Miracle-dz/UniFAR-FTUs huggingface dataset:
Manipulating phloem transport affects wood formation but not nonstructural carbon concentrations in an evergreen conifer

Wood formation is a crucial process for carbon sequestration, yet how variations in carbon supply affect wood formation and carbon dynamics in trees more generally remains poorly understood. To better understand the role of carbon supply in wood formation, we restricted phloem transport using girdling and compression around the stem of mature white pines and monitored the effects on local wood formation and stem CO2 efflux, as well as nonstructural carbon concentrations in needles, stems, and roots. Growth and stem CO2 efflux varied with location relative to treatment (i.e., above or below on the stem). We observed up to a two-fold difference in the number of tracheids formed above versus below the manipulations over the remaining growing season. In contrast, the treatments did not affect mean cell size noticeably and mean cell-wall area decreased only slightly below them. Surprisingly, nonstructural carbon pools and concentrations in the xylem, needles, and roots remained largely unchanged, although starch reserves declined and increased marginally below and above the girdle, respectively. Our results suggest that phloem transport strongly affects cell proliferation and respiration in the cambial zone of mature white pine, but has little impact on nonstructural carbon concentrations. These findings contribute to our understanding of how wood formation is controlled. Highlight Restrictions in phloem transport designed to affect carbon supply, lead to changes in wood formation and stem respiration of mature white pines without substantially changing local nonstructural carbon concentrations.
Mental compression of spatial sequences in human working memory using numerical and geometrical primitives

How does the human brain store sequences of spatial locations? The standard view is that each consecutive item occupies a distinct slot in working memory. Here, we formulate and test the alternative hypothesis that the human brain compresses the whole sequence using an abstract, language-like code that captures the numerical and geometrical regularities of the sequence at multiple nested levels. We exposed participants to spatial sequences of fixed length but variable regularity, and asked them to remember the sequence in order to detect deviants, while their brain activity was recorded using magneto-encephalography. Using multivariate decoders, each successive location could be decoded from brain signals, and upcoming locations were anticipated prior to their actual onset. Crucially, sequences with lower complexity, defined as the minimal description length provided by the formal language, and whose memory representation was therefore predicted to be more compressed, led to lower error rates and to increased anticipations. Furthermore, neural codes specific to the numerical and geometrical primitives of the postulated language could be detected, both in isolation and within the sequences. These results suggest that the human brain detects sequence regularities at multiple nested levels and uses them to compress long sequences in working memory.
Elevation of Gut-Derived p-Cresol During Spaceflight and its Effect on Drug Metabolism and Performance in Astronauts

Metabolites produced by enteric microbes may have important effects on astronauts on long-duration missions. The NASA Twins Study provided the most comprehensive multi-scale omics data to date from which to extract molecular features of potential clinical significance to spaceflight. From the multivariate data, we identified an elevation of the uremic toxin p-cresol, which is produced by gut microbial fermentation of dietary tyrosine. p-Cresol has adverse metabolic effects via depletion of the hepatic sulfur pool, which impacts metabolism of drugs, endogenous metabolites, and xenobiotics. Moreover, p-cresol reshapes gut microbial community structure by facilitating survival of species such as clostridia and inhibition of butyrate producers. Spaceflight may also impact the genes responsible for the metabolism of p-cresol (e.g. SULT) and for the safe metabolism of common drugs used in space, such as acetaminophen (e.g. SULT, CYP4502E1, GST). Understanding p-cresol production and its related molecular networks in astronauts may lead to precision medicine advances that enhance astronaut safety and performance on long-duration missions.
The Human Cytomegalovirus UL116 Glycoprotein Is a Chaperone to Control gH-Based Complexes Levels on Virions

Human cytomegalovirus (HCMV) relies in large part upon the viral membrane fusion glycoprotein B (gB) and two alternative gH/gL complexes, gH/gL/gO (Trimer) and the gH/gL/UL128/UL130/UL131A (Pentamer) to enter into cells. The relative amounts of the Trimer and Pentamer vary among HCMV strains and contribute to differences in cell tropism. Although the viral ER resident protein UL148 has been shown to interact with gH to facilitate gO incorporation, the mechanisms that favor the assembly and maturation of one complex over another remain poorly understood. HCMV virions also contain an alternative non-disulfide bound heterodimer comprised of gH and UL116 whose function remains unknown. Here, we show that disruption of HCMV gene UL116 causes infectivity defects of ~10-fold relative to wild-type virus and leads to reduced expression of both gH/gL complexes in virions. Furthermore, gH that is not covalently bound to other viral glycoproteins, which are readily detected in wild-type HCMV virions, become undetectable in the absence of UL116 suggesting that the gH/UL116 complex is abundant in virions. We find evidence that UL116 and UL148 interact during infection indicating that the two proteins might cooperate to regulate the abundance of HCMV gH complexes. Altogether, these results are consistent with a role of UL116 as a chaperone for gH during the assembly and maturation of gH complexes in infected cells.
Donnan dominated ion homeostasis and the longevity of ischemic Na+-loaded dystrophic skeletal muscle

The inherited muscle-wasting disease, Duchenne muscular dystrophy (DMD), renders skeletal muscle fibers (SMFs) Na+-overloaded, ischemic, membrane-damaged, cation-leaky, depolarized, and prone to myogenic firing. DMD fibers nevertheless survive up to 3 decades before succumbing to Ca2+-necrosis. The Ca2+-necrosis is explicable, the longevity is not. Modeling here shows that SMFs’ ion homeostasis strategy, a low-cost resilient Pump-Leak/Donnan feedback process we term “Donnan dominated”, underpins that longevity. Together, SMFs’ huge chloride-permeability and tiny sodium-permeability minimize excitability and pump costs, facilitating the outsized SMF pump-reserve that lets DMD fibers withstand deep ischemia and leaky channels. We illustrate how, as these impairments intensify, patients’ chronic Na+-overload (now non-invasively evident via Na23-MRI) would change. In simulations, prolonged excitation (→physiological Na+-overloading) and/or intense ischemia (→too little Na+-pumping) and accumulated bleb-damage (→too much Na+-leaking) eventually trigger Ca2+-overloading conditions. Our analysis implies an urgent need to identify SMFs’ pivotal small PNa, thereby opening new therapeutic remediation routes.
Salicylate, Bile Acids and Extreme Acid Cause Fitness Tradeoffs for Multidrug Pumps in Escherichia coli K-12

The aspirin derivative salicylate selects against bacterial multidrug efflux pumps of Escherichia coli K-12 such as MdtEF-TolC and EmrAB-TolC, and acid stress regulators such as GadE. Salicylate uptake is driven by the transmembrane pH gradient (ΔpH) and the proton motive force (PMF) which drives many efflux pumps. We used flow cytometry to measure the fitness tradeoffs of salicylate, bile acids, and extreme low pH for E. coli cultured with pump deletants. The AcrAB-TolC efflux pump conferred a fitness advantage in the presence of bile acids, an efflux substrate. Without bile acids, AcrA incurred a small fitness cost. The fitness advantage with bile acids was eliminated by the PMF uncoupler CCCP. The Gad acid fitness island encodes components of MdtEF-TolC (an acid-adapted efflux pump) as well as acid regulator GadE. The fitness advantage of E. coli cocultured with a Gad deletant (Δslp-gadX) was lost in the presence of salicylate. Salicylate caused an even larger fitness cost for GadE. MdtE incurred negative or neutral fitness under all media conditions, as did EmrA. But when the competition cycle included two hours at pH 2, MdtE conferred a fitness advantage. The MdtE advantage required the presence of bile acids. Thus, the MdtEF-TolC pump is useful to E. coli for transient extreme acid exposure comparable to passage through the acidic stomach. Salicylate selects against some multidrug efflux pumps, whereas bile acids selects for them; and these fitness tradeoffs are amplified by extreme acid. IMPORTANCE Control of drug resistance in gut microbial communities is a compelling problem for human health. Growth of gut bacteria is limited by host-produced acids such as bile acids, and may be modulated by plant-derived acids such as salicylic acid. Membrane-soluble organic acids can control bacterial growth by disrupting membranes, decreasing cell pH, and depleting PMF. Our flow cytometry assay measures the fitness effects of exposure to membrane-soluble organic acids, with growth cycles that may include a period of extreme acid. We find that extreme-acid exposure leads to a fitness advantage for a multidrug pump, MdtEF-TolC, which otherwise incurs a large fitness cost. Thus, organic acids and stomach acid may play important roles in controlling multidrug resistance in the gut microbiome. Therapeutic acids might be developed to limit the prevalence of multidrug resistance pumps in environmental and host-associated communities.
An Adhesive-Based Fabrication Technique for Culture of Lung Airway Epithelial Cells with Applications in Microfluidics and Lung-on-a-Chip

This work describes a versatile and cost-effective cell culture method for growing adherent cells on a porous membrane using pressure-sensitive double-sided adhesives. This technique allows cell culture using conventional methods and easy transfer to microfluidic chip devices. To support the viability of our system, we evaluate the toxicity effect of four different adhesives on two distinct airway epithelial cell lines and show functional applications for microfluidic cell culture chip fabrication. We showed that cells could be grown and expanded on a “floating” membrane, which can be transferred upon cell confluency to a microfluidic chip for further analysis. The viability of cells and their inflammatory responses to IL-1β stimulation was investigated. Such a technique would be useful to culture cells in a conventional fashion, which is more convenient and faster, and stimulate cells in an advanced model with perfusion when needed.
Automatic Analysis of Bees’ Waggle Dance

This work describe an algorithm for the automatic analysis of the waggle dance of honeybees. The algorithm analyses a video of a beehive with 13,624 frames, acquired at 25 frames/second. The algorithm employs the following traditional image processing steps: conversion to grayscale, low pass filtering, background subtraction, thresholding, tracking and clustering to detect run of bees that perform waggle dances. The algorithm detected 44,530 waggle events, i.e. one bee waggling in one time frame, which were then clustered into 511 waggle runs. Most of these were concentrated in one section of the hive. The accuracy of the tracking was 90% and a series of metrics like intra-dance variation in angle and duration were found to be consistent with literature. Whilst this algorithm was tested on a single video, the ideas and steps, which are simple as compared with Machine and Deep Learning techniques, should be attractive for researchers in this field who are not specialists in more complex techniques.
Deep Learning-based Ligand Design using Shared Latent Implicit Fingerprints from Collaborative Filtering

In their previous work, Srinivas et al.1 have shown that implicit fingerprints capture ligands and proteins in a shared latent space, typically for the purposes of virtual screening with collaborative filtering models applied on known bioactivity data. In this work, we extend these implicit fingerprints/descriptors using deep learning techniques to translate latent descriptors into discrete representations of molecules (SMILES), without explicitly optimizing for chemical properties. This allows the design of new compounds based upon the latent representation of nearby proteins, thereby encoding drug-like properties including binding affinities to known proteins. The implicit descriptor method does not require any fingerprint similarity search, which makes the method free of any bias arising from the empirical nature of the fingerprint models. 1 We evaluate the properties of the novel drugs generated by our approach using physical properties of drug-like molecules and chemical complexity. Additionally, we analyze the reliability of the biological activity of the new compounds generated using this method by employing models of protein ligand interaction, which assists in assessing the potential binding affinity of the designed compounds. We find that the generated compounds exhibit properties of chemically feasible compounds and are likely to be excellent binders to known proteins. Furthermore, we also analyze the diversity of compounds created using the Tanimoto distance and conclude that there is a wide diversity in the generated compounds. Graphical TOC Entry
A conserved ubiquitin- and ESCRT-dependent pathway to regulate human lysosomal membrane proteins

The lysosome is an essential organelle to recycle cellular materials and maintain nutrient homeostasis, but the mechanism to down-regulate lysosomal membrane proteins is poorly understood. In this study, we developed a cycloheximide chase assay to measure the half-lives of ~30 human lysosomal membrane proteins, and identified RNF152 as a short-lived protein. The degradation of RNF152 depends on ubiquitin and the endosomal sorting complexes required for transport (ESCRT) machinery. Ubiquitinated RNF152 is sorted and internalized by the ESCRT machinery into the lysosomal lumen for degradation. Strikingly, when expressed in budding yeast, human RNF152 is also degraded by the vacuole (yeast lysosome) in an ESCRT-dependent manner. Thus, our study uncovered a conserved mechanism to down-regulate lysosome membrane proteins.
Genetic Drift Dominates Genome-Wide Regulatory Evolution Following an Ancient Whole-Genome Duplication in Atlantic Salmon

Whole genome duplications (WGD) have been considered as springboards that potentiate lineage diversification through increasing functional redundancy. Divergence in gene regulatory elements is a central mechanism for evolutionary diversification, yet the patterns and processes governing regulatory divergence following events that lead to massive functional redundancy, such as WGD, remain largely unknown. We studied the patterns of divergence and strength of natural selection on regulatory elements in the Atlantic salmon (Salmo salar) genome, which has undergone WGD 100-80 Mya. Using ChIPmentation, we first show that H3K27ac, a histone modification typical to enhancers and promoters, is associated with genic regions, tissue specific transcription factor binding motifs, and with gene transcription levels in immature testes. Divergence in transcription between duplicated genes from WGD (ohnologs) correlated with difference in the number of proximal regulatory elements, but not with promoter elements, suggesting that functional divergence between ohnologs after WGD is mainly driven by enhancers. By comparing H3K27ac regions between duplicated genome blocks, we further show that a longer polyploid state post-WGD has constrained asymmetric regulatory evolution. Patterns of genetic diversity across natural populations inferred from re-sequencing indicate that recent evolutionary pressures on H3K27ac regions are dominated by largely neutral evolution. In sum, our results suggest that post-WGD functional redundancy in regulatory elements continues to have an impact on the evolution of the salmon genome, promoting largely neutral evolution of regulatory elements despite their association with transcription levels. These results highlight a case where genome-wide regulatory evolution following an ancient WGD is dominated by genetic drift. Significance statement Regulatory evolution following whole genome duplications (WGD) has been investigated at the gene expression level, but studies of the regulatory elements that control expression have been lacking. By investigating regulatory elements in the Atlantic salmon genome, which has undergone a whole genome duplication 100-80 million years ago, we discovered patterns suggesting that neutral divergence is the prevalent mode of regulatory element evolution post-WGD. Our results suggest mechanisms for explaining the prevalence of asymmetric gene expression evolution following whole genome duplication, as well as the mismatch between evolutionary rates in enhancers versus that of promoters.
Fast neutron mutagenesis in soybean creates frameshift mutations

The mutagenic effects of ionizing radiation have been used for decades to create novel variants in experimental populations. Fast neutron (FN) bombardment as a mutagen has been especially widespread in plants, with extensive reports describing the induction of large structural variants, i.e., deletions, insertions, inversions, and translocations. However, the full spectrum of FN-induced mutations is poorly understood. We contrast small insertions and deletions (indels) observed in 27 soybean lines subject to FN irradiation with the standing indels identified in 107 diverse soybean lines. We use the same populations to contrast the nature and context (bases flanking a nucleotide change) of single nucleotide variants. The accumulation of new single nucleotide changes in FN lines is marginally higher than expected based on spontaneous mutation. In FN treated lines and in standing variation, C→T transitions and the corresponding reverse complement G→A transitions are the most abundant and occur most frequently in a CpG local context. These data indicate that most SNPs identified in FN lines are likely derived from spontaneous de novo processes in generations following mutagenesis, rather than from the FN irradiation mutagen. However, small indels in FN lines differ from standing variants. Short insertions, from 1 – 6 base pairs, are less abundant than in standing variation. Short deletions are more abundant and prone to induce frameshift mutations that should disrupt the structure and function of encoded proteins. These findings indicate that FN irradiation generates numerous small indels, increasing the abundance of loss of function mutations that will impact single genes. Significance Statement Irradiation mutagenesis is commonly viewed as a method to induce large structural variants in genomes. We also find enrichment in small insertion and deletion (indel) variants. The radiation-mutagenized lines averaged 32 indels per line, far exceeding the number estimated to occur by spontaneous processes, indicating that these arose from the irradiation treatment. Nevertheless, naturally-occurring standing variation among soybean accessions is still four orders of magnitude higher than the level of diversity introduced by mutagenesis. Induced mutations from any source are likely to constitute a relatively small portion of the genetic variation present in crop species. However, irradiation mutagenesis is useful for altering genomes by introducing small indels into single genes or disrupting gene clusters by creating structural variants.
SeRenDIP-CE: sequence-based interface prediction for conformational epitopes

Motivation Antibodies play an important role in clinical research and biotechnology, with their specificity determined by the interaction with the antigen’s epitope region, as a special type of protein-protein interaction (PPI) interface. The ubiquitous availability of sequence data, allows us to predicting epitopes from sequence in order to focus time-consuming wet-lab experiments onto the most promising epitope regions. Here, we extend our previously developed sequence-based predictors for homodimer and heterodimer PPI interfaces to predict epitope residues that have the potential to bind an antibody. Results We collected and curated a high quality epitope dataset from the SAbDaB database. Our generic PPI heterodimer predictor obtained an AUC-ROC of 0.666 when evaluated on the epitope test set. We then trained a random forest model specifically on the epitope dataset, reaching AUC 0.694. Further training on the combined heterodimer and epitope datasets, improves our final predictor to AUC 0.703 on the epitope test set. This is better than the best state-of-the-art sequence-based epitope predictor BepiPred-2.0. On one solved antibody-antigen structure of the COVID19 virus spike RNA binding domain, our predictor reaches AUC 0.778. We added the SeRenDIP-CE Conformational Epitope predictors to our webserver, which is simple to use and only requires a single antigen sequence as input, which will help make the method immediately applicable in a wide range of biomedical and biomolecular research. Availability Webserver, source code and datasets are available at www.ibi. vu.nl/programs/serendipwww/ Contact k.a. feenstra@vu.nl
Recurrent circuit based neural population codes for stimulus representation and inference

A large part of the synaptic input received by cortical neurons comes from local cortico-cortical connectivity. Despite their abundance, the role of local recurrence in cortical function is unclear, and in simple coding schemes it is often the case that a circuit with no recurrent connections performs optimally. We consider a recurrent excitatory-inhibitory circuit model of a cortical hypercolumn which performs sampling-based Bayesian inference to infer latent hierarchical stimulus features. We show that local recurrent connections can store an internal model of the correlations between stimulus features that are present in the external world. When the resulting recurrent input is combined with feedforward input it produces a population code from which the posterior over the stimulus features can be linearly read out. Internal Poisson spiking variability provides the proper fluctuations for the population to sample stimulus features, yet the resultant population variability is aligned along the stimulus feature direction, producing what are termed differential correlations. Importantly, the amplitude of these internally generated differential correlations is determined by the associative prior in the model stored in the recurrent connections, thus providing experimentally testable predictions for how population connectivity and response variability are connected to the structure of latent external stimuli.