scaling of metabolic rate and what drives it are major questions in biology with a long history. Since the metabolic rate at any level of biological organization is an emergent property of its lower-level constituents, it is an outcome of the intrinsic heterogeneity among these units and the interactions among them. However, the influence of lower-level heterogeneity on system-level metabolic rate is difficult to investigate, given the tightly integrated body plan of unitary organisms. In this context, social insects such as honeybees can serve as important model systems because unlike unitary organisms, these superorganisms can be taken apart and reassembled in different configurations to study metabolic rate and its various drivers at different levels of organization. This commentary discusses the background of such an approach and how combining it with artificial selection to generate heterogeneity in metabolic rate with an analytical framework to parse out the different mechanisms that contribute to the effects of heterogeneity can contribute to the various models of metabolic scaling. Finally, the absence of the typical allometric scaling relationship among different species of honeybees is discussed as an important prospect for deciphering the role of top-down ecological factors on metabolic scaling.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Intergenerational plasticity aligns with temperature-dependent selection on offspring metabolic rates
Authors: Pettersen Amanda K. , Metcalfe Neil B. , Seebacher Frank
Published: January 2024

Metabolic rates are linked to key life-history traits that are thought to set the pace of life and affect fitness, yet the role that parents may have in shaping the metabolism of their offspring to enhance survival remains unclear. Here, we investigated the effect of temperature (24°C or 30°C) and feeding frequency experienced by parent zebrafish (
Danio rerio
) on offspring phenotypes and early survival at different developmental temperatures (24°C or 30°C). We found that embryo size was larger, but survival lower, in offspring from the parental low food treatment. Parents exposed to the warmer temperature and lower food treatment also produced offspring with lower standard metabolic rates—aligning with selection on embryo metabolic rates. Lower metabolic rates were correlated with reduced developmental and growth rates, suggesting selection for a slow pace of life. Our results show that intergenerational phenotypic plasticity on offspring size and metabolic rate can be adaptive when parent and offspring temperatures are matched: the direction of selection on embryo size and metabolism aligned with intergenerational plasticity towards lower metabolism at higher temperatures, particularly in offspring from low-condition parents. These findings provide evidence for adaptive parental effects, but only when parental and offspring environments match.

This article is part of the theme issue ‘The evolutionary significance of variation in metabolic rates’.
Clinical and genomic features of a Listeria monocytogenes fatal case of meningitis in Madagascar
Authors: Rasoanandrasana Saïda , RABENANDRASANA Mamitina Alain Noah , Ravaoharisoa Lucia Mélanie , Randrianaivo Narindra , Rahajamanana Vonintsoa Lalaina , Rakotovao-Ravahatra’ Zafindrasoa Domoina , Moura Alexandra , Lecuit Marc , Rakotovao Andriamiadana Luc
Published: January 2024

Listeriosis constitutes a significant public health threat due to its high mortality rate. This study investigates the microbiological and genomic characteristics of Listeria monocytogenes isolates in Madagascar, where listeriosis is a notifiable disease. The analysis focuses on a fatal case of meningeal listeriosis in a 12-year-old child. Genomic analysis revealed a novel cgMLST type (L2-SL8-ST8-CT11697; CC8, serogroup Iia) with typical virulence and antibiotic resistance profiles. These isolates, unique to Madagascar, formed an independent clade in the phylogenetic tree. This study presents the first genomic characterization of Listeria isolates in Madagascar, highlighting the necessity of ongoing genomic surveillance to strengthen listeriosis prevention and control strategies in the region.
Cyclooxygenase-2/prostaglandin E2 pathway regulates infectious bronchitis virus replication in avian macrophages
Authors: Mahmoud Motamed Elsayed , Farooq Muhammad , Isham Ishara M. , Ali Ahmed , Hassan Mohamed S.H. , Herath-Mudiyanselage Heshanthi , Ranaweera Hiruni A. , Najimudeen Shahnas M. , Abdul-Careem Mohammad Faizal
Published: January 2024

Infectious bronchitis virus (IBV) is a significant respiratory pathogen that affects chickens worldwide. As an avian coronavirus, IBV leads to productive infection in chicken macrophages. However, the effects of IBV infection in macrophages on cyclooxygenase-2 (COX-2) expression are still to be elucidated. Therefore, we investigated the role of IBV infection on the production of COX-2, an enzyme involved in the synthesis of prostaglandin E2 (PGE2) in chicken macrophages. The chicken macrophage cells were infected with two IBV strains, and the cells and culture supernatants were harvested at predetermined time points to measure intracellular and extracellular IBV infection. IBV infection was quantified as has been the COX-2 and PGE2 productions. We found that IBV infection enhances COX-2 production at both mRNA and protein levels in chicken macrophages. When a selective COX-2 antagonist was used to reduce the COX-2 expression in macrophages, we observed that IBV replication decreased. When IBV-infected macrophages were treated with PGE2 receptor (EP2 and EP4) inhibitors, IBV replication was reduced. Upon utilizing a selective COX-2 antagonist to diminish PGE2 expression in macrophages, a discernible decrease in IBV replication was observed. Treatment of IBV-infected macrophages with a PGE2 receptor (EP2) inhibitor resulted in a reduction in IBV replication, whereas the introduction of exogenous PGE2 heightened viral replication. Additionally, pretreatment with a Janus-kinase two antagonist attenuated the inhibitory effect of recombinant chicken interferon (IFN)-γ on viral replication. The evaluation of immune mediators, such as inducible nitric oxide (NO) synthase (iNOS), NO, and interleukin (IL)−6, revealed enhanced expression following IBV infection of macrophages. In response to the inhibition of COX-2 and PGE2 receptors, we observed a reduction in the expressions of iNOS and IL-6 in macrophages, correlating with reduced IBV infection. Overall, IBV infection increased COX-2 and PGE2 production in addition to iNOS, NO, and IL-6 expression in chicken macrophages in a time-dependent manner. Inhibition of the COX-2/PGE2 pathway may lead to increased macrophage defence mechanisms against IBV infection, resulting in a reduction in viral replication and iNOS and IL-6 expressions. Understanding the molecular mechanisms underlying these processes may shed light on potential antiviral targets for controlling IBV infection.
Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR
Authors: Wang Lin , Dong Wenjuan , Yin Zheng , Sheng Jianting , Ezeana Chika F. , Yang Li , Yu Xiaohui , Wong Solomon SY , Wan Zhihao , Danforth Rebecca L. , Han Kun , Gao Dingcheng , Wong Stephen T. C.
Published: January 2024

Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov model’s attributes, reconstructs cellular lineage pathways, shedding light on the cell’s evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.
Gene-environment correlation: The role of family environment in academic development
Authors: Zhou Quan , Gidziela Agnieszka , Allegrini Andrea G. , Cheesman Rosa , Wertz Jasmin , Maxwell Jessye , Plomin Robert , Rimfeld Kaili , Malanchini Margherita
Published: January 2024

Academic achievement is partly heritable and highly polygenic. However, genetic effects on academic achievement are not independent of environmental processes. We investigated whether aspects of the family environment mediated genetic effects on academic achievement across development. Our sample included 5,151 children who participated in the Twins Early Development Study, as well as their parents and teachers. Data on academic achievement and family environments (parenting, home environments, and geocoded indices of neighbourhood characteristics) were available at ages 7, 9, 12 and 16. We computed educational attainment polygenic scores (PGS), and further separated genetic effects into cognitive and noncognitive PGS. Three core findings emerged. First, aspects of the family environment, but not the wider neighbourhood context, consistently mediated the PGS effects on achievement across development –accounting for up to 34.3% of the total effect. Family characteristics mattered beyond socio-economic status. Second, family environments were more robustly linked to noncognitive PGS effects on academic achievement than cognitive PGS effects. Third, when we investigated whether environmental mediation effects could also be observed when considering differences between siblings, adjusting for family fixed effects, we found that environmental mediation was nearly exclusively observed between families. This is consistent with the proposition that family environmental contexts contribute to academic development via passive gene-environment correlation processes, or genetic nurture. Our results show how parents tend to shape environments that foster their children’s academic development partly based on their own genetic disposition, particularly towards noncognitive skills, rather than responding to each child’s genetic disposition.
Agonist efficacy at the β2AR is driven by agonist-induced differences in receptor affinity for the Gsprotein, not ligand binding kinetics
Authors: Harwood Clare R. , Sykes David A. , Redfern-Nichols Theo , Ladds Graham , Briddon Stephen J. , Veprintsev Dmitry B.
Published: January 2024

Introduction

The β2-adrenoceptor (β2AR) is a class A G protein-coupled receptor (GPCR). It is therapeutically relevant in asthma, whereby β2AR agonists relieve bronchoconstriction. The β2AR is a prototypical GPCR for structural and biophysical studies. However, the molecular basis of agonist efficacy at the β2AR is not understood. We hypothesized that the kinetics of ligand binding and GPCR-G protein interactions could play a role in ligand efficacy. We characterised the molecular pharmacology of a range of β2AR agonists and examined the correlation between ligand and mini-Gsbinding kinetics and efficacy.

Methods

We used a Time-resolved Fluorescence Resonance Energy Transfer (TR-FRET) based competition ligand binding assay to measure the affinity and residence times of a range of β2AR agonists binding to the human β2AR. TR-FRET between Lumi4-Tb3+on the N terminus of the β2AR and fluorescent CA200693 (S)-propranolol-green was measured using a PHERAstar FSX. The ability of these β2AR agonists to activate the heterotrimeric Gsprotein was measured using the CASE Gsprotein biosensor. This assay senses a reduction in NanoBRET between the nano-luciferase (nLuc) donor on the Gα subunit and Venus acceptor on the Gψ, on receptor activation, quantified using the operational model of agonism. NanoBRET was also used to measure interactions between DDM solubilised β2AR-nLuc and purified Venus-mini-Gs. A large excess of unlabelled mini-Gswas used to dissociate the β2AR-nLuc: Venus-mini-Gscomplex.

Results

Characterisation of the molecular pharmacology of seven β2AR agonists showed a broad range of ligand binding affinities (pKi= 4.4 ± 0.09 to 9.2 ± 0.08) and kinetics parameters. There was no correlation between ligand residence times and their ability (logτ) to activate the Gsprotein (R2=0.26, p=0.29). However, there were statistically significant differences in the association rate (kon (fast)) (3.36±0.64×105to 9.19± 0.42×105) and affinity (Kd) values of mini-Gsbinding to the agonist-β2AR complex (pKd=6.0 to 6.7). Both an increase in ligand driven mini-Gskon(fast)rate and associated increase in mini-GspKdfor the receptor, were moderately correlated with efficacy (logτ) (R2=0.58 and R2=0.50 respectively).

Conclusions

These data support a model in which agonists of increased efficacy cause the β2AR to adopt a conformation that is more likely to recruit G protein. Conversely, these data did not support a role for agonist binding kinetics in the molecular basis of efficacy.
eMOSAIC: Multi-modal Out-of-distribution Uncertainty Quantification Streamlines Large-scale Polypharmacology
Authors: Badkul Amitesh , Xie Li , Zhang Shuo , Xie Lei
Published: January 2024

Polypharmacology has emerged as a new paradigm to discover novel therapeutics for unmet medical needs. Accurate, reliable and scalable predictions of protein-ligand binding affinity across multiple proteins are essential for polypharmacology. Machine learning is a promising tool for multi-target binding affinity predictions, often formulated as a multi-modal regression problem. Despite considerable efforts, three challenges remain: out-of-distribution (OOD) generalizations for compounds with new chemical scaffolds, uncertainty quantification of OOD predictions, and scalability to billions of compounds, which structure-based methods fail to achieve. To address aforementioned challenges, we propose a new model-agnostic anomaly detection-based uncertainty quantification method,embeddingMahalanobisOutlierScoring andAnomalyIdentification viaClustering (eMOSAIC). eMOSAIC uniquely quantifies distribution similarities or differences between the multi-modal representation of known cases and that of a new unseen one. We apply eMOSAIC to a multi-modal deep neural network model for multi-target ligand binding affinity predictions, leveraging a pre-trained strucrture-informed large protein language model. We extensively validate eMOSAIC in OOD settings, showing that it significantly outperforms state-of-the-art sequence-based deep learning and structure-based protein-ligand docking (PLD) methods by a large margin as well as existing uncertainty quantification methods. This finding highlights eMOSAIC’s potential for real-world polypharmacology and other applications.
Cooperation between Nodal and FGF signals regulates zebrafish cardiac cell migration and heart morphogenesis
Authors: Gonzalez Vanessa , Grant Meagan G. , Suzuki Makoto , Christophers Briana , Williams Jessica Rowland , Burdine Rebecca D.
Published: January 2024

Asymmetric vertebrate heart development is driven by an intricate sequence of morphogenetic cell movements, the coordination of which requires precise interpretation of signaling cues by heart primordia. Here we show that Nodal functions cooperatively with FGF during heart tube formation and asymmetric placement. Both pathways act as migratory stimuli for cardiac progenitor cells (CPCs), but FGF is dispensable for directing heart tube asymmetry, which is governed by Nodal. We further find that Nodal controls CPC migration by inducing left-right asymmetries in the formation of actin-based protrusions in CPCs. Additionally, we define a developmental window in which FGF signals are required for proper heart looping and show cooperativity between FGF and Nodal in this process. We present evidence FGF may promote heart looping through addition of the secondary heart field. Finally, we demonstrate that loss of FGF signaling affects proper development of the atrioventricular canal (AVC), which likely contributes to abnormal chamber morphologies in FGF-deficient hearts. Together, our data shed insight into how the spatiotemporal dynamics of signaling cues regulate the cellular behaviors underlying organ morphogenesis.

Summary statement

This study explores the cooperative and independent roles of Nodal and FGF signaling in generating heart asymmetry.
A precision microgel platform to direct vascular morphogenesisin vitro
Authors: Kühn S. , Magno V. , Zimmermann R. , Limasale Y. D. P. , Atallah P. , Stoppa A. , Männel M.J. , Thiele J. , Freudenberg U. , Werner C.
Published: January 2024

The dynamic organization of tissue development is reciprocally controlled by localized gradients of morphogens emanating from distinct clusters of cells that act as signaling centers1. While microgels2,3have shown promise to recapitulate this process in engineered tissue constructs, their capacity to tailor morphogen distribution in space and time remained limited4–7. Here, we introduce a library of sulfated glycosaminoglycan (sGAG)-based microgels that offer unprecedented control over morphogen affinity (μGUIDe, μGel Units to Instruct Development), thus enabling precise formation of concentration gradients. Multiparametric adjustment of the microgel charge patterns resulting from sGAG ionization was key to programmable morphogen release. The potential of our microgel system to guide tissue morphogenesis is demonstrated through the local administration of VEGF gradients in amicrogel-in-gelinvitrovasculogenesis model and in hiPSC-derived kidney organoid cultures. Our micromaterials-based methodology offers valuable new options to mimic and modulate morphogen signaling centers, thereby advancing tissue/organ development research.
mRNA initiation and termination are spatially coordinated
Authors: Calvo-Roitberg Ezequiel , Carroll Christine L. , Venev Sergey V. , Kim GyeungYun , Mick Steven T. , Dekker Job , Fiszbein Ana , Pai Athma A.
Published: January 2024

The expression of a precise mRNA transcriptome is crucial for establishing cell identity and function, with dozens of alternative isoforms produced for a single gene sequence. The regulation of mRNA isoform usage occurs by the coordination of co-transcriptional mRNA processing mechanisms across a gene. Decisions involved in mRNA initiation and termination underlie the largest extent of mRNA isoform diversity, but little is known about any relationships between decisions at both ends of mRNA molecules. Here, we systematically profile the joint usage of mRNA transcription start sites (TSSs) and polyadenylation sites (PASs) across tissues and species. Using both short and long read RNA-seq data, we observe that mRNAs preferentially using upstream TSSs also tend to use upstream PASs, and congruently, the usage of downstream sites is similarly paired. This observation suggests that mRNA 5’ end choice may directly influence mRNA 3’ ends. Our results suggest a novel “Positional Initiation-Termination Axis” (PITA), in which the usage of alternative terminal sites are coupled based on the order in which they appear in the genome. PITA isoforms are more likely to encode alternative protein domains and use conserved sites. PITA is strongly associated with the length of genomic features, such that PITA is enriched in longer genes with more area devoted to regions that regulate alternative 5’ or 3’ ends. Strikingly, we found that PITA genes are more likely than non-PITA genes to have multiple, overlapping chromatin structural domains related to pairing of ordinally coupled start and end sites. In turn, PITA coupling is also associated with fast RNA Polymerase II (RNAPII) trafficking across these long gene regions. Our findings indicate that a combination of spatial and kinetic mechanisms couple transcription initiation and mRNA 3’ end decisions based on ordinal position to define the expression mRNA isoforms.
The control of overt and covert attention across two nodes of the attention-control network
Authors: Polosecki Pablo , Steenrod Sara C. , Stemmann Heiko , Freiwald Winrich A.
Published: January 2024

Attention is a central cognitive capability whose focus is thought to be directed by a spatial map coding behavioral priority. Here we tested the three defining properties of priority map theory with electrophysiological recordings from two attentional control areas. Both areas, lateral intraparietal area LIP and dorsal posterior inferotemporal cortex PITd, selected behaviorally relevant locations even in the absence of visual stimuli (cognitive sustainment principle). Second, priority signals are thought to arise from the summation of multiple spatial signals (superposition principle). LIP approximated linear summation for visual stimuli, spatial attention, and eye movements, while PITd did not. Third, the same priority signal should guide different behaviors (agnosticity principle). LIP, instead, used separable processing channels for representing attentional focus and eye position, while PITd coded attentional focus only. Thus primate attentional control circuits implement multiple priority maps, whose functional diversity and dimensionality increase the computational capacity of attentional selection.

SIGNIFICANCE STATEMENT

A central theory of attention poses that the brain computes a priority map to highlight spatial locations of relevance for behavior. Here we tested the hypothesis and its key predictions about how priority signals are assembled and used, through electrophysiological single-unit recordings from two nodes of the attention control network, localized by functional magnetic resonance imaging. We found both areas to highlight locations even in the absence of a stimulus, and that each assembled spatial signals differently and provided spatial information in different forms. These findings force a revision of how and where spatial attention is controlled in the brain.
The sea urchinParacentrotus lividusorients to visual stimuli
Authors: Kirwan John D. , Li Tianshu , Ullrich-Lüter Jack , La Camera Giancarlo , Nilsson Dan-Eric , Arnone Maria Ina
Published: January 2024

Though lacking eyes, some sea urchins can see: Several species exhibit resolving vision, as distinct from mere light detection. How and where light is captured in the eyeless sea urchins, and how this information is integrated to elicit visual behaviour, remains a fascinating enigma. We assessed the spatial resolution of the sea urchinParacentrotus lividusin laboratory experiments using fifty adults from the Bay of Naples. This keystone species is an important grazer of the NE Atlantic and Mediterranean and a model system to study development.

We carried out behavioural trials in which individuals were placed in a submerged cylindrical arena to determine if they orient towards a visual stimulus on the arena wall, under diffuse, downwelling light. We adopted a novel isoluminant stimulus, necessitating vision of a given resolving power around the horizon to be detected. We tested individuals at five stimulus widths, including a uniform control. Animals oriented (upon clearing an obstacle) only to the widest stimuli (45 deg and above). This acuity may suffice for tasks such as finding nearby shelters or distant patches of habitat.

We modelled the visual and neuronal processes to recapitulate these responses inP. lividus, by fine-tuning the model of Li et al. (2022), as applied to the sea urchinDiadema africanum. While these species differ morphologically, the model robustly predicts angular sensitivity in keeping with the behavioural experiments. We find thatP. lividus(and likely many Echinacea) possesses coarse spatial vision and that the neurosensory model applies broadly to sea urchins.
Rabphilin-3A negatively regulates neuropeptide release, through its SNAP25 interaction
Authors: Abramian Adlin , Hoogstraaten Rein I. , Murphy Fiona H. , mcDaniel Kathryn F. , Toonen Ruud F. , Verhage Matthijs
Published: January 2024

Neuropeptides and neurotrophins are stored in and released from dense-core vesicles (DCVs). While DCVs and synaptic vesicles (SVs) share fundamental SNARE/SM proteins for exocytosis, a detailed understanding of DCV exocytosis remains elusive. We recently identified the RAB3-RIM1 pathway to be essential for DCV-, but not SV exocytosis, highlighting a significant distinction between the SV- and DCV secretory pathways. Whether RIM1 is the only RAB3 effector that is essential for DCV exocytosis is currently unknown. In this study, we show that rabphilin-3A (RPH3A), a known downstream effector of RAB3A, is a negative regulator of DCV exocytosis. Using live-cell imaging at single vesicle resolution with RPH3A-deficient hippocampal neurons, we show that DCV exocytosis increased 3-fold in the absence of RPH3A. RAB3A-binding deficient RPH3A lost its punctate distribution, but still restored DCV exocytosis to WT levels when re-expressed. SNAP25-binding deficient RPH3A did not rescue DCV exocytosis. In addition, we show that RPH3A did not travel with DCVs, but remained stationary at pre-synapses. RPH3A null neurons also had longer neurites, which was partly restored when ablating all regulated secretion with tetanus neurotoxin. Taken together, these results show that RPH3A negatively regulates DCV exocytosis, potentially also affecting neuron size. Furthermore, RAB3A interaction is required for the synaptic enrichment of RPH3A, but not for limiting DCV exocytosis. Instead, the interaction of RPH3A with SNAP25 is relevant for inhibiting DCV exocytosis.
Sequence clustering confounds AlphaFold2
Authors: Schafer Joseph W. , Chakravarty Devlina , Chen Ethan A. , Porter Lauren L.
Published: January 2024

Though typically associated with a single folded state, some globular proteins remodel their secondary and/or tertiary structures in response to cellular stimuli. AlphaFold21(AF2) readily generates one dominant protein structure for these fold-switching (a.k.a. metamorphic) proteins2, but it often fails to predict their alternative experimentally observed structures3,4. Wayment-Steele, et al. steered AF2 to predict alternative structures of a few metamorphic proteins using a method they call AF-cluster5. However, their Paper lacks some essential controls needed to assess AF-cluster’s reliability. We find that these controls show AF-cluster to be a poor predictor of metamorphic proteins. First, closer examination of the Paper’s results reveals that random sequence sampling outperforms sequence clustering, challenging the claim that AF-cluster works by “deconvolving conflicting sets of couplings.” Further, we observe that AF-cluster mistakes some single-folding KaiB homologs for fold switchers, a critical flaw bound to mislead users. Finally, proper error analysis reveals that AF-cluster predicts many correct structures with low confidence and some experimentally unobserved conformations with confidences similar to experimentally observed ones. For these reasons, we suggest using ColabFold6-based random sequence sampling7–augmented by other predictive approaches–as a more accurate and less computationally intense alternative to AF-cluster.
Single cell proteomics by mass spectrometry reveals deep epigenetic insight into the actions of an orphan histone deacetylase inhibitor
Authors: Orsburn Benjamin C.
Published: January 2024

Epigenetic programming has been shown to play a role in nearly every human system and disease where anyone has thought to look. However, the levels of heterogeneity at which epigenetic or epiproteomic modifications occur at single cell resolution across a population remains elusive. While recent advances in sequencing technology have allowed between 1 and 3 histone post-translational modifications to be analyzed in each single cell, over twenty separate chemical PTMs are known to exist, allowing thousands of possible combinations. Single cell proteomics by mass spectrometry (SCP) is an emerging technology in which hundreds or thousands of proteins can be directly quantified in typical human cells. As the proteins detected and quantified by SCP are heavily biased toward proteins of highest abundance, chromatin proteins are an attractive target for analysis. To this end, I applied SCP to the analysis of cancer cells treated with mocetinostat, a class specific histone deacetylase inhibitor. I find that 16 PTMs can be confidently identified and localized with high site specificity in single cells. In addition, the high abundance of histone proteins allows higher throughput methods to be utilized for SCP than previously described. While quantitative accuracy suffers when analyzing more than 700 cells per day, 9 histone proteins can be measured in single cells analyzed at even 3,500 cells per day, a throughput 10-fold greater than any previous report. In addition, the unbiased global approach utilized herein identifies a previously uncharacterized response to this drug through the S100-A8/S100-A9 protein complex partners. This response is observed in nearly every cell of the over 1,000 analyzed in this study, regardless of the relative throughput of the method utilized. While limitations exist in the methods described herein, current technologies can easily improve upon the results presented here to allow comprehensive analysis of histone PTMs to be performed in any mass spectrometry lab. All raw and processed data described in this study has been made publicly available through the ProteomeXchange/MASSIVE repository system as MSV000093434

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A Survey of theDesulfuromonadiacytochromome provides a glimpse of the unexplored diversity of multiheme cytochromes in nature
Authors: Soares Ricardo , Fonseca Bruno M. , Nash Benjamin W. , Paquete Catarina M. , Louro Ricardo O.
Published: January 2024

Multiheme cytochromes (MHC) provide prokaryotes with a broad metabolic versatility that contributes to their role in the biogeochemical cycling of the elements. However, MHC were isolated and studied in detail only from a limited number of species. To obtain a broader view of the diversity of MHC, we employed bioinformatics tools to study the cytochromome encoded in the genomes of theDesulfuromonadiaclass. We found that MHC predicted to be extracellular are the least conserved and present higher diversity. Although the most prevalent MHC have homologues already characterized, nearly half of the MHC families in theDesulforomonadiaclass have no known homologues and AlphaFold2 was employed to predict their 3D structures. This work illuminates for the first time the universe of experimentally uncharacterized cytochromes that are likely to contribute to the metabolic versatility and to the fitness ofDesulfuromonadiain diverse environmental conditions and to drive biotechnological applications.
COFFEE: Consensus Single Cell-Type Specific Inference for Gene Regulatory Networks
Authors: Lodi Musaddiq K , Chernikov Anna , Ghosh Preetam
Published: January 2024

The inference of gene regulatory networks (GRNs) is crucial to understanding the regulatory mechanisms that govern biological processes. GRNs may be represented as edges in a graph, and hence have been inferred computationally for scRNA-seq data. A wisdom of crowds approach to integrate edges from several GRNs to create one composite GRN has demonstrated improved performance when compared to individual algorithm implementations on bulk RNA-seq and microarray data. In an effort to extend this approach to scRNA-seq data, we present COFFEE (COnsensus single cell-type speciFic inFerence for gEnE regulatory networks), a Borda voting based consensus algorithm that integrates information from 10 established GRN inference methods. We conclude that COFFEE has improved performance across synthetic, curated and experimental datasets when compared to baseline methods. Additionally, we show that a modified version of COFFEE can be leveraged to improve performance on newer cell-type specific GRN inference methods. Overall, our results demonstrate that consensus based methods with pertinent modifications continue to be valuable for GRN inference at the single cell level.
Identification of Novel Biomarkers for Alzheimer’s Disease and Related Dementias Using Unbiased Plasma Proteomics
Authors: Lacar Benjamin , Ferdosi Shadi , Alavi Amir , Stukalov Alexey , Venkataraman Guhan R. , de Geus Matthijs , Dodge Hiroko , Wu Chao-Yi , Kivisakk Pia , Das Sudeshna , Guturu Harendra , Hyman Brad , Batzoglou Serafim , Arnold Steven E. , Siddiqui Asim
Published: January 2024

Alzheimer’s disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer’s Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The ProteographTMProduct Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.
HDAC inhibitor derivatives induce differentiation of leukemic cells through two distinct and separable mechanisms
Authors: Kumar Purnima , Josa-Culleré Laia , Jackson Thomas R. , Bataille Carole J. R. , Vyas Paresh , Milne Thomas A. , Russell Angela J.
Published: January 2024

Acute myeloid leukaemia (AML) is a haematopoietic malignancy comprising different genetic subtypes with a common hallmark of differentiation arrest. In abnormal haematopoiesis, overcoming the differentiation blockade has emerged as an attractive therapeutic strategy. In a screen with genetically distinct AML cell lines, histone deacetylase inhibitors (HDACis) were observed to cause an upregulation in the expression of CD11b, a myeloid differentiation marker. These caused changes in cell morphology, block in proliferation, and cell cycle arrest at the G1 phase. To gain insights onto the mechanism of these compounds, we planned to prepare inactive probes devoid of the zinc binding motif. However, these compounds were unexpectedly still able to initiate differentiation, albeit through a distinct target and via a G2 arrest. Subsequent RNA sequencing studies supported the differentiation phenotype for the HDACis and highlighted the role of cell cycle regulatory kinases for the effect observed in the probe molecules. We then showed that these inhibit Aurora A and GSK3α kinases, suggesting their potential as therapeutic targets for differentiation therapy in AML. Our work supports the importance of properly validating inactive tool compounds and their potential to identify novel targets.
Small Intestinal Goblet Cells Control Humoral Immune Responses and Mobilization During Enteric Infection
Authors: Kulkarni Devesha H. , Talati Khushi , Joyce Elisabeth L. , Kousik Hrishi , Harris Dalia L. , Floyd Alexandria N. , Vavrinyuk Vitaly , Barrios Bibianna , Udayan Sreeram , McDonald Keely , John Vini , Hsieh Chyi-Song , Newberry Rodney D.
Published: January 2024

Humoral immune responses within the gut play diverse roles including pathogen clearance during enteric infections, maintaining tolerance, and facilitating the assemblage and stability of the gut microbiota. How these humoral immune responses are initiated and contribute to these processes are well studied. However, the signals promoting the expansion of these responses and their rapid mobilization to the gut mucosa are less well understood. Intestinal goblet cells form goblet cell-associated antigen passages (GAPs) to deliver luminal antigens to the underlying immune system and facilitate tolerance. GAPs are rapidly inhibited during enteric infection to prevent inflammatory responses to innocuous luminal antigens. Here we interrogate GAP inhibition as a key physiological response required for effective humoral immunity. Independent of infection, GAP inhibition resulted in enrichment of transcripts representing B cell recruitment, expansion, and differentiation into plasma cells in the small intestine (SI), which were confirmed by flow cytometry and ELISpot assays. Further we observed an expansion of isolated lymphoid follicles within the SI, as well as expansion of plasma cells in the bone marrow upon GAP inhibition. S1PR1-induced blockade of leukocyte trafficking during GAP inhibition resulted in a blunting of SI plasma cell expansion, suggesting that mobilization of plasma cells from the bone marrow contributes to their expansion in the gut. However, luminal IgA secretion was only observed in the presence ofS. typhimuriuminfection, suggesting that although GAP inhibition mobilizes a mucosal humoral immune response, a second signal is required for full effector function. Overriding GAP inhibition during enteric infection abrogated the expansion of laminar propria IgA+ plasma cells. We conclude that GAP inhibition is a required physiological response for efficiently mobilizing mucosal humoral immunity in response to enteric infection.