title: Privacy-preserving harmonization via distributed ComBat

abstract: Challenges in clinical data sharing and the need to protect data privacy have led to the development and popularization of methods that do not require directly transferring patient data. In neuroimaging, integration of data across multiple institutions also introduces unwanted biases driven by scanner differences. These scanner effects have been shown by several research groups to severely affect downstream analyses. To facilitate the need of removing scanner effects in a distributed data setting, we introduce distributed ComBat, an adaptation of a popular harmonization method for multivariate data that borrows information across features. We present our fast and simple distributed algorithm and show that it yields equivalent results using data from the Alzheimers Disease Neuroimaging Initiative. Our method enables harmonization while ensuring maximal privacy protection, thus facilitating a broad range of downstream analyses in functional and structural imaging studies.


title: Deliberation gated by opportunity cost adapts to context with urgency

abstract: Finding the right amount of deliberation, between insufficient and excessive, is a hard decision making problem that depends on the value we place on our time. Average-reward, putatively encoded by tonic dopamine, serves in existing reinforcement learning theory as the stationary opportunity cost of time, and of deliberation in particular. However, this cost often varies with environmental context that can change over time. Here, we introduce an opportunity cost of deliberation estimated adaptively on multiple timescales to account for non-stationary contextual factors. We use it in a simple decision-making heuristic based on average-reward reinforcement learning (AR-RL) that we call Performance-Gated Deliberation (PGD). We propose PGD as a strategy used by animals wherein deliberation cost is implemented directly as urgency, a previously characterized neural signal effectively controlling the speed of the decision-making process. We show PGD outperforms AR-RL solutions in explaining behaviour and urgency of non-human primates in a context-varying random walk prediction task and is consistent with relative performance and urgency in a context-varying random dot motion task. We make readily testable predictions for both neural activity and behaviour and call for an integrated research program in cognitive and systems neuroscience around the value of time.

category: neuroscience


title: Disparate energy consumption despite similar network activity

abstract: Neural circuits can produce similar activity patterns from vastly different combinations of channel and synaptic conductances. These conductances are tuned for specific activity patterns but might also reflect additional constraints, such as metabolic cost or robustness to perturbations. How do such constraints influence the range of permissible conductances? Here, we investigate how metabolic cost affects the parameters of neural circuits with similar activity in a model of the pyloric network of the crab Cancer borealis. We use a novel machine learning method to identify a range of network models that can generate activity patterns matching experimental data, and find that neural circuits can consume largely different amounts of energy despite similar circuit activity. Furthermore, a reduced but still significant range of circuit parameters gives rise to energy-efficient circuits. We then examine the space of parameters of energy-efficient circuits and identify potential tuning strategies for low metabolic cost. Finally, we investigate the interaction between metabolic cost and temperature robustness. We show that metabolic cost can vary across temperatures, but that robustness to temperature changes does not necessarily incur an increased metabolic cost. Our analyses show that, despite metabolic efficiency and temperature robustness constraining circuit parameters, neural systems can generate functional, efficient, and robust network activity with widely disparate sets of conductances.


title: Energy efficient network activity from disparate circuit parameters


title: Multi-omic Analysis of Developing Human Retina and Organoids Reveals Cell-Specific Cis-Regulatory Elements and Mechanisms of Non-Coding Genetic Disease Risk.

abstract:
Cis-regulatory elements (CREs) play a critical role in the development, maintenance, and disease-states of all human cell types. In the human retina, CREs have been implicated in a variety of inherited retinal disorders. To characterize cell-class-specific CREs in the human retina and elucidate their potential functions in development and disease, we performed single-nucleus (sn)ATAC-seq and snRNA-seq on the developing and adult human retina and on human retinal organoids. These analyses allowed us to identify cell-class-specific CREs, enriched transcription factor binding motifs, putative target genes, and to examine how these features change over development. By comparing DNA accessibility between the human retina and retinal organoids we found that CREs in organoids are highly correlated at the single-cell level, validating the use of organoids as a model for studying disease-associated CREs. As a proof of concept, we studied the function of a disease-associated CRE at 5q14.3 in organoids, identifying its principal target gene as the miR-9-2 primary transcript and demonstrating a dual role for this CRE in regulating neurogenesis and gene regulatory programs in mature glia. This study provides a rich resource for characterizing cell-class-specific CREs in the human retina and showcases retinal organoids as a model in which to study the function of retinal CREs that influence retinal development and disease.

HIGHLIGHTSO_LISingle-cell map of cis-regulatory elements in developing and adult human retina.
C_LIO_LICorrelation of single-cell DNA accessibility between human retina and retinal organoids.
C_LIO_LIAssociation of disease risk loci with cell-class-specific accessibility.
C_LIO_LIModeling of enhancer function at the 5q14.3 retinal disease-risk locus.
C_LI

category: developmental biology


title: TaxiBGC: a Taxonomy-guided Approach for the Identification of Experimentally Verified Microbial Biosynthetic Gene Clusters in Shotgun Metagenomic Data

abstract: Biosynthetic gene clusters (BGCs) in microbial genomes encode for the production of bioactive secondary metabolites (SMs). Given the well-recognized importance of SMs in microbe-microbe and microbe-host interactions, the large-scale identification of BGCs from microbial metagenomes could offer novel functional insights into complex chemical ecology. Despite recent progress, currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read-assembly and prediction of a narrow breadth of BGC classes. To overcome these limitations, we developed TaxiBGC (Taxonomy-guided Identification of Biosynthetic Gene Clusters), a computational pipeline for identifying experimentally verified BGCs in shotgun metagenomes by first pinpointing the microbial species likely to produce them. We show that our species-centric approach was able to identify BGCs in simulated metagenomes more accurately than by solely detecting BGC genes. By applying TaxiBGC on 5,423 metagenomes from the Human Microbiome Project and various case-control studies, we identified distinct BGC signatures of major human body sites and candidate stool-borne biomarkers for multiple diseases, including inflammatory bowel disease, colorectal cancer, and psychiatric disorders. In all, TaxiBGC demonstrates a significant advantage over existing techniques for systematically characterizing BGCs and inferring their SMs from microbiome data.

category: bioinformatics


title: LEVELNET: diving into the multiple layers of protein-protein physical interaction networks

abstract:
AO_SCPLOWBSTRACTC_SCPLOWThe complexity underlying protein-protein interaction (PPI) networks calls for the development of comprehensive knowledge bases organizing PPI-related data. The constant growth and high reliability of structural data make them a suitable source of evidence for the determination of PPI. We present LEVELNET, a fully-automated and scalable environment designed to integrate, explore, and infer protein interactions and non-interactions based on physical contacts and other PPI sources, including user-defined annotations. LEVELNET helps to break down the complexity of PPI networks by representing them as multi-layered graphs and allowing the selection of subnetworks and their direct comparison. LEVELNET proposes an interactive visualisation based on a user-friendly web interface. LEVELNET applications are multiple. It allows to explore PPIs of biological processes, identify co-localised partners, assess PPI predictions from computational or experimental sources, unravel cross-interactions, show and compare multiple PPI sources, and help creating PPI benchmarks with specific properties.

AvailabilityLEVELNET is freely available to the community at http://www.lcqb.upmc.fr/levelnet/.


title: Ageing-associated myelin dysfunction drives amyloid deposition in mouse models of Alzheimer's disease

abstract: The prevalence of Alzheimers disease (AD), the leading cause of dementia, shows a strict age-dependency, but why ageing constitutes the main risk factor for this disease is still poorly understood. Brain ageing affects oligodendrocytes1 and the structural integrity of myelin sheaths2, the latter associated with secondary neuroinflammation3. Since oligodendrocytes support axonal and neuronal health4-7, we hypothesised that ageing-associated loss of myelin integrity could be an upstream risk factor for neuronal amyloid-{beta} (A{beta}) deposition, the primary neuropathological hallmark of AD. Here, we show that in AD mouse models different genetically induced defects of myelin integrity or demyelinating injuries are indeed potent drivers of amyloid deposition in vivo, quantified by whole brain light sheet microscopy. Conversely, the lack of myelin in the forebrain provides protection against plaque deposition. Mechanistically, we find that myelin dysfunction causes the accumulation of the A{beta} producing machinery within axonal swellings and increases cortical amyloid precursor protein (APP) cleavage. Surprisingly, AD mice with dysfunctional myelin lack plaque-corralling microglia but show a disease-associated microglia (DAM)-like signature as revealed by bulk and single cell transcriptomics. These activated microglia, however, are primarily engaged with myelin, preventing the protective reactions of microglia to A{beta} plaques. Our data suggest a working model, in which age-dependent structural defects of myelin promote plaque formation, directly and indirectly, and are thus an upstream AD risk factor. Improving oligodendrocyte health and myelin integrity could be a promising target to delay AD.g


title: Zona Incerta activity dynamics underlying associative fear learning and fear generalization

abstract: Recent studies suggest that the Zona Incerta (ZI) plays a role in fear learning and recall. However, there is a clear gap in knowledge as to whether the ZI can encode fear evoking threats and cues that predict them. Here, we subject mice to a classical fear conditioning paradigm while recording the in-vivo calcium dynamics of ZI neurons. We observed that ZI neurons can encode not only a fear evoking stimulus, but can also learn to encode predictive cues, associate them with the unconditioned fear evoking stimulus, and discriminate them from neutral non-predictive cues. While the ZI across all mice learned to become mainly excited by fear predictive cues, only mice that did not generalize fear became largely inhibited by non-predictive cues and better discriminated the two. Together, we provide extensive evidence that the ZI differentially encode fear predictive and non-predictive cues in a generalization dependent manner.


title: Geometric complexity and the information-theoretic comparison of functional-response models

abstract:
The assessment of relative model performance using information criteria like AIC and BIC has become routine among functional-response studies, reflecting trends in the broader ecological literature. Such information criteria allow comparison across diverse models because they penalize each models fit by its parametric complexity -- in terms of their number of free parameters -- which allows simpler models to outperform similarly fitting models of higher parametric complexity. However, criteria like AIC and BIC do not consider an additional form of model complexity, referred to as geometric complexity, which relates specifically to the mathematical form of the model. Models of equivalent parametric complexity can differ in their geometric complexity and thereby in their ability to flexibly fit data. Here we use the Fisher Information Approximation to compare, explain, and contextualize how geometric complexity varies across a large compilation of single-prey functional-response models -- including prey-, ratio-, and predator-dependent formulations -- reflecting varying apparent degrees and forms of non-linearity. Because a models geometric complexity varies with the datas underlying experimental design, we also sought to determine which designs are best at leveling the playing field among functional-response models. Our analyses illustrate (1) the large differences in geometric complexity that exist among functional-response models, (2) there is no experimental design that can minimize these differences across all models, and (3) even the qualitative nature by which some models are more or less flexible than others is reversed by changes in experimental design. Failure to appreciate model flexibility in the empirical evaluation of functional-response models may therefore lead to biased inferences for predator-prey ecology, particularly at low experimental sample sizes where its impact is strongest. We conclude by discussing the statistical and epistemological challenges that model flexibility poses for the study of functional responses as it relates to the attainment of biological truth and predictive ability.

Contribution to Field StatementThe use of criteria like AIC and BIC for selecting among functional-response models is now standard, well-accepted practice, just as it is in the ecological literature as a whole. The generic desire underlying the use of these criteria is to make the comparison of model performance an unbiased and equitable process by penalizing each models fit to data by its parametric complexity (relating to its number of free parameters). Here we introduce the Fisher Information Approximation to the ecological literature and use it to understand how the geometric complexity of models -- a form of model complexity relating to a models functional flexibility that is not considered by criteria like AIC and BIC -- varies across a large compilation of 40 different single-prey functional-response models. Our results add caution against the simplistic use and interpretation of information-theoretic model comparisons for functional-response experiments, showing just how large an effect that model flexibility can have on inferences of model performance. We therefore use our work to help clarify the challenges that ecologists studying functional responses must face in the attainment of biological truth and predictive ability.

category: ecology


title: Within-Arctic horizontal gene transfer as a driver of convergent evolution in distantly related microalgae

abstract: The Arctic Ocean is being impacted by warming temperatures, increasing freshwater and highly variable ice conditions. The microalgal communities underpinning Arctic marine food webs, once thought to be dominated by diatoms, include a phylogenetically diverse range of small algal species, whose biology remains poorly understood. Here, we present genome sequences of a cryptomonad, a haptophyte, a chrysophyte, and a pelagophyte, isolated from the Arctic water column and ice. Comparing protein family distributions and sequence similarity across a densely-sampled set of algal genomes and transcriptomes, we note striking convergences in the biology of distantly related small Arctic algae, compared to non-Arctic relatives; although this convergence is largely exclusive of Arctic diatoms. Using high-throughput phylogenetic approaches, incorporating environmental sequence data from Tara Oceans, we demonstrate that this convergence was partly explained by horizontal gene transfers (HGT) between Arctic species, in over at least 30 other discrete gene families, and most notably in ice-binding domains (IBD). These Arctic-specific genes have been repeatedly transferred between Arctic algae, and are independent of equivalent HGTs in the Antarctic Southern Ocean. Our data provide insights into the specialized Arctic marine microbiome, and underlines the role of geographically-limited HGT as a driver of environmental adaptation in eukaryotic algae.

category: evolutionary biology


title: Genes used together are more likely to be fusedtogether in evolution by mutational mechanisms: Abioinformatic test of the used-fused hypothesis

abstract: Cases of parallel or recurrent gene fusions, whether in evolution or in cancer and genetic disease, are difficult to explain, as they require multiple of the same or similar breakpoints to repeat. The used-together-fused-together hypothesis holds that genes that are used together repeatedly and persistently in a certain context are more likely than otherwise to undergo a fusion mutation in the course of evolution--reminiscent of the Hebbian learning rule where neurons that fire together wire together. This mutational hypothesis offers to explain both evolutionary parallelism and recurrence in disease of gene fusions under one umbrella. Here, we test this hypothesis using bioinformatic data. Various measures of gene interaction, including co-expression, co-localization, same-TAD presence and semantic similarity of GO terms show that human genes whose homologs are fused in one or more other organisms are significantly more likely to interact together than random genes, controlling for genomic distance between genes. In addition, we find a statistically significant overlap between pairs of genes that fused in the course of evolution in non-human species and pairs that undergo fusion in human cancers. These results provide support for the used-together-fused-together hypothesis over several alternative hypotheses, including that all gene pairs can fuse by random mutation, but among pairs that have thus fused, those that have interacted previously are more likely to be favored by selection. Multiple consequences are discussed, including the relevance of mutational mechanisms to exon shuffling, to the distribution of fitness effects of mutation and to parallelism.


title: Quantitative traits under selection: derivations of distributions, higher moments, and the effects of recombination

abstract:
The mathematical theory of quantitative traits is over one hundred years old but it is still a fertile area for research and analysis. However, the effects of selection on a quantitative trait, while well understood for the effects on the mean and variance, have traditionally been difficult to attack from the perspective of analyzing the probability density of the breeding values and deriving higher (third and fourth) moments as well as analyzing the impact of recombination. In this paper, the exact formula for the breeding value distribution after selection is derived and, using new integral tables, the first four moments are given exact expressions for the first time. In addition, the effects of recombination on the full distribution of breeding values are demonstrated. Finally, the changes of GXE covariance in the selected parent population caused by factors similar to the Bulmer Effect are also investigated in detail.

Mathematics Subject Classification (2020)MSC code 92D10 {middle dot} MSC code 92D15

category: genetics


title: Large differences in carbohydrate degradation and transport potential in the genomes of lichen fungal symbionts

abstract:
Lichen symbioses are generally thought to be stabilized by the transfer of fixed carbon compounds from a photosynthesizing unicellular symbiont to a fungus. In other fungal symbioses, carbohydrate subsidies correlate with genomic reductions in the number of genes for plant cell wall-degrading enzymes (PCWDEs), but whether this is the case with lichen fungal symbionts (LFSs) is unknown. We predicted genes encoding carbohydrate-active enzymes (CAZymes) and sugar transporters in 17 existing and 29 newly sequenced genomes from across the class Lecanoromycetes, the largest extant clade of LFSs. Despite possessing lower mean numbers of PCWDE genes compared to non-symbiont Ascomycota, all LFS genomes possessed a robust suite of predicted PCWDEs. The largest CAZyme gene numbers, on par with model species such as Penicillium, were retained in genomes from the subclass Ostropomycetidae, which are found in crust lichens with highly specific ecologies. The lowest numbers were in the subclass Lecanoromycetidae, which are symbionts of many generalist macrolichens. Our results suggest that association with phototroph symbionts does not in itself result in functional loss of PCWDEs and that PCWDE losses may have been driven by adaptive processes within the evolution of specific LFS lineages. The inferred capability of some LFSs to access a wide range of carbohydrates suggests that some lichen symbioses may augment fixed CO2 with carbon from external sources.

SignificanceLichen symbioses are considered self-contained autotrophic systems in which the total carbon economy is the sum of phototroph-fixed CO2, supplied to a fungus as sugars. In other fungal-plant symbioses, such as mycorrhizae, plant-derived sugar subsidies are associated with loss of plant cell wall-degrading enzymes (PCWDEs). We compared PCWDE inventories in 46 genomes from the largest group of lichen fungal symbionts (LFSs) with non-symbionts from across Ascomycota. We found that despite lower overall gene numbers, all LFSs retain PCWDEs, and some possess gene numbers and functional diversity on par with non-symbionts. Our results suggest that association with a phototroph does not necessarily result in PCWDE loss, and some lichens may obtain carbon from sources other than CO2 fixation.

category: genomics


title: DESIGNER DNA HYDROGELS TO STIMULATE 3D CELL INVASION BY ENHANCED RECEPTOR EXPRESSION AND MEMBRANE ENDOCYTOSIS

abstract: DNA has emerged as one of the smartest biopolymers to bridge the gap between chemical science and biology to design scaffolds like hydrogels by physical entanglement or chemical bonding with remarkable properties. We present here a completely new application of DNA based hydrogels in terms of their capacity to stimulate membrane endocytosis, leading to enhanced cell spreading and invasion for cells in ex-vivo 3D spheroids models. Multiscale simulation studies along with DLS data showed that the hydrogel formation was enhanced at lower temperature and it converts to liquid with increase in temperature. DNA hydrogels induced cell spreading as observed by increase in cellular area by almost two-folds followed by increase in receptor expression, endocytosis and 3D invasion potential of migrating cells. Our first results lay the foundation for upcoming diverse applications of hydrogels to probe and program various cellular and physiological processes that can have lasting applications in stem cells programming and regenerative therapeutics.

category: bioengineering


title: Rational Design of Self-assembling Artificial Proteins Utilizing a Micelle-Assisted Protein Labeling Technology (MAPLabTech): Testing the Scope

abstract: Self-assembling artificial proteins (SAPs) have gained enormous interest in recent years due to their applications in different fields. Synthesis of well-defined monodisperse SAPs is accomplished predominantly through genetic methods. However, the last decade witnessed the use of few chemical technologies for that purpose. In particular, micelle-assisted protein labeling technology (MAPLabTech) has made huge progress in this area. The first generation MAPLabTech focused on site-specific labeling of the active-site residue of serine proteases to make SAPs. Further, this methodology was exploited for labeling of N-terminal residue of a globular protein to make functional SAPs. In this study, we describe the synthesis of novel SAPs by developing a chemical method for site-specific labeling of a surface-exposed cysteine residue of globular proteins. In addition, we disclose the synthesis of redox- and pH-sensitive SAPs and their systematic self-assembly and dis-assembly studies using complementary biophysical studies. Altogether these studies further expand the scope of MAPLabTech in different fields such as vaccine design, targeted drug delivery, diagnostic imaging, biomaterials, and tissue engineering.


title: Water soluble, red emitting, carbon nanoparticles stimulate 3D cell invasion via clathrin-mediated endocytic uptake

abstract: Bright, fluorescent nanoparticles with excitation and emission towards the red end of the spectrum are highly desirable in the field of bioimaging. We present here a new class of organic carbon-based nanoparticles (CNPs) with robust quantum yield and fluorescence towards the red region of the spectrum. Using organic substrates like para-phenylenediamine (PPDA) dispersed in diphenyl ether and reflux conditions, we achieved scalable amounts of CNPs of the average size of 25 nm. These CNPs were readily uptaken by different mammalian cells, and we show that they prefer clathrin-mediated endocytosis for their cellular entry route. Not only can these CNPs be specifically uptaken in cells, but they also stimulate cellular processes like cell invasion from 3D spheroid models. These new class of CNPs, which have sizes similar to proteinaceous ligands, hold immense potential for their surface functionalization, whereby they could be explored as promising bioimaging agents for biomedical imaging and intracellular drug delivery.


title: HIV-1 drug resistance profiling using amino acid sequence space cartography

abstract: Human immunodeficiency virus (HIV) drug resistance is a global healthcare issue. The emergence of drug resistance demands treatment adaptation. Computational methods predicting the drug resistance profile from genomic data of HIV isolates are advantageous for monitoring drug resistance in patients. Yet, the currently existing computational methods for drug resistance prediction are either not suitable for complex mutational patterns in emerging HIV strains or lack interpretability of prediction results which is of paramount importance in clinical practice. Hence, to overcome these limitations, new approaches for the HIV drug resistance prediction combining high accuracy and interpretability are required. In this work, a new methodology for the analysis of protein sequence data based on the application of generative topographic mapping was developed and applied for HIV drug resistance profiling. It allowed achieving high accuracy of resistance predictions and intuitive interpretation of prediction results. The developed approach was successfully applied for the prediction of HIV resistance towards protease, reverse-transcriptase and integrase inhibitors and in-depth analysis of HIV resistance-inducing mutation patterns. Hence, it can serve as an efficient and interpretable tool to suggest optimal treatment regimens.


title: Protein language model embeddings for fast, accurate, alignment-free protein structure prediction

abstract: All state-of-the-art (SOTA) protein structure predictions rely on evolutionary information captured in multiple sequence alignments (MSAs), primarily on evolutionary couplings (co-evolution). Such information is not available for all proteins and is computationally expensive to generate. Prediction models based on Artificial Intelligence (AI) using only single sequences as input are easier and cheaper but perform so poorly that speed becomes irrelevant. Here, we described the first competitive AI solution exclusively inputting embeddings extracted from pre-trained protein Language Models (pLMs), namely from the transformer pLM ProtT5, from single sequences into a relatively shallow (few free parameters) convolutional neural network (CNN) trained on inter-residue distances, i.e. protein structure in 2D. The major advance originated from processing the attention heads learned by ProtT5. Although these models required at no point any MSA, they matched the performance of methods relying on co-evolution. Although not reaching the very top, our lean approach came close at substantially lower costs thereby speeding up development and each future prediction. By generating protein-specific rather than family-averaged predictions, these new solutions could distinguish between structural features differentiating members of the same family of proteins with similar structure predicted alike by all other top methods.


title: Revisiting the identification of breast cancer tumour suppressor genes defined by copy number loss of the long arm of chromosome 16.

abstract:
In breast cancer loss of the long-arm of chromosome 16 is frequently observed, suggesting this is the location of tumour suppressor gene or genes. Previous studies localised two or three minimal regions for the LOH genes in the vicinity of 16q22.1 and 16q24.3, however the identification of the relevant tumour suppressor genes has proved elusive. The current availability of large datasets from breast cancers, that include both gene expression and gene dosage of the majority of genes on the long-arm of chromosome 16 (16q), provides the opportunity to revisit the identification of the critical tumour suppressor genes in this region.

Utilising such data it was found 37% of breast cancers are single copy for all genes on 16q and this was more frequent in the luminal A and B subtypes. Since luminal breast cancers are associated with a superior prognosis this is consistent with previous data associating loss of 16q with breast cancers of better survival. Previous chromosomal studies found a karyotype with a der t(1;16) to be the basis for a proportion of breast cancers with loss of 16q. Use of data indicating the dosage of genes 21.9% of breast cancers were consistent with a der t(1;16) as the basis for loss of 16q. In such cases there is both loss of one dose of 16q and three doses of 1q suggesting a tumour suppressor function associated with long-arm of chromosome 16 and an oncogene function for 1q.

Previous studies have approached the identification of tumour suppressor genes on 16q by utilising breast cancers with partial loss of 16q with the assumption regions demonstrating the highest frequency of loss of heterozygosity pinpoint the location of tumour suppressor genes. Sixty one of 816 breast cancers in this study showed partial loss of 16q defined by dosage of 357 genes. There was no compelling evidence for "hot-spots" of localised LOH which would pinpoint major tumour suppressor genes. Comparison of gene expression data between various groups of breast cancers based on 16q dosage was used to identify possible tumour suppressor genes. Combining these comparisons, together with known gene functional data, allowed the identification of eleven potential tumour suppressor genes spread along 16q. It is proposed that breast cancers with a single copy of 16q results in the simultaneous reduction of expression of several tumour suppressor genes. The existence of multiple tumour suppressor genes on 16q would severely limit any attempt to pinpoint tumour suppressor genes locations based on localised hot-spots of loss of heterozygosity.

Interestingly, the majority of the identified tumour suppressor genes are involved in the modulation of wild-type p53 function. This role is supported by the finding that 80.5% of breast cancers with 16q loss have wild-type p53. TP53 is the most common mutated gene in cancer. In cancers with wild-type p53 would require other strategies to circumvent the key tumour suppressor role of p53. In breast cancers with complete loss of one dose of 16q it is suggested this provides a mechanism that contributes to the amelioration of p53 function.

category: cancer biology


title: Fillable and Unfillable Gaps in Rice Transcriptome under Field and Controlled Environments

abstract: The differences between plants grown in field and controlled environments have long been recognised; however, few studies have addressed the underlying molecular mechanisms. Here, we show fillable and unfillable gaps in the transcriptomes of rice grown in field and controlled environments by utilising SmartGC, a high-performance growth chamber that reproduces the fluctuating irradiance, temperature, and humidity of field environments. Rice transcriptome dynamics in SmartGC mimicked those in the field, particularly during the morning and evening; those in conventional growth chamber conditions did not. Further analysis revealed that fluctuation of irradiance affects transcriptome dynamics in the morning and evening, while fluctuation of temperature only affects transcriptome dynamics in the morning. We found upregulation of genes related to biotic and abiotic stress, whose expression was affected by environmental factors that cannot be mimicked by SmartGC. Our results accelerate the understanding of plant responses to field environments for both field and laboratory studies.

category: plant biology


title: Three conserved hydrophobic residues in the CC domain of Pit contribute to its plasma membrane localization and immune induction

abstract: Nucleotide-binding leucine-rich repeat (NLR) proteins work as crucial intracellular immune receptors. N-terminal domains of NLRs fall into two groups, namely coiled-coil (CC) and Toll-interleukin 1 receptor (TIR) domains, which play critical roles in signal transduction and disease resistance. However, the activation mechanisms of NLRs, and how their N-termini are involved in immune induction, remain largely unknown. Here, we revealed that the rice NLR Pit self-associates through its CC domain. The CC domain of Pit possesses three conserved hydrophobic residues that are known to be involved in homodimer formation in two NLRs, barley MLA10 and Arabidopsis RPM1. Interestingly, the function of these residues in Pit is different from that in MLA10 and RPM1. Although the three hydrophobic residues are important for Pit-induced disease resistance against rice blast fungus, they do not participate in self-association or in binding to downstream signaling molecules. Based on homology modeling of Pit using the structure of the Arabidopsis NLR ZAR1, we tried to clarify the role of the three conserved hydrophobic residues and found that they are involved in the plasma membrane localization. Our findings provide novel insights for understanding the mechanisms of NLR activation as well as the relationship between subcellular localization and immune induction.


title: High-fidelity, high-spatial-resolution diffusion MRI of the ex-vivo whole human brain on the 3T Connectom scanner using structured low-rank EPI ghost correction

abstract:
Diffusion MRI (dMRI) of whole, intact, fixed postmortem human brain at high spatial resolution serves as key bridging technology for 3D mapping of structural connectivity and tissue microstructure at the mesoscopic scale. Ex vivo dMRI offers superior spatial resolution compared to in vivo dMRI but comes with its own technical challenges due to the significantly reduced T2 relaxation times and decreased diffusivity incurred by tissue fixation. The altered physical properties of fixed tissue necessitate the use of alternative acquisition strategies to preserve SNR and achieve sufficient diffusion weighting. Multi-shot or segmented 3D echo planar imaging (EPI) sequences have been used to shorten echo times (TEs) with reduced distortions from field inhomogeneity and eddy currents on small-bore MR scanners and have been adopted for high b-value dMRI of ex vivo whole human brain specimens.

The advent of stronger gradients on human MRI scanners has led to improved image quality and a wider range of diffusion-encoding parameters for dMRI but at the cost of more severe eddy currents that result in spatial and temporal variations in the background magnetic field, which cannot be corrected for using standard vendor-provided ghost correction solutions. In this work, we show that conventional ghost correction techniques based on navigators and linear phase correction may be insufficient for EPI sequences using strong diffusion-sensitizing gradients in ex vivo dMRI experiments, resulting in orientationally biased dMRI estimates. This previously unreported problem is a critical roadblock in any effort to leverage scanners with ultra-high gradients for high-precision mapping of human neuroanatomy at the mesoscopic scale. We propose an advanced reconstruction method based on structured low-rank matrix modeling that reduces the ghosting substantially. We show that this method leads to more accurate and reliable dMRI metrics, as exemplified by diffusion tensor imaging and high angular diffusion imaging analyses in distributed neuroanatomical areas of fixed whole human brain specimens. Our findings advocate for the use of advanced reconstruction techniques for recovering unbiased metrics from ex vivo dMRI acquisitions and represent a crucial step toward making full use of strong diffusion-encoding gradients for neuroscientific studies seeking to study brain structure at multiple spatial scales.


title: Environmental enrichment mitigatesthe long-lasting sequelae of perinatal fentanyl exposure

abstract:
The opioid epidemic is a rapidly evolving societal issue driven, in part, by a surge in synthetic opioid use. A rise in fentanyl use among pregnant women has led to a 40-fold increase in the number of perinatally-exposed infants in the past decade. These children are more likely to develop mood- and somatosensory-related conditions later in life, suggesting that fentanyl may permanently alter neural development. Here, we examined the behavioral and synaptic consequences of perinatal fentanyl exposure in adolescent male and female C57BL/6J mice and assessed the therapeutic potential of environmental enrichment to mitigate these effects. Dams were given ad libitum access to fentanyl (10 {micro}g/mL, per os) across pregnancy and until weaning (PD 21). Perinatally-exposed adolescent mice displayed hyperactivity (PD 45), enhanced sensitivity to anxiogenic environments (PD 46), and sensory maladaptation (PD 47) - sustained behavioral effects that were completely normalized by environmental enrichment (PD 21-45). Additionally, environmental enrichment normalized the fentanyl-induced changes in the frequency of miniature excitatory postsynaptic currents of layer 2/3 neurons in the primary somatosensory cortex (S1). We also demonstrate that fentanyl impairs short- and long-term potentiation in S1 layer 2/3 neurons which, instead, exhibit a sustained depression of synaptic transmission that is restored by environmental enrichment. On its own, environmental enrichment suppressed long-term depression of control S1 neurons from vehicle-treated mice subjected to standard housing conditions. These results demonstrate that the lasting effects of fentanyl can be ameliorated with a non-invasive intervention introduced during early development.

Significance StatementIllicit use of fentanyl accounts for a large proportion of opioid-related overdose deaths. Children exposed to opioids during development have a higher risk of developing neuropsychiatric disorders later in life. Here, we employ a preclinical model of perinatal fentanyl exposure that recapitulates these long-term impairments and show, for the first time, that environmental enrichment can reverse deficits in somatosensory circuit function and behavior. These findings have the potential to directly inform and guide ongoing efforts to mitigate the consequences of perinatal opioid exposure.


title: Multidimensional encoding of movement and contextual variables by rat globus pallidus neurons during a novel environment exposure task

abstract: The basal ganglia (BG) play a critical role in a variety of functions that are essential for animal survival. Information from different cortical areas propagates through the BG in anatomically segregated circuits along the parallel direct and indirect pathways. We examined how the globus pallidus (GP), a central nucleus within the indirect pathway, encodes input from the motor and cognitive domains. We chronically recorded and analyzed neuronal activity in the GP of rats engaged in a novel environment exposure task. GP neurons displayed multidimensional responses to movement and contextual information. A model predicting single unit activity required many task-related variables, thus confirming the multidimensionality of GP neurons. In addition, populations of GP neurons, but not single units, reliably encoded the animals locomotion speed and the environmental novelty. We posit that the GP independently processes information from different domains, effectively compresses it and collectively conveys it to successive nuclei.


title: Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography

abstract:
The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons.

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title: The beneficial rhizobacterium Bacillus velezensis acquires iron from roots via a type VII secretion system for colonization

abstract: Niche colonization is the key for bacterial adaptation to the environment, and competition for iron largely determines root colonization by rhizosphere microbes. Pathogenic and beneficial symbiotic bacteria use various unique secretion systems to support plant colonization or acquire limited resources from the environment. However, ubiquitous nonsymbiotic beneficial rhizobacteria have never been reported to use a unique secretion system to facilitate colonization. Here, we show that the type VII secretion system (T7SS) of the beneficial rhizobacterium Bacillus velezensis SQR9 contributes to root colonization. Knocking out T7SS and the major secreted protein YukE in SQR9 caused a significant decrease in root colonization. Moreover, the T7SS and YukE caused iron loss in plant roots in the early stage after inoculation, which contributed to root colonization by SQR9. Interestingly, purified YukE, but not inactivated YukE, could change the permeability of root cells. We speculated that secreted YukE might be directly inserted into the root cell membrane to cause iron leakage, indicating that the bacterial protein and root cell membrane interact directly. Moreover, a bacterial siderophore and the T7SS may be coordinately involved in iron acquisition by B. velezensis SQR9 for efficient root colonization. We showed that the beneficial rhizobacterium B. velezensis SQR9 could acquire iron from roots via the T7SS for rapid colonization. These findings provide the first insight into the function of the unique secretion system in nonsymbiotic beneficial rhizobacteria and reveal a novel mutualism in which plants and bacteria might share iron in a sequential manner.

category: microbiology


title: Evolutionary conservation of maternal RNA localization in fishes and amphibians revealed by TOMO-Seq

abstract: Asymmetrical localization of biomolecules inside the egg, results in uneven cell division and establishment of many biological processes, cell types and the body plan. However, our knowledge about evolutionary conservation of localized mRNAs is still limited to a few candidates. Our goal was to compare localization profiles along the animal-vegetal axis of mature eggs from four models, Xenopus laevis, Danio rerio, Ambystoma mexicanum and Acipenser ruthenus using the spatial expression method called TOMO-Seq. We revealed that RNAs of many known important genes such as germ layer determinants, germ plasm factors and members of key signalling pathways, are localized in completely different profiles among the models. There was also a poor correlation between vegetally localized genes but a relatively good correlation between animally localized genes. These findings indicate that the regulation of embryonic development within the animal kingdom is highly diverse and cannot be deduced based on a single model.


title: Individual-level specialisation and interspecific resource partitioning in bees revealed by pollen DNA metabarcoding

abstract: It is increasingly recognised that intraspecific variation in traits, such as morphology, behaviour, or diet is both ubiquitous and ecologically important. While many species of predators and herbivores are known to display high levels of between-individual diet variation, there is a lack of studies on pollinators. It is important to fill in this gap because individual-level specialisation of flower-visiting insects is expected to affect their efficiency as pollinators with consequences for plant reproduction. Accordingly, the aim of our study was to quantify the level of individual-level specialisation and foraging preferences, as well as interspecific resource partitioning, across different temporal scales in three co-occurring species of bees of the genus Ceratina (Hymenoptera: Apidae: Xylocopinae), C. chalybea, C. nigrolabiata, and C. cucurbitina. We conducted a field experiment where we provided artificial nesting opportunities for the bees and combined a short-term mark-recapture study with the dissection of the bees nests to obtain repeated samples from individual foraging females and complete pollen provisions from their nests. Hence, we could study variation of the composition of pollen collected by the bees at different temporal scales. We used DNA metabarcoding based on the ITS2 locus to identify the composition of the pollen samples. We found that the composition of pollen carried on the bodies of female bees and stored in the brood provisions in their nests significantly differed among the three co-occurring species. At the intraspecific level, individual females consistently differed in their level of specialisation and in the composition of pollen carried on their bodies and stored in their nests. Our study thus provides evidence of consistent individual-level specialisation in pollinators across multiple temporal scales. We also demonstrate that higher generalisation at the species level stemmed from larger among-individual variation in diets as observed in other types of consumers, such as predators. Our study thus reveals how specialisation and foraging preferences of bees change from the scale of individual foraging bouts to complete pollen provisions accumulated in their nests over their lifetime. Such multi-scale view of foraging behaviour is necessary to improve our understanding of the functioning of plant-flower visitor communities.


title: A comparative study of population genetic structure reveals patterns consistent with selection at functional microsatellites in common sunflower

abstract: Microsatellites have long been considered non-functional, neutrally evolving regions of the genome. Recent findings suggest that they can function as drivers of rapid adaptive evolution. Previous work on common sunflower identified 479 transcribed microsatellites where allele length significantly correlates with gene expression (eSTRs) in a stepwise manner. Here, a population genetic approach is used to test whether eSTR allele length variation is under selection. Genotypic variation among and within populations at 13 eSTRs was compared with that at 19 anonymous microsatellites in 672 individuals from 17 natural populations of sunflower from across a cline running from Saskatchewan to Oklahoma. Expected heterozygosity, allelic richness, and allelic diversity were significantly lower at eSTRs, a pattern consistent with higher relative rates of purifying selection. Further, an analysis of variation in microsatellite allele lengths (lnRV), and heterozygosities (lnRH), indicate recent selective sweeps at the eSTRs. Mean microsatellite allele lengths at four eSTRs within populations are significantly correlated with latitude consistent with the predictions of the tuning knob model which predicts stepwise relationships between microsatellite allele length and phenotypes. This finding suggests that shorter or longer alleles at eSTRs may be favored in climatic extremes. Collectively, our results imply that eSTRs are likely under selection and that they may be playing a role in facilitating local adaptation across a well-defined cline in the common sunflower.


title: The genetic code is very close to a global optimum in a model of its origin taking into account both the partition energy of amino acids and their biosynthetic relationships

abstract: We used the Morans I index of global spatial autocorrelation with the aim of studying the distribution of the physicochemical or biological properties of amino acids within the genetic code table. First, using this index we are able to identify the amino acid property - among the 530 analyzed - that best correlates with the organization of the genetic code in the set of amino acid permutation codes. Considering, then, a model suggested by the coevolution theory of the genetic code origin - which in addition to the biosynthetic relationships between amino acids took into account also their physicochemical properties - we investigated the level of optimization achieved by these properties either on the entire genetic code table, or only on its columns or only on its rows. Specifically, we estimated the optimization achieved in the restricted set of amino acid permutation codes subject to the constraints derived from the biosynthetic classes of amino acids, in which we identify the most optimized amino acid property among all those present in the database. Unlike what has been claimed in the literature, it would appear that it was not the polarity of amino acids that structured the genetic code, but that it could have been their partition energy instead. In actual fact, it would seem to reach an optimization level of about 96% on the whole table of the genetic code and 98% on its columns. Given that this result has been obtained for amino acid permutation codes subject to biosynthetic constraints, that is to say, for a model of the genetic code consistent with the coevolution theory, we should consider the following conclusions reasonable. (i) The coevolution theory might be corroborated by these observations because the model used referred to the biosynthetic relationships between amino acids, which are suggested by this theory as having been fundamental in structuring the genetic code. (ii) The very high optimization on the columns of the genetic code would not only be compatible but would further corroborate the coevolution theory because this suggests that, as the genetic code was structured along its rows by the biosynthetic relationships of amino acids, on its columns strong selective pressure might have been put in place to minimize, for example, the deleterious effects of translation errors. (iii) The finding that partition energy could be the most optimized property of amino acids in the genetic code would in turn be consistent with one of the main predictions of the coevolution theory. In other words, since the partition energy is reflective of the protein structure and therefore of the enzymatic catalysis, the latter might really have been the main selective pressure that would have promoted the origin of the genetic code. Indeed, we observe that the {beta}-strands show an optimization percentage of 94.45%, so it is possible to hypothesize that they might have become the object of selection during the origin of the genetic code, conditioning the choice of biosynthetic relationships between amino acids. (iv) The finding that the polarity of amino acids is less optimized than their partition energy in the genetic code table might be interpreted against the physicochemical theories of the origin of the genetic code because these would suggest, for example, that a very high optimization of the polarity of amino acids in the code could be an expression of interactions between amino acids and codons or anticodons, which would have promoted their origin. This might now become less sustainable, given the very high optimization that is instead observed in favor of partition energy but not polarity. Finally, (v) the very high optimization of the partition energy of amino acids would seem to make a neutral origin of the ability of the genetic code to buffer, for example, the deleterious effects of translation errors very unlikely. Indeed, an optimization of about 100% would seem that it might not have been achieved by a simple neutral process, but this ability should probably have been generated instead by the intervention of natural selection. In actual fact, we show that the neutral hypothesis of the origin of error minimization has been falsified for the model analyzed here. Therefore, we will discuss our observations within the theories proposed to explain the origin of the organization of the genetic code, reaching the conclusion that the coevolution theory is the most strongly corroborated theory.


title: Prediction Of Plastic Degrading Microbes

abstract: Plastic pollution is one of the challenging problems in the environment. But a life without plastic we cannot imagine. This paper deals with the prediction of plastic degrading microbes using Machine Learning. Here we have used Decision Tree, Random Forest, Support vector Machine and K Nearest Neighbor algorithms in order to predict the plastic degrading microbes. Among the four classifiers, Random Forest model gave the best accuracy of 99.1%.


title: Scalable Clustering with Supervised Linkage Methods

abstract: Data clustering plays a significant role in biomedical sciences, particularly in single-cell data analysis. Researchers use clustering algorithms to group individual cells into populations that can be evaluated across different levels of disease progression, drug response, and other clinical statuses. In many cases, multiple sets of clusters must be generated to assess varying levels of cluster specificity. For example, there are many subtypes of leukocytes (e.g. T cells), whose individual preponderance and phenotype must be assessed for statistical/functional significance. In this report, we introduce a novel hierarchical density clustering algorithm (HAL-x) that uses supervised linkage methods to build a cluster hierarchy on raw single-cell data. With this new approach, HAL-x can quickly predict multiple sets of labels for immense datasets, achieving a considerable improvement in computational efficiency on large datasets compared to existing methods. We also show that cell clusters generated by HAL-x yield near-perfect F1-scores when classifying different clinical statuses based on single-cell profiles. Our hierarchical density clustering algorithm achieves high accuracy in single cell classification in a scalable, tunable and rapid manner. We make HAL-x publicly available at: https://pypi.org/project/hal-x/


title: Harnessing protein folding neural networks for peptide-protein docking

abstract: Highly accurate protein structure predictions by the recently published deep neural networks such as AlphaFold2 and RoseTTAFold are truly impressive achievements, and will have a tremendous impact far beyond structural biology. If peptide-protein binding can be seen as a final complementing step in the folding of a protein monomer, we reasoned that these approaches might be applicable to the modeling of such interactions. We present a simple implementation of AlphaFold2 to model the structure of peptide-protein interactions, enabled by linking the peptide sequence to the protein c-terminus via a poly glycine linker. We show on a large non-redundant set of 162 peptide-protein complexes that peptide-protein interactions can indeed be modeled accurately. Importantly, prediction is fast and works without multiple sequence alignment information for the peptide partner. We compare performance on a smaller, representative set to the state-of-the-art peptide docking protocol PIPER-FlexPepDock, and describe in detail specific examples that highlight advantages of the two approaches, pointing to possible further improvements and insights in the modeling of peptide-protein interactions. Peptide-mediated interactions play important regulatory roles in functional cells. Thus the present advance holds much promise for significant impact, by bringing into reach a wide range of peptide-protein complexes, and providing important starting points for detailed study and manipulation of many specific interactions.


title: Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction using Spatially Localized Immuno-Oncology Markers

abstract: Spatially resolved characterization of the transcriptome and proteome promises to provide further clarity on cancer pathogenesis and etiology, which may inform future clinical practice through classifier development for clinical outcomes. However, batch effects may potentially obscure the ability of machine learning methods to derive complex associations within spatial omics data. Profiling thirty-five stage three colon cancer patients using the GeoMX Digital Spatial Profiler, we found that mixed-effects machine learning (MEML) methods{dagger} may provide utility for overcoming significant batch effects to communicate key and complex disease associations from spatial information. These results point to further exploration and application of MEML methods within the spatial omics algorithm development life cycle for clinical deployment.

category: pathology


title: Mechanisms governing protective pregnancy-induced adaptions of the pelvic floor muscles in the rat pre-clinical model

abstract:
BackgroundThe intrinsic properties of pelvic soft tissues in women who do and do not sustain birth injuries are likely divergent, however little is known about this. Rat pelvic floor muscles undergo protective pregnancy-induced structural adaptations, sarcomerogenesis and increase in intramuscular collagen content, that protect against birth injury.

ObjectivesWe aimed to test the following hypotheses: 1) increased mechanical load of gravid uterus drives antepartum adaptations; 2) load-induced changes are sufficient to protect pelvic muscles from birth injury.

Study DesignIndependent effects of load uncoupled from hormonal milieu of pregnancy were tested in 3- to 4-month-old Sprague-Dawley rats randomly divided into four groups, N=5- 10/group: (1) load-/pregnancy hormones- (controls); (2) load+/pregnancy hormones-; (3) reduced load/pregnancy hormones+; (4) load+/pregnancy hormones+. Mechanical load simulating a gravid uterus was simulated by weighing uterine horns with beads similar to fetal rat size and weight. Reduced load was achieved by unilateral pregnancy after unilateral uterine horn ligation. To assess acute and chronic phases required for sarcomerogenesis, rats were sacrificed at 4 hours or 21 days post bead loading. Coccygeus, iliocaudalis, pubocaudalis and non-pelvic tibialis anterior were harvested for myofiber and sarcomere length measurements. Intramuscular collagen content was assessed using hydroxyproline assay. Additional 20 load+/pregnancy hormones- rats underwent vaginal distention to determine whether load-induced changes are sufficient to protect from mechanical muscle injury in response to parturition-associated strains of various magnitude. Data, compared using two-way repeated measures analysis of variance/pairwise comparisons, are presented as mean {+/-} standard error of mean.

ResultsAcute increase in load resulted in significant pelvic floor muscle stretch, accompanied by acute increase in sarcomere length compared to non-loaded control muscles (coccygeus: 2.69{+/-}0.03 vs 2.30{+/-}0.06 {micro}m, P<0.001; pubocaudalis: 2.71{+/-}0.04 vs 2.25{+/-}0.03 {micro}m, P<0.0001; iliocaudalis: 2.80{+/-}0.06 vs 2.35{+/-}0.04 {micro}m, P<0.0001). After 21 days of sustained load, sarcomeres returned to operational length in all pelvic muscles (P>0.05). However, the myofibers remained significantly longer in load+/pregnancy hormones- compared to load- /pregnancy hormones- in coccygeus (13.33{+/-}0.94 vs 9.97{+/-}0.26 mm, P<0.0001) and pubocaudalis (21.20{+/-}0.52 vs 19.52{+/-}0.34 mm, P<0.04) and not different from load+/pregnancy hormones+ (12.82{+/-}0.30 and 22.53{+/-}0.32mm, respectively, P>0.1), indicating that sustained load induced sarcomerogenesis in these muscles. Intramuscular collagen content in load+/pregnancy hormones- group was significantly greater relative to controls in coccygeus (6.55{+/-}0.85 vs 3.11{+/-}0.47{micro}g/mg, P<0.001) and pubocaudalis (5.93{+/-}0.79 vs 3.46{+/-}0.52 {micro}g/mg, P<0.05) and not different from load+/pregnancy hormones+ (7.45{+/-}0.65 and 6.05{+/-}0.62 {micro}g/mg, respectively, P>0.5). Iliocaudalis required both mechanical and endocrine cues for sarcomerogenesis. Tibialis anterior was not affected by mechanical or endocrine alterations. Despite equivalent extent of adaptations, load-induced changes were only partially protective against sarcomere hyperelongation.

ConclusionsLoad induces plasticity of the intrinsic pelvic floor muscle components that renders protection against mechanical birth injury. The protective effect, which varies between individual muscles and strain magnitudes, is further augmented by the presence of pregnancy hormones. Maximizing impact of mechanical load on pelvic floor muscles during pregnancy, such as with specialized pelvic floor muscle stretching regimens, is a potentially actionable target for augmenting pregnancy-induced adaptations to decrease birth injury in women who may otherwise have incomplete antepartum muscle adaptations.

AJOG at a GlanceO_LIWhy was the study conducted?
O_LITo determine the role of mechanical load, uncoupled from the hormonal milieu of pregnancy, in driving protective pregnancy-induced adaptations previously discovered in the rat pelvic floor muscles.
C_LI
C_LIO_LIWhat are the key findings?
O_LIMechanical load, in the absence of pregnancy hormones, induces sarcomerogenesis and extracellular matrix remodeling in rat pelvic floor muscles.
C_LIO_LILoad-induced adaptations are partially protective against mechanical pelvic floor muscle injury consequent to parturition-associated strains.
C_LI
C_LIO_LIWhat does this study add to what is already known?
O_LIThe effect of sustained increased mechanical load, uncoupled from the hormonal milieu of pregnancy, on pelvic floor muscle plasticity has not been previously studied.
C_LIO_LIModulating pelvic floor muscles stretch antepartum, such as with specialized pelvic floor physical therapy regimens, could be a promising approach for augmentation of protective muscle adaptations in women.
C_LI
C_LI

category: physiology


title: Validation of non-invasive body-surface gastric mapping for detecting electrophysiological biomarkers by simultaneous high-resolution serosal mapping in a porcine model

abstract:
Gastric disorders are increasingly prevalent, but reliable clinical tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a non-invasive method for the detection of gastric electrophysiological biomarkers including slow wave direction, which have correlated with symptoms in patients with gastroparesis and functional dyspepsia. However, no studies have validated the relationship between gastric slow waves and body surface activation profiles. This study aimed to comprehensively evaluate the relationship between gastric slow waves and body-surface recordings. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32x6 electrodes at 4 mm resolution) and abdominal surface (8x8 at 20 mm inter-electrode spacing) in a porcine model. BSGM signals were extracted based on a combination of wavelet and phase information analyses. A total of 1185 individual cycles of slow waves assessed, out of which 897 (76%) were normal antegrade waves, occurring in 10/14 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency (r = 0.99, p = 0.43) as well as the direction of propagation (p = 0.41, F-measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow waves in terms either or both temporal and spatial abnormalities was demonstrated. These results validate BSGM as a suitable method for non-invasively and accurately detecting gastric slow wave activation profiles from the body surface.

Single sentence summarySimultaneous recordings of the stomach using serosal and body-surface electrode arrays demonstrated reliable detection of frequency and classification of propagation.


title: MVsim: a toolset for quantifying and designing multivalent interactions

abstract: Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim, an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim, we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. We then quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim is freely available at https://sarkarlab.github.io/MVsim/.

category: systems biology


title: Adult neuromarkers of sustained attention and working memory predict inter- and intra-individual differences in these processes in youth

abstract: Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9-11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM network model predicted WM performance both across and within children--and captured individual differences in later recognition memory--but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed two network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in one. Thus, functional connectivity predicts SA and WM in youth, with networks predicting WM changing more from preadolescence to adulthood than those predicting SA.


title: Connectome-based predictions reveal developmental change in the functional architecture of sustained attention and working memory


title: Transcriptomes of Electrophysiologically Recorded Dbx1-derived Inspiratory Neurons of the preBötzinger Complex in Neonatal Mice

abstract: Breathing depends on interneurons in the preBotzinger complex (preBotC) derived from Dbx1-expressing precursors. Here we investigate whether rhythm- and pattern-generating functions reside in discrete classes of Dbx1 preBotC neurons. In a slice model of breathing with [~]5 s cycle period, putatively rhythmogenic Type-1 Dbx1 preBotC neurons activate 100-300 ms prior to Type-2 neurons, putatively specialized for output pattern, and 300-500 ms prior to the inspiratory motor output. We sequenced Type-1 and Type-2 transcriptomes and identified differential expression of 123 genes including ionotropic receptors (Gria3 and Gabra1) that may explain their preinspiratory activation profiles and Ca2+ signaling (Cracr2a, Sgk1) involved in inspiratory and sigh bursts. Surprisingly, neuropeptide receptors that influence breathing (e.g., {micro}-opioid and bombesin-like peptide receptors) were only sparsely expressed, which suggests that cognate peptides and opioid drugs exert their profound effects on a small fraction of the preBotC core. These data in the public domain help explain breathings neural origins.


title: Ectopic cervical thymi and no thymic involution until midlife in naked mole-rats

abstract: Immunosenescence is a hallmark of aging and manifests as increased susceptibility to infection, autoimmunity, and cancer in the elderly. One component of immunosenescence is thymic involution, age-associated shrinkage of the thymus, observed in all vertebrates studied to date. The naked mole-rat (Heterocephalus glaber) has become an attractive animal model in aging research due to its extreme longevity and resistance to disease. Here we show that naked mole rats display no thymic involution up to 11 years of age. Furthermore, we found large ectopic cervical thymi in addition to the canonical thoracic thymus, both being identical in their cell composition. The developmental landscape in naked mole-rat thymi revealed overt differences from the murine T cell compartment, most notably a decrease of CD4+/CD8+ double-positive cells and lower abundance of cytotoxic effector T cells. Our observations suggest that naked mole rats display a delayed immunosenescence. Therapeutic interventions aimed at reversing thymic aging remain limited, underscoring the importance of understanding the cellular and molecular mechanisms behind a sustained immune function in the naked mole rat.

category: immunology


title: An abundant myeloid progenitor shapes neonatal hematopoiesis of naked mole-rats

abstract: The naked mole-rat became an attractive model for biomedical research due to its exceptional longevity and resistance to disease, yet the developmental properties of naked mole-rat stem and progenitor compartments are poorly understood. Here we report a high frequency bone marrow progenitor, which we termed TC90, exclusively present in neonatal animals. TC90s were marked by an immunophenotype resembling adult naked mole-rat common myeloid progenitors (CMP) with mature neutrophilic Thy1.1-antigen levels and showed a clear differentiation bias and transcriptome signature towards myelopoiesis. TC90s overexpressed both CXCL12 and its alternative receptor CXCR7, thereby abrogating their homing capacity and produced multiple secreted matrix components related to neonatal bone marrow niche formation. We hypothesize that the TC90 cell population protects newborns during the critical transition at birth and shortly beyond by boosting a supply of innate immune cells. In summary, our results identify a transient cell stage during postnatal hematopoiesis unique to naked mole-rats.


title: Hidden in the deep: distinct benthic trajectories call for monitoring of mesophotic reefs

abstract: Long-term monitoring studies are central to coral reef ecology and conservation management. However, ongoing monitoring programs are almost exclusively focused on shallow depths, and it remains unclear to what extent those are representative of the whole ecosystem. Here, we present a temporal comparison (2012-2017) of directly adjacent shallow and mesophotic benthic communities across seven sites from the Great Barrier Reef and Western Coral Sea. We found a positive correlation initially between shallow and mesophotic coral cover, with higher cover at shallow depths. However, this correlation broke down after multiple disturbances, with coral cover declining only at shallow depths. Point-based tracking revealed the dynamic nature of mesophotic communities, with their consistent coral cover reflecting a net balance between substantial growth and mortality. Overall, the divergent trajectories highlight the urgency to expand monitoring efforts into mesophotic depths, to decipher the processes governing these habitats and enable better-informed management of the overall ecosystem.


title: Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data

abstract: Massively bulk RNA sequencing databases incorporating drug screening have opened up an avenue to inform the optimal clinical application of cancer drugs. Meanwhile, the growing single-cell RNA sequencing (scRNA-seq) data contributes to improving therapeutic effectiveness by studying the heterogeneity of drug responses for cancer cell subpopulations. There is a clear significance in developing computational biology approaches to predict and interpret cancer drug response in single cell data from clinical samples. Here, we introduce scDEAL, a deep transfer learning framework for cancer drug response prediction at single-cell level by integrating large-scale bulk cell line data. The true innovation of scDEAL is to translate cancer cell line drug responses into predicting clinical drug responses via learning relations of gene expressions and drug responses at bulk-level and transfer to predict drug responses in scRNA-seq. Another innovation is the integrated gradient feature interpretation to infer a comprehensive set of signature genes to reveal potential drug resistance mechanisms. We benchmarked scDEAL on six scRNA-seq datasets and indicate its model interpretability through these case studies. We believe that this work may help study cell reprogramming, drug selection, and repurposing for improving therapeutic efficacy.


title: Deep Transfer Learning of Drug Responses by Integrating Bulk and Single-cell RNA-seq data


title: Evolutionarily conserved regions of THAP9 transposase reveal new motifs for subcellular localization and post-translational modification.

abstract: THAP9 is a transposable element-derived gene that encodes the THAP9 protein, which is homologous to the Drosophila P-element transposase (DmTNP) and can cut and paste DNA. However, the exact functional role of THAP9 is unknown. Here, we perform evolutionary analysis and extensive in silico characterization of THAP9, including predicting domains and putative post-translational modification sites. We predict previously unreported mammalian-specific post-translational modification sites that may play a role in the subcellular localization of THAP9. We also observe that although THAP9 has evolved under a strong pervasive purifying selection, yielding high conservation of THAP9, there are distinct class-specific conservation patterns of key functional residues in certain domains. Furthermore, investigation of THAP9 expression profiles in various cancer and matched normal datasets demonstrated underexpression and overexpression in testicular cancers and thymic epithelial tumors, respectively, thus suggesting a possible role of THAP9 in cancer.


title: Evolutionary analysis of THAP9 transposase: conserved regions, novel motifs


title: piRNAs of Caenorhabditis elegans broadly silence nonself sequences through functionally random targeting

abstract: Small non-coding RNAs such as piRNAs serve as guides for Argonaute proteins, enabling sequence-specific, post-transcriptional regulation of gene expression. The piRNAs of Caenorhabditis elegans have been observed to bind targets with high mismatch tolerance, and appear to lack specific transposon targets, unlike piRNAs in Drosophila melanogaster and other organisms. These observations support a model in which C. elegans piRNAs provide a broad, indiscriminate net of silencing, acting in competition with siRNAs associated with the CSR-1 Argonaute that specifically protect self genes from silencing. However, the breadth of piRNA targeting has not been subject to in-depth quantitative analysis, nor has it been explained how piRNAs are distributed across sequence space to achieve complete coverage. Through a bioinformatic analysis of piRNA sequences, incorporating an original metric of piRNA-target distance, we demonstrate that C. elegans piRNAs are functionally random, in that their coverage of sequence space is comparable to that of random sequences. By possessing a sufficient number of distinct, essentially random piRNAs, C. elegans is able to target arbitrary nonself sequences with high probability. This result elucidates the mechanism by which newly transcribed mRNAs in C. elegans are classified as self or nonself, and has implications for piRNA evolution and biogenesis.


title: Multidirectional measures of shear modulus in skeletal muscle

abstract: The material properties of muscle play a central role in how muscle resists joint motion, transmits forces internally, and repairs itself. While many studies have evaluated muscles tensile material properties, few have investigated muscles shear properties. None of which have taken into account muscles anisotropic structure or investigated how different muscle architecture affect muscles shear properties. The objective of this study was to quantify the shear moduli of skeletal muscle in three orientations relevant to the function of whole muscle. We collected data from the extensor digitorum longus, tibialis anterior, and soleus harvested from both hindlimbs of 12 rats. These muscles were chosen to further evaluate the consistency of shear moduli across muscles with different architectures. We calculated the shear modulus in three orientations: parallel, perpendicular, and across with respect to muscle fiber alignment; while the muscle was subjected to increasing shear strain. For all muscles and orientations, the shear modulus increased with increasing strain. The shear modulus measured perpendicular to fibers was greater than in any other orientation. Despite architectural differences between muscles, we did not find a significant effect of muscle type on shear modulus. Our results show that in rat, muscles shear moduli vary with respect to fiber orientation and are not influenced by architectural differences in muscles.


title: Regulatory perturbations of ribosome allocation results in a trade-off between fast growth and adaptation capacity

abstract:
Bacteria regulate their cellular resource allocation to enable fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth and expression profiles of two sets of fast-growing mutants of Escherichia coli K-12 MG1655 in glucose minimal medium. Mutants with only 3 of the seven copies of ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied rpoB mutants. Higher growth rates due to increased ribosome content affected resource allocation. Expression profiles of fast-growing mutants shared downregulation of hedging functions and upregulated growth functions. Mutants showed longer diauxic shifts and reduced activity of gluconeogenic promoters during glucose-acetate shifts, suggesting reduced availability of the RNA Polymerase for expressing hedging proteome. These results show that the regulation of ribosomal allocation underlies the growth/hedging phenotypes obtained from laboratory evolution experiments. We show how two different regulatory perturbations (rRNA promoters or rpoB mutations) reshape the proteome for growth with a concomitant fitness cost

HighlightsMutants with only 3 ribosomal operons grow faster than wild-type in minimal medium

 {Delta}4 rrn and rpoB mutants share phenotypic traits

Faster growth of mutants is achieved by increased ribosome content

Fast-growing mutants display reduced hedging expression and adaptation trade-offs

Despite similar ribosomal content in rich medium the mutants present growth defects


title: Regulatory perturbations of ribosome allocation optimize the growth proteome with a trade-off in adaptation capacity


title: Regulatory perturbations of ribosome allocation reshape the growth proteome with a trade-off in adaptation capacity


title: On the discovery of ADRAM, an experience-dependent long noncoding RNA that drives fear extinction through a direct interaction with the chaperone protein 14-3-3

abstract: Long-noncoding RNA (lncRNA) comprise a new class of genes that have been assigned key roles in development and disease. Many lncRNAs are specifically transcribed in the brain where they regulate the expression of protein-coding genes that underpin neuronal function; however, their role in learning and memory remains largely unexplored. We used RNA Capture-Seq to identify a large population of lncRNAs that are expressed in the infralimbic cortex of adult male mice in response to fear-related learning, with 14.5% of these annotated in the GENCODE database as lncRNAs with no known function. We combined these data with cell-type-specific ATAC-seq on neurons that had been selectively activated by fear-extinction learning, and revealed 434 lncRNAs derived from enhancer regions in the vicinity of protein-coding genes. In particular, we discovered an experience-induced lncRNA called ADRAM that acts as both a scaffold and a combinatorial guide to recruit the brain-enriched chaperone protein 14-3-3 to the promoter of the memory-associated immediate early gene Nr4a2. This leads to the expulsion of histone deactylases 3 and 4, and the recruitment of the histone acetyltransferase creb binding protein, which drives learning-induced Nr4a2 expression. Knockdown of ADRAM disrupts this interaction, blocks the expression of Nr4a2, and ultimately impairs the formation of fear-extinction memory. This study expands the lexicon of experience-dependent lncRNA activity in the brain, highlights enhancer-derived RNAs (eRNAs) as key players in the epigenetic regulation of gene expression associated with fear extinction, and suggests eRNAs, such as ADRAM, may constitute viable targets in developing novel treatments for fear-related anxiety disorders.


title: Claudin-5 binder enhances focused ultrasound-mediated opening in an in vitro blood-brain barrier model

abstract:
RationaleThe blood-brain barrier (BBB) while functioning as a gatekeeper of the brain, impedes cerebral drug delivery. An emerging technology to overcome this limitation is focused ultrasound (FUS). When FUS interacts with intravenously injected microbubbles (FUS+MB), the BBB opens, transiently allowing the access of therapeutic agents into the brain. However, the ultrasound parameters need to be tightly tuned: when the acoustic pressure is too low there is no opening, and when it is too high, bleeds can occur. We therefore asked whether BBB permeability can be increased by combining FUS+MB with a second modality such that in a clinical setting lower acoustic pressures could be potentially used.

MethodsGiven that FUS achieves BBB opening by the disruption of tight junction (TJ) proteins such as claudin-5 of brain endothelial cells, we generated a stable MDCK II cell line (eGFP-hCldn5-MDCK II) that expresses fluorescently tagged human claudin-5. Two claudin-5 binders, mC5C2 (a peptide) and cCPEm (a truncated form of an enterotoxin), that have been reported previously to weaken the barrier, were synthesized and assessed for their abilities to enhance the permeability of cellular monolayers. We then performed a comparative analysis of single and combination treatments.

ResultsWe successfully generated a novel cell line that formed functional monolayers as validated by an increased transendothelial electrical resistance (TEER) reading and a low (< 0.2%) permeability to sodium fluorescein (376 Da). We found that the binders exerted a time- and concentration-dependent effect on BBB opening when incubated over an extended period, whereas FUS+MB caused a rapid barrier opening followed by recovery after 12 hours within the tested pressure range. Importantly, preincubation with cCPEm prior to FUS+MB treatment resulted in greater barrier opening compared to either FUS+MB or cCPEm alone as measured by reduced TEER values and an increased permeability to fluorescently labelled 40 kDa dextran (FD40).

ConclusionThe data suggest that pre-incubation with clinically suitable binders to TJ proteins may be a general strategy to facilitate safer and more effective ultrasound-mediated BBB opening in cellular and animal systems and potentially also for the treatment of human diseases of the brain.


title: Microbial transformation of traditional fermented fertilizer bokashi alters chemical composition and improves plant growth

abstract: Bokashi is an organic soil amendment that makes use of microbial processes to break down agricultural waste and create a nutrient-rich fertilizer. The benefits of various types of bokashi on soil fertility and plant growth are well documented, however the changes in microbial community composition and nutrients during bokashi maturation remain poorly characterized. Here, we aimed to identify potential differences in the quality of bokashi made using different ingredients and to investigate the biochemical transformation and microbial community succession of bokashi throughout the maturation process. We compared the effects of these different types of bokashi on the growth of cucumber (Cucumis sativus) and kale (Brassica napus subsp. pabularia) seedlings, measured concentrations of NH4+ and PO43-, and characterized the bokashi bacterial and fungal communities over a 12-day maturation period. We found that cucumber and kale plants growing in all types of bokashi-amended soils exhibited increased chlorophyll levels and dry biomass. During bokashi maturation, we observed a decrease in available PO43-, and an increase in NH4+. There also appeared to be an increase in relative abundances of decomposers and beneficial microbes and a decrease in putative plant pathogens. Regardless of starting bokashi ingredients and differences in microbial composition and nutrient trends, all types of bokashi similarly improve plant growth and contain beneficial microbes.


title: Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission

abstract: Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.


title: Genome-wide protein-DNA interaction site mapping using a double strand DNA-specific cytosine deaminase

abstract: DNA-protein interactions (DPIs) are central to such fundamental cellular processes as transcription and chromosome maintenance and organization. The spatiotemporal dynamics of these interactions dictate their functional consequences; therefore, there is great interest in facile methods for defining the sites of DPI within cells. Here, we present a general method for mapping DPI sites in vivo using the double stranded DNA-specific cytosine deaminase toxin DddA. Our approach, which we term DddA-sequencing (3D-seq), entails generating a translational fusion of DddA to a DNA binding protein of interest, inactivating uracil DNA glycosylase, modulating DddA activity via its natural inhibitor protein, and DNA sequencing for genome-wide DPI detection. We successfully applied this method to three Pseudomonas aeruginosa transcription factors that represent divergent protein families and bind variable numbers of chromosomal locations. 3D-seq offers several advantages over existing technologies including ease of implementation and the possibility to measure DPIs at single-cell resolution.


title: Multi-run Concrete Autoencoder to Identify Prognostic lncRNAs for 12 Cancers

abstract: Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that leads to cancer development. Thus, identifying prognostic lncRNAs related to different cancers might help in developing cancer therapy. To discover the critical lncRNAs that can identify the origin of different cancers, we proposed to use the state-of-the-art deep learning algorithm Concrete Autoencoder (CAE) in an unsupervised setting, which efficiently identifies a subset of the most informative features. However, CAE does not identify reproducible features in different runs due to its stochastic nature. We proposed a multi-run CAE (mrCAE) to identify a stable set of features to address this issue. The assumption is that a feature appearing in multiple runs carries more meaningful information about the data under consideration. The genome-wide lncRNA expression profiles of 12 different types of cancers, a total of 4,768 samples available in The Cancer Genome Atlas (TCGA), were analyzed to discover the key lncRNAs. The lncRNAs identified by multiple runs of CAE were added to the final list of key lncRNAs, which are capable of identifying 12 different cancers. Our results showed that mrCAE performs better in feature selection than single-run CAE, standard autoencoder (AE), and other state-of-the-art feature selection techniques. This study discovered a set of top-ranking 128 lncRNAs that could identify the origin of 12 different cancers with an accuracy of 95%. Survival analysis showed that 76 of 128 lncRNAs have the prognostic capability in differentiating high- and low-risk groups of patients in different cancers. The proposed mrCAE outperformed AE, which select latent features and were thought to be the best tools for dimensionality reduction. By selecting actual features instead of pseudo-features, mrCAE can be valuable for precision medicine. The identified prognostic lncRNAs (this work), mRNAs, miRNAs, and DNA methylated genes (future work) can lead to biomarkers and therapies for different cancers.


title: Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers

abstract: The recent development and application of methods based on the general principle of "crosslinking and proximity ligation" (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here we introduce a set of computational tools for the systematic analysis of data from a wide variety of cross-link-ligation methods, specifically focusing on read mapping, alignment classification and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover 8 types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and inter-twined gapped alignments, we develop a network/graph-based tool CRSSANT (Crosslinked RNA Secondary Structure Analysis using Network Techniques), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multi-segment alignments to report complex high level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.


title: Alternative oxidase1a and 1d limit proline-dependent oxidative stress and aid salinity recovery in Arabidopsis

abstract:
A link between Pro catabolism and mitochondrial reactive oxygen species production has been established across eukaryotes and in plants increases in leaf respiration rates have been reported following Pro exposure. Here we investigated how alternative oxidases (AOXs) of the mitochondrial electron transport chain accommodate the large, atypical flux resulting from Pro catabolism and limit oxidative stress during Pro breakdown in mature Arabidopsis leaves. Following Pro treatment, AOX1a and AOX1d accumulate at transcript and protein levels, with AOX1d approaching the level of the typically dominant AOX1a isoform. We therefore sought to determine the function of both AOX isoforms under Pro respiring conditions. Oxygen consumption rate measurements in aox1a and aox1d leaves suggested these AOXs can functionally compensate for each other to establish enhanced AOX catalytic capacity in response to Pro. Generation of aox1a.aox1d lines showed complete loss of AOX proteins and activity upon Pro treatment, yet full respiratory induction in response to Pro remained possible via the cytochrome pathway. However, aox1a.aox1d leaves suffered increased levels of oxidative stress and damage during Pro metabolism compared to WT or the single mutants. During recovery from salt stress, when high rates of Pro catabolism occur naturally, photosynthetic rates in aox1a.aox1d recovered slower than WT or the single aox lines, showing that both AOX1a and AOX1d are beneficial for cellular metabolism during Pro drawdown following osmotic stress. This work provides physiological evidence of a beneficial role for AOX1a but also the less studied AOX1d isoform in allowing safe catabolism of alternative respiratory substrates like Pro.

One sentence summaryThe alternative oxidase of plant mitochondria contributes to Pro catabolism by preventing oxidative stress in the electron transport chain and this aids recovery of leaf metabolic rates following salinity stress.


title: Artificial mimicry of seasonal transcriptome dynamics in Arabidopsis thaliana reveals short- and long-term responses to environmental conditions

abstract:
O_LIPlants must respond to various environmental factors that change seasonally. In a previous study, seasonally oscillating genes were identified by a massive time-series transcriptome analysis in a wild population of Arabidopsis halleri ssp. gemmifera, a sister species of Arabidopsis thaliana.
C_LIO_LITo analyze the function of these seasonally oscillating genes, we established an experimental system to mimic seasonal expression trends using A. thaliana. Arabidopsis thaliana plants were cultured under conditions that mimicked average monthly temperatures and daylengths in a "smart growth chamber mini," a hand-made low-cost small chamber.
C_LIO_LIUnder different short-term incubations, the seasonal trends of 1627 seasonally oscillating genes were mimicked. These seasonally oscillating genes had varying temporal responsiveness (constant, transient, and incremental).
C_LIO_LIOur findings suggest that plants perceive and integrate information about environmental stimuli in the field by combining seasonally oscillating genes with temporal responsiveness.
C_LI


title: Functional specialization of monocot DCL3 and DCL5 proteins through the evolution of the PAZ domain

abstract: Monocot DICER-LIKE3 (DCL3) and DCL5 produce distinct 24-nt heterochromatic small interfering RNAs (hc-siRNAs) and phased secondary siRNAs (phasiRNAs). The former small RNAs are linked to plant heterochromatin, and the latter to reproductive processes. It is assumed that these DCLs evolved from an ancient "eudicot-type" DCL3 ancestor, which may have produced both types of siRNAs. However, how functional differentiation was achieved after gene duplication remains elusive. Here, we find that monocot DCL3 and DCL5 exhibit biochemically distinct preferences for 3' overhangs and 5' phosphates, consistent with the structural properties of their in vivo double-stranded RNA substrates. Importantly, these distinct substrate specificities are determined by the PAZ domains of DCL3 and DCL5 which have accumulated mutations during the course of evolution. These data explain the mechanism by which these DCLs cleave their cognate substrates from a fixed end, ensuring the production of functional siRNAs. Our study also indicates how plants have diversified and optimized RNA silencing mechanisms during evolution.