bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of anti-freezing proteins from their evolutionary profile
Authors: Kumar Nishant , Choudhury Shubham , Bajiya Nisha , Patiyal Sumeet , Raghava Gajendra P. S.
Published: May 2024

1.

Prediction of antifreeze proteins (AFPs) holds significant importance due to their diverse applications in healthcare. An inherent limitation of current AFP prediction methods is their reliance on unreviewed proteins for evaluation. This study evaluates proposed and existing methods on an independent dataset containing 81 AFPs and 73 non-AFPs obtained from Uniport, which have been already reviewed by experts. Initially, we constructed machine learning models for AFP prediction using selected composition-based protein features and achieved a peak AUC of 0.90 with an MCC of 0.69 on the independent dataset. Subsequently, we observed a notable enhancement in model performance, with the AUC increasing from 0.90 to 0.93 upon incorporating evolutionary information instead of relying solely on the primary sequence of proteins. Furthermore, we explored hybrid models integrating our machine learning approaches with BLAST-based similarity and motif-based methods. However, the performance of these hybrid models either matched or was inferior to that of our best machine-learning model. Our best model based on evolutionary information outperforms all existing methods on independent/validation dataset. To facilitate users, a user-friendly web server with a standalone package named “AFPropred” was developed (https://webs.iiitd.edu.in/raghava/afpropred).

Highlights

Prediction of antifreeze proteins with high precision

Evaluation of prediction models on an independent dataset

Machine learning based models using sequence composition

Evolutionary information based prediction models

A webserver for predicting, scanning, and designing AFPs.

Author’s Biography

Nishant Kumar is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.

Shubham Choudhury is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India

Nisha Bajiya is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India

Sumeet Patiyal is currently working as a postdoctoral visiting fellow Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Gajendra P. S. Raghava is currently working as Professor and Head of Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Venom-inspired somatostatin receptor 4 (SSTR4) agonists as new drug leads for peripheral pain conditions
Authors: Bjørn-Yoshimoto Walden E. , Ramiro Iris Bea L. , Koch Thomas Lund , Engholm Ebbe , Yeung Ho Yan , Sørensen Kasper K. , Goddard Carolyn M. , Jensen Kathrine L. , Smith Nicholas A. , Martin Laurent F. , Smith Brian J. , Madsen Kenneth L. , Jensen Knud J. , Patwardhan Amol , Safavi-Hemami Helena
Published: May 2024

Persistent pain affects one in five people worldwide, often with severely debilitating consequences. Current treatment options, which can be effective for mild or acute pain, are ill-suited for moderate-to-severe persistent pain, resulting in an urgent need for new therapeutics. In recent years, the somatostatin receptor 4 (SSTR4), which is expressed in sensory neurons of the peripheral nervous system, has emerged as a promising target for pain relief. However, the presence of several closely related receptors with similar ligand-binding surfaces complicates the design of receptor-specific agonists. In this study, we report the discovery of a potent and selective SSTR4peptide, consomatin Fj1, derived from extensive venom gene datasets from marine cone snails. Consomatin Fj1 is a mimetic of the endogenous hormone somatostatin and contains a minimized binding motif that provides stability and drives peptide selectivity. Peripheral administration of synthetic consomatin Fj1 provided analgesia in mouse models of postoperative and neuropathic pain. Using structure-activity studies, we designed and functionally evaluated several Fj1 analogs, resulting in compounds with improved potency and selectivity. Our findings present a novel avenue for addressing persistent pain through the design of venom-inspired SSTR4-selective pain therapeutics.

One Sentence Summary

Venom peptides from predatory marine mollusks provide new leads for treating peripheral pain conditions through a non-opioid target.
Megabarcoding reveals a tale of two very different dark taxa along the same elevational gradient
Authors: Pei Wenya , Feng Vivian , Hansen Aslak Kappel , Yan Liping , Srivathsan Amrita , Xu Wentian , Sun Haoran , Yang Jun , Zhang Xiaochen , Yang Nan , Yuan Qiuyue , Zhang Dong , Meier Rudolf
Published: May 2024

Our planet is entering the sixth mass extinction without detailed spatio-temporal distribution and abundance information for most insect species. Particularly lacking is this information for dark taxa although they contain most animal species. This problem can be addressed with high-throughput single specimen barcoding (megabarcoding), but it remain unknown to what extent one dark taxon can be used as a proxy for another because of similar biodiversity patterns. This is here tested and we show that two Diptera taxa (Phoridae, Mycetophilidae) have very different spatio-temporal distributions across the same elevational gradient. We applied COI megabarcoding to samples collected every 14 days over three seasons at six elevations (800 to 1,800 m) in a temperate forest ecosystem in Northern China (Baihua Mountain Reserve). Elevation, precipitation, and temperature were used as environmental variables to understand the data obtained for 17,179 specimens representing 492 mOTUs of Phoridae and 2,281 specimens of 148 mOTUs of Mycetophilidae. Congruent is that the alpha diversity for both taxa increased in the summer and there is evidence for a mid-domain effect and phylogenetic clustering in high elevations. However, the extent and pattern of seasonal variation differed considerably. Phorid communities exhibited shifts between spring, summer and autumn seasons, but surprisingly little difference between elevations. In contrast, mycetophilid communities were structured along the elevational gradient and dependent on precipitation. Our study highlights the urgent need for obtaining detailed spatio-temporal information for the most diverse dark taxa, but also illustrates that these data can be readily obtained with megabarcoding.
Modeling mTORopathy-related epilepsy in cultured murine hippocampal neurons using the multi-electrode array
Authors: Heuvelmans Anouk M. , Onori Martina Proietti , Frega Monica , de Hoogen Jeffrey D. , Nel Eveline , Elgersma Ype , van Woerden Geeske M.
Published: May 2024

The mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway is a ubiquitous cellular pathway. mTORopathies, a group of disorders characterized by hyperactivity of the mTORC1 pathway, illustrate the prominent role of the mTOR pathway in disease pathology, often profoundly affecting the central nervous system. One of the most debilitating symptoms of mTORopathies is drug-resistant epilepsy, emphasizing the urgent need for a deeper understanding of disease mechanisms to develop novel anti-epileptic drugs. In this study, we explored the multiwell Multi-electrode array (MEA) system as a tool to identify robust network activity parameters in an approach to model mTORopathy-related epilepsyin vitro. To this extent, we cultured mouse primary hippocampal neurons on the multiwell MEA to identify robust network activity phenotypes in mTORC1-hyperactive neuronal networks. mTOR-hyperactivity was induced either through deletion ofTsc1or overexpression of a constitutively active RHEB variant identified in patients, RHEBp.P37L. mTORC1 dependency of the phenotypes was assessed using rapamycin, and vigabatrin was applied to treat epilepsy-like phenotypes. We show that hyperactivity of the mTORC1 pathway leads to aberrant network activity. In both theTsc1-KO and RHEB-p.P37L models, we identified changes in network synchronicity, rhythmicity, and burst characteristics. The presence of these phenotypes is prevented upon early treatment with the mTORC1-inhibitor rapamycin. Application of rapamycin in mature neuronal cultures could only partially rescue the network activity phenotypes. Additionally, treatment with the anti-epileptic drug vigabatrin reduced network activity and restored burst characteristics. Taken together, we showed that mTORC1-hyperactive neuronal cultures on the multiwell MEA system present reliable network activity phenotypes that can be used as an assay to explore the potency of new drug treatments targeting epilepsy in mTORopathy patients and may give more insights into the pathophysiological mechanisms underlying epilepsy in these patients.

ABBREVIATIONS

AED, anti-epileptic drug, CoVNIBI, coefficient of variance of NIBI, CTR, control transduced cultures, DIV, days in vitro, DMEM, Dulbecco’s modified Eagle medium, DMSO, dimethyl sulfoxide, GABA, gamma-aminobutyric acidergic, GAPDH, Glyceraldehyde-3-Phosphate Dehydrogenase, iPSC, induced pluripotent stem cell, KO, knock-out, LV, lentivirus, MEA, multi-electrode array, MFR, mean firing rate, mTORC1, mechanistic target of rapamycin complex 1, NB, network burst, NBC, network burst composition, NBD, network burst duration, NBM, neurobasal medium, NBR, network burst rate, NIBI, network interburst interval, NT, non-transduced, RHEB, Ras-homolog enriched in brain, %RS, percentage of random spikes, TBS, tris buffered saline, TSC, Tuberous sclerosis complex, WT, wildtype
Distinct neural computations scale the violation of expected reward and emotion in social transgressions
Authors: Xu Ting , Zhang Lei , Zhou Feng , Fu Kun , Gan Xianyang , Chen Zhiyi , Zhang Ran , Lan Chunmei , Wang Lan , Kendrick Keith M , Yao Dezhong , Becker Benjamin
Published: May 2024

Traditional decision-making models conceptualize humans as optimal learners aiming to maximize outcomes by leveraging reward prediction errors (PE). While violated emotional expectations (emotional PEs) have recently been formalized, the underlying neurofunctional basis and whether it differs from reward PEs remain unclear. Using a modified fMRI Ultimatum Game on n=43 participants we modelled reward and emotional PEs in response to unfair offers and subsequent punishment decisions. Computational modelling revealed distinct contributions of reward and emotional PEs to punishment decisions, with reward PE exerting a stronger impact. This process was neurofunctionally dissociable such that (1) reward engaged the dorsomedial prefrontal cortex while emotional experience recruited the anterior insula, (2) multivariate decoding accurately separated reward and emotional PEs. Predictive neural expressions of reward but not emotional PEs in fronto-insular systems predicted neurofunctional and behavioral punishment decisions. Overall, these findings suggest distinct neurocomputational processes underlie reward and emotional PEs which uniquely impact social decisions.
Frequency-dependence in multidimensional diffusion-relaxation correlation MRI of the brain: overfitting or meaningful parameter?
Authors: Yon Maxime , Narvaez Omar , Martin Jan , Jiang Hong , Bernin Diana , Forssell-Aronsson Eva , Laun Frederik , Sierra Alejandra , Topgaard Daniel
Published: May 2024

Time- or frequency-dependent (“restricted”) diffusion potentially provides useful information about cellular-scale structures in the brain but is challenging to interpret because of the intravoxel tissue heterogeneity. Frequency-dependence was recently incorporated in a multidimensional diffusion-relaxation correlation MRI framework relying on tensor-valued diffusion encoding at multiple frequencies, as well as variable echo and repetition times, to give model-free characterization of intravoxel heterogeneity by Monte Carlo data inversion into nonparametric distributions of frequency-dependent diffusion tensors and nuclear relaxation rates. While microimaging equipment with high-amplitude magnetic field gradients allows exploration of frequencies from tens to hundreds of Hz, clinical scanners with more moderate gradient capabilities are limited to a narrow frequency range, which may be insufficient to observe effects of restricted diffusion for brain tissues. We here investigate the effects of including or omitting frequency-dependence in the data inversion from isotropic and anisotropic liquids, excised tumor tissue, ex vivo mouse brain, and in vivo human brain. For microimaging measurements covering a wide frequency range, from 35 to 320 Hz atb-values over 4·109sm−2, the inclusion of frequency-dependence drastically reduces the fit residuals and avoids bias in the diffusion metrics for tumor and brain voxels with micrometer-scale structures. Conversely, for the case of in vivo human brain investigated in the narrow frequency range from 5 to 11 Hz atb= 3·109sm−2, analyses with and without inclusion of frequency-dependence yield similar fit residuals and diffusion metrics for all voxels. These results indicate that frequency-dependent inversion may be generally applied to diffusion-relaxation correlation MRI data with and without observable effects of restricted diffusion.
DNA Calorimetric Force Spectroscopy at Single Base Pair Resolution
Authors: Rissone P. , Rico-Pasto M. , Smith S. B. , Ritort F.
Published: May 2024

DNA hybridization is a fundamental reaction with wide-ranging applications in biotechnology. The nearest-neighbor (NN) model provides the most reliable description of the energetics of duplex formation. Most DNA thermodynamics studies have been done in melting experiments in bulk, of limited resolution due to ensemble averaging. In contrast, single-molecule methods have reached the maturity to derive DNA thermodynamics with unprecedented accuracy. We combine single-DNA mechanical unzipping experiments using a temperature jump optical trap with machine learning methods and derive the temperature-dependent DNA energy parameters of the NN model. In particular, we measure the previously unknown ten heat-capacity change parametersΔCp, relevant for thermodynamical predictions throughout the DNA stability range. Calorimetric force spectroscopy establishes a groundbreaking methodology to accurately study nucleic acids, from chemically modified DNA to RNA and DNA/RNA hybrid structures.
Metabolic readouts of tumor instructed normal tissues (TINT) identify aggressive prostate cancer subgroups for tailored therapy
Authors: Dudka Ilona , Wikström Pernilla , Bergh Anders , Gröbner Gerhard
Published: May 2024

Background

Prostate cancer (PC) diagnosis relies on histopathological examination of prostate biopsies, which is restricted by insufficient sampling of all tumors present. Including samples from non-PC but tumor instructed normal tissues (TINT) may increase the diagnostic power by exploring the adaptive responses in benign tissues near tumors.

Methods

Here, we applied high-resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) to identify metabolomic biomarkers with high diagnostic value in benign prostate tissues near low/high-grade tumors.

Results

Benign samples near high-grade tumors (B ISUP 3+4) exhibit altered metabolic profiles compared to those close to low-grade tumors (B ISUP 1+2). The levels of six metabolites were significantly different between the two groups; myo-inositol, lysine, serine and combined signal of lysine/leucine/arginine were increased in benign samples near high-grade tumors (B ISUP 3+4) compared to near low-grade tumors (B ISUP 1+2), while levels of ethanolamine and lactate decreased. Additionally, we revealed metabolic differences in non-cancer tissues as a function of their distance to the nearest tumor. Eight metabolites (glutathione, glutamate, combined signal of glutamate/glutamine - glx, glycerol, inosine, ethanolamine, serine and arginine) significantly differentiated between benign tissue located close to the tumor (d ≤ 5 mm) compared to those far away (d ≥ 1 cm).

Conclusions

Our HR MAS NMR-based approach identified metabolic signatures in prostate biopsies that reflect the response of benign tissues to the presence of nearby located tumors in the same prostate and confirmed the power of the TINT concept for improved PC diagnostics and understanding of tumor-tissue interactions.
Modelling sex-specific whole-body metabolic responses to feeding and fasting
Authors: Abo Stéphanie M. C. , Layton Anita T.
Published: May 2024

Men exhibit a preference for carbohydrate metabolism, whereas women tend to favor lipid metabolism. Significant sex-based differences in energy oxidation are evident across various metabolic states, including fasting and feeding. While some of these differences can be attributed to variations in body composition—such as increased fat mass in women and higher muscle mass in men—there are also inherent disparities in metabolic fluxes. For instance, women exhibit increased rates of lipolysis independent of body composition. However, there remain gaps in our understanding of how sex influences the metabolism of specific organs and how these differences manifest at the systemic level. To address some of these gaps, we developed a sex-specific, whole-body, multi-scale model of metabolism during feeding and fasting. Our model represents healthy young adults (male and female) and integrates cellular metabolism in organs with whole-body responses following various mixed meals, particularly high-carbohydrate and high-fat meals. We explored sex-related variations in metabolic responses during both the absorptive and postabsorptive phases following meals. Our model predicted that sex-related metabolic differences observed at the systemic level are driven by variations in nutrient storage and oxidation patterns in the liver, skeletal muscle, and adipose tissue. We hypothesized that sex differences in hepatic glucose output during short-term fasts are partly influenced by variations in free fatty acids, glycerol, and glycogen handling. We also identified a candidate mechanism, possibly more prevalent in the female liver, where lipids are redirected toward carbohydrate metabolism to support hepatic glucose production. Integrating sex-specific data and parameters into multi-scale frameworks holds promise for enhancing our understanding of human metabolism and its modulation by sex.

Author summary

Men and women exhibit different metabolic preferences, with men favoring carbohydrate metabolism and women favoring lipid metabolism. These differences impact energy usage during fasting and feeding, influenced by body composition and inherent metabolic variations. However, there remain gaps in our understanding of how sex influences the metabolism of specific organs and how these differences manifest at the systemic level. To address these gaps, we developed a sex-specific whole-body metabolic model, representing healthy young adults. Our model explores how men and women metabolize mixed meals, especially high-carbohydrate and high-fat meals. We found that sex-related metabolic variations arise from differences in nutrient storage and utilization in key organs like the liver, muscles, and fat tissue. We propose that variations in free fatty acids and glycogen handling contribute to differences in hepatic glucose output between men and women during short-term fasting. Integrating sex-specific data into metabolic models can enhance our understanding of human metabolism and its modulation by sex.
Predictive modeling of microbial data with interaction effects
Authors: Stadler Mara , Bien Jacob , Müller Christian L.
Published: May 2024

Microbial interactions are of fundamental importance for the functioning and the maintenance of microbial communities. Deciphering these interactions from observational data or controlled lab experiments remains a formidable challenge due to their context-dependent nature, i.e., their dependence on (a)biotic factors, host characteristics, and overall community composition. Here, we present a statistical regression framework for microbial data that allows the inclusion and parsimonious estimation of species interaction effects for an outcome of interest. We adapt the penalized quadratic interaction model to accommodate common microbial data types as predictors, including microbial presence-absence data, relative (or compositional) abundance data from microbiome surveys, and quantitative (absolute abundance) microbiome data. We study the effect of including hierarchical interaction constraints and stability-based model selection on model performance and propose novel interaction model formulations for compositional data. To illustrate our framework’s versatility, we consider prediction tasks across a wide range of microbial datasets and ecosystems, including metabolite production in model communities in designed experiments and environmental covariate prediction from marine microbiome data. While we generally observe superior predictive performance of our interaction models, we also assess limits of these models in presence of extreme data sparsity and with respect to data type. On a large-scale gut microbiome cohort data, we identify sparse family-level interaction models that accurately predict the abundance of antimicrobial resistance genes, enabling the formulation of novel biological hypotheses about microbial community interactions and antimicrobial resistance.
Neural bases of proactive and predictive processing of meaningful sub-word units in speech comprehension
Authors: Matar Suhail , Marantz Alec
Published: May 2024

To comprehend speech, human brains identify meaningful units in the speech stream. But whereas the English ‘She believed him.’ has 3 words, the Arabic equivalent ‘ṣaddaqathu.’ is a single word with 3 meaningful sub-word units, called morphemes: a verb stem (‘ṣaddaqa’), a subject suffix (‘-t-’), and a direct object pronoun (‘-hu’). It remains unclear whether and how the brain processes morphemes, above and beyond other language units, during speech comprehension. Here, we propose and test hierarchically-nested encoding models of speech comprehension: a NAÏVE model with word-, syllable-, and sound-level information; a BOTTOM-UP model with additional morpheme boundary information; and PREDICTIVE models that process morphemes before these boundaries. We recorded magnetoencephalography (MEG) data as participants listened to Arabic sentences like ‘ṣaddaqathu.’. A temporal response function (TRF) analysis revealed that in temporal and left inferior frontal regions PREDICTIVE models outperform the BOTTOM-UP model, which outperforms the NAÏVE model. Moreover, verb stems were either length-AMBIGUOUS (e.g., ‘ṣaddaqa’ could initially be mistaken for the shorter stem ‘ṣadda’=‘blocked’) or length-UNAMBIGUOUS (e.g., ‘qayyama’=‘evaluated’ cannot be mistaken for a shorter stem), but shared a uniqueness point, at which stem identity is fully disambiguated. Evoked analyses revealed differences between conditions before the uniqueness point, suggesting that, rather than await disambiguation, the brain employs PROACTIVE PREDICTIVE strategies, processing the accumulated input as soon as any possible stem is identifiable, even if not unique. These findings highlight the role of morpheme processing in speech comprehension, and the importance of including morpheme-level information in neural and computational models of speech comprehension.

Significance statement

Many leading models of speech comprehension include information about words, syllables and sounds. But languages vary considerably in the amount of meaning packed into word units. This work proposes speech comprehension models with information about meaningful sub-word units, called morphemes (e.g., ‘bake-’ and ‘-ing’ in ‘baking’), and shows that they explain significantly more neural activity than models without morpheme information. We also show how the brain predictively processes morphemic information. These findings highlight the role of morphemes in speech comprehension and emphasize the contributions of morpheme-level information-theoretic metrics, like surprisal and entropy. Our models can be used to update current neural, cognitive, and computational models of speech comprehension, and constitute a step towards refining those models for naturalistic, connected speech.
Oligomerization and cellular localization of SLC26A11
Authors: Bungert-Plümke Stefanie , Guzman Raul E. , Fahlke Christoph
Published: May 2024

The solute carrier family 26 (SLC26) encompasses multifunctional anion exchangers in all kingdoms of life. SLC26 proteins are known to assemble as dimers, and co-expression of multiple isoforms in certain cells raises the question whether different SLC26s can assemble into hetero-dimers. We focused on SLC26A11, a broadly expressed isoform that differs from other isoforms in its subcellular localization. Whereas the vast majority of SLC26-FP fusion proteins, i.e. SLC26A1, SLC26A2, SlC26A3, SLC26A4/pendrin, SLC26A5/prestin, SLC26A6, SlC26A7, and SLC26A9, localize to the surface membrane of transfected mammalian cells, we found exclusive lysosomal localization of SLC26A11. Renal collecting duct intercalated cells express SLC26A11 together with SLC26A4/pendrin and SLC26A7, and we therefore tested whether heterodimerization between these transporters might result in SLC26 transporter re-localization. Neither in HEK293T nor in immortalized intercalated cells co-expressing SLC26A11 with SLC26A4/pendrin or with SLC26A7, changes of SLC26A11 localization were observed. Moreover, native gel electrophoresis did not provide any evidence for heterodimerization of these isoforms. We next tested heterodimerization of SLC26A11 with SLC26A1, SLC26A2, SLC26A6 or SLC26A9 via co-expression in HEK293T cells and confocal imaging. For all combinations, no changes in subcellular distribution were observed. We conclude that SLC26A11 does not heterodimerize with other SLC26 proteins, and that heterodimerization does not target SLC26A11 to cellular surface membranes.
Crystallographic fragment screen of Enterovirus D68 3C protease and iterative design of lead-like compounds using structure-guided expansions
Authors: Lithgo Ryan M. , Tomlinson Charles W.E. , Fairhead Michael , Winokan Max , Thompson Warren , Wild Conor , Aschenbrenner Jasmin Cara , Balcomb Blake H. , Marples Peter G. , Chandran Anu V , Golding Mathew , Koekemoer Lizbe , Williams Eleanor P. , Wang SiYl , Ni Xiaomin , MacLean Elizabeth , Giroud Charline , Zarganes-Tzitzikas Tryfon , Godoy Andre Schutzer , Xavier Mary-Ann , Walsh Martin , Fearon Daren , von Delft Frank
Published: May 2024

The development of effective broad-spectrum antivirals forms an important part of preparing for future pandemics. One cause for concern is the currently emerging pathogenEnterovirus D68(EV-D68) which primarily spreads through respiratory routes causing mostly mild to severe respiratory illness but, in severe cases, acute flaccid myelitis. The 3C protease of EV-D68 (3Cpro) is a potential target for the development of antiviral drugs due to its essential role in the viral life cycle and high sequence conservation amongst family members. In this study, we describe the identification of fragments which bind to3Cprousing crystallographic screening and the expansion of these into more lead-like compounds. The hits revealed interesting directions for hit-to-lead progression, specifically the importance of the pocket occupied by the conserved glutamine sidechain of the substrates and the interactions formed. Additionally, two pockets could be joined by not following the backbone of the native substrates, thus circumventing the screening issues arising from the flexibility of the catalytic triad. These observations of the novel binding modes of the chemical matter found by this screen can help shape future drug design campaigns against 3C proteases.
Tau filaments with the Alzheimer fold in cases withMAPTmutations V337M and R406W
Authors: Qi Chao , Lövestam Sofia , Murzin Alexey G. , Peak-Chew Sew , Franco Catarina , Bogdani Marika , Latimer Caitlin , Murrell Jill R. , Cullinane Patrick W. , Jaunmuktane Zane , Bird Thomas D. , Ghetti Bernardino , Scheres Sjors H.W. , Goedert Michel
Published: May 2024

Frontotemporal dementia (FTD) and Alzheimer’s disease are the most common forms of early-onset dementia. Dominantly inherited mutations inMAPT, the microtubule-associated protein tau gene, cause FTD and parkinsonism linked to chromosome 17 (FTDP-17). Individuals with FTDP-17 develop abundant filamentous tau inclusions in brain cells. Here we used electron cryo-microscopy to determine the structures of tau filaments from the brains of individuals withMAPTmutations V337M and R406W. Both mutations gave rise to tau filaments with the Alzheimer fold, which consisted of paired helical filaments in all V337M and R406W cases and of straight filaments in two V337M cases. We also identified a new assembly of the Alzheimer fold into triple tau filaments in a V337M case. Filaments assembled from recombinant tau(297-391) with mutation V337M had the Alzheimer fold and showed an increased rate of assembly.
“A Low-Cost Microfluidics System for Light Microscopy Experiments”
Authors: Harrison Logan M. , Brisard Benjamin M. , Cashwell Kylie D. , Mulkey Aaron L. , Schmidt Cameron A.
Published: May 2024

Microfluidics devices are powerful tools for studying dynamic processes in live cells, especially when used in conjunction with light microscopy. There are many applications of microfluidics devices including recording dynamic cellular responses to small molecules or other chemical conditions in perfused media, monitoring cell migration in constrained spaces, or collecting media perfusate for the study of secreted compounds in response to experimental inputs/manipulations. Here we describe a configurable low-cost (channel-based) microfluidics platform for live-cell microscopy, intended to be useful for experiments that require more precision/flexibility than simple rubber spacers, but less precision than molded elastomer-based platforms. The materials are widely commercially available, low-cost, and device assembly takes only minutes.
New insights into the echinocandin resistance inCandidaspp. in the clinical setting
Authors: Gedeon Antoine , Kalboussi Yasmine , Bigot Jeanne , Le Vicky , Dannaoui Eric , Vellaissamy Sandra , Antignac Marie , Petrella Stéphanie , Hennequin Christophe , Guitard Juliette
Published: May 2024

Despite a huge consumption of echinocandins, the emergence of resistance inCandida spphas remained overall limited. Here, we depicted the epidemiology ofCandidaspp in our center face to the echinocandins’ consumption. We postulate new hypotheses that may explain the shaping of candines resistance in the clinical setting. Epidemiology ofCandidainfections and echinocandin consumption were evaluated in our center over 12 years (2006-2018). Glucan synthase genes (fks1, fks2)were sequenced. Thein vitrofitness was assessed for couple of isogenic strains, of which one was resistant. Finally, the modelling ofCandidaFKS proteins was realized. Despite a three-fold increase in echinocandin consumption, no significant emergence of resistance was observed. InCandida albicans, fks1mutations affect the three-dimensional conformation of the glucan synthase, which may result in altered export of the glucan chain, which could explain the observed reduced fitness. In contrast, cross-complementation between FKS1 and FKS2 inNakaseomyces glabratusmight circumvent the negative impact on fitness.

Conclusions

Our results support the fact thatN. glabratus is more prone to the spread of echinocandin-resistant strains. The link between mutations in the glucan synthase and fitness ofCandidastrains might explain the difference in the species-specific emergence of echinocandins-resistant strains.
DeepKin: precise estimation of in-depth relatedness and its application in UK Biobank
Authors: Zhang Qi-Xin , Jayasinghe Dovini , Lee Sang Hong , Xu Hai-Ming , Chen Guo-Bo
Published: May 2024

Accurately estimating relatedness between samples is crucial in genetics and epidemiological analysis. Using genome-wide single nucleotide polymorphisms (SNPs), it is now feasible to measure realized relatedness even in the absence of pedigree. However, the sampling variation in SNP-based measures and factors affecting method-of-moments relatedness estimators have not been fully explored, whilst static cut-off thresholds have traditionally been employed to classify relatedness levels for decades. Here, we introduce the deepKin framework as a moment-based relatedness estimation and inference method that incorporates data-specific cut-off threshold determination. It addresses the limitations of previous moment estimators by leveraging the sampling variance of the estimator to provide statistical inference and classification. Key principles in relatedness estimation and inference are provided, including inferring the critical value required to reject the hypothesis of unrelatedness, which we refer to as the deepest significant relatedness, determining the minimum effective number of markers, and understanding the impact on statistical power. Through simulations, we demonstrate that deepKin accurately infers both unrelated pairs and relatives with the support of sampling variance. We then apply deepKin to two subsets of the UK Biobank dataset. In the 3K Oxford subset, tested with four sets of SNPs, the SNP set with the largest effective number of markers and correspondingly the smallest expected sampling variance exhibits the most powerful inference for distant relatives. In the 430K British White subset, deepKin identifies 212,120 pairs of significant relatives and classifies them into six degrees. Additionally, cross-cohort significant relative ratios among 19 assessment centers located in different cities are geographically correlated, while within-cohort analyses indicate both an increase in close relatedness and a potential increase in diversity from north to south throughout the UK. Overall, deepKin presents a novel framework for accurate relatedness estimation and inference in biobank-scale datasets. For biobank-scale application we have implemented deepKin as an R package, available in the GitHub repository (https://github.com/qixininin/deepKin).
Taxonomic Treatment ofBlighiaK.D.Koenig occurring in Ghana
Authors: Larbi Samuel , Fatah Lateef Hanan Abdul , Anum Bismark , Williams Benjamin Darko
Published: May 2024

Blighia, a genus consisting of trees in the Sapindaceae, is found in sub-Saharan Africa and other parts of the world. It is characterized by three species globally:B. unijugataBaker,B. sapidaK.D. Koenig, andB. welwitschii(Hiern) Radlk butB. unijugatais absent in Ghana. Research onBlighiain West Africa has been primarily conducted in Nigeria, Togo, and Benin. However, the taxonomy of the genus is lacking in West Africa, with the Flora of West Tropical Africa being the only authoritative literature. A revision of this genus in Ghana is needed due to the monotonous concentration of research onB. sapidaand the knowledge gap from Hutchinson & Dalziel. This paper seeks to update the taxonomy of members inBlighiaoccurring in Ghana.

The study collected specimens ofBlighia sapidaandB. welwitschiifrom 15 localities across Ghana. Fossil records, voucher specimens, and digital collections obtained from the Ghana Herbarium and GBIF respectively, were also examined. Standard georeferencing software was used to generate distribution maps.

B. sapidaproduces oblanceolate or obovate leaves with rounded or emarginate apices and acute bases. They are mostly distributed along the coastal belt of the country whileB. welwitschiiproduces lanceolate leaves with bluntly attenuate or acute apices and cuneate bases. They are however distributed mainly in the middle belt of the country.
CuBe: a geminivirus-based copper-regulated expression system suitable for post-harvest activation
Authors: Garcia-Perez Elena , Vazquez-Vilar Marta , Lozano-Duran Rosa , Orzaez Diego
Published: May 2024

The growing demand for sustainable platforms for biomolecule manufacturing has fueled the development of plant-based production systems. Agroinfiltration, the current industry standard, offers several advantages but faces limitations for large-scale production due to high operational costs and batch-to-batch variability. Alternatively, here, we describe the CuBe system, a novel bean yellow dwarf virus (BeYDV)-derived conditional replicative expression platform stably transformed inNicotiana benthamianaand activated by copper sulfate (CuSO4), an inexpensive and widely used agricultural input. The CuBe system utilizes a synthetic circuit of four genetic modules integrated into the plant genome: (i) a replicative vector harboring the gene of interest (GOI) flanked by cis-acting elements for geminiviral replication and novelly arranged to enable transgene transcription exclusively upon formation of the circular replicon, (ii) copper-inducible Rep/RepA proteins essential for replicon formation, (iii) the yeast-derived CUP2-Gal4 copper-responsive transcriptional activator for Rep/RepA expression, and (iv) a copper-inducible Flp recombinase to minimize basal Rep/RepA expression. Copper sulfate application triggers the activation of the system, leading to the formation of extrachromosomal replicons, expression of the GOI, and accumulation of the desired recombinant protein. We demonstrate the functionality of the CuBe system inN. benthamianaplants expressing high levels of eGFP and an anti-SARS-CoV-2 antibody upon copper treatment. Notably, the system is also functional with post-harvest copper application, a strategy with potential advantages for large-scale biomanufacturing. This work presents the CuBe system as a promising alternative to agroinfiltration for cost-effective and scalable production of recombinant proteins in plants.
Darwinian Evolution of Self-Replicating DNA in a Synthetic Protocell
Authors: Abil Zhanar , Restrepo Sierra Ana María , Stan Andreea R. , Châne Amélie , del Prado Alicia , de Vega Miguel , Rondelez Yannick , Danelon Christophe
Published: May 2024

Replication, heredity, and evolution are characteristic of Life. We and others have postulated that the reconstruction of a synthetic living system in the laboratory will be contingent on the development of a genetic self-replicator capable of undergoing Darwinian evolution. Although DNA-based life dominates, the in vitro reconstitution of an evolving DNA self-replicator has remained challenging. We hereby emulate in liposome compartments the principles according to which life propagates information and evolves. Using two different experimental configurations supporting intermittent or semi-continuous evolution (i.e., with or without DNA extraction, PCR, and re-encapsulation), we demonstrate sustainable replication of a linear DNA template – encoding the DNA polymerase and terminal protein from the Phi29 bacteriophage – expressed in the ‘protein synthesis using recombinant elements’ (PURE) system. The self-replicator can survive across multiple rounds of replication-coupled transcription-translation reactions in liposomes and, within only ten evolution rounds, accumulates mutations conferring a selection advantage. Combined data from next-generation sequencing with reverse engineering of some of the enriched mutations reveal nontrivial and context-dependent effects of the introduced mutations. The present results are foundational to build up genetic complexity in an evolving synthetic cell, as well as to study evolutionary processes in a minimal cell-free system.
Highly Multiplexed Proteomic Analysis of HCMV-Infected Dendritic Cells Reveals Global Manipulation of Adaptive Immunity and Host Restriction of Viral Replication
Authors: Kerr-Jones Lauren E. , Soday Lior , Hughes Nia Cwyfan , Wang Xinyue , Hunter Leah H. , Antrobus Robin , Miners Kelly L. , Ladell Kristin , Price David A. , Fielding Ceri A. , Wang Eddie C. Y. , Weekes Michael P. , Stanton Richard J.
Published: May 2024

Human cytomegalovirus (HCMV) is a clinically significant herpesvirus and a paradigm for pathogen-mediated immune-evasion. Its broad tropism includes antigen-presenting cells such as dendritic cells (DCs), which may partly explain a unique, dramatic imprint on host immunity that occurs following lifelong carriage. Despite this breadth of infection, most studies use fibroblasts as a model. We therefore developed systems to isolate pure populations of DCs infected with wild-type HCMV, before applying quantitative temporal proteomic technologies to systematically characterise the virus:DC interaction within cells and at the cell surface. This comprehensive dataset quantifying almost 9,000 proteins throughout the infection timecourse revealed multiple DC-specific viral:host effects, including key impacts on innate, intrinsic, and adaptive immunity. These effects included observations that APOBEC3A is downregulated in infected cells and restricts HCMV infection inex vivoDCs, delaying the progression of lytic infection, and that cell surface ICOS-Ligand was downregulated by the viral genes US16 and US20, inhibiting the induction of adaptive immunity.
Late killing ofPlasmodium bergheisporozoites in the liver by an anti-circumsporozoite protein antibody
Authors: Aguirre-Botero Manuela C. , Pacios Olga , Celli Susanna , Aliprandini Eduardo , Gladston Anisha , Thiberge Jean-Michel , Formaglio Pauline , Amino Rogerio
Published: May 2024

Plasmodiumsporozoites are inoculated into the skin during the bite of an infected mosquito. This motile stage invades cutaneous blood vessels to reach the liver and infect hepatocytes. The circumsporozoite protein (CSP) on the sporozoite surface is an important antigen targeted by protective antibodies in immunoprophylaxis or elicited by vaccination. Antibody-mediated protection mainly unfolds during parasite skin migration, but rare and potent protective antibodies additionally neutralize sporozoite in the liver. Here, using a rodent malaria model, microscopy and bioluminescence imaging, we show a late neutralizing effect of 3D11 anti-CSP monoclonal antibody (mAb) in the liver. The need for several hours to eliminate parasites in the liver was associated with an accumulation of 3D11 effects, starting with the inhibition of sporozoite motility, sinusoidal extravasation, cell invasion, and terminating with the parasite killing inside the invaded cell. This late neutralizing activity could be helpful to identify more potent therapeutic mAbs with stronger activity in the liver.
NSUN2 Facilitates DICER Cleavage of DNA Damage-Associated R-Loops to Promote Repair
Authors: Alagia Adele , Di Fazio Arianna , Ajit Kamal , Long Qilin , Gullerova Monika
Published: May 2024

DNA integrity is constantly challenged by both endogenous and exogenous damaging agents, resulting in various forms of damage. Failure to repair DNA accurately leads to genomic instability, a hallmark of cancer. Distinct pathways exist to repair different types of DNA damage. Double-strand breaks (DSBs) represent particularly severe form of damage, due to the physical separation of DNA strands. The repair of DSBs requires the activity of RNA Polymerase II (RNAPII) and the generation of Damage-associated transcripts (DARTs).

Here we show that the RNA m5C-methyltransferase NSUN2 localizes to DSBs in a transcription-dependent manner, where it binds to and methylates DARTs. The depletion of NSUN2 results in an accumulation of nascent primary DARTs around DSBs. Furthermore, we detected an RNA-dependent interaction between NSUN2 and DICER, which was stimulated by DNA damage. NSUN2 activity promoted DICER cleavage of DARTs-associated R-loops, which is required for efficient DNA repair.

We report a previously unrecognized role of the RNA m5C-methyltransferase NSUN2 within the RNA-dependent DNA damage response, highlighting its function as a DICER chaperone for the clearance of non-canonical substrates such as DARTs, thereby contributing to genomic integrity.
Influence of Wobbling Tryptophan and Mutations on PET Degradation Explored by QM/MM Free Energy Calculations
Authors: Jäckering Anna , van der Kamp Marc , Strodel Birgit , Zinovjev Kirill
Published: May 2024

Plastic-degrading enzymes, particularly poly(ethylene terephthalate) (PET) hydrolases, have garnered significant attention in recent years as potential eco-friendly solutions for recycling plastic waste. However, understanding of their PET-degrading activity and influencing factors remains incomplete, impeding the development of uniform approaches for enhancing PET hydrolases for industrial applications. A key aspect of PET hydrolase engineering is optimizing the PET-hydrolysis reaction by lowering the associated free energy barrier. However, inconsistent findings have complicated these efforts. Therefore, our goal is to elucidate various aspects of enzymatic PET degradation by means of quantum mechanics / molecular mechanics (QM/MM) reaction simulations and analysis, focusing on the initial reaction step, acylation, in two thermophilic PET hydrolases: LCC and PES-H1, along with their highly active variants, LCCICCGand PES-H1FY. Our findings highlight the impact of semi-empirical QM methods on proton transfer energies, affecting the distinction between a two-step reaction involving a metastable tetrahedral intermediate and a one-step reaction. Moreover, we uncovered a concerted conformational change involving the orientation of the PET benzene ring, altering its interaction with the side-chain of the ‘wobbling’ tryptophan from T-stacking to parallel π-π interactions, a phenomenon overlooked in prior research. Our study thus enhances the understanding of the acylation mechanism of PET hydrolases, in particular by characterizing it for the first time for the promising PES-H1FYusing QM/MM simulations. It also provides insights into selecting a suitable QM method and a reaction coordinate, valuable for future studies on PET degradation processes.

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Real-time label-free exploration of the dynamics and interactions of bacteriophages
Authors: Giorgi Francesco , Curran Judith M. , Duignan Liberty , Fothergill Joanne L. , Chenery Sam , Patterson Eann A.
Published: May 2024

1.

Bacteriophages are the focus of extensive research and monitoring their dynamics and interactions with bacterial hosts is crucial to characterise the mechanisms of infection and support potential applications in biotechnology and medicine. Traditional monitoring techniques rely on the fluorescent labelling of bacteriophages due to their size being nanometric. In this paper, we propose a novel, label-free method to generate optical signatures of bacteriophages in a conventional microscopy setup by exploiting the optical phenomenon of caustics. We utilised previously isolatedPseudomonas aeruginosaphage (pelp20 and phiKZ) and a novelEscherichia coli phage(EcoLiv25) to demonstrate detection and tracking within liquid laboratory media. The results obtained confirm the feasibility of visualising and monitoring over time a diverse array of bacteriophages, offering a simpler and less invasive means of observation for research and application in microbiology and related fields.