High-throughput proteomics approaches have revolutionised the identification of RNA-binding proteins (RBPome) and RNA-binding sequences (RBDome) across organisms. Many novel putative RNA-binding proteins (RBPs) were discovered, including those that lack recognisable RNA-binding domains. Yet the extent of noise, including false-positive identifications, associated with these methodologies is difficult to quantify as experimental approaches for validating the results are generally low throughput. To address this, we introduce pyRBDome, a pipeline for in-depth in silico enhancement of RNA-binding proteome data. It does so by comparing experimental results with RNA-binding site (RBS) predictions from several distinct machine learning tools and integrates high-resolution structural data of protein-RNA complexes when available. By providing a statistical evaluation of RBDome data, users can rapidly identify protein sequences from RBDome experiments most likely to be bona fide RNA-binders. Furthermore, by leveraging the predictions collated by pyRBDome, we have enhanced the sensitivity and specificity of RBS detection through training new ensemble machine learning models. We describe a pyRBDome analysis of a large human RBDome dataset and conducted a comparision with know structural data. These analyses reinforced the significance of stacking interactions in UV cross-linking protein-RNA interactions. Surprisingly, our analyses revealed two contrasting findings: While UV cross-linked amino acids were more likely to contain predicted RBSs, they infrequently bind RNA in high-resolution structures. Given the known limitations of structural data as benchmarks, these finding highlights the utility of pyRBDome as a valuable alternative approach for enhancing confidence in RBDome datasets. Finally, our comprehensive analysis of hundreds of (putative) RBPs offers a valuable resource for RBP enthusiasts. less

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here we integrated CODEX multiplexed tissue imaging with multiscale modeling software, to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface. less

Previous vaccination trials have demonstrated that thiol proteins affinity purified from Ostertagia ostertagi excretory-secretory products (O. ostertagi ES-thiol) are protective against homologous challenge. Here we have shown that protection induced by this vaccine was consistent across four independent vaccine-challenge experiments. Protection is associated with reduced cumulative faecal egg counts across the duration of the trials, relative to control animals. To better understand the diversity of antigens in O. ostertagi ES-thiol we used high-resolution shotgun proteomics to identify 490 unique proteins in the vaccine preparation. The most numerous ES-thiol proteins, with 91 proteins identified, belong to the sperm-coating protein/Tpx/antigen 5/pathogenesis-related protein 1 (SCP/TAPS) family. This family includes previously identified O. ostertagi vaccine antigens O. ostertagi ASP-1 and ASP-2. The ES-thiol fraction also has numerous proteinases, representing three distinct classes, including: metallo-; aspartyl- and cysteine proteinases. In terms of number of family members, the M12 astacin-like metalloproteinases, with 33 proteins, are the most abundant family in O. ostertagi ES-thiol. The O. ostertagi ES-thiol proteome provides a comprehensive database of proteins present in this vaccine preparation and will guide future vaccine antigen discovery projects. less

This research paper gives insight into the physico-chemical characteristics of the Rana stream located in the Mandi district of Himachal Pradesh, India, with a particular emphasis on the diversity of diatoms. During the course of this study, eight genera of phytoplankton were identified. Statistical analysis using Pearson correlation unveiled significant associations between the physicochemical parameters and the different groups of diatoms. To assess the diversity of phytoplankton within the stream, several diversity indices were employed. Highest diversity was observed during the month of February. Furthermore, the calculation of water quality indices for the Rana stream yielded values falling within the range of 47.34 to 59.01. This range signifies that the water quality within the Rana stream can be categorized according to the Water Quality Index (WQI) scale, spanning from \"good\" to \"poor.\" It is worth noting that the presence of a diverse assembly of pollution-tolerant diatoms such as Fragilaria, Navicula, Gomphonema, and Cymbella, particularly during the month of March, which coincided with the period of the poorest water quality, is indicative of the eutrophic nature of the stream. less

Interactions between the tubercle bacilli and lung cells during the early stages of tuberculosis (TB) are crucial for disease outcomes. Conventional 2D cell culture inadequately replicates the multicellular complexity of lungs. We introduce a 3D pulmosphere model for Mycobacterium tuberculosis infection in bovine systems, demonstrating through comprehensive transcriptome and proteome analyses that these 3D structures closely replicate the diverse cell populations and abundant extracellular matrix proteins, emphasizing their similarity to the in vivo pulmonary environment. While both avirulent BCG and virulent M. tuberculosis-infected pulmospheres exhibit commonalities in the upregulation of several host signaling pathways, distinct features such as upregulation of ECM receptors, neutrophil chemotaxis, interferon signaling, and RIG-1 signaling pathways characterize the unique early response to virulent M. tuberculosis. Moreover, a signature of seven genes/proteins, including IRF1, CCL5, CXCL8, CXCL10, ICAM1, COL17A1, and CFB, emerges as indicative of the early host response to M. tuberculosis infection. Overall, this study presents a superior ex vivo multicellular bovine pulmosphere TB model, with implications for discovering disease biomarkers, enabling high-throughput drug screening, and improving TB control strategies. less

Seed development in flowering plants starts with a double fertilization process driven by the fusion of the maternal egg and central cells with two paternal sperm cells. This leads to the formation of the embryo and endosperm. These fertilization products are enveloped by the maternally-derived seed coat, the development of which is inhibited prior to fertilization by epigenetic regulator Polycomb Repressive Complex 2 (PRC2). This complex deposits the repressive histone mark H3K27me3, whose removal is necessary for seed coat formation. However, H3K27me3 marks are stable and PRC2 removal does not explain how seed coat genes become activated after fertilization. Here, we show that JUMONJI-type (JMJ) histone demethylases are expressed in the seed coats of Arabidopsis thaliana (Arabidopsis) seeds and are necessary for its formation. We further propose that JMJ activity is coupled to Brassinosteroid (BR) function, as BR effectors have been shown to physically recruit JMJ proteins to target loci. Consistent with this hypothesis, we show that loss of BR function leads to seed coat defects, which can be rescued by depletion of H3K27me3. Finally, we reveal an additional pathway through which BRs directly regulate seed coat development, independently of H3K27me3 deposition. This discovery highlights the diverse functions of BRs in coordinating seed development, beyond their known roles in plant growth and development. less

Vascular cognitive impairment (VCI) is an understudied cerebrovascular disease. As it can result in a significant amount of functional and cognitive disabilities, it is vital to reveal proteins related to it. Our study focuses on revealing proteins related to this complex disease by deciphering the crosstalk between cardiovascular and cognitive diseases. We build protein-protein interaction networks related to cardiovascular and cognitive diseases. After merging these networks, we analyze the network to extract the hub proteins and their interactors. We found the clusters on this network and built the structural protein-protein interaction network of the most connected cluster on the network. We analyzed the interactions of this network with molecular modeling via PRISM. PRISM predicted several interactions that can be novel in the context of VCI-related interactions. Two mutant forms of APP (V715M and L723P), previously not connected to VCI, were discovered to interact with other proteins. Our findings demonstrate that two mutant forms of APP interact differently with TP53 and MAPK\'s. Furthermore, TP53, AKT1, PARP1, and FGFR1 interact with MAPKs through their mutant conformations. We hypothesize that these interactions might be crucial for VCI. We suggest that these interactions and proteins can act as early VCI markers or as possible therapeutic targets. less

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite the surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis. less

Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E and M markers. Even after E and M (E-M) subpopulations are isolated and then cultured independently, E-M heterogeneity can re-equilibrate in each population over time, sometimes regaining the initial distribution of the parental cell population. However, it remains unclear which population-level processes give rise to the dynamical changes in E-M heterogeneity observed experimentally, including 1) differential growth, 2) cell-state switching, and 3) frequency-dependent growth or state-transition rates. Here, we analyse the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that growth differences among E and M subpopulations, with and without any frequency-dependent interactions (cooperation or suppression) among E-M sub-populations, are insufficient to explain the observed population dynamics. This insufficiency is ameliorated by including cell-state transitions, albeit at slow rates, in explaining both PMC42-LA and HCC38 cells data. Further, our models predict that treatment of HCC38 cells with TGFbeta signalling and JAK2/3 inhibitors could significantly enhance the transition rates from M state to E state, but does not prevent transitions from E to M. Finally, we devise a selection criterion to identify the next most informative time points for which future experimental data can optimally improve the identifiability of our estimated best fit model parameters. Overall, our study identifies the necessary population-level processes shaping the dynamics of E-M heterogeneity in breast cancer cells. less

The molecular framework underlying apoplastic root barrier formation has been unveiled in the model species Arabidopsis thaliana where establishment of Casparian strips occurs at an early stage of root development. In legumes, this region overlaps with the area where nitrogen-fixing bacteria can induce nodule formation, termed the susceptible zone. Moreover, while nodules themselves also contain an endodermis spanning their vascular bundles, it is current unknown if Casparian strips serve as a filter for transport across this specialized organ. Here we establish barrier mutants in the symbiosis model Lotus japonicus. We find that the while the genetic network controlling Casparian strip formation is conserved in this legume species, formation of functional barriers is crucial for establishment of N-fixing nodules. By probing this in detail, we establish a model where the Casparian strip, via its linked Schengen pathway, converge with long distance N signaling and systemic regulation of nodulation. Moreover, this also reveal that the genetic system for barrier establishment in the root endodermis is shared in nodule vascular endodermis and required for nodule function. Combined, our findings uncover a novel role of apoplastic root barriers and establishes a mutant collection suitable to probe the role of root barriers in symbiotic plant-microbe relationships. less