Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of amphipathic helix—membrane interactions with Rosetta

Amphipathic helices have hydrophobic and hydrophilic/charged residues situated on opposite faces of the helix. They can anchor peripheral membrane proteins to the membrane, be attached to integral membrane proteins, or exist as independent peptides. Despite the widespread presence of membrane-interacting amphipathic helices, there is no computational tool within Rosetta to model their interactions with membranes. In order to address this need, we developed the AmphiScan protocol with PyRosetta, which runs a grid search to find the most favorable position of an amphipathic helix with respect to the membrane. The performance of the algorithm was tested in benchmarks with the RosettaMembrane, ref2015_memb, and franklin2019 score functions on six engineered and 44 naturally-occurring amphipathic helices using membrane coordinates from the OPM and PDBTM databases, OREMPRO server, and MD simulations for comparison. The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3Å of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. Overall, AmphiScan stands as fast, accurate, and highly-customizable protocol that can be pipelined with other Rosetta and Python applications.
Asynchronous Emergence of Flatback Seaturtles, Natator Depressus, from a Beach Hatchery in Northern Australia

Abstract The timing and synchrony of sea turtle emergences from the nests are primary factors in determining hatchling vigor and likelihood of survival. A clear benefit of synchronous emergence is a reduction in energy expenditure through social facilitation, but disadvantages also result from reduction in energy stores if hatchlings have to wait any appreciable time in the nest. We investigated hatchling emergence times throughout emergence of the entire clutch for 21 clutches of Flatback Seaturtles, Natator depressus, incubating in a beach hatchery at three clutch sizes and three nest depths. Emergence of the entire clutch spanned an average of 3.1 days, with shallower nests exhibiting greater emergence asynchrony (mean20cm = 4.0 days, mean35cm = 4.5 days) than deeper nests (mean50cm = 1.7 days). Hatchlings emerged through the night, peaking between 2100 and 2200 h, with hatchlings from shallower nests emerging earlier in the night. For natural nests, hatchlings generally emerged within a single night, evident from the low number of hatchlings remaining in the nest the day after emergence. The disparate observations between a beach hatchery, and natural nests provide important conservation implications for hatchery management.
Concentration and σ13C of leaf carbohydrates in relation to gas exchange in Quercus robur under elevated CO2 and drought

The variations of leaf carbohydrate concentration, carbon isotope discrimination (A) of leaf soluble carbohydrate, gas-exchange and growth during a soil drying cycle under 350 and 700 μmol mol -1 CO 2 concentrations ([CO 2 ]) in Quercus robur seedlings were analysed. In well-watered conditions, a doubling of [CO 2 ] caused an increase of CO 2 assimilation rate (A) (+47%) and a decrease of stomatal conductance for water vapour (g) (-25%), and doubled the intrinsic water-use efficiency (A/g). The values of Δ were not affected by elevated [CO 2 ] which was consistent with the 2-fold increase of A/g. Elevated [CO 2 ] also significantly increased sucrose and starch leaf concentrations as well as aerial growth and plant dry weight. The stimulating effect of CO 2 enrichment on A and A/g was maintained in moderate drought conditions, but disappeared in the most severe drought conditions. Drought induced an increase of hexose concentrations in both [CO 2 ], but this effect was more pronounced under elevated [CO 2 ], which may contribute to increase osmoregulation. From the onset of drought, starch was depleted in both [CO 2 ]. Carbon isotope discrimination decreased in response to drought, which corresponded to an increase in A/g according to the two-step model of isotopic discrimination. In contrast, the A/g values derived from instantaneous leaf gas-exchange measurements decreased along the drying cycle. The discrepancy observed between the two independent estimates of water-use efficiency is discussed in terms of time-scale integration. The results obtained with the isotopic approach using soluble carbohydrate suggest a predominant stomatal limitation of CO 2 assimilation in response to drought.
Red fox viromes across an urban-rural gradient

The Red fox (Vulpes vulpes) has established large populations in Australia’s urban and rural areas since its introduction following European settlement. Foxes’ cryptic and highly adaptable nature allows them to invade cities and live among humans while remaining largely unnoticed. Urban living and access to anthropogenic food resources also influences fox ecology. Urban foxes grow larger, live at higher densities and are more social than their rural counterparts. These ecological changes in urban red foxes are likely to impact the pathogens that they harbour, and foxes could pose a disease risk to humans and other species that share these urban spaces. To assess this possibility, we used a meta-transcriptomic approach to characterise the viromes of urban and rural foxes across the Greater Sydney region in Australia. Urban and rural foxes differed significantly in virome composition, with rural foxes harbouring a greater abundance of viruses compared to their urban counterparts. In contrast, urban fox viromes comprised a greater diversity of viruses compared to rural foxes. We identified nine potentially novel vertebrate-associated viruses in both urban and rural foxes, some of which are related to viruses associated with disease in domestic species and humans. These included members of the Astroviridae, Picobirnaviridae, Hepeviridae and Picornaviridae as well as rabbit haemorrhagic disease virus-2 (RHDV2). This study sheds light on the viruses carried by urban and rural foxes and emphasises the need for greater genomic surveillance of foxes and other invasive species at the human-wildlife interface. Importance Urbanisation of wild environments is increasing as human populations continue to expand. Remnant pockets of natural environments and other green spaces in urban landscapes provide invasive wildlife such as red foxes with refuges within urban areas, where they thrive on the food resources provisioned by humans. Close contact between humans, domestic species and foxes likely increases the risk of novel pathogen emergence. Indeed, the vast majority of emerging infectious diseases in humans originate in wild animals. Here, we explored potential differences in viromes between urban fox invaders and their rural counterparts. Viromes of foxes and their ectoparasites comprise a diversity of viruses including those from the Astroviridae, Picobirnaviridae, Hepeviridae, Caliciviridae and Picornaviridae. Microbial surveillance in foxes and other urban wildlife is vital for monitoring viral emergence and for the prevention of infectious diseases.
Suppressors of mRNA decapping defects isolated by experimental evolution ameliorate transcriptome disruption without restoring mRNA decay

Faithful degradation of mRNAs is a critical step in gene expression, and eukaryotes share a major conserved mRNA decay pathway. In this major pathway, the two rate determining steps in mRNA degradation are the initial gradual removal of the poly(A) tail, followed by removal of the cap structure. Removal of the cap structure is carried out by the decapping enzyme, containing the Dcp2 catalytic subunit. While the mechanism and regulation of mRNA decay is well-understood, the consequences of defects in mRNA degradation are less clear. Dcp2 has been reported as either essential or nonessential. Here we clarify that Dcp2 is essential for continuous growth and use experimental evolution to identify suppressors of this essentiality. We show that null mutations in at least three different are each sufficient to restore viability to a dcp2Δ, of which kap123Δ and tl(gag)gΔ appear the most specific. Unlike previously reported suppressors of decapping defects, these suppressor do not restore decapping or mRNA decay to normal rates, but instead allow survival while only modestly affecting transcriptome homeostasis. These effects are not limited to mRNAs, but extend to ncRNAs including snoRNAs and XUTs. These results provide important new insight into the importance of decapping and resolves previously conflicting publications about the essentiality of DCP2.
Identification of potential biomarkers or therapeutic targets of mesenchymal stem cells in multiple myeloma by bioinformatics analysis

Objectives Mesenchymal stem cells (MSCs) play important roles in multiple myeloma (MM) pathogenesis. Previous studies have discovered a group of MM-associated potential biomarkers in MSCs derived from bone marrow (BM-MSCs). However, no study of the bioinformatics analysis was conducted to explore the key genes and pathways of MSCs derived from adipose (AD-MSCs) in MM. The aim of this study was to screen potential biomarkers or therapeutic targets of AD-MSCs and BM-MSCs in MM. Methods The gene expression profiles of AD-MSCs (GSE133346) and BM-MSCs (GSE36474) were downloaded from Gene Expression Omnibus (GEO) database. Gene Oncology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network of differentially expressed genes (DEGs) were performed. Results A total of 456 common downregulated DEGs in two datasets were identified and the remaining DEGs in GSE133346 were further identified as specific DEGs of AD-MSCs. Furthermore, a PPI network of common downregulated DEGs was constructed and seven hub genes were identified. Importantly, cell cycle was the most significantly enrichment pathway both in AD-MSCs and BM-MSCs from MM patients. Conclusion We identified key genes and pathways closely related with MM progression, which may act as potential biomarkers or therapeutic targets of MM.
Modelling photosynthesis of cotton grown in elevated CO2

Cotton plants were grown in CO2-controlled growth chambers in atmospheres of either 35 or 65 Pa CO2. A widely accepted model of C3 leaf photosynthesis was parameterized for leaves from both CO2 treatments using non-linear least squares regression techniques, but in order to achieve reasonable fits, it was necessary to include a phosphate limitation resulting from inadequate triose phosphate utilization. Despite the accumulation of large amounts of starch (>50 g m−2) in the high CO2 plants, the photosynthetic characteristics of leaves in both treatments were similar, although the maximum rate of Rubisco activity (Vcmax), estimated from A versus Ci response curves measured at 29°C, was ∼10% lower in leaves from plants grown in high CO2. The relationship between key model parameters and total leaf N was linear, the only difference between CO2 treatments being a slight reduction in the slope of the line relating Vcmax to leaf N in plants grown at high CO2. Stomatal conductance of leaves of plants grown and measured at 65 Pa CO2 was approximately 32% lower than that of plants grown and measured at 35 Pa. Because photosynthetic capacity of leaves grown in high CO2 was only slightly less than that of leaves grown in 35 Pa CO2, net photosynthesis measured at the growth CO2, light and temperature conditions was approximately 25% greater in leaves of plants grown in high CO2, despite the reduction in leaf conductance. Greater assimilation rate was one factor allowing plants grown in high CO2 to incorporate 30% more biomass during the first 36 d of growth.
Gene Embeddings of Complex network (GECo) and hypertension disease gene classification

Diseases such as hypertension, cancer, and diabetes are the causes of nearly 70% of the deaths in the U.S. Such complex diseases involve multiple genes and their interactions with environmental factors. Therefore, identification of genetic factors to understand and decrease the morbidity rates of those complex diseases is an important and challenging task. With the generation of an unprecedented amount of multi-omics datasets, network-based methods have become popular to represent the multilayered complex molecular interactions. Particularly network embeddings, the low-dimensional representations of nodes in a network are utilized for gene function prediction. Most of the network embedding methods, however, could not integrate multiple types of datasets from genes and phenotypes. This is an important limitation as multi-omics data integration alleviates the issues due to missing data and lack of context-specific data. To address this limitation, we developed a network embedding algorithm named GECo that can utilize multilayered heterogeneous networks of genes and phenotypes. We evaluated the performance of GECo using genotypic and phenotypic datasets of the model organism Rattus norvegicus to classify hypertension disease-related genes. Our method significantly outperformed the state-of-the-art network embedding methods by 94.97% AUC in prediction where the second-best performer achieved 85.98% AUC.
Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells

Rationale While animal model studies have extensively defined mechanisms controlling cell diversity in the developing mammalian lung, the limited data available from late stage human lung development represents a significant knowledge gap. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. Methods Single cell RNA sequencing generated transcriptional profiles of 5500 cells obtained from two one-day old human lungs (born at gestational ages of 39 and 31 weeks) from the LungMAP Human Tissue Core Biorepository at the University of Rochester. Frozen single cell isolates were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Single cell sequence data from 32000 postnatal day 1, 3, 7 and 10 mouse lung (n = 2 at each time point) cells generated by the LungMAP Research Center at Cincinnati Children’s Hospital and Medical Center, using Dropseq platform, was integrated with the human data. In situ hybridization was used to confirm the spatial location of cellular phenotypes. Results Transcriptional interrogation of donor newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, and immune cells and signature genes for each of these populations were identified. Computational integration of newborn human and postnatal mouse lung development cellular transcriptomes facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the human and mouse cellular transcriptomes also demonstrated cell type-specific differences in developmental states of the newborn human lung cells. In particular, matrix fibroblasts could be separated into those representative of younger cells (n=393), or older cells (n=158). This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of development. Our results indicate that integrated single cell RNA profiling of human and mouse lung will help identify common and species-specific mechanisms of lung development and respiratory disease.
A Yeast BiFC-seq Method for Genome-wide Interactome Mapping

Genome-wide physical protein-protein interaction (PPI) mapping remains a major challenge for current technologies. Here, we report a high-efficiency yeast bimolecular fluorescence complementation method coupled with next-generation DNA sequencing (BiFC-seq) for interactome mapping. We applied this technology to systematically investigate an intraviral network of Ebola virus (EBOV). Two-thirds (9/13) of known interactions of EBOV were recaptured and five novel interactions were discovered. Next, we used BiFC-seq method to map the interactome of the tumor protein p53. We identified 97 interactors of p53 with more than three quarters are novel. Furthermore, in more complex background, we screened potential interactors by pooling two BiFC-libraries together, and revealing a network of 229 interactions among 205 proteins. These results show that BiFC-seq is a highly sensitive, rapid and economical method in genome-wide interactome mapping.
Development of a sensitive molecular diagnostic assay for detecting Borrelia burgdorferi DNA from blood of Lyme disease patients by digital PCR

Lyme disease patients would benefit greatly from a timely, sensitive and specific molecular diagnostic test that can detect the causal agent, Borrelia burgdorferi, at the onset of symptoms. Currently available diagnostic methods recommended by the Centers for Disease Control and Prevention for Lyme disease, involve indirect serological tests that rely on the detection of a host-antibody response which often takes more than three weeks to develop. This results in non-detection of many genuine cases on a timely basis, preventing complete cure. In this study we have developed a digital PCR (polymerase chain reaction) assay that detects Lyme disease on clinical presentation at twice the sensitivity of the currently available diagnostic methods, using a cohort of patient samples collected from the Lyme disease endemic state of Connecticut, USA in 2016-2018. Digital PCR technology was chosen as it is more advanced and sensitive than other PCR techniques in detecting rare targets and the lower limit of detection of this diagnostic assay was found to be three genome copies of B. burgdorferi. The paucity of spirochetes in the bloodstream of Lyme disease patients that hinders the clinical adoption of PCR-based diagnostic tests, was overcome by using a comparatively larger sample volume, pre-analytical processing of blood samples and a pre-amplification step to enrich for B. burgdorferi-specific gene targets before using the digital PCR technology to analyze patient samples. Pre-analytical processing of blood samples from acute patients revealed that the best sample type for Lyme disease detection is platelet-rich plasma and not whole blood. If detected on time, Lyme disease can be cured completely limiting the overuse of antibiotics and associated morbidities.
Dissociation of task engagement and arousal effects in auditory cortex and midbrain

Both generalized arousal and engagement in a specific task influence sensory neural processing. To isolate effects of these state variables in the auditory system, we recorded single-unit activity from primary auditory cortex (A1) and inferior colliculus (IC) of ferrets during a tone detection task, while monitoring arousal via changes in pupil size. We used a generalized linear model to assess the influence of task engagement and pupil size on sound-evoked activity. In both areas, these two variables affected independent neural populations. Pupil size effects were more prominent in IC, while pupil and task engagement effects were equally likely in A1. Task engagement was correlated with larger pupil; thus, some apparent effects of task engagement should in fact be attributed to fluctuations in pupil size. These results indicate a hierarchy of auditory processing, where generalized arousal enhances activity in midbrain, and effects specific to task engagement become more prominent in cortex.
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations

Current state-of-the-art object recognition models are largely based on convolutional neural network (CNN) architectures, which are loosely inspired by the primate visual system. However, these CNNs can be fooled by imperceptibly small, explicitly crafted perturbations, and struggle to recognize objects in corrupted images that are easily recognized by humans. Here, by making comparisons with primate neural data, we first observed that CNN models with a neural hidden layer that better matches primate primary visual cortex (V1) are also more robust to adversarial attacks. Inspired by this observation, we developed VOneNets, a new class of hybrid CNN vision models. Each VOneNet contains a fixed weight neural network front-end that simulates primate V1, called the VOneBlock, followed by a neural network back-end adapted from current CNN vision models. The VOneBlock is based on a classical neuroscientific model of V1: the linear-nonlinear-Poisson model, consisting of a biologically-constrained Gabor filter bank, simple and complex cell nonlinearities, and a V1 neuronal stochasticity generator. After training, VOneNets retain high ImageNet performance, but each is substantially more robust, outperforming the base CNNs and state-of-the-art methods by 18% and 3%, respectively, on a conglomerate benchmark of perturbations comprised of white box adversarial attacks and common image corruptions. Finally, we show that all components of the VOneBlock work in synergy to improve robustness. While current CNN architectures are arguably brain-inspired, the results presented here demonstrate that more precisely mimicking just one stage of the primate visual system leads to new gains in ImageNet-level computer vision applications.
Negative Interplay between Biofilm Formation and Competence in the Environmental Strains of Bacillus subtilis

The soil bacterium Bacillus subtilis can form robust biofilms, which are important for its survival in the environment. B. subtilis also exhibits natural competence. By investigating competence development in B. subtilis in situ during biofilm formation, we reveal that robust biofilm formation often greatly reduces the frequency of competent cells within the biofilm. We then characterize a cross-pathway regulation that allows cells in these two developmental events to undergo mutually exclusive cell differentiation during biofilm formation. Finally, we discuss potential biological implications of limiting competence in a bacterial biofilm. ABSTRACT Environmental strains of the soil bacterium Bacillus subtilis have valuable applications in agriculture, industry, and biotechnology; however, environmental strains are genetically less accessible. This reduced accessibility is in sharp contrast to laboratory strains, which are well known for their natural competence, and a limitation in their applications. In this study, we observed that robust biofilm formation by environmental strains of B. subtilis greatly reduced the frequency of competent cells in the biofilm. By using model strain 3610, we revealed a cross-pathway regulation that allows biofilm matrix producers and competence-developing cells to undergo mutually exclusive cell differentiation. We further demonstrated that the competence activator ComK represses the key biofilm regulatory gene sinI by directly binding to the sinI promoter, thus blocking competent cells from simultaneously becoming matrix producers. In parallel, the biofilm activator SlrR represses competence through three distinct mechanisms involving both genetic regulation and cell morphological changes. Finally, we discuss the potential implications of limiting competence in a bacterial biofilm. IMPORTANCE The soil bacterium Bacillus subtilis can form robust biofilms, which are important for its survival in the environment. B. subtilis also exhibits natural competence. By investigating competence development in B. subtilis in situ during biofilm formation, we reveal that robust biofilm formation often greatly reduces the frequency of competent cells within the biofilm. We then characterize a cross-pathway regulation that allows cells in these two developmental events to undergo mutually exclusive cell differentiation during biofilm formation. Finally, we discuss potential biological implications of limiting competence in a bacterial biofilm.