bluuebunny/crossref_metadata_2025 huggingface dataset:
TRPA1 analgesia is mediated by kappa opioid receptors
Authors: Semizoglou Evangelia , Gentry Clive , Vastani Nisha , Stucky Cheryl L. , Andersson David A. , Bevan Stuart
Published: September 2022

TRPA1 expressed in peripheral sensory neurons is important for nociception. Pharmacological inhibition or genetic ablation of TRPA1 profoundly reduces normal behavioural sensitivity to noxious cold and mechanical stimulation, as well as sensory neuron responses to mechanical stimulation. TRPA1 inhibition also reverses cold and mechanical hypersensitivities in chronic pain models in vivo. Here we demonstrate that these striking effects of TRPA1 inactivation result from an increased constitutive activity of kappa opioid receptors (KOR) co-expressed with TRPA1 in sensory neurons. Inhibition of KOR in Trpa1-/- mice restores nociception and neuronal activity to the levels observed in wild-type mice and reverses the analgesic effects of TRPA1 antagonism in naïve mice and in neuropathic and inflammatory pain conditions. TRPA1 regulation of KOR activity in sensory neurons provides a novel mechanism to produce peripherally mediated analgesia. Our findings suggest that TRP channel regulation of constitutive GPCR activity, may be a process of general physiological importance.
Release of lipid nanodiscs from charged nano-droplets in the electrospray ionization process revealed by microsecond atomistic molecular dynamics simulations
Authors: Wang Beibei , Tieleman D. Peter
Published: September 2022

Electrospray ionization (ESI) prevents the analyte being split into fragments and is widely used to analyze biomolecules. Nanodiscs provide a native-like environment for membrane proteins, while making them accessible in aqueous solution for analysis. We performed microsecond (μs) molecular dynamics simulations at different temperatures, to provide atomistic insight in the release of intact nanodiscs from charged nano-droplets, the late stage of the ESI process. Two distinct main scenarios, at-center and off-center, were observed. The at-center scenario follows the charged residue model, and in the process the nanodisc stays well in the droplet interior, with the membrane scaffold protein (MSP) keeping its annular geometry. As solvent evaporates, lipids turn over to protect the hydrophilic surface. The off-center scenario conforms to a hybrid model of the charged residue model and chain ejection model. The nanodisc migrates to the water/air interface, leading to lipids escaping from the dissociated dimer and the partial ejection of one monomer of MSP. A diversity of morphologies of product gaseous ions was observed, as evidenced by their structural details, collision cross sections and moments of inertia. Our results are in reasonable agreement with results of mass spectrometry in mass-to-charge ratio, charge state and collision cross section. Our work displays the first atomistic view of a heterogeneous system, a lipid nanodisc, releasing from highly charged nano-droplets into the gas phase, which may provide structural supports for the interpretation of mass spectra of complicated systems. What we observe in our simulations could also be generalized to other protein-lipid systems.
Dissociated amplitude and phase effects of alpha oscillation in a nested structure of rhythm- and sequence-based temporal expectation
Authors: Su Zhongbin , Zhou Xiaolin , Wang Lihui
Published: September 2022

The human brain can utilize various information to form temporal expectation and optimize perceptual performance. Here we show dissociated amplitude and phase effects of pre-stimulus alpha oscillation in a nested structure of rhythm- and sequence-based expectation. A visual stream of rhythmic stimuli was presented in a fixed sequence such that their temporal positions could be predicted by either the low-frequency rhythm, the sequence, or the combination. The behavioral modelling indicated that rhythmic and sequence information additively led to increased accumulation of sensory evidence and alleviated threshold for the perceptual discrimination of the expected stimulus. The electroencephalographical (EEG) results showed that the alpha amplitude was dominated by rhythmic information, with the amplitude fluctuating in the same frequency of the oscillation entrained by the rhythmic information (i.e., phase-amplitude coupling). The alpha phase, however, was affected by both rhythmic and sequence information. Importantly, rhythm-based expectation improved the perceptual performance by decreasing the alpha amplitude, whereas sequence-based expectation did not further decrease the amplitude on top of rhythm-based expectation. Moreover, rhythm-based and sequence-based expectation collaboratively improved the perceptual performance by biasing the alpha oscillation toward the optimal phase. Our findings suggested flexible coordination of multiscale brain oscillations in dealing with a complex environment.
Combating pancreatic cancer with ovarian cancer cells
Authors: Lin Xiao , Cui Chunmei , Cui Qinghua
Published: September 2022

With overall five-year survival rate less than 10%, pancreatic cancer (PC) represents the most lethal one in all human cancers. Given that the incidence of PC is still increasing and current cancer treatment strategies are often inefficacious, its therapy is still a huge challenge. Here, we first revealed ovarian serous carcinoma is mostly anti-correlated with pancreatic cancer in gene expression signatures. Based on this observation, we proposed that ovarian cancer cells could defense PC. To confirm this strategy, we first showed that ovarian cancer cell SKOV3 can significantly inhibit the proliferation of pancreatic cancer cell SW1990 when they were co-cultured. We further validated this strategy by an animal model of pancreatic cancer xenografts. The result showed that the injection of SKOV3 significantly inhibits pancreatic cancer xenografts. Moreover, we found that SKOV3 with transgenic African elephant TP53 gene further enhances the therapeutic effect. RNA-sequencing analysis revealed that the ovarian cancer cell treatment strikingly induced changes of genes being involved in pancreas function and phenotype (e.g. enhancing pancreas function, pancreas regeneration, and cell adhesion) but not immune and inflammation related functions, suggesting that the proposed strategy is different from immunotherapy and could be a novel strategy for cancer treatment.
In silicoconformational features of botulinum toxins A1 and E1 according to the intraluminal acidification
Authors: Cottone Grazia , Chiodo Letizia , Maragliano Luca , Popoff Michel-Robert , Rasetti-Escargueil Christine , Lemichez Emmanuel , Malliavin Thérèse E.
Published: September 2022

Although the botulinum neurotoxins (BoNTs) are among the most toxic compounds found in nature, their molecular mechanism of action is far from being elucidated. A key event is the conformational transition due to the acidification of the interior of synaptic vesicles, and leading to the translocation of the BoNT catalytic domain into the neuronal cytosol. To investigate these conformational variations, homology modelling and atomistic simulations are combined to explore the internal dynamics of the subtypes BoNT/A1, the most-used in medical applications, and BoNT/E1, the most kinetically efficient. This first simulation study of di-chain BoNTs in closed and open states includes the effects of neutral and acidic pH. The conformational mobility is driven by domains displacements; the ganglioside binding site in the receptor binding domain, the translocation domain (HCNT) switch and the beltαhelix visit multiple conformations depending on the primary sequence and on the pH. Fluctuations of the beltαhelix are observed for closed conformations of the toxins and at acidic pH, and patches of more accessible residues appear in the same conditions in the core translocation domain HCNT. These findings suggest that during translocation, the larger mobility of belt could be transmitted to HCNT, leading to a favorable interaction of HCNTresidues with the non-polar membrane environment.

Key Contribution

The molecular dynamics simulations presented here provide a structural and functional annotation of full-length BoNTs composed by two distinct protein chains. Two different conformations (open and closed) as well as two different protonation states, corresponding to acidic and neutral pH, have been considered. Results from the present work supports a model of mobility in which the individual domains fluctuate around stable conformations and the overall structure mobility arise from relative displacements of the domains.
Alpha oscillations reflect similar mapping mechanisms for localizing touch on hands and tools
Authors: Fabio Cécile , Salemme Romeo , Farnè Alessandro , Miller Luke E.
Published: September 2022

Numerous studies have suggested that tools become incorporated into a representation of our body. A prominent hypothesis suggests that our brain re-uses body-based computations when we use tools. However, little is known about how this is implemented at the neural level. Here we used the ability to localize touch on both tools and body parts as a case study to fill this gap. Neural oscillations in the alpha (8-13 Hz) and beta (15-25 Hz) frequency bands are involved in mapping touch on the body in distinct reference frames. Alpha activity reflects the mapping of touch in external coordinates, whereas beta activity reflects the mapping of touch in skin-centered coordinates. Here, we aimed at pinpointing the role of these oscillations during tool-extended sensing. We recorded participants’ oscillatory activity while tactile stimuli were applied to either hands or the tips of hand-held rods. The posture of the hands/tool-tips was uncrossed or crossed at participants’ body midline in order for us to disentangle brain responses related to different coordinate systems. We found that alpha-band activity was modulated similarly across postures when localizing touch on hands and on tools, reflecting the position of touch in external space. Source reconstruction also indicated a similar network of cortical regions involved for tools and hands. Our findings strongly suggest that the brain uses similar oscillatory mechanisms for mapping touch on the body and tools, supporting the idea of neural processes being repurposed for tool-use.

SIGNIFICANCE STATEMENT

Tool use is one of the defining traits of humankind. Tools allow us to explore our environment and expand our sensorimotor abilities. A prominent hypothesis suggests that our brain re-uses body-based neural processing to swiftly adapt to the use of tools. However, little is known about how this is implemented at the neural level. In the present study we used the ability to map touch on both tools and body parts as a case study to fill this gap. We found that the brain uses similar oscillatory mechanisms for mapping touch on a hand-held tool and on the body. These results provide novel and compelling support to the idea that neural processes devoted to body-related information are re-purposed for tool-use.
Two-Dimensional-Dwell-Time Analysis of Ion Channel Gating using High Performance Computing Clusters
Authors: Oikonomou Efthymios , Gruber Thomas , Chandra Achanta Ravi , Höller Sarina , Alzheimer Christian , Wellein Gerhard , Huth Tobias
Published: September 2022

The power of single-channel patch-clamp recordings is widely acknowledged among ion channel enthusiasts. The method allows observing the action of a single protein complex in real time and hence the deduction of the underlying conformational changes in the ion channel protein. Commonly, recordings are modeled using hidden Markov chains, connecting open and closed states in the experimental data with protein conformations. The rates between states denote transition probabilities that, for instance, could be modified by membrane voltage or ligand binding. Preferably, the time resolution of recordings should be in the range of microseconds or below, potentially bridging Molecular Dynamic simulations and experimental patch-clamp data. Modeling algorithms have to deal with limited recording bandwidth and a very noisy background. It was previously shown that the fit of 2-Dimensional-Dwell-Time histograms (2D-fit) with simulations is very robust in that regard. Errors introduced by the low-pass filter or noise cancel out to a certain degree when comparing experimental and simulated data. In addition, the topology of models, that is, the chain of open and closed states could be inferred from 2D-histograms. However, the 2D-fit was never applied to its full potential. The reason was the extremely time-consuming and unreliable fitting process, due to the stochastic variability in the simulations. We have now solved both issues by introducing a Message Passing Interface (MPI) allowing massive parallel computing on a High Performance Computing (HPC) cluster and obtaining ensemble solutions. With the ensembles, we have optimized the fit algorithm and demonstrated how important the ranked solutions are for difficult tasks related to a noisy background, fast gating events beyond the corner frequency of the low-pass filter and topology estimation of the underlying Markov model. The fit can reliably extract events down to a signal-to-noise ratio of one and rates up to ten times higher than the filter frequency. It is even possible to identify equivalent Markov topologies. Finally, we have shown that, by combining the objective function of the 2D-fit with the deviation of the current amplitude distributions automatic determination of the current level of the conducting state is possible. It is even possible to infer the level with an apparent current reduction due to the application of the low-pass filter. Making use of an HPC cluster, the power of 2D-Dwell-Time analysis can be used to its fullest, allowing extraction of the matching Markov model from a time series with minor input of the experimenter. Additionally, we add the benefit of estimating the reliability of the results by generating ensemble solutions.
Epistatic effects between amino acid insertions and substitutions mediate toxin-resistance of vertebrate Na+,K+-ATPases
Authors: Mohammadi Shabnam , Özdemir Halil İbrahim , Ozbek Pemra , Sumbul Fidan , Stiller Josefin , Deng Yuan , Crawford Andrew J. , Rowland Hannah M. , Storz Jay F. , Andolfatto Peter , Dobler Susanne
Published: September 2022

The recurrent evolution of resistance to cardiotonic steroids (CTS) across diverse animals most frequently involves convergent amino-acid substitutions to the H1-H2 extracellular loop of Na+,K+-ATPase (NKA). Previous work established that hystricognath rodents (e.g. chinchilla) and pterocliform birds (sandgrouse) have convergently evolved amino-acid insertions in the H1-H2 loop, but their functional significance is not known. Using protein engineering, we show that these insertions have distinct effects on CTS resistance of NKA in the two lineages that strongly depend on intramolecular interactions with other residues. Removing the insertion in the chinchilla lineage unexpectedly increases CTS resistance and decreases NKA activity. In the sandgrouse lineage, the insertion works in concert with the substitution Q111R to increase CTS resistance while maintaining wild-type ATPase activity levels. Molecular docking simulations provide additional insight into the biophysical mechanisms responsible for the context-specific CTS insensitivity of the enzyme. Our results highlight the diversity of genetic substrates that underlie CTS insensitivity in vertebrate NKA and reveal how amino-acid insertions can alter the phenotypic effects of point mutations at key sites in the same protein domain.
Epistasis decreases with increasing antibiotic pressure but not temperature
Authors: Ghenu Ana-Hermina , Amado André , Gordo Isabel , Bank Claudia
Published: September 2022

Predicting mutational effects is essential for the control of antibiotic resistance (ABR). Predictions are difficult when there are strong genotype-by-environment (G×E), gene-by-gene (G×G or epistatic), or gene- by-gene-by-environment (G×G×E) interactions. We quantified G×G×E effects inEscherichia coliacross environmental gradients. We created intergenic fitness landscapes using gene knock-outs and single nucleotide ABR mutations previously identified to vary in the extent of G×E effects in our environments of interest. Then, we measured competitive fitness across a complete combinatorial set of temperature and antibiotic dosage gradients. In this way, we assessed the predictability of 15 fitness landscapes across 12 different but related environments. We found G×G interactions and rugged fitness landscapes in the absence of antibiotic, but as antibiotic concentration increased, the fitness effects of ABR genotypes quickly overshadowed those of gene knock-outs, and the landscapes became smoother. Our work reiterates that some single mutants, like those conferring resistance or susceptibility to antibiotics, have consistent effects across genetic backgrounds in stressful environments. Thus, although epistasis may reduce the predictability of evolution in benign environments, evolution may be more predictable in adverse environments.
Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures
Authors: Hasan A M Mahedi , Cremaschi Paolo , Wetterskog Daniel , Jayaram Anuradha , Wong Stephen Q , Williams Scott , Pasam Anupama , Trigos Anna , Trujillo Blanca , Grist Emily , Friedrich Stefanie , Vainauskas Osvaldas , Parry Marina , Ismail Mazlina , Devlies Wout , Wingate Anna , Lise Stefano , Sandhu Shahneen , Attard Gerhardt
Published: September 2022

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genomewide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07×10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories.

Statement of significance

Lethal prostate cancer evolves from a single clone of origin and upon a treatment-mediated selection, progresses to lethal disease via a limited number of related clones harboring patient-unique androgen receptor gene architectures.
Novel Laser Capture Microdissection-Proteomic Analysis Identifies Spatially Distinct Extracellular Matrix Signatures in the Core and Infiltrating Edge of Human Glioblastoma
Authors: Pedley Robert , Prescott Danielah T. , Appleton Ellen , Dingle Lewis , Minshull James , D’Urso Pietro Ivo , Djoukhadar Ibrahim , Gilmore Andrew P. , Roncaroli Federico , Swift Joe
Published: September 2022

Background

Glioblastoma is the most common and aggressive primary brain tumour in adults. Hallmarks of glioblastoma include its intra-tumoural heterogeneity and extensive invasion of the surrounding brain. Glioblastoma is known to remodel the extracellular matrix (ECM) of the brain, resulting in altered mechanical properties and the establishment of a tumour-promoting microenvironment. How changes in the expression and spatial distribution of ECM constituents within glioblastoma contribute to invasion and disease progression is still unclear.

Methods

Here we report on a protocol for laser-capture microdissection coupled with mass spectrometry (LCM-proteomics) that allowed a spatially resolved and unbiased analysis of the regional ECM proteome (matrisome) in formalin-fixed and paraffin-embedded (FFPE) samples of human glioblastoma. We investigated five molecularly characterised hemispheric adult glioblastomas where the brain/tumour interface and tumour epicentre were represented in the surgical specimens and snap-frozen tissue was available. LCM-proteomic analysis was validated with immunohistochemistry.

Results

LCM-proteomics identified 53 matrisome proteins in FFPE tissue, demonstrating comparable performance with conventional analysis of snap-frozen tissue. The analysis revealed distinct matrisome components in the brain/tumour interface versus the tumour epicentre. Guided by data from LCM-proteomic analysis, immunostaining for tenascin-R confirmed greater staining in the brain/tumour interface, whilst expression of fibronectin was higher in the tumour epicentre.

Conclusion

The protocol described in this work allowed for accurate, spatially resolved analysis of ECM in FFPE tissues, with performance comparable to analysis of snap-frozen tissue. While the focus for this work was on the regional ECM composition of glioblastoma, we found that the LCM-proteomics protocol is also applicable to the study of the wider proteome, and represents a valuable tool for investigating tumour/tissue heterogeneity. This protocol opens the possibility to apply LCM-proteomics to retrospective studies with the advantage of accessing clinical history and follow-up information, providing a valuable resource for translational research in glioblastoma.
FAS: Assessing the similarity between proteins using multi-layered feature architectures
Authors: Dosch Julian , Bergmann Holger , Tran Vinh , Ebersberger Ingo
Published: September 2022

Motivation

Expert curation to differentiate between functionally diverged homologs and those that may still share a similar function routinely relies on the visual interpretation of domain architecture changes. However, the size of contemporary data sets integrating homologs from hundreds to thousands of species calls for alternate solutions. Scoring schemes to evaluate domain architecture similarities can help to automatize this procedure, in principle. But existing schemes are often too simplistic in the similarity assessment, many require an a-priori resolution of overlapping domain annotations, and those that allow overlaps to extend the set of annotations sources cannot account for redundant annotations. As a consequence, the gap between the automated similarity scoring and the similarity assessment based on visual architecture comparison is still too wide to make the integration of both approaches meaningful.

Results

Here, we present FAS, a scoring system for the comparison of multi-layered feature architectures integrating information from a broad spectrum of annotation sources. Feature architectures are represented as directed acyclic graphs, and redundancies are resolved in the course of comparison using a score maximization algorithm. A benchmark using more than 10,000 human-yeast ortholog pairs reveals that FAS consistently outperforms existing scoring schemes. Using three examples, we show how automated architecture similarity assessments can be routinely applied in the benchmarking of orthology assignment software, in the identification of functionally diverged orthologs, and in the identification of entries in protein collections that most likely stem from a faulty gene prediction.

Availability and implementation

FAS is available as python package: https://pypi.org/project/greedyFAS/
Antibiotic effects on microbial communities are modulated by resource competition
Authors: Newton Daniel Philip , Ho Po-Yi , Huang Kerwyn Casey
Published: September 2022

Antibiotic treatment significantly impacts the human gut microbiota, but quantitative understanding of how antibiotics affect community diversity is lacking. Here, we build on classical ecological models of resource competition to investigate community responses to antibiotic-induced species-specific death rates. Our analyses highlight the complex dependence of species coexistence that can arise from the interplay of resource competition and antibiotic activity, independent of other biological mechanisms. We show that resource competition can cause richness to change non-monotonically as antibiotic concentrations are increased. We identified resource competition structures that cause richness to depend on the order of sequential application of antibiotics (non-transitivity), and the emergence of synergistic and antagonistic effects under simultaneous application of multiple antibiotics (non-additivity). These complex behaviors can be prevalent, especially when generalist consumers are targeted. Communities can be prone to either synergism or antagonism, but typically not both, and antagonism is more common. Furthermore, we identify a striking overlap in competition structures that lead to non-transitivity during antibiotic sequences and those that lead to non-additivity during antibiotic combination, suggesting that our analysis is broadly applicable across a wide range of clinically relevant antibiotic treatment schemes. In sum, our results will facilitate the engineering of community dynamics via deleterious agents.
SpaCeNet: Spatial Cellular Networks from omics data
Authors: Schrod Stefan , Lück Niklas , Lohmayer Robert , Solbrig Stefan , Völkl Dennis , Wipfler Tina , Shutta Katherine H. , Guebila Marouen Ben , Schäfer Andreas , Beißbarth Tim , Zacharias Helena U. , Oefner Peter J. , Quackenbush John , Altenbuchinger Michael
Published: September 2022

Advances in omics technologies have allowed spatially resolved molecular profiling of single cells, providing a window not only into the diversity and distribution of cell types within a tissue, but also into the effects of interactions between cells in shaping the transcriptional landscape. Cells send chemical and mechanical signals which are received by other cells, where they can subsequently initiate context-specific gene regulatory responses. These interactions and their responses shape the individual molecular phenotype of a cell in a given microenvironment. RNAs or proteins measured in individual cells together with the cells’ spatial distribution provide invaluable information about these mechanisms and the regulation of genes beyond processes occurring independently in each individual cell. “SpaCeNet” is a method designed to elucidate both the intracellular molecular networks (how molecular variables affect each other within the cell) and the intercellular molecular networks (how cells affect molecular variables in their neighbors). This is achieved by estimating conditional independence relations between captured variables within individual cells and by disentangling these from conditional independence relations between variables of different cells. A python implementation of SpaCeNet is publicly available athttps://github.com/sschrod/SpaCeNet.
Tailored machine learning models for functional RNA detection in genome-wide screens
Authors: Klapproth Christopher , Zöztsche Siegfried , Kühnl Felix , Fallmann Jörg , Stadler Peter F. , Findeiß Sven
Published: September 2022

The in silico prediction of non-coding and protein-coding genetic loci is an area of research that has gathered large attention in the field of comparative genomics. In the last decade, much effort has been made to investigate numerous properties of nucleotide sequences that hint at their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive in silico annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results. Furthermore, we showcase the usage of our software package in a full-genome screen of Drosophila melanogaster and evaluate our results against the well-known but much less flexible program RNAz.
Quantitative proteomics and lipidomics of TFG-deficient B cells provide insights into mechanisms of autophagic flux and plasma cell biology
Authors: Steinmetz Tobit D. , Reimann Lena , Schulz Sebastian R. , Urbanczyk Sophia , Thomas Jana , Himmelreich Ann-Kathrin , Golombek Florian , Castiglione Kathrin , Brodesser Susanne , Warscheid Bettina , Mielenz Dirk
Published: September 2022

The autophagy-flux-promoting protein TFG (Trk-fused gene) is up-regulated during B cell differentiation into plasma cells and supports survival of CH12 B cells. We hypothesized that quantitative proteomics analysis of CH12tfgKO B cells with intact or blocked autophagy-lysosome flux (via NH4Cl) will identify mechanisms of TFG-dependent autophagy, plasma cell biology and B cell survival. Analysis of CH12WT B cells in the presence of NH4Cl will identify proteins whose presence is continuously regulated by lysosomes independent of TFG. We determined hundreds of proteins to be controlled by TFG and/or NH4Cl. Notably, NH4Cl treatment alone increased the abundance of a cluster of cytosolic and mitochondrial translational proteins while it also reduced a number of proteins. Within the B cell relevant protein pool, BCL10 was reduced, while JCHAIN was increased in CH12tfgKO B cells. Furthermore, TFG regulated the abundance of transcription factors, such as JUNB, metabolic enzymes, such as the short-chain fatty acid activating enzyme ACOT9 or the glycolytic enzyme ALDOC. Gene ontology enrichment analysis revealed that TFG-regulated proteins localized to mitochondria and membrane-bounded organelles. Due to these findings we performed shotgun lipidomics of glycerophospholipids, uncovering that a particular phosphatidylethanolamine (PE) species, 32:0 PE, which lipidates LC3 most efficiently, was less abundant while phosphatidylglycerol (PG) was more abundant in CH12tfgKO B cells. In line with the role of PG as precursor for Cardiolipin (CL), the CL content was higher in CH12tfgKO B cells and addition of PG liposomes to B cells increased the amount of CL. We propose a role for TFG in B cell activation and plasma cell biology via regulation of proteins involved in germinal center and plasma cell development, such as BCL10 or JCHAIN, as well as in lipid homeostasis, mitochondria and metabolism.
Outcome of Crash Course Training on Protein Structure Prediction with Artificial Intelligence
Authors: Balamurugan D. , Dougherty Maureen , Lubin Joseph , Arias Paul , Chang Janet , Dalenberg Kenneth , Kholodovych Vlad , Zelzion Ehud , Khare Sagar D. , von Oehsen James Barr , Zwick Michael E. , Burley Stephen K.
Published: September 2022

Protein structure predictions have broad impact on several science disciplines such as biology, bioengineering, and medical science. AlphaFold2[1] and RoseTTAFold[2] are the current state-of-the-art AI methods to predict the structures of proteins with an accuracy comparable to lower-resolution experimental methods. In its 2021 year review, both these methods were recognized as “breakthrough of the year” by Science magazine[3] and “method of the year” by Nature magazine [4]. It is timely and important to provide training and support on these emerging methods. Our crash course “Enabling Protein Structure Prediction with Artificial Intelligence “was conducted in collaboration with domain experts and research computing professionals. The crash course was well received by the community as there were 750 registrants from all over the world. Here we provide the summary of the crash course, describe our findings in organizing the crash course, and explain what preparation steps helped us with the hands-on training.

CCS CONCEPTS

Computing methodologies à Machine learning à Machine learning approaches à Bio-inspired approaches
Intra-islet glucagon signalling regulates pulsatile insulin secretion and glucose homeostasis
Authors: Suba K , Patel Y , Martin-Alonso A , Roberts A , Hansen B , Norton M , Shrewsbury J , Kwok R , Kalogianni V , Chen S , Liu X , Rutter GA , Jones B , Minnion J , Owen BM , Distaso W , Drucker DJ , Tan TM , Bloom SR , Murphy KG , Salem V
Published: September 2022

Background

Type 2 diabetes (T2D) is characterised by the loss of pulsatile insulin secretion. We studied mice with β-cell specific loss of the glucagon receptor (Gcgr fl/fl X Ins-1Cre), to investigate the role of intra-islet glucagon receptor signalling on pan-islet calcium oscillations and insulin pulsatility.

Methods

Frequently sampled intravenous glucose tolerance tests were conducted on Gcgr β-cell-/- and littermate controls. Crossing with GCaMP6f (STOP flox) animals further allowed for β-cell specific expression of a fluorescent calcium indicator. These islets were functionally imaged in vitro and in vivo. Wild-type mice were transplanted with islets expressing GCaMP6f in β-cells into the anterior eye chamber and placed on a high fat diet. Part of the cohort received a glucagon analogue (GCG-analogue) for 40 days and the control group were fed to achieve weight matching. Calcium imaging was performed regularly during the development of hyperglycaemia and in response to GCG-analogue treatment.

Results

Gcgr β-cell-/- mice exhibited impaired glucose tolerance following intraperitoneal glucose challenge (control 12.7mmol/L ±0.6 vs. Gcgr β-cell-/- 15.4mmol/L ±0.0 at 15 min, p=0.002); fasting glycaemia was not different to controls. In vitro, Gcgr β-cell-/- islets showed profound loss of synchronised calcium waves in response to glucose which was only partially rescued in vivo. First-phase insulin pulsatility on peripheral blood sampling (n=5) was significantly disordered in Gcgr β-cell-/- mice (burst mass Gcgr β-cell-/- 0.30 ±0.03 versus 0.84 ±0.23 for controls p=0.04). Diet induced obesity and hyperglycaemia resulted in a loss of co-ordinated [Ca2+]I waves in transplanted islets. This was reversed with GCG-analogue treatment, independently of weight-loss (n=8).

Conclusion

These data provide novel evidence for the role of intra-islet GCGR signalling in sustaining synchronised calcium oscillations and support a possible therapeutic role for glucagonergic agents to restore the insulin pulsatility lost in T2D.
Sophorolipid Candidates Demonstrate Cytotoxic Efficacy Against 2D And 3D Breast Cancer Models
Authors: Roberge Cassandra L. , Miceli Rebecca T. , Murphy Lillian R. , Kingsley David M. , Gross Richard A. , Corr David T.
Published: September 2022

Sophorolipids are biosurfactants derived from the non-pathogenic yeast Starmerella bombicola, with potential efficacy in anti-cancer applications. Simple and cost-effective synthesis of these drugs makes them a promising alternative to traditional chemotherapeutics, pending their success in preliminary drugscreening. Drug screening typically utilizes 2D cell monolayers due to their simplicity and potential for high-throughput assessment. However, 2D assays fail to capture the complexity and 3D context of the tumor microenvironment, and have consequently been implicated in the high percentage of drugs investigated in vitro that later fail in clinical trials. We screened two sophorolipid candidates and clinically-used chemotherapeutic, doxorubicin, on in vitro breast cancer models ranging from 2D monolayers to 3D spheroids, employing Optical Coherence Tomography to confirm these morphologies. We calculated corresponding IC50 values for these drugs and found one of the sophorolipids to have comparable toxicities to the chemotherapeutic control. Our findings show increased drug resistance associated with model dimensionality, such that all drugs tested showed that 3D spheroids exhibited higher IC50 values than their 2D counterparts. These findings demonstrate promising preliminary data to support the use of sophorolipids as a more affordable alternative to traditional clinical interventions and demonstrate the importance of 3D tumor models in assessing drug response.
Targeted degradation of microtubule-associated protein tau using an engineered nanobody-E3 ubiquitin ligase adapter fusion
Authors: Wang Shiyao , Jiang Shaowei , Zheng Guoan , Cho Yong Ku
Published: September 2022

Reducing the level of microtubule-associated protein tau has recently emerged as a promising therapeutic approach for a range of neurodegenerative diseases. Among the various approaches, targeted protein degradation provides a reversible means to rapidly reduce and specifically target disease-relevant forms of tau. However, in aging cells, the protein turnover activity is generally weakened, reducing the efficacy of protein degradation. A potential solution to this is to harness the nuclear proteasomal activity. The nucleus has a high proteasomal content and the degradation activity remains relatively unaffected even in aged cells. Here we show that an E3 ligase F-box domain from the nuclear protein human speckle type BTB/POZ protein (SPOP) is effective in degrading the microtubule-associated protein tau in primary mouse hippocampal neurons. Using EGFP-tagged tau and a GFP-binding nanobody fused to SPOP, we found that the native nuclear localization signal in SPOP causes nuclear sequestration of the target protein. However, degradation of the sequestered target proteins is incomplete, resulting in nuclear accumulation. Replacing the native SPOP nuclear localization signal (NLS) with variants having altered nuclear localization efficiency dramatically affects in the degree of nuclear accumulation of the target protein. Interestingly, nanobody-SPOP with no NLS was more efficient than that with a NLS in reducing overall tau level, causing an approximately 50% reduction in ectopically expressed human tau in mouse neurons. These results show the potential for harnessing the nuclear proteasomal activity for targeted tau degradation in cells and demonstrate a new modality of regulating intracellular protein degradation.
Role of astroglial ACBP in energy metabolism flexibility and feeding responses to metabolic challenges in male mice
Authors: Bouyakdan K. , Manceau R. , Robb J. , Rodaros D. , Fulton S. , Alquier T.
Published: September 2022

Acyl-CoA Binding Protein (ACBP), also known as Diazepam Binding Inhibitor (DBI), has recently emerged as a hypothalamic and brainstem gliopeptide regulating energy balance. Previous work has shown that the ACBP-derived octadecaneuropeptide exerts strong anorectic action via POMC neuron activation and the melanocortin-4 receptor. Importantly, targeted ACBP loss-of-function in astrocytes promotes hyperphagia and diet-induced obesity while its overexpression in arcuate astrocytes reduces feeding and body weight. Despite this knowledge, the role of astroglial ACBP in adaptive feeding and metabolic responses to acute metabolic challenges has not been investigated. Using different paradigms, we found that ACBP deletion in Glial Fibrillary Acidic Protein (GFAP)-positive astrocytes does not affect diet-induced weight loss in obese male mice nor metabolic parameters in chow-fed mice (e.g. energy expenditure, body temperature) during fasting, cold exposure and at thermoneutrality. In contrast, astroglial ACBP deletion impairs meal pattern and feeding responses during refeeding after a fast and during cold exposure, thereby showing that ACBP is required to mount an appropriate feeding response in states of increased energy demand. These findings challenge the general view that astroglial ACBP exerts anorectic effects and suggest that regulation of feeding by ACBP is dependent on metabolic status.
Size-tunable ICG-based contrast agent platform for targeted near-infrared photoacoustic imaging
Authors: Singh Shrishti , Giammanco Giovanni , Hu Chih-Hsiang , Bush Joshua , Cordova Leandro Soto , Lawrence Dylan J , Moran Jeffrey L , Chitnis Parag V , Veneziano Remi
Published: September 2022

Near-infrared photoacoustic imaging (NIR-PAI) combines the advantages of optical and ultrasound imaging to provide anatomical and functional information of tissues with high resolution. Although NIR-PAI is promising, its wide application is hindered by the limited availability of NIR contrast agents. J-aggregates (JA) made of indocyanine green dye (ICG) represents an attractive class of biocompatible contrast agents for PAI. Here, we present a facile synthesis method that combines ICG and ICG-azide dyes for producing contrast agent with tunable size down to 230 nm and direct functionalization with targeting moieties. The ICG-JA platform has a detectable PA signalin vitrothat is two times stronger than whole blood and high photostability. The targeting ability of ICG-JA was measuredin vitrousing HeLa cells. The ICG-JA platform was then injected into mice andin vivoNIR-PAI showed enhanced visualization of liver and spleen for 90 minutes post-injection with a contrast-to-noise ratio of 2.42.
Effect of time spent on active learning on exam performance: A controlled case study on a course with different instructors but identical teaching materials
Authors: Cen Xinjian , Lee Rachel J. , Contreras Christopher , Owens Melinda T. , Maloy Jeffrey
Published: September 2022

Active learning, including student thinking and discussion in class, has been shown to increase student learning gains. However, it is less clear how variations in how instructors implement active learning affect student gains. Our study aims to investigate the extent to which the time spent on individual episodes of active learning activities influences student performance. We hypothesized that instructors who let students spend more time on peer discussion and individual thinking on practice problems associated with particular learning objectives will have better student exam scores on exam questions addressing those objectives. To test this hypothesis, we obtained a large data set of classroom recordings and student exam scores from an introductory biology course at a large four-year university, where three instructors shared identical teaching materials and exams for different course offerings.

Contrary to our hypothesis, although the three instructors spent significantly different amounts of time on episodes of thinking and peer discussion, there was no correlation between the total time spent on active learning activities and student performance on exam questions. Linear mixed-effects modeling of the effect of length of episodes of student thinking and discussion on exam score found that the amount of course time spent on active learning activities did not reliably predict student performance on associated exam questions. This result held true even when only considering learning objectives with high variations in performance between offerings, difficult exam questions, exam questions requiring higher-order thinking skills, or within-instructor performance. Although our study was only conducted in one course, our results imply that time spent per individual episode of student thinking or peer discussion may not be the primary factor explaining the positive effects of active learning and that it may be worthwhile to explore other factors.
Application of Data-Driven computing to patient-specific simulation of brain neuromodulation
Authors: Salahshoor Hossein , Ortiz Michael
Published: September 2022

We present a class of model-free Data-Driven solvers that effectively enable the utilization ofin situandin vivoimaging datadirectlyin full-scale calculations of the mechanical response of the human brain to sonic and ultrasonic stimulation, entirely bypassing the need for analytical modeling or regression of the data. The well-posedness of the approach and its convergence with respect to data are proven analytically. We demonstrate the approach, including its ability to make detailed spatially-resolved patient-specific predictions of wave patterns, using public-domain MRI images, MRE data and commercially available solid-mechanics software.
Random and natural non-coding RNA have similar structural motif patterns but can be distinguished by bulge, loop, and bond counts
Authors: Ghaddar Fatme , Dingle Kamaludin
Published: September 2022

An important question in evolutionary biology is whether and in what ways genotype-phenotype (GP) map biases can influence evolutionary trajectories. Untangling the relative roles of natural selection and biases (and other factors) in shaping phenotypes can be difficult. Because RNA secondary structure (SS) can be analysed in detail mathematically and computationally, is biologically relevant, and a wealth of bioinformatic data is available, it offers a good model system for studying the role of bias. For quite short RNA (lengthL≤ 126), it has recently been shown that natural and random RNA are structurally very similar, suggesting that bias strongly constrains evolutionary dynamics. Here we extend these results with emphasis on much larger RNA with length up to 3000 nucleotides. By examining both abstract shapes and structural motif frequencies (ie the numbers of helices, bonds, bulges, junctions, and loops), we find that large natural and random structures are also very similar, especially when contrasted to typical structures sampled from the space of all possible RNA structures. Our motif frequency study yields another result, that the frequencies of different motifs can be used in machine learning algorithms to classify random and natural RNA with quite high accuracy, especially for longer RNA (eg ROC AUC 0.86 forL= 1000). The most important motifs for classification are found to be the number of bulges, loops, and bonds. This finding may be useful in using SS to detect candidates for functional RNA within ‘junk’ DNA regions.
Is evolutionary conservation a useful predictor for cancer long noncoding RNAs? Insights from the Cancer lncRNA Census 3
Authors: Vancura Adrienne , Gutierrez Alejandro H. , Hennig Thorben , Pulido-Quetglas Carlos , Slack Frank , Johnson Rory , Häfliger Simon
Published: September 2022

Evolutionary conservation is a measure of gene functionality that is widely used to prioritise long noncoding RNAs (lncRNA) in cancer research. Intriguingly, while updating our Cancer LncRNA Census, we observed an inverse relationship between year of discovery and evolutionary conservation. This observation is specific to cancer over other diseases, implying a sampling bias in selection of lncRNA candidates and casting doubt on the value of evolutionary metrics for prioritisation of cancer-related lncRNAs.
Myelin plasticity in ventral tegmental area is required for opioid reward
Authors: Yalçın Belgin , Pomrenze Matthew B. , Malacon Karen , Chau Isabelle J. , Taylor Kathryn R. , Ni Lijun , Contreras-Esquivel Daniel , Malenka Robert C. , Monje Michelle
Published: September 2022

All drugs of abuse induce long-lasting changes in synaptic transmission and neural circuit function that underlie substance use disorders. Here, we demonstrate that dopaminergic neuronal activity-regulated myelin plasticity is a key modulator of dopaminergic circuit function and opioid reward. Oligodendroglial lineage cells respond to dopaminergic neuronal activity evoked by either optogenetic stimulation or by morphine administration specifically within the reward center ventral tegmental area (VTA), but not along the axonal projections in the medial forebrain bundle nor within the target nucleus accumbens (NAc). Genetic blockade of oligodendrogenesis dampens NAc dopamine release dynamics, which is critical for reward learning, and impairs behavioral conditioning to morphine. Our findings identify dopaminergic neuronal activity-regulated myelin plasticity as an important circuit modification that is required for opioid reward.

One-Sentence Summary

Activity-dependent myelin plasticity in the ventral tegmental area modulates dopaminergic circuit function and opioid reward