bluuebunny/crossref_metadata_2025 huggingface dataset:
CXCR3-CXCL11 signaling restricts angiogenesis and promotes pericyte recruitment
Authors: Goeckel Megan E. , Lee Jihui , Levitas Allison , Colijn Sarah , Mun Geonyoung , Burton Zarek , Chintalapati Bharadwaj , Yin Ying , Abello Javier , Stratman Amber
Published: September 2023

Endothelial cell (EC)-pericyte interactions are known to remodel in response to hemodynamic forces, yet there is a lack of mechanistic understanding of the signaling pathways that underlie these events. Here, we have identified a novel signaling network regulated by blood flow in ECs—the chemokine receptor, CXCR3, and one of its ligands, CXCL11—that delimits EC angiogenic potential and suppresses pericyte recruitment during development through regulation ofpdgfbexpression in ECs.In vitromodeling of EC-pericyte interactions demonstrates that suppression of EC-specific CXCR3 signaling leads to loss of pericyte association with EC tubes.In vivo, phenotypic defects are particularly noted in the cranial vasculature, where we see a loss of pericyte association with and expansion of the vasculature in zebrafish treated with the Cxcr3 inhibitor AMG487. We also demonstrate using flow modeling platforms that CXCR3-deficient ECs are more elongated, move more slowly, and have impaired EC-EC junctions compared to their control counterparts. Together these data suggest that CXCR3 signaling in ECs drives vascular stabilization events during development.
Predicting the responses in colour matching experiments from the symmetries of colour space
Authors: Vattuone Nicolás , Samengo Inés
Published: September 2023

In conceptual spaces, the distance between concepts is represented by a metric that cannot usually be expressed as a function of a few, salient physical properties of the represented items. For example, the space of colours can be endowed with a metric capturing the degree to which two chromatic stimuli are perceived as different. As many optical illusions have shown, the colour with which a stimulus is perceived depends, among other contextual factors, on the chromaticity of its surround, an effect called “chromatic induction”. Heuristically, the surround pushes the colour of the stimulus away from its own chromaticity, increasing the salience of the boundary. Previous studies have described how the magnitude of the push depends on the chromaticity of both the stimulus and the surround, concluding that the space of colours contains anisotropies and inhomogeneities. The importance of contextuality has cast doubt on the practical or predictive utility of perceptual metrics, beyond a mathematical curiosity. Here we provide evidence that the metric structure of the space of colours is indeed useful and has predictive power. By using a notion of distance between colours emerging from a subjective metric, we show that the anisotropies and inhomogeneities reported in previous studies can be eliminated. The resulting symmetry allows us to derive a universal curve for the average chromatic induction that contains no fitting parameters and is confirmed by experimental data. The theory also predicts the magnitude of chromatic induction for every possible combination of stimulus and surround demonstrating that, at least in the case of colours, the metric captures the symmetries of perception, and augments the predictive power of theories.
Outer membrane proteins inMycobacterium tuberculosisand its potential role in small molecule permeation
Authors: Palande Aseem , Patil Saniya , Veeram Anjali , Sahoo Soumya Swastik , Balaji M , Chugh Jeetender , Mukherjee Raju
Published: September 2023

Increased resistance to current anti-mycobacterial and a potential bias towards relatively hydrophobic chemical entities highlight an urgent need to understand how current anti-TB drugs enter the tubercle bacilli. While inner membrane proteins are well-studied, how small molecules cross the impenetrable outer membrane remains unknown. Here we employed mass spectrometry-based proteomics to show that octyl-β-glucopyranoside selectively extracts the outer membrane proteins ofMycobacterium tuberculosis. Differentially expressed proteins between nutrient replete and depleted conditions were enriched to identify proteins involved in nutrient uptake. We demonstrate cell surface localization of seven new proteins using immunofluorescence and show that overexpression of the proteins LpqY and ProX leads to hypersensitivity towards streptomycin, while expression of SubI, FecB2, and Rv0999 exhibited higher membrane permeability, assessed through EtBr accumulation assay. Further, proton NMR metabolomics suggests the role of four outer membrane proteins in glycerol uptake. This study identifies several outer membrane proteins that are involved in the permeation of small hydrophilic molecules and are potential targets for enhancing uptake and efficacy of anti-TB drugs.
Interaction between task-evoked and spontaneous brain activities: Insights from two event-related fMRI studies
Authors: Nayak Siddharth , Hojjati Seyed Hani , Ozoria-Blake Sindy , Feiz Farnia , Shteingart Jacob , Guerrero Antonio Fernandez , Razlighi Qolamreza R
Published: September 2023

Human brain activities measured by fMRI can be categorized into at least two distinct categories; 1) spontaneous: slow (< 0.1 Hz) but inter-regionally coherent fluctuations in MR signal, and 2) task-evoked: change in the MR signal due to external stimulation. To date, there is no consensus in the field about the roles of spontaneous brain activity and whether it interacts with task-evoked activity. This is mainly because direct measurements of spontaneous activity during task performance is challenging, if not impossible. Here for the first time, we used a data-driven approach to obtain the time course of the spontaneous brain activity in two of the well-studied brain networks; 1) the Default mode network (DMN), where the strongest task-evoked negative BOLD response is also observed and 2) the dorsal attention network (DAN), where some of the strongest task-evoked positive BOLD response is observed. Voxel-wise multiple regression analysis is used to model fMRI timeseries with anticipated task-evoked BOLD response, the obtain time course of the spontaneous activity, and their interaction at each participant. Using 46 young and cognitively normal participants performing an event-related perceptual speed task inside the fMRI scanner, we showed that there is no significant interaction between the spontaneous and the task-evoked activity either as negative BOLD response in the DMN or as positive BOLD response in the DAN. We replicate our findings in a separate dataset with 24 young and cognitively normal participants performing a different event-related task inside another fMRI scanner. Our results suggest that the presence or absence of coherent spontaneous activity in the DMN, or DAN has negligible effect on the magnitude of the BOLD response and vice versa, which consequently means that the fMRI signal is a linear superposition of spontaneous and task evoked activity.
Large scale spatio-temporal study on European hake depicts sensitivity to sea bottom temperature, sea bottom oxygen concentration and sea surface temperature
Authors: Paradinas Iosu , Chust Guillem , Garcia Dorleta , Ibaibarriaga Leire
Published: September 2023

European hake (Merluccius merluccius) is a commercially important fish species that is known to have a marked bathymetric preference. No other environmental variable has yet been identified to drive the distribution of hake. This study looked into different climatic variables at different depths and identified sea bottom temperature, sea bottom dissolved oxygen concentration and chlorophyll concentration to affect the distribution of both juvenile and adult hake distributions.
ZeptoCTC - Sensitive Protein Analysis of True Single Cell Lysates using Reverse Phase Protein Arrays (RPPA)
Authors: Rivandi Mahdi , Franken André , Yang Liwen , Abramova Anna , Stamm Nadia , Eberhardt Jens , Gierke Berthold , Beer Meike , Fehm Tanja , Niederacher Dieter , Pawlak Michael , Neubauer Hans
Published: September 2023

Circulating Tumor Cells (CTCs) are commonly analyzed through genomic profiling, which does not capture posttranslational and functional alterations of encoded proteins. To address this limitation, we developed ZeptoCTC, a single-cell protein analysis workflow that combines established technologies for single-cell isolation and sensitive Reverse Phase Protein Array (RPPA) analysis to assess multiple protein expression and activation in individual CTCs. The workflow involves single cell labeling, isolation, lysis, and printing of the true single cell lysates onto a ZeptoChip using a modified micromanipulator CellCelectorTM. Subsequently, the printed lysates undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader followed by signal quantification with Image J software. ZeptoCTC was successfully optimized, beginning with the measurement of EpCAM protein expression—a standard marker for CTC detection. As expected, mean fluorescence signals for EpCAM levels were significantly higher in single MCF-7 cells compared to MDA-MB-231 cells. Next, Capivasertib-treated MCF-7 cells exhibited an approximately 2-fold increase in the pAkt/Akt ratio compared to non-treated control cells. This finding was consistent with a co-performed western blot analysis of pooled MCF-7 cells. Application of ZeptoCTC to the analysis of single CTCs derived from a metastasized breast cancer (MBC) patient indicated a significantly higher level of pAkt, accompanied by a corresponding increase in pErk level when compared to patient-matched WBC. Finally, the current workflow successfully indicated the detectable pAkt and Akt signal difference in CTCs from two MBC patients: one with an Akt1 wild-type genotype, and the other harboring approximately 80% Akt1(E17K) mutated CTCs. The mutated CTCs revealed clearly elevated pAkt levels (1.8-fold), along with an even more strongly elevated total Akt (3.4-fold) when compared to the respective signals measured in wild-type CTCs. In conclusion, ZeptoCTC is a highly sensitive method for measuring the expression and phosphorylation of treatment-relevant proteins in key cancer-driving signaling pathways from true single cell samples.
Ectopic assembly of an auxin efflux control machinery shifts developmental trajectories
Authors: Aliaga Fandino Ana Cecilia , Jelinkova Adriana , Marhava Petra , Petrasek Jan , Hardtke Christian S.
Published: September 2023

Polar auxin transport in the Arabidopsis root tip maintains high auxin levels around the stem cell niche that gradually decrease in dividing cells but increase again once they transition towards differentiation. Protophloem differentiates earlier than other proximal tissues and employs a unique auxin ‘canalization’ machinery that is thought to balance auxin efflux with retention. It consists of a proposed activator of PIN auxin efflux carriers, the AGC kinase PAX; its inhibitor, BRX; and PIP5K enzymes, which promote polar PAX and BRX localization. Because of dynamic PAX-BRX-PIP5K interplay, the net cellular output of this machinery remains unclear. Here we deciphered the dosage-sensitive regulatory interactions between PAX, BRX and PIP5K by their ectopic expression in developing xylem vessels. The data suggest that the dominant collective output of the PAX-BRX-PIP5K module is a localized reduction in PIN abundance. This requires PAX-stimulated clathrin-mediated PIN endocytosis by site-specific phosphorylation, which distinguishes PAX from other AGC kinases. Importantly, ectopic assembly of the PAX-BRX-PIP5K module is sufficient to cause cellular auxin retention and affects root growth vigor by accelerating the trajectory of xylem vessel development. Our data thus provide direct evidence that local manipulation of auxin efflux alters the timing of cellular differentiation in the root.
RIDGE, a tool tailored to detect gene flow barriers across species pairs
Authors: Burban Ewen , Tenaillon Maud I. , Glémin Sylvain
Published: September 2023

Characterizing the processes underlying reproductive isolation between diverging lineages is central to understanding speciation. Here, we present RIDGE – Reproductive Isolation Detection using Genomic polymorphisms – a tool tailored for quantifying gene flow barrier proportions and identifying the corresponding genomic regions. RIDGE relies on an Approximate Bayesian Computation with a model-averaging approach to accommodate diverse scenarios of lineage divergence. It captures heterogeneity in effective migration rate along the genome while accounting for variation in linked selection and recombination. The barrier detection test relies on numerous summary statistics to compute a Bayes factor, offering a robust statistical framework that facilitates cross-species comparisons. Simulations revealed that RIDGE is particularly efficient both at capturing signals of ongoing migration and at identifying barrier loci, including for recent divergence times (~0.1 2Negenerations). Applying RIDGE to four published crow datasets, we validated our tool by identifying a well-known large genomic region associated with mate choice patterns. We identified additional barrier loci between species pairs, which have shown, on the one hand, that depending on the biological, demographic, and selection contexts, different combinations of summary statistics are informative for the detection of signals. On the other hand, these analyses also highlight the value of our newly developed outlier statistics in challenging detection conditions.
Conformational dynamics of a nicotinic receptor neurotransmitter site
Authors: Singh Mrityunjay , Indurthi Dinesh C. , Mittal Lovika , Auerbach Anthony , Asthana Shailendra
Published: September 2023

Agonists increase receptor activity by providing net-favorable binding energy to active versus resting conformations of their target sites. We used molecular dynamics (MD) simulations to explore dynamics of the low-to-high affinity conformational change (L→H) at theTorpedoα–δ nicotinic acetylcholine receptor neurotransmitter site, using 4 agonists. Alternative conformations were identified in trajectories generated from a single starting structure by matching approximate binding energies calculatedin silicowith exact values measured experimentallyin vitro. In all simulations, the L→H transition started with a rotation of the agonist about its cationic center (’flip’), followed by a staged downward displacement of loop C (’flop’) and the formation of a compact, hydrophobic and stable high-affinity pocket (’fix’). Agonist rotation and a transient intermediate state are only in simulations but can be confirmed or refuted, for example by time-resolved structures.
Quantitative Learning of Cellular Features From Single-cell Transcriptomics Data Facilitates Effective Drug Repurposing
Authors: Zhong Jianmei , Yang Junyao , Song Yinghui , Zhang Zhihua , Wang Chunming , Tong Renyang , Li Chenglong , Yu Nanhui , Zou Lianhong , Liu Sulai , Pu Jun , Lin Wei
Published: September 2023

In this study, we have devised a computational framework SuperFeat that allows for the training of a machine learning model and evaluate the canonical cellular states/features in pathological tissues that underlie the progression of disease. This framework also enables the identification of potential drugs that target the presumed detrimental cellular features. This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes. The training data comprised single-cell RNA-seq datasets that encompassed the specific cell lineage during the developmental progression of cell features. A few models of the canonical cancer-involved cellular states/features were tested by such framework. Finally, we have illustrated the drug repurposing pipeline, utilizing the training parameters derived from the adverse cellular states/features, which has yielded successful validation results bothin vitroandin vivo. SuperFeat is accessible athttps://github.com/weilin-genomics/rSuperFeat.
Sound-mediated nucleation and growth of amyloid fibrils
Authors: Kozell Anna , Solomonov Aleksei , Gaidarov Roman , Benyamin Doron , Rosenhek-Goldian Irit , Greenblatt Harry Mark , Levy Yaakov , Amir Ariel , Raviv Uri , Shimanovich Ulyana
Published: September 2023

Mechanical energy, specifically in the form of ultrasound, can induce pressure variations and temperature fluctuations when applied to an aqueous media. These conditions can both positively and negatively affect protein complexes, consequently altering their stability, folding patterns, and self-assembling behavior. Despite much scientific progress, our current understanding of the effects of ultrasound on the self-assembly of amyloidogenic proteins remains limited. In the present study, we demonstrate that when the amplitude of the delivered ultrasonic energy is sufficiently low, it can induce refolding of specific motifs in protein monomers, which is sufficient for primary nucleation; this has been revealed by MD. These ultrasound-induced structural changes are initiated by pressure perturbations and are accelerated by a temperature factor. Furthermore, the prolonged action of low-amplitude ultrasound enables the elongation of amyloid protein nanofibrils directly from natively folded monomeric lysozyme protein, in a controlled manner, until it reaches a critical length. Using solution X-ray scattering, we determined that nanofibrillar assemblies, formed either under the action of sound or from natively fibrillated lysozyme, share identical structural characteristics. Thus, these results provide insights into the effects of ultrasound on fibrillar protein self-assembly and lay the foundation for the potential use of sound energy in protein chemistry.

Significance Statement

Understanding how and why proteins form amyloid fibrils is crucial for research into various diseases, including neurodegeneration. Ultrasound is routinely used in research settings as a tool for generating amyloid seeds (nucleation sites) from mature fibrils, which accelerate the rate of fibril growth. However, ultrasound can have various effects on aqueous media including temperature, extreme shear, and free radicals. Here we show that when the ultrasound parameters are precisely adjusted, they can be utilized as a tool for amyloid growth directly from the natively folded monomers. Thus, it is possible to induce minor changes in the folding of proteins, which trigger nucleation and accelerate amyloid growth. This knowledge lays the foundation for the potential use of sound in protein chemistry.
The TcdE holin drives toxin secretion and virulence inClostridioides difficile
Authors: DiBenedetto NV , Oberkampf M , Cersosimo L , Yeliseyev V , Bry L , Peltier J , Dupuy B
Published: September 2023

Clostridioides difficileis the leading cause of healthcare associated infections. The Pathogenicity Locus (PaLoc) toxins TcdA and TcdB promote host disease. These toxins lack canonical N-terminal signal sequences for translocation across the bacterial membrane, suggesting alternate mechanisms of release, which have included targeted secretion and passive release from cell lysis. While the holin TcdE has been implicated in TcdA and TcdB release, its rolein vivoremains unknown. Here, we show profound reductions in toxin secretion intcdEmutants in the highly virulent strains UK1 (epidemic ribotype 027, Clade 3) and VPI10463 (ribotype 087, Clade 1). Notably,tcdEdeletion in either strain rescued highly susceptible gnotobiotic mice from lethal infection by reducing acute extracellular toxin to undetectable levels, limiting mucosal damage, and enabling long-term survival, in spite of continued toxin gene expression intcdEmutants. Our findings confirm TcdE’s critical functionsin vivofor toxin secretion andC. difficilevirulence.
Live-Attenuated CHIKV Vaccine with Rearranged Genome Replicatesin vitroand Induces Immune Response in Mice
Authors: Tretyakova Irina , Joh Joongho , Lukashevich Igor S. , Alejandro Brian , Gearon Mary , Chung Donghoon , Pushko Peter
Published: September 2023

Chikungunya fever virus (CHIKV) is a mosquito-borne alphavirus that causes wide-spread human infections and epidemics in Asia, Africa and recently, in the Americas. There is no approved vaccine and CHIKV is considered a priority pathogen by CEPI and WHO. Previously, we developed immunization DNA (iDNA) plasmid capable of launching live-attenuated CHIKV vaccinein vivo. Here we report the use of CHIKV iDNA plasmid to prepare a novel, live-attenuated CHIKV vaccine V5040 with rearranged RNA genome for improved safety. In V5040, genomic RNA was rearranged to encode capsid gene downstream from the glycoprotein genes. To secure safety profile, attenuated mutations derived from experimental CHIKV 181/25 vaccine were also engineered into E2 gene of V5040. The DNA copy of rearranged CHIKV genomic RNA with attenuated mutations was cloned into iDNA plasmid pMG5040 downstream from the CMV promoter. After transfection in vitro, pMG5040 launched replication of V5040 virus with rearranged genome and attenuating E2 mutations. Furthermore, V5040 virus was evaluated in experimental murine models for safety and immunogenicity. Vaccination with V5040 virus subcutaneously resulted in elicitation of CHIKV-specific, virus-neutralizing antibodies. The results warrant further evaluation of V5040 virus with rearranged genome as a novel live-attenuated vaccine for CHIKV.
Agents seeking long-term access to the wisdom of the crowd reduce immediate decision-making accuracy
Authors: Mann Richard P.
Published: September 2023

Abstract

Living in groups offers social animals the significant advantage of accessing collective wisdom and enhanced information processing, enabling more accurate decisions related to foraging, navigation, and habitat selection. Preserving group membership is crucial for sustaining access to collective wisdom, incentivising animals to prioritise group cohesion. However, when individuals encounter divergent information about the quality of various options this can create a conflict between pursuing immediate rewards and the maintenance of group membership to improve access to future payoffs. In this study I show that rational agents who seek to maximise long-term rewards will be more inclined to follow the decisions of their peers than those with short-term horizons. In doing so, they necessarily make less-rewarding decisions in the short-term, which manifests in a lower individual accuracy when choosing the better of two options. Further, I demonstrate that intuitions about collective wisdom can be misleading in groups of agents who prioritise long-term rewards, with disagreement being a better signal for the accuracy of collective choices than consensus. These results demonstrate that observed patterns of sociality should be interpreted in the context of the life history of an individual and its peers, rather than through the lens of an isolated decision.
Epigenetic coordination of transcriptional and translational programs in hypoxia
Authors: Watt Kathleen , Dauber Bianca , Szkop Krzysztof J , Lee Laura , Jovanovic Predrag , Chen Shan , Masvidal Laìa , Tandoc Kristofersson , Palia Ranveer , Topisirovic Ivan , Larsson Ola , Postovit Lynne-Marie
Published: September 2023

Adaptation to stresses entails coordination of transcriptional and post-transcriptional gene regulation, but the mechanisms remain largely unknown. We interrogated the effects of hypoxia on transcriptomes, epigenomes and translatomes of T47D breast cancer cells and H9 human embryonic stem cells. This revealed hypoxia-induced alterations in H3K4me3 associating with pervasive changes in transcription start site (TSS) selection, leading to 5’UTR remodeling and a concomitant reshaping of translational landscapes. Importantly, this epigenetically driven reprogramming of translation is distinct from HIF1-dependent transcriptional mechanisms, and TSS switching appears to occur independently of alterations in transcript abundance. While TSS switching is coordinated with the integrated stress response (ISR) and mTOR-guided translational reprogramming, it also acts independently to regulate translation in hypoxia. Moreover, comparable TSS switching was observed following H3K4me3 accumulation in the absence of hypoxia, pinpointing H3K4me3 as underlying TSS selection. These results demonstrate a previously unappreciated mechanism of translational regulation driven by epigenetic reprogramming of the 5’UTRome, which is orchestrated with other hypoxia-triggered adaptive mechanisms.
A Light sheet fluorescence microscopy and machine learning-based approach to investigate drug and biomarker distribution in whole organs and tumors
Authors: Kumar Niyanta , Hrobař Petr , Vagenknecht Martin , Soukup Jindrich , Patterson Nadia , Bloomingdale Peter , Freshwater Tomoko , Bardehle Sophia , Peter Roman , Mangadu Ruban , Pastuskovas Cinthia V. , Chabu Chiswili Y. , Cancilla Mark T.
Published: September 2023

Tissue clearing and Light sheet fluorescence microscopy (LSFM) provide spatial information at a subcellular resolution in intact organs and tumors which is a significant advance over tools that limit imaging to a few representative tissue sections. The spatial distribution of drugs, targets, and biomarkers can help inform relationships between exposure at the site of action, efficacy, and safety during drug discovery. We demonstrate the use of LSFM to investigate distribution of an oncolytic virus (OV) and vasculature in xenograft tumors, as well as brain Aβ pathology in an Alzheimer’s disease (AD) mouse model. Machine learning-based image analysis tools developed to segment vasculature in tumors showed that random forest and deep learning methods provided superior segmentation accuracy vs intensity-based thresholding. Sub-cellular resolution enabled detection of punctate and diffuse intracellular OV distribution profiles. LSFM investigation in the brain in a TgCRND8 AD mouse model at 6.5 months of age enabled evaluation of Aβ plaque density in different brain regions. The utility of LSFM data to support quantitative systems pharmacology (QSP) and physiology-based pharmacokinetics (PBPK) modeling to inform drug development are also discussed. In summary, we showcase how LSFM can expand our understanding of macromolecular drug and biomarker distribution to advance drug discovery and development.
Poly-basic peptides and polymers as new drug candidate againstPlasmodium falciparum
Authors: Sivakumar Roshan , Floyd Katherine , Jessey Erath , Kim Kim Jenny , Bayguinov Peter O. , Fitzpatrick James A.J. , Goldfrab Dennis , Jovanovic Marko , Tripathi Abhai , Djuranovic Sergej , Pavlovic-Djuranovic Slavica
Published: September 2023

Plasmodium falciparum, the malaria-causing parasite, is a leading cause of infection-induced deaths worldwide. The preferred treatment approach is artemisinin-combination therapy, which couples fast-acting artemisinin derivatives with longer-acting drugs like lumefantrine, mefloquine, and amodiaquine. However, the urgency for new treatments has risen due to the parasite’s growing resistance to existing therapies. Our study shows that a common characteristic of theP. falciparumproteome – stretches of poly-lysine residues such as those found in proteins related to adhesion and pathogenicity – can serve as an effective peptide treatment for infected erythrocytes. A single dose of these poly-basic peptides can successfully diminish parasitemia in human erythrocytesin vitrowith minimal toxicity. The effectiveness of the treatment correlates with the length of the poly-lysine peptide, with 30 lysine peptides supporting the eradication of erythrocytic parasites within 72 hours. PEG-ylation of the poly-lysine peptides or utilizing poly-lysine dendrimers and polymers further increases parasite clearance efficiency and bolsters the stability of these potential new therapeutics. Lastly, our affinity pull-downs and mass-spectrometry identifyP. falciparum’souter membrane proteins as likely targets for polybasic peptide medications. Since poly-lysine dendrimers are already FDA-approved for drug delivery, their adaptation as antimalarial drugs presents a promising new therapeutic strategy.

One-Sentence Summary

Our study demonstrates that poly-lysine peptides, particularly those modified through PEG-ylation or in the form of poly-lysine dendrimers, can effectively reducePlasmodium falciparum,the causative agent of malaria, in human erythrocytesin vitro,with potential for use as a promising new antimalarial therapy.
Theory on the power-law distribution of the Michaelis-Menten enzyme kinetic parameters
Authors: Murugan Rajamanickam
Published: September 2023

We show on the biophysical basis that the observed enzyme kinetic parameters related to the substrate binding, product turnover and catalytic efficiency follow power-law type density functions. These finding are validated with the available datasets on various enzymes across different substrates. The product turnover rates and catalytic efficiencies seems to follow a bimodal type density functions in line with the single molecule experiments on enzyme catalysis which can be explained by a sum of two different power-law type density functions. The curve geometry of the density functions is decided by the underlying biophysical factors and the location of the peak is dictated by the natural selection pressure.
Evaluating the effectiveness of artifact correction and rejection in event-related potential research
Authors: Zhang Guanghui , Garrett David R. , Simmons Aaron M. , Kiat John E. , Luck Steven J.
Published: September 2023

Eyeblinks and other large artifacts can create two major problems in event-related potential (ERP) research, namely confounds and increased noise. Here, we developed a method for assessing the effectiveness of artifact correction and rejection methods at minimizing these two problems. We then used this method to assess a common artifact minimization approach, in which independent component analysis (ICA) is used to correct ocular artifacts, and artifact rejection is used to reject trials with extreme values resulting from other sources (e.g., movement artifacts). This approach was applied to data from five common ERP components (P3b, N400, N170, mismatch negativity, and error-related negativity). Four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency) were examined for each component. We found that eyeblinks differed systematically across experimental conditions for several of the components. We also found that artifact correction was reasonably effective at minimizing these confounds, although it did not usually eliminate them completely. In addition, we found that the rejection of trials with extreme voltage values was effective at reducing noise, with the benefits of eliminating these trials outweighing the reduced number of trials available for averaging. For researchers who are analyzing similar ERP components and participant populations, this combination of artifact correction and rejection approaches should minimize artifact-related confounds and lead to improved data quality. Researchers who are analyzing other components or participant populations can use the method developed in this study to determine which artifact minimization approaches are effective in their data.
The Atlantic Forest of South America: spatiotemporal dynamics of remaining vegetation and implications for conservation
Authors: Vancine Maurício Humberto , Muylaert Renata L. , Niebuhr Bernardo Brandão , Oshima Júlia Emi de Faria , Tonetti Vinicius , Bernardo Rodrigo , De Angelo Carlos , Rosa Marcos Reis , Grohmann Carlos Henrique , Ribeiro Milton Cezar
Published: September 2023

The Atlantic Forest in South America (AF) is one of the world’s most diverse and threatened biodiversity hotspots. We present a comprehensive spatiotemporal analysis of 34 years of AF landscape change between 1986-2020. We analyzed landscape metrics of forest vegetation only (FV), forest plus other natural vegetation (NV), and investigated the sensitivity of metrics to linear infrastructure. Currently, remnants comprise about 23% of FV and 36% of NV, and have decreased by 2.4% and 3.6% since 1986, respectively. Linear infrastructure negatively affected large fragments (>500,000 ha) by breaking them apart. Our findings suggest that AF protection legislation adopted in mid-2005 has taken effect: between 1986-2005, there was a loss of FV and NV (3% and 3.45%) and a decrease in the number of FV and NV fragments (8.6% and 8.3%). Between 2005-2020, there was a relative recovery of FV (1 Mha; 0.6%), slight loss of NV (0.25 Mha; 0.15%) and increase in the number of FV and NV fragments (12% and 9%). Still, 97% of the vegetation fragments are small (<50 ha), with an average fragment size between 16 and 26 ha. Furthermore, 50-60% of the vegetation is <90 m from its edges, and the isolation between fragments is high (250-830 m). Alarmingly, protected areas and indigenous territories cover only 10% of the AF and are very far from any fragments (>10 km). Our work highlights the importance of legislation and landscape dynamics analysis to help monitor and keep track of AF biodiversity conservation and restoration programs in the future.

Highlights

There is 23% forest and 36% natural vegetation cover remaining in the Atlantic Forest.

Between 1986-2020, native forest cover decreased by 2.4% and natural vegetation by 3.6%.

Since 2005, there has been a 1 Mha increase in forest area by small fragments (1 ha).

Roads and railways reduced by 56%-89% fragment size, especially on large fragments.

Alarmingly, 97% of fragments are small (<50 ha) and 60% are under edge effect (<90 m).
Early life stress impairs VTA coordination of BLA network and behavioral states
Authors: Stone Bradly T. , Antonoudiou Pantelis , Teboul Eric , Scarpa Garrett , Weiss Grant , Maguire Jamie L.
Published: September 2023

Motivated behaviors, such as social interactions, are governed by the interplay between mesocorticolimbic structures, such as the ventral tegmental area (VTA), basolateral amygdala (BLA), and medial prefrontal cortex (mPFC). Adverse childhood experiences and early life stress (ELS) can impact these networks and behaviors, which is associated with increased risk for psychiatric illnesses. While it is known that the VTA projects to both the BLA and mPFC, the influence of these inputs on local network activity which govern behavioral states – and whether ELS impacts VTA-mediated network communication – remains unknown. Our study demonstrates that VTA inputs influence BLA oscillations and mPFC activity, and that ELS weakens the ability of the VTA to coordinate BLA network states, likely due to ELS-induced impairments in dopamine signaling between the VTA and BLA. Consequently, ELS mice exhibit increased social avoidance, which can be recapitulated in control mice by inhibiting VTA-BLA communication. These data suggest that ELS impacts social reward via the VTA-BLA dopamine network.
Surprising Features of Nuclear Receptor Interaction Networks Revealed by Live Cell Single Molecule Imaging
Authors: Dahal Liza , Graham Thomas GW , Dailey Gina M , Heckert Alec , Tjian Robert , Darzacq Xavier
Published: September 2023

Type 2 Nuclear Receptors (T2NRs) require heterodimerization with a common partner, the Retinoid X Receptor (RXR), to bind cognate DNA recognition sites in chromatin. Based on previous biochemical and over-expression studies, binding of T2NRs to chromatin is proposed to be regulated by competition for a limiting pool of the core RXR subunit. However, this mechanism has not yet been tested for endogenous proteins in live cells. Using single molecule tracking (SMT) and proximity-assisted photoactivation (PAPA), we monitored interactions between endogenously tagged retinoid X receptor (RXR) and retinoic acid receptor (RAR) in live cells. Unexpectedly, we find that higher expression of RAR, but not RXR increases heterodimerization and chromatin binding in U2OS cells. This surprising finding indicates the limiting factor is not RXR but likely its cadre of obligate dimer binding partners. SMT and PAPA thus provide a direct way to probe which components are functionally limiting within a complex TF interaction network providing new insights into mechanisms of gene regulation in vivo with implications for drug development targeting nuclear receptors.
Hallmark molecular and pathological features of POLG disease are recapitulated in cerebral organoids
Authors: Chen Anbin , Yangzom Tsering , Hong Yu , Lundberg Bjørn Christian , Sullivan Gareth John , Tzoulis Charalampos , Bindoff Laurence A. , Liang Kristina Xiao
Published: September 2023

In our research, we developed a 3D brain organoid model to study POLG-related encephalopathy, a mitochondrial disease stemming fromPOLGgene mutations. We utilized induced pluripotent stem cells (iPSCs) derived from patients with these mutations to generate cortical organoids, which exhibited typical POLG disease features, such as altered morphology, neuronal loss, and mtDNA depletion. We also identified significant dysregulation in pathways crucial for neuronal development and function, alongside upregulated NOTCH and JAK-STAT signaling pathways. Metformin treatment ameliorated many of these abnormalities, except for the persistent affliction of inhibitory DA GLU neurons. This novel model effectively mirrors both the molecular and pathological attributes of POLG disease, providing a valuable tool for mechanistic understanding and therapeutic screening for POLG-related disorders and other conditions characterized by compromised neuronal mtDNA maintenance and complex I deficiency.

Highlights

We have successfully developed cortical organoid model that represents POLG-related disease.

This model effectively replicates both histological and molecular signatures seen in the brains of patients.

The cortical organoid model displays a range of features common in POLG-related disease, including neurodegeneration, mtDNA depletion, and neuronal complex I deficiency.

The use of metformin supplementation in this model improved mitochondria protein and reduced cell death.
Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease
Authors: Weinstock Joshua S. , Arce Maya M. , Freimer Jacob W. , Ota Mineto , Marson Alexander , Battle Alexis , Pritchard Jonathan K.
Published: September 2023

The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes incis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. Mapping trans-regulators based on natural genetic variation, including eQTL mapping, has been challenging due to small effects. Experimental perturbation approaches offer a complementary and powerful approach to mapping trans-regulators. We used CRISPR knockouts of 84 genes in primary CD4+ T cells to perturb an immune cell gene network, targeting both inborn error of immunity (IEI) disease transcription factors (TFs) and background TFs matched in constraint and expression level, but without a known immune disease association. We developed a novel Bayesian structure learning method called Linear Latent Causal Bayes (LLCB) to estimate the gene regulatory network from perturbation data and observed 211 directed edges among the genes which could not be detected in existing CD4+ trans-eQTL data. We used LLCB to characterize the differences between the IEI and background TFs, finding that the gene groups were highly interconnected, but that IEI TFs were much more likely to regulate immune cell specific pathways and immune GWAS genes. We further characterized nine coherent gene programs based on downstream effects of the TFs and linked these modules to regulation of GWAS genes, finding that canonical JAK-STAT family members are regulated byKMT2A, a global epigenetic regulator. These analyses reveal the trans-regulatory cascade from upstream epigenetic regulator to intermediate TFs to downstream effector cytokines and elucidate the logic linking immune GWAS genes to key signaling pathways.
Digitize your Biology! Modeling multicellular systems through interpretable cell behavior
Authors: Johnson Jeanette A.I. , Stein-O’Brien Genevieve L. , Booth Max , Heiland Randy , Kurtoglu Furkan , Bergman Daniel R. , Bucher Elmar , Deshpande Atul , Forjaz André , Getz Michael , Godet Ines , Lyman Melissa , Metzcar John , Mitchell Jacob , Raddatz Andrew , Rocha Heber , Solorzano Jacobo , Sundus Aneequa , Wang Yafei , Gilkes Danielle , Kagohara Luciane T. , Kiemen Ashley L. , Thompson Elizabeth D. , Wirtz Denis , Wu Pei-Hsun , Zaidi Neeha , Zheng Lei , Zimmerman Jacquelyn W. , Jaffee Elizabeth M. , Chang Young Hwan , Coussens Lisa M. , Gray Joe W. , Heiser Laura M. , Fertig Elana J. , Macklin Paul
Published: September 2023

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells’ characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework—a cell behavior hypothesis grammar—that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual “thought experiments” that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.
Multimodal subspace independent vector analysis effectively captures the latent relationships between brain structure and function
Authors: Li Xinhui , Kochunov Peter , Adali Tulay , Silva Rogers F. , Calhoun Vince D.
Published: September 2023

A key challenge in neuroscience is to understand the structural and functional relationships of the brain from high-dimensional, multimodal neuroimaging data. While conventional multivariate approaches often simplify statistical assumptions and estimate one-dimensional independent sources shared across modalities, the relationships between true latent sources are likely more complex – statistical dependence may exist within and between modalities, and span one or more dimensions. Here we present Multimodal Subspace Independent Vector Analysis (MSIVA), a methodology to capture both joint and unique vector sources from multiple data modalities by defining both cross-modal and unimodal subspaces with variable dimensions. In particular, MSIVA enables flexible estimation of varying-size independent subspaces within modalities and their one-to-one linkage to corresponding sub-spaces across modalities. As we demonstrate, a main benefit of MSIVA is the ability to capture subject-level variability at the voxel level within independent subspaces, contrasting with the rigidity of traditional methods that share the same independent components across subjects. We compared MSIVA to a unimodal initialization baseline and a multimodal initialization baseline, and evaluated all three approaches with five candidate subspace structures on both synthetic and neuroimaging datasets. We show that MSIVA successfully identified the ground-truth subspace structures in multiple synthetic datasets, while the multimodal baseline failed to detect high-dimensional subspaces. We then demonstrate that MSIVA better detected the latent subspace structure in two large multimodal neuroimaging datasets including structural MRI (sMRI) and functional MRI (fMRI), compared with the unimodal baseline. From subsequent subspace-specific canonical correlation analysis, brain-phenotype prediction, and voxelwise brain-age delta analysis, our findings suggest that the estimated sources from MSIVA with optimal subspace structure are strongly associated with various phenotype variables, including age, sex, schizophrenia, lifestyle factors, and cognitive functions. Further, we identified modality- and group-specific brain regions related to multiple phenotype measures such as age (e.g., cerebellum, precentral gyrus, and cingulate gyrus in sMRI; occipital lobe and superior frontal gyrus in fMRI), sex (e.g., cerebellum in sMRI, frontal lobe in fMRI, and precuneus in both sMRI and fMRI), schizophrenia (e.g., cerebellum, temporal pole, and frontal operculum cortex in sMRI; occipital pole, lingual gyrus, and precuneus in fMRI), shedding light on phenotypic and neuropsychiatric biomarkers of linked brain structure and function.
Dynamics of membrane tubulation coupled with fission by a two-component module revealed on polymer cushioned bilayer islands
Authors: Bhattacharyya Soumya , Pucadyil Thomas J.
Published: September 2023

Membrane tubulation coupled with fission (MTCF) is a widespread cellular phenomenon but mechanisms for their coordination remain unclear. This is partly because of the lack of assays to monitor dynamics of membrane tubulation. Using polymer cushioned bilayer islands, we analyze functions of the membrane tubulator Bridging Integrator 1 (BIN1) mixed with the fission catalyst dynamin2 (Dyn2). Our results reveal that this mixture constitutes a minimal two-component module that demonstrates MTCF. MTCF is an emergent property and arises because BIN1 dually functions in facilitating peripheral recruitment while inhibiting membrane binding of Dyn2 in a dose-dependent manner. MTCF is therefore apparent only at high Dyn2 to BIN1 ratios. Because of their mutual involvement in T-tubules biogenesis, mutations in BIN1 and Dyn2 are associated with centronuclear myopathies (CNM) and our analysis links the pathology with aberrant MTCF. Together, our results establish cushioned bilayer islands as a facile template for the quantitative analysis of membrane tubulation and inform of mechanisms that coordinate MTCF.
Decoding genetic architecture of dog complex traits by constructing fine-scale genomic ancestry of admixture
Authors: Zhao Shilei , Wang Guo-Dong , Liu Yanhu , Zhang Ya-Ping , Chen Hua
Published: September 2023

Domestic animals and plants exhibit remarkable phenotypic diversity in terms of morphology, behavior, and physiology, which can be attributed to the complex interbreeding process of various breeds and artificial selection. Here we develop a method that can efficiently construct fine-scale interbreeding history of local segments along the genome. Since ancestral breeds usually exhibit diverse phenotypes, the method provides a valuable approach for unraveling the genetic architecture of complex traits in admixed breeds. Simulated data demonstrates that the method performs well, even in scenarios involving complex interbreeding with up to 19 ancestral breeds.

The method is applied to analyze three mixed dog breeds, Irish Wolfhound, Giant Schnauzer, and Miniature Schnauzer, representing instances of body-size enlargement and miniaturization. Numerous novel ancestor breed-specific genes determining body size are identified, includingFGFR2, WDR11, andFARS2. We also validate genes reported in previous GWAS or genomic sweep scans, such asLCORL, STC2, NPR2, andFGF4. These findings highlight the validity of the method as a valuable tool for investigating the genetic basis underlying ancestry-specific traits in domestic animals and plants with complex interbreeding histories.
Motivation upregulates the adaptive response in sensorimotor learning
Authors: Khatib Salma , Chib Vikram S. , Mawase Firas
Published: September 2023

Motivational state plays a critical role in our ability to learn new motor skills; however, the mechanisms by which motivation influences motor learning are poorly understood. Using a motor learning paradigm in which motivation was varied in a trial-by-trial manner, we found that motivation affects learning by upregulating the rate of the adaptive response, increasing individuals’ speed of learning. This unveils previously unidentified evidence for a mechanism through which motivation shapes error-based motor learning.